CN113256976A

CN113256976A - Vehicle-road cooperative system, analog simulation method, vehicle-mounted equipment and road side equipment

Info

Publication number: CN113256976A
Application number: CN202110517707.XA
Authority: CN
Inventors: 李森; 马坤; 裴俊龙
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Shanghai ICT Co Ltd; CM Intelligent Mobility Network Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Shanghai ICT Co Ltd; CM Intelligent Mobility Network Co Ltd
Priority date: 2021-05-12
Filing date: 2021-05-12
Publication date: 2021-08-13
Anticipated expiration: 2041-05-12
Also published as: WO2022237866A1; CN113256976B

Abstract

The invention provides a vehicle-road cooperative system, an analog simulation method, vehicle-mounted equipment and road side equipment, and relates to the technical field of computers. The vehicle-road cooperation system includes: the edge cloud is used for collecting first data of the road side equipment and second data of the vehicle-mounted equipment, and carrying out simulation on the vehicle-road cooperative environment according to the configuration information, the first data and the second data to obtain a simulation result; the roadside equipment is used for establishing communication with the edge cloud, providing first data for the edge cloud, and making a behavior decision according to a simulation result; the vehicle-mounted equipment is used for establishing communication with the edge cloud, providing second data for the edge cloud, and making a behavior decision according to a simulation result; the road side equipment adopts a road side SDK which is consistent with the behavior and the communication mode of the simulation road side equipment, and the vehicle-mounted equipment adopts a vehicle-mounted SDK which is consistent with the behavior and the communication mode of the simulation vehicle-mounted equipment. The scheme can solve the problems that the traditional vehicle-road cooperative system is long in communication process, full of noise and high in development and verification cost.

Description

Vehicle-road cooperative system, analog simulation method, vehicle-mounted equipment and road side equipment

Technical Field

The invention relates to the technical field of computers, in particular to a vehicle-road cooperative system, an analog simulation method, vehicle-mounted equipment and road side equipment.

Background

The Vehicle-road cooperation is used as the basic capability of the Vehicle-to-all-things (Vehicle-to-all) service of the Vehicle networking system V2X, and aims to avoid traffic accidents, improve road safety, relieve congestion, reduce energy consumption and environmental pollution, and meet the necessary input of services such as Vehicle auxiliary driving and automatic driving.

The RSU (Road Side Unit) and the OBU (On-Board Unit) are used as important equipment links for vehicle-to-vehicle network vehicle-to-vehicle Road cooperation, and can provide necessary information input for a vehicle-to-vehicle Road cooperation platform cloud and receive information of the cloud or other equipment ends through a wireless or wired communication pipeline.

At present, the industry technology innovation parks such as intelligent traffic and intelligent driving are greatly developed in China, and the construction and application of 5G (the 5th Generation Mobile communication technology, fifth Generation Mobile communication technology) and MEC (Mobile Edge Computing) Edge clouds are actively promoted. However, at present, manufacturers of vehicle-mounted terminals and roadside devices are numerous, behaviors of communication protocol people changing devices are not completely unified, and due to the fact that main scenes in a vehicle-road cooperation system relate to various external terminal devices, various communication protocols and mutual communication among the devices, invisible risks and uncontrollable factors in debugging, optimization and development of the system are numerous.

In the traditional vehicle-road cooperative equipment simulation scheme, service logic of road side or vehicle-mounted equipment is considered in a simplified mode, equipment communication protocols and equipment behavior logic are not standardized and complicated, and mutual cooperation of multi-level clouds and multi-type equipment in a real scene is not considered in a centralized server design, so that the existing vehicle-road cooperative system is long in communication process, full of noise and high in development and verification cost.

Disclosure of Invention

The invention aims to provide a vehicle-road cooperation system, an analog simulation method, vehicle-mounted equipment and roadside equipment, and solves the problems that the communication process of the vehicle-road cooperation system is long and full of noise, and the development and verification cost is high in the prior art.

To achieve the above object, an embodiment of the present invention provides a vehicle-road cooperation system, including:

the edge cloud is used for collecting first data of road side equipment and second data of vehicle-mounted equipment, and carrying out simulation on the vehicle-road cooperative environment according to configuration information, the first data and the second data to obtain a simulation result;

the roadside equipment is used for establishing communication with the edge cloud, providing the first data for the edge cloud, and making a behavior decision according to the simulation result;

the vehicle-mounted equipment is used for establishing communication with the edge cloud, providing the second data for the edge cloud, and making a behavior decision according to the simulation result;

the simulated vehicle-road cooperative environment on the edge cloud comprises simulated road-side equipment and simulated vehicle-mounted equipment; the road side device adopts a road side SDK (Software Development Kit) consistent with the behavior and communication mode of the simulation road side device, and the vehicle-mounted device adopts a vehicle-mounted SDK consistent with the behavior and communication mode of the simulation vehicle-mounted device.

Optionally, the vehicle-road coordination system further includes:

and the core cloud is used for providing routing information for the road side equipment and the vehicle-mounted equipment in each regional range to access the edge cloud, establishing communication with the edge cloud in the whole regional range, and performing big data comprehensive analysis and prediction on the traffic road condition in the whole regional range.

Optionally, the edge cloud is further configured to:

and sending the first data, the second data and the road condition data obtained through the edge cloud computing to the core cloud.

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP (MAP, MAP message);

SPAT (Signal phase timing message, traffic light phase and timing message);

roadside traffic time messages;

RSI (Road Side Information);

RSM (Road Safety Message).

Optionally, the second data comprises at least one of:

vehicle geographic location information;

BSM (Basic Safety Message) of vehicle driving state;

vehicle sensor data.

Optionally, the performing, by the edge cloud, simulation of the vehicle-road cooperative environment according to the configuration information, the first data, and the second data includes:

according to the configuration information, the first data and the second data, scene arrangement is carried out to form a simulation scene;

executing the simulation scene to obtain at least one of the following:

first simulation data of the simulated roadside device; the first simulation data comprises simulation traffic data, simulation MAP, simulation SPAT, simulation roadside traffic time information, simulation RSI and simulation RSM;

second simulation data of the simulated vehicle-mounted device; wherein the second simulation data includes simulated vehicle BSM and simulated vehicle sensor data;

third simulation data of the vehicle, the third simulation data comprising road events and/or early warning information.

Optionally, the edge cloud is further configured to:

and verifying the service capability of the vehicle-road cooperative system according to the simulation result.

Optionally, the verifying the service capability of the vehicle-road cooperative system according to the simulation result includes:

and verifying the service capability of the vehicle-road cooperative system by comparing whether the first data and the first simulation data under the same simulation scene are the same or not and comparing whether the second data and the second simulation data under the same simulation scene are the same or not.

Optionally, the edge cloud is further configured to collect the configuration information;

wherein the configuration information comprises:

device metadata;

scene metadata;

path metadata.

Optionally, the edge cloud collecting the device metadata includes:

collecting device initial metadata;

verifying the initial metadata of the equipment;

and in the case of passing the verification, storing the initial metadata of the equipment into a database as the metadata of the equipment.

Optionally, the device initial metadata comprises at least one of:

the vehicle end metadata comprise vehicle information data and corresponding vehicle-mounted equipment data;

road end metadata, the road end metadata including road side equipment information and local area map information;

simulation event metadata including a GPS (Global Positioning System) point location, an equipment attribute, an operation or driving state and a simulation event, which are manually collected on a map.

Optionally, the checking the device initial metadata includes:

when the initial equipment metadata is vehicle-end metadata, performing uniqueness verification on the vehicle information data in the vehicle-end metadata;

and if the vehicle information data is unique, the verification is passed.

Optionally, the checking the device initial metadata includes:

setting an action range of road side traffic equipment in the road side equipment information under the condition that the equipment initial metadata is road end metadata;

setting a Global Positioning System (GPS) coordinate of the road side traffic equipment, or setting a position relation between the road side traffic equipment and a road on a map;

checking the path end metadata;

if the route end metadata meets a first preset condition, the verification is passed;

the road side equipment information is related information of road side traffic equipment;

the roadside traffic device includes at least one of: RSU, traffic signal lamp, laser radar, millimeter wave radar, high definition digtal camera and temperature and humidity sensor.

Optionally, the case that the way end metadata satisfies a first preset condition includes the following three items:

the roadside device information and the local area map information are accurate;

the incidence relation between the roadside device information and the local area map information has no logic error;

there is no conflict between the roadside device information and the local area map information and the device metadata in the database.

Optionally, the checking the device initial metadata includes:

selecting a device associated with the simulation event if the device initial metadata is simulation event metadata; wherein the equipment comprises the roadside equipment, the on-board equipment, the simulation roadside equipment and the simulation on-board equipment;

selecting the type of the simulation event; the types of different simulation events correspond to different simulation scenes;

setting parameters and mutual exclusion conditions of the simulation events;

verifying the simulation event;

and when the simulation event meets a second preset condition, the verification is passed.

Optionally, the parameters include event level, execution time, period, location, and value.

Optionally, the simulation event satisfies a second preset condition, and includes at least the following three items:

the simulation event is accurate;

the incidence relation between the simulation event and the equipment and the map has no logic error;

there is no conflict between the simulation event and the device metadata in the database.

Optionally, the edge cloud collects the scene metadata, including at least one of:

receiving first scripted data uploaded manually; the first scripted data are scripted data formed by screening and processing third data uploaded by the road side equipment and the vehicle-mounted equipment; the third data includes behavior data of a vehicle and roadside device data related to the vehicle;

acquiring fourth data of the road side equipment and the vehicle-mounted equipment through a vehicle-road cooperative platform on the edge cloud, and processing the fourth data to form second scripted data; wherein the fourth data includes all vehicles and roadside device data related to the vehicles;

editing and inputting third scripted data on the visual operation interface;

the first scripted data, the first scripted data and the first scripted data are scripted data which conform to the running of the simulation scene.

Optionally, the edge cloud collecting the path metadata includes:

loading self-defined dynamic path metadata, and displaying a planned path through a map interface;

segmenting the path on the path to form a running point;

and collecting and summarizing the operating points and storing the operating points to form path metadata.

Optionally, the edge cloud segments the path, including at least one of the following:

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

Optionally, the edge cloud performs scene editing, including:

setting a scene event on a path according to the path metadata and the scene metadata;

selecting a simulation vehicle, and binding the path metadata with the simulation vehicle.

Optionally, the setting, by the edge cloud, a scene event on the path according to the path metadata and the scene metadata includes:

setting a scene event on a path; wherein, the scene event is formed by freely combining basic scenes;

checking the scene event;

if the verification is successful, adding the scene event into a queue to be stored;

and after the scene event on the path is recorded, storing the scene event in the queue to be stored.

Optionally, the verifying the scene event by the edge cloud includes:

judging whether behavior mutual exclusion exists between the scene events and the path metadata;

if the behavior mutual exclusion does not exist, the verification is passed; otherwise, the check fails.

Optionally, the simulation scenario includes a historical playback fixed scenario and an interactive fusion simulation scenario.

Optionally, the edge cloud executes the simulation scenario, including:

initializing a scene execution engine;

judging the type of the simulation scene according to parameter configuration or API (Application Programming Interface) call;

and executing the simulation scene according to the type.

Optionally, the edge cloud performs scene execution engine initialization, including at least one of:

initializing a program space required by operation;

loading operation parameters;

connecting a local database, a cache or a message queue;

loading device metadata;

a network communication link is initialized.

Optionally, in a case that the type is a historical playback fixed scene, the edge cloud executes the simulation scene, including:

selecting equipment which needs to execute the simulation scene; the equipment comprises the road side equipment, the vehicle-mounted equipment, the simulation road side equipment and the simulation vehicle-mounted equipment;

loading stored historical scene metadata from a database; wherein the historical scene metadata comprises device operation data and scene recording data;

and sending the scene recording data to the equipment.

Optionally, in a case that the type is an interactive fusion simulation scene, the executing the simulation scene by the edge cloud includes:

loading associated scene metadata according to the type of the current equipment; the scene metadata comprise equipment basic information and a regional traffic road relation network; the equipment comprises the road side equipment, the vehicle-mounted equipment, the simulation road side equipment and the simulation vehicle-mounted equipment;

matching scripted data for the device.

Optionally, one simulation scene is bound with at least one simulation device, and one simulation device is bound with only one simulation scene; wherein the simulation equipment comprises the simulation vehicle-mounted equipment and the simulation road-side equipment.

Optionally, the edge cloud is further configured to:

and sending a dynamic perception map to the vehicle-mounted equipment and/or the simulated vehicle-mounted equipment within the edge cloud coverage range according to a simulation result.

Optionally, the establishing, by the vehicle-mounted device, communication with the edge cloud includes:

receiving a network address of the edge cloud sent by the core cloud;

and selecting a first edge cloud corresponding to the network address closest to the position of the vehicle-mounted equipment from the network addresses, and establishing connection with the first edge cloud.

Optionally, the vehicle-mounted device provides the second data for the edge cloud, including:

pulling corresponding scripted data from the edge cloud according to the SDK configuration, connecting corresponding road side equipment according to the SDK configuration, and receiving a first message from the road side equipment after the connection is successful;

decoding the scripted data, and sequentially executing the first message and the script according to the execution sequence and the frequency of the script;

and uploading the second data to the edge cloud according to the first message.

Optionally, the vehicle-mounted device executes the script, and executes the following steps in a loop:

receiving scene events broadcast by other vehicle-mounted equipment or roadside equipment;

processing the scene event;

and sending the driving data of the vehicle and the processing result of the scene event to the edge cloud.

Optionally, each time the vehicle-mounted device completes execution of one script, a path for executing the script is sent to the edge cloud; and sending a processing result of the scene event to the edge cloud once every time the scene event processing is completed.

Optionally, the roadside apparatus is further configured to:

selecting a second edge cloud corresponding to the network address closest to the position of the road side equipment through the built-in or configured network address of the edge cloud, and establishing connection with the second edge cloud;

periodically acquiring a list of the vehicle-mounted devices in a second preset range and a communication address corresponding to each vehicle-mounted device, and establishing an association relation with a traffic road network or other device metadata.

Optionally, the roadside apparatus is further configured to cyclically execute the following steps within a preset period:

receiving an alarm event sent by the edge cloud, or generating the alarm event according to data collected by the roadside equipment;

and broadcasting the alarm event to vehicles within a third preset range.

Optionally, the roadside apparatus is further configured to:

periodically checking the validity of the alarm event;

discarding the alarm event if the alarm event has expired.

To achieve the above object, an embodiment of the present invention provides an analog simulation method applied to an edge cloud, including:

the method comprises the steps of collecting first data of road side equipment and second data of vehicle-mounted equipment, and carrying out simulation of a vehicle-road cooperative environment according to configuration information, the first data and the second data to obtain a simulation result.

Optionally, the performing, according to the configuration information, the first data, and the second data, simulation of the vehicle-road collaborative environment to obtain a simulation result includes:

executing the simulation scene to obtain at least one of the following:

simulating first simulation data of the roadside device; the first simulation data comprises simulation traffic data, simulation MAP, simulation SPAT, simulation roadside traffic time information, simulation RSI and simulation RSM;

second simulation data of the simulation vehicle-mounted equipment; wherein the second simulation data includes simulated vehicle BSM and simulated vehicle sensor data;

Optionally, the simulation method further includes:

and sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

To achieve the above object, an embodiment of the present invention provides an analog simulation method applied to a core cloud, including:

and providing routing information for access of roadside equipment and vehicle-mounted equipment in each area range to the edge cloud.

Optionally, the simulation method further includes:

and establishing communication with the edge cloud in the whole area range, and performing big data comprehensive analysis and prediction on the traffic road condition in the whole area range.

In order to achieve the above object, an embodiment of the present invention provides an analog simulation method applied to roadside equipment, including:

establishing communication with an edge cloud, and providing first data for the edge cloud;

making a behavior decision according to the simulation result of the edge cloud;

and the roadside equipment adopts a roadside SDK which is consistent with the behavior and communication mode of the simulation roadside equipment on the edge cloud.

Optionally, the simulation method further includes:

in a preset period, circularly executing the following steps:

and broadcasting the alarm event to vehicles within a third preset range.

In order to achieve the above object, an embodiment of the present invention provides an analog simulation method applied to a vehicle-mounted device, including:

establishing communication with an edge cloud, providing second data for the edge cloud, and making a behavior decision according to a simulation result of the edge cloud;

and the vehicle-mounted equipment adopts a vehicle-mounted SDK which is consistent with the behavior and communication mode of the simulation vehicle-mounted equipment on the edge cloud.

Optionally, the establishing communication with the edge cloud includes:

receiving a network address of the edge cloud sent by a core cloud;

Optionally, the providing second data for the edge cloud includes:

and uploading the second data to the edge cloud according to the first message.

To achieve the above object, an embodiment of the present invention provides an edge cloud, including a processor; the processor is used for collecting first data of road side equipment and second data of vehicle-mounted equipment, and carrying out simulation of the vehicle-road collaborative environment according to configuration information, the first data and the second data to obtain a simulation result.

To achieve the above object, an embodiment of the present invention provides a core cloud, including: a processor; the processor is used for providing routing information for access edge clouds of the road side equipment and the vehicle-mounted equipment in each area range.

To achieve the above object, an embodiment of the present invention provides an in-vehicle apparatus including: a transceiver and a processor; the transceiver is used for establishing communication with an edge cloud and providing second data for the edge cloud;

the processor is used for making a behavior decision according to the simulation result of the edge cloud;

To achieve the above object, an embodiment of the present invention provides a roadside apparatus including a processor and a transceiver, including: a transceiver and a processor;

the transceiver is used for establishing communication with an edge cloud and providing first data for the edge cloud;

To achieve the above object, an embodiment of the present invention provides an analog simulation apparatus applied to an edge cloud, including:

the simulation module is used for collecting first data of the road side equipment and second data of the vehicle-mounted equipment, and carrying out simulation on the vehicle-road cooperative environment according to the configuration information, the first data and the second data to obtain a simulation result.

To achieve the above object, an embodiment of the present invention provides an analog simulation apparatus applied to a core cloud, including:

and the routing module is used for providing routing information for access of the road side equipment and the vehicle-mounted equipment in each area range to the edge cloud.

In order to achieve the above object, an embodiment of the present invention provides an analog simulation apparatus applied to road side equipment, including:

the device comprises a first communication module, a second communication module and a third communication module, wherein the first communication module is used for establishing communication with an edge cloud and providing first data for the edge cloud;

the first decision module is used for making a behavior decision according to the simulation result of the edge cloud;

In order to achieve the above object, an embodiment of the present invention provides an analog simulation apparatus applied to a vehicle-mounted device, including:

the second communication module is used for establishing communication with the edge cloud and providing second data for the edge cloud;

the second decision module is used for making a behavior decision according to the simulation result of the edge cloud;

To achieve the above object, an embodiment of the present invention provides a communication device, including a transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; the processor implements the above-described simulation method applied to the edge cloud, or implements the above-described simulation method applied to the core cloud, or implements the above-described simulation method applied to the roadside device, or implements the above-described simulation method applied to the in-vehicle device, when executing the program or the instruction.

To achieve the above object, an embodiment of the present invention provides a readable storage medium on which a program or instructions are stored, which when executed by a processor, implement the steps in the analog simulation method applied to the edge cloud as described above, or implement the steps in the analog simulation method applied to the core cloud as described above, or implement the steps in the analog simulation method applied to the roadside apparatus as described above, or implement the steps in the analog simulation method applied to the in-vehicle apparatus as described above.

The technical scheme of the invention has the following beneficial effects:

the vehicle-road cooperative system provided by the embodiment of the invention realizes the cloud equipment simulation environment on the MEC edge cloud, so as to provide simulation interaction of roadside equipment and vehicle-mounted equipment close to the real environment for the vehicle-road cooperative platform. The SDK consistent with the behavior and the communication mode of the simulation equipment is provided on the real road side equipment and the real vehicle-mounted equipment, so that the real equipment can realize 17 vehicle-road cooperative typical and basic application scenes defined by national standards, the real equipment can be quickly accessed to multi-edge cloud, regional cloud and centralized core cloud fusion infrastructures with the vehicle-road cooperative vehicle networking capability, 5G NR (New Radio, New air interface) -V2X, artificial intelligence and other information infrastructures can be quickly applied, the real equipment can be quickly deployed in innovative infrastructures such as industrial technology innovation bases and automatic driving test yards, and meanwhile, development, test, operation and maintenance low-cost schemes consistent with the simulation equipment are provided for the real equipment.

Drawings

FIG. 1 is a data flow diagram of a vehicle-road coordination system according to an embodiment of the invention;

FIG. 2 is a schematic diagram of an overall architecture of a vehicle-road coordination system according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart illustrating the collection of vehicle-side metadata by an edge cloud according to an embodiment of the present invention;

fig. 4 is a schematic flowchart of an edge cloud collection route end metadata according to an embodiment of the present invention;

FIG. 5 is a schematic flow chart of collecting metadata of simulation events by an edge cloud according to an embodiment of the present invention;

FIG. 6 is a flowchart illustrating an edge cloud collecting scene metadata according to an embodiment of the present invention;

FIG. 7 is a flowchart illustrating an edge cloud collection path metadata according to an embodiment of the present invention;

FIG. 8 is a flowchart illustrating setting a scene event according to an embodiment of the present invention;

fig. 9 is a schematic diagram of a scene device binding flow according to an embodiment of the present invention;

FIG. 10 is a flowchart illustrating a scenario execution process according to an embodiment of the present invention;

FIG. 11 is a schematic diagram of a work flow of a vehicle-mounted SDK according to an embodiment of the present invention;

FIG. 12 is a schematic diagram of a roadside SDK workflow according to an embodiment of the present invention;

FIG. 13 is a flow chart of a simulation method according to an embodiment of the present invention;

FIG. 14 is a flow chart of a simulation method according to another embodiment of the present invention;

FIG. 15 is a flow chart of a simulation method according to another embodiment of the present invention;

FIG. 16 is a flow chart of a simulation method according to yet another embodiment of the present invention;

FIG. 17 is a block diagram of an analog simulation apparatus according to an embodiment of the present invention;

FIG. 18 is a block diagram of an analog simulation apparatus according to another embodiment of the present invention;

FIG. 19 is a block diagram of an analog simulation apparatus according to still another embodiment of the present invention;

FIG. 20 is a block diagram of an analog simulation apparatus according to still another embodiment of the present invention;

FIG. 21 is a block diagram of an edge cloud in accordance with an embodiment of the present invention;

fig. 22 is a structural diagram of an in-vehicle apparatus according to an embodiment of the invention;

FIG. 23 is a block diagram of an edge cloud of another embodiment of the present invention;

fig. 24 is a structural diagram of an in-vehicle apparatus according to another embodiment of the present invention.

Detailed Description

In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

In addition, the terms "system" and "network" are often used interchangeably herein.

In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.

As shown in fig. 1 to fig. 2, a vehicle-road cooperation system according to an embodiment of the present invention includes:

the edge cloud is used for collecting first data of road side equipment and second data of vehicle-mounted equipment, and carrying out simulation of the vehicle-road cooperative environment according to configuration information, the first data and the second data to obtain a simulation result. Optionally, the edge cloud is further configured to: and verifying the service capability of the vehicle-road cooperative system according to the simulation result.

As an optional embodiment of the present invention, the edge cloud (i.e., the MEC edge cloud platform) includes a vehicle-road coordination platform and a cloud-end simulation environment, which can be respectively used for collecting data and performing simulation, and specifically, specific situations of the vehicle-road coordination platform and the cloud-end simulation environment can be detailed as follows:

the vehicle-road cooperative platform can have multiple functions of traffic information fusion perception, real-time calculation and analysis, data storage and opening, resource scheduling and cooperative calculation and the like. The vehicle road supports services with low time delay, high bandwidth and massive device connection in an edge range in cooperation with the edge node, and can process or generate 5 types of basic information (including BSM, SPAT, MAP, RSI and RSM).

As shown in fig. 2, in the embodiment of the present invention, the related functions of the vehicle-road cooperation platform may include:

collecting roadside traffic equipment data, reported local MAP MAP information, SPAT state of intersection signal lamps and other information collected by real roadside equipment units (namely roadside equipment) in an edge cloud range through a roadside communication module for subsequent edge cloud computing;

the method comprises the steps that simulation traffic data of simulated roadside equipment units in an edge cloud range, simulation MAP, SPAT and other information are collected through a roadside communication module and used for verifying vehicle-road cooperative service capability in edge cloud;

the method comprises the steps that a road side communication module sends a road side traffic time message, traffic sign board information (RSI) and a road side safety message (RSM) which are obtained through calculation to a simulated (or real) road side equipment unit in an edge cloud range;

BSM information including vehicle geographic positions and driving states and data collected by various sensors, which are collected by real vehicle-mounted equipment units in the edge cloud range, are collected through a vehicle-end communication module for subsequent edge cloud computing;

vehicle BSM data generated by a simulated vehicle-mounted equipment unit in the edge cloud range and various simulated vehicle sensor data are collected through a vehicle-end communication module and are used for verifying the vehicle-road cooperative service capability in the edge cloud;

the calculated dynamic perception map is sent to the simulated (or real) vehicle-mounted equipment unit in the edge cloud range through the vehicle-end communication module, and the information of advanced auxiliary driving and automatic driving can be used.

Optionally, the first data comprises at least one of: roadside traffic device data; MAP message MAP; traffic light phase and timing messages SPAT; roadside traffic time messages; road side information RSI; roadside safety messages RSM. The second data includes at least one of: vehicle geographic location information; a basic safety message BSM of the vehicle driving state; vehicle sensor data.

It should be noted that the first data of the roadside device and the second data of the vehicle-mounted device collected by the edge cloud include, but are not limited to, the data types listed in the above embodiments.

And (II) the cloud simulation environment (namely the cloud equipment simulation environment) can comprise equipment data collection, simulation scene arrangement, simulation road side equipment and simulation vehicle-mounted equipment. The cloud simulation environment simulates network links, message data transmission, collection and storage under the whole vehicle-road cooperative environment, analyzes and calculates data from simulation input (or real equipment), generates sensing events to people, vehicles or roads, simulates decision-making behaviors of the equipment, simulates and realizes driving behaviors and emergency decisions of the real vehicles in corresponding scenes and early warning, scheduling and emergency decisions of roadside traffic equipment in the corresponding scenes.

The cloud simulation environment can perform cloud scene simulation, which means simulation of road side equipment and vehicle-mounted equipment in the edge cloud node. The device simulation data in the edge cloud can provide rapid device verification for the vehicle-road cooperation platform, and provide traffic simulation data in corresponding ranges for the regional cloud and the global core cloud.

The simulation road side equipment can simulate the behavior of a road side unit (namely RSU), and realizes the functions of management of communication between the vehicle-road cooperation platform and the vehicle-mounted equipment unit, equipment registration login, data receiving and sending, protocol conversion, information life cycle management of RSI, RSM, SPAT and MAP, coding and decoding, forwarding and storing of communication information, parameter configuration, safety management and the like. The simulated road side device (namely the simulated road side device) can carry out scene verification together with other real or simulated road side devices and vehicle-mounted devices.

The simulation vehicle-mounted equipment can simulate the behavior of a vehicle-mounted communication unit (namely OBU), and realize the decision-making behavior, display early warning, message prompting, management of communication between the vehicle and a road side cooperation platform and a road side unit, equipment registration and login, data receiving and sending, protocol conversion, message life cycle management of BSM, RSI, RSM, SPAT and MAP, coding and decoding, forwarding and storing of communication messages, parameter configuration, safety management and other functions of the vehicle in a specific scene. The simulated vehicle-mounted equipment (namely the simulated vehicle-mounted equipment) can carry out scene verification together with other real or simulated road-side equipment and vehicle-mounted equipment.

Therefore, the simulation of the vehicle-road cooperative environment is carried out through the cloud simulation environment, the problems that a large number of real devices need to be in butt joint in the development process of a conventional vehicle-road cooperative platform and a large amount of debugging time cost needs to be spent can be solved, the simulation environment has the advantages that other simulators are high in availability, easy to expand, wide in application, flexible in expansion, low in cost and the like, and the advantages that the other simulators do not have are guaranteed, the pluggable and switchable functions between the simulation device and the real devices are achieved, testing and development personnel can conveniently verify corresponding platform functions in the whole development and verification processes, and corresponding required data are obtained.

The vehicle-road cooperation system further includes:

the simulated vehicle-road cooperative environment on the edge cloud comprises simulated road-side equipment and simulated vehicle-mounted equipment; the road side equipment adopts a road side Software Development Kit (SDK) consistent with the behavior and the communication mode of the simulation road side equipment, and the vehicle-mounted equipment adopts a vehicle-mounted SDK consistent with the behavior and the communication mode of the simulation vehicle-mounted equipment.

In this way, by providing the roadside SDK to the roadside device, the roadside device (here, the real roadside device) can inherit the capability of realizing the simulated roadside device; the capability of realizing the simulation of the vehicle-mounted device can be inherited by providing the vehicle-mounted SDK to the vehicle-mounted device (herein, the real vehicle-mounted device); the vehicle-mounted equipment and the road side equipment can be quickly accessed to the edge cloud vehicle-road cooperation platform through the SDK to verify the vehicle-road cooperation scene.

Specifically, in an optional embodiment of the present invention, the functions of the roadside SDK and the vehicle SDK are detailed as follows:

the roadside SDK (i.e., the roadside SDK) may be used to provide the real roadside device, and inherit the capability of implementing the simulated roadside unit (i.e., the simulated roadside device). For example, after the real roadside device integrates the roadside SDK, most of the vehicle and road cooperative service functions can be realized, including: the simulation scene capability can inherit the vehicle and road cooperation related service scene realized in the multiplex roadside simulation; the edge cloud communication capability, namely the communication capability realized in the multiplexing roadside simulation can be inherited, and the corresponding edge cloud nodes are selected for communication according to the range of the roadside units (namely roadside devices) managed in the edge cloud; the vehicle-end broadcasting capability can inherit the communication capability realized in the multiplexing roadside simulation, and wirelessly broadcast the information such as the RSI, the RSM, the SPAT, the MAP and the like to the vehicles connected to the edge cloud; the message life cycle management capability can inherit the capabilities of encoding and decoding, forwarding, storing, state maintaining and the like of the communication message realized in the multiplex roadside simulation; the parameter configuration capability can inherit the equipment parameter configuration capability realized in the multiplexing road side simulation.

The vehicle-mounted SDK can be used for providing real vehicle-mounted intelligent equipment (namely vehicle-mounted equipment) and inheriting the capability of realizing a simulation vehicle-mounted unit (namely simulation vehicle-mounted equipment). For example, after the real vehicle-mounted device unit (i.e., the real vehicle-mounted device) integrates the SDK, most of the vehicle-road cooperative service functions can be implemented, including: the simulation scene capability can inherit the editing, generating and operating capability of the vehicle-road cooperative related service scene realized in the simulation of the multiplex vehicle end; the early warning decision capability can inherit the early warning and decision capability of the events V2V and V2I in the simulation of the multiplex vehicle end, and it needs to be explained that the decision capability of the vehicle-mounted equipment is continuously improved by training and improving an algorithm model through machine learning in the simulation environment; the edge cloud communication capability, namely the communication capability realized in the multiplexing roadside simulation can be inherited, and the corresponding edge cloud nodes are selected for communication according to the vehicle range managed in the edge cloud, it needs to be noted that the vehicle can carry a 5G communication module, the communication time delay is reduced, the type and the number of transmission data are enriched by using the enhanced bandwidth, and a V2X platform (namely a vehicle-road cooperation platform) in the edge cloud can also be accessed to a large number of vehicles or equipment; the communication capability of the road side equipment, namely the communication capability realized in the simulation of the multiplex vehicle end can be inherited, and messages such as RSI, RSM, SPAT, MAP and the like broadcast by the road side equipment are received; the message life cycle management capability can inherit the capabilities of encoding and decoding, forwarding, storing, state maintaining and the like of communication messages realized in the simulation of the multiplex vehicle end; the parameter configuration capability can inherit the equipment parameter configuration capability realized in the vehicle-end simulation.

In the embodiment of the invention, the SDK consistent with the behavior and communication mode of the simulation equipment is provided on the real road side equipment and the real vehicle-mounted equipment, so that the problem of long passing process in the vehicle-road cooperative system can be avoided, and the development and verification cost is saved; the method can ensure that the real equipment can realize 17 types of road-vehicle cooperation typical application scenes defined by national standards, so that the real equipment can be quickly accessed to multi-edge cloud, regional cloud and centralized core cloud fusion infrastructures with the road-vehicle cooperation vehicle networking capability, information infrastructures such as 5G NR-V2X and artificial intelligence are quickly applied and are quickly deployed in innovation infrastructures such as industrial technology innovation bases and automatic driving test fields, the excessively complex network environment influence and hardware requirements are avoided, and the cost problems in all aspects of the life cycle of a road simulation system are better solved. In addition, a development and test low-cost scheme consistent with that of simulation equipment can be provided for real equipment, and a design scheme on a key link is provided for realizing the car networking of vehicle road cooperation, intelligent traffic and the like and building a express train of novel infrastructure construction in China. The problems that in the design and development process of a common vehicle-road cooperative system, due to the fact that the number of participants is large, the communication process is long and noise is full are solved; the method can accurately, stably and quickly acquire related multilateral data as required, and greatly saves development cost and development period.

Optionally, the vehicle-road coordination system further includes: and the core cloud is used for providing routing information for the road side equipment and the vehicle-mounted equipment in each regional range to access the edge cloud, establishing communication with the edge cloud in the whole regional range, and performing big data comprehensive analysis and prediction on the traffic road condition in the whole regional range so as to guide the planning of traffic infrastructure.

It should be noted that, in the embodiment of the present invention, the core cloud (i.e., the regional/core cloud platform) may provide functions such as edge collaborative computing scheduling and multi-level computing capability scheduling in a corresponding range in a region and a global range. The simulation (or real) equipment is accessed to the traffic events generated by the edge cloud for fusion calculation, so that the analysis and prediction of traffic service scenes with relatively low service delay requirements can be realized, and the planning of traffic infrastructure is guided.

Optionally, the edge cloud is further configured to: and sending the first data, the second data and the road condition data obtained through the edge cloud computing to the core cloud.

In the embodiment of the invention, after the MEC edge cloud in the multi-region range collects the equipment data in the administered range and the road condition data calculated by the MEC edge cloud, the MEC edge cloud can report and synchronize the equipment data and the road condition data to the core cloud.

It should be noted that, when the MEC is applied to a multi-access edge cloud, on one hand, the simulation platform (i.e., the cloud simulation environment) operates in a single edge cloud, and provides cloud access and simulation services for road-side devices and running vehicles within the scope governed by the edge cloud, and then provides device operation data input for the V2X vehicle-road cooperation platform and the external platform of the edge cloud; on the other hand, a plurality of edge clouds distributed at different geographic positions simultaneously operate the simulation platform to provide access and simulation services for road ends and vehicle-mounted equipment within the range governed by each edge cloud, so that simulation data of the edge clouds with multiple accesses are filtered, preprocessed, summarized and encoded, horizontal expansion of a wider geographic range is provided for equipment cooperated by the vehicle and the road, fusion data uplink input is provided for a centralized core cloud, and downlink management channels are provided for road end vehicle-mounted equipment (namely road side equipment and vehicle-mounted equipment) accessed in the edge clouds uniformly controlled by the core cloud.

In the embodiment of the invention, based on a side-cloud cooperative architecture, a side-cloud multistage simulation system is established, and layered design of side-side data collection, side-small-particle region scene simulation and cloud large-particle global scene simulation is supported. The method has the advantage of easy expansion, the server cluster of the simulation platform running in the single-edge cloud has the advantage of longitudinal expansion, and the server cluster running in the multi-access-edge cloud has the advantage of horizontal expansion.

executing the simulation scene to obtain at least one of the following:

It should be noted that, in the embodiment of the present invention, a collaborative processing method supporting entry, arrangement, execution flow, and construction of simulation and real data (SDK) of scene metadata of hybrid simulation and real devices is provided, and a multidimensional simulation library such as a simulation vehicle model library, a meteorological road model library, and the like is established based on methods such as machine learning and deep learning, so that a complex and diversified intelligent traffic scene can be flexibly supported, and SDKs consistent with behaviors and communication modes of simulation devices are provided on real roadside devices and real vehicle-mounted devices.

It should be further noted that the scene design, the communication protocol and the communication mode in the invention all adopt the predetermined scene and definition, and the development and design criteria are standardized to a certain extent, so that the multilateral string development can be changed into the parallel development, the efficiency is greatly improved, and the cost in each aspect is saved.

wherein the configuration information comprises: device metadata; scene metadata; path metadata.

Optionally, the edge cloud collecting the device metadata includes:

collecting device initial metadata;

verifying the initial metadata of the equipment;

Optionally, the device initial metadata comprises at least one of:

simulation event metadata, which includes GPS points collected manually on a map, device attributes, operating or driving states, and simulation events.

Here, the way end metadata mainly includes two types of static metadata: roadside device information and local area map information in a traffic infrastructure. In the embodiment of the invention, the real and simulated metadata can be simultaneously supported, and the real and simulated metadata of the road side equipment and the map can also be combined and input, so that the method is not limited to all real equipment or all simulation equipment.

The roadside device information is mainly used for roadside communication, traffic control, detection and monitoring of basic information of real (or simulation) devices such as pedestrians, vehicles and environments on the road surface. For example, the mark information of the real or simulation metadata, RSU, traffic signal light, laser or millimeter wave radar, high definition camera, device name of the temperature and humidity sensor, device number, device initialization state, angle, position, communication address, frequency band, and other parameters.

The map information of the local area, that is, the mark information of the real or simulation metadata in the map of the area range for which the MEC edge cloud is responsible, and the information of the road traffic relationship network such as the road, the lane, the phase, the intersection, the position point and the like.

In the embodiment of the invention, based on a vehicle-road cooperative architecture, the design of vehicle-end and road-end multi-source data collection, fusion processing and scene simulation is established, and national standard, non-standard and fusion perception data are supported.

Optionally, the checking the device initial metadata includes: when the initial equipment metadata is vehicle-end metadata, performing uniqueness verification on the vehicle information data in the vehicle-end metadata; and if the vehicle information data is unique, the verification is passed.

Here, the vehicle-side metadata is mainly divided into vehicle information data and corresponding vehicle-mounted device data, wherein the vehicle information data contains necessity information for simulating a vehicle, such as a frame number, a license plate number, and the like, and also contains information useful for driving assistance, such as a vehicle length and width; the necessary information of the vehicle-mounted equipment comprises data information such as equipment numbers, equipment types and the like applied to communication transmission.

As shown in fig. 3, the vehicle-end metadata entry mainly refers to entry of necessary basic information of a vehicle and a vehicle-mounted device, so as to package and arrange data and messages in subsequent simulation and emulation processes. The uniqueness verification of the vehicle information data in the vehicle end metadata mainly means that uniqueness verification is carried out on a frame number and a vehicle-mounted equipment number of a vehicle in an entry process, and information of the type of the vehicle needs to have uniqueness so as to determine vehicle identity information.

Specifically, the flowchart of collecting vehicle-end metadata is shown in fig. 3:

s301: vehicle information is input;

s302: verifying the vehicle information;

s303: judging whether the current information is available;

s304: and in the case that the verification passes, storing the information into the database.

Optionally, the checking the device initial metadata includes:

checking the path end metadata;

As shown in fig. 4, the entry of the way end metadata mainly includes the following steps:

s401: inputting road side equipment basic metadata, such as the road side equipment information and local area map information;

s402: setting a device action range, namely setting the action range of part of roadside traffic devices, for example, setting the area range scanned by a laser radar, the area range of temperature detected by a temperature sensor and the like;

s403: setting the geographical position of the equipment, namely setting the position of part of roadside traffic equipment on a map or the position relation with a road network layer on the map;

s404: checking the road end metadata, namely judging that the road end metadata meets a first preset condition, wherein the checking specifically comprises checking whether the recorded map information of the road side equipment and the area is accurate, whether a logic error exists in the association relation or not, or whether a conflict exists with the history recorded information or not; if the verification is passed, executing S405; if the verification fails, re-entry is needed, namely S401 is executed;

s405: if the verification is passed, storing the data into the database, and ending the processing.

Optionally, the checking the device initial metadata includes:

setting parameters and mutual exclusion conditions of the simulation events;

verifying the simulation event;

Here, the simulation event mainly refers to a traffic event generated or associated with a predicted road traffic participant in a vehicle-road cooperation scenario, and corresponds to a vehicle-road cooperation typical scenario. Such as road congestion, construction, accidents or hazards. It should be noted that the simulation event may cooperate with a real event occurring on a real device (i.e., a roadside device and an on-board device) to cooperate with a vehicle road in a scene. For example, data collected by a real road end laser radar and a camera in an area range can generate a plurality of intersection traffic jam events, and simultaneously, a strong wind hazard warning event generated by simulation can be used, and the two times jointly act on an automatic driving automobile to prompt the automobile to avoid the area.

As shown in fig. 5, the simulation event metadata entry mainly goes through the following main steps:

s501: selecting equipment or equipment groups related to simulation events, wherein the equipment comprises road side equipment, vehicle-mounted equipment, simulation road side equipment and simulation vehicle-mounted equipment; for example, a set of traffic light associated SPAT event information for an area;

s502: selecting an event type (namely the type of the simulation event) to correspond to a specific scene; such as congestion, construction, accidents, hazards, forward collisions, speed limits, etc.;

s503: setting parameters of an event, including event level, execution time, period, place, value or other triggering conditions; for example, a certain road section in the area is expected to have a road icing dangerous event at a certain time point, the grade is three, and the thickness of the road surface icing is 15 mm;

s504: setting a mutual exclusion condition of the event; for example, a road icing hazard should not occur in the same area as a high temperature hazard within the same time frame;

s505: checking the simulation event, namely checking whether the simulation event is accurate, whether a logic error exists in the association relation with the equipment or the area map, or whether a conflict exists with the history recorded information; if the verification is passed, executing S506; if the verification fails, re-entry is needed, namely S501 is executed;

s506: if the verification is passed, storing the data into the database, and ending the processing.

the simulation event is accurate;

As shown in fig. 6, in the embodiment of the present invention, the method for entering a script may be divided into template import, online recording of device data, and online metadata formulation.

firstly, receiving first scripted data uploaded manually as shown by a line in FIG. 6; the first scripted data are scripted data formed by screening and processing third data uploaded by the road side equipment and the vehicle-mounted equipment; the third data includes behavior data of a vehicle and roadside device data related to the vehicle.

Specifically, the script running according with the scene of the vehicle-road cooperative system can be formed by summarizing and formatting data uploaded by real equipment according to equipment types after being screened according to time periods, the user uploads the data script to be imported on line manually, and the data content needs to include behavior data of a vehicle to be entered and all road side equipment data related to the vehicle.

(II) as shown in a step b in fig. 6, acquiring fourth data of the roadside device and the vehicle-mounted device through a vehicle-road cooperative platform on the edge cloud, and processing the fourth data to form second scripted data; wherein the fourth data includes all vehicles and roadside device data related to the vehicles.

Specifically, the simulation service side requests the V2X platform to obtain data of a specific device through various settings, the data V2X platform of the real device is forwarded to the simulation simulator side, the simulation simulator collects, summarizes and formats scripted data which are formed and recorded and conform to the operation of the scene of the vehicle-road cooperative system, and the data content needs to include all vehicles and related roadside device data.

And (III) editing and entering third scripted data on the visual operation interface as shown by a line c in FIG. 6.

Specifically, scripted data which conform to the scene operation of the vehicle-road cooperative system, that is, a planned driving route or a passing place of the vehicle, can be edited and input manually on the visual operation interface. It should be noted that this type of data can only be used as metadata in the scene layout process, and the executable script data is generated according to the path metadata in the scene layout process.

It should be noted that, in the embodiment of the present invention, according to different script types, two execution modes may be adopted: replaying historical behaviors of real equipment (including road side equipment and vehicle-mounted equipment), wherein metadata of equipment data online recording and template importing can only be used for the scene; the custom-entered script data (namely, the script entered in a mode formulated by the online metadata) can only be used as scene support metadata for planning and designing the running route of the vehicle-mounted equipment in the scene and used as bottom layer support data in the scene.

In the embodiment of the invention, the edge cloud can be used for collecting the simulation data of the road side equipment and the vehicle-mounted equipment, and the simulation data can be obtained from the real equipment data in three ways. The real equipment data are from real equipment at a road end and a vehicle end in a vehicle cooperation platform, and the real equipment performs automatic data acquisition and data filtration, standardized coding and transcoding and forwarding of the acquired data when the real road side equipment and the vehicle-mounted equipment run through a simulation SDK; the editing and inputting mode is derived from manually collecting information such as GPS point positions (for example, continuous GPS point positions on a vehicle driving path), inputting equipment attributes (for example, frequency of traffic signal lamp state change), running or driving states (for example, vehicle speed, direction angles and the like), simulation events (for example, road construction events) and the like on a map, and then carrying out standardized coding and transcoding which are consistent with the real equipment data reporting mode; the method has the advantages that real equipment data and edited and input simulation equipment data are fused during simulation of the vehicle-road cooperation scene, free combination of real equipment and simulation equipment is achieved (for example, combination of real road-end equipment and simulation vehicle-mounted equipment or combination of simulation road-end equipment and real vehicle-mounted equipment), efficient and flexible practical schemes are provided for verification of vehicle-road cooperation capacity of a large number of road-end equipment and vehicle-mounted equipment by a vehicle-road cooperation platform, investment of real equipment can be reduced in a specific scene, and accordingly cost is saved.

Optionally, the edge cloud collecting the path metadata includes:

segmenting the path on the path to form a running point;

The path metadata is used as basic information for simulating vehicle operation, and after the path metadata is generated, the path metadata and the vehicle need to be bound one to many according to needs.

It should be noted that the online metadata entry function can enter one or more path metadata at a time, and provides necessary support for matching a specific vehicle scene.

As shown in fig. 7, when setting the custom path metadata, manual segmentation is required according to the path planning assumption. Specifically, the starting point and the starting point of the segmented road section can be set in a mode of manually selecting points on a visual map page, and the strategy information of two-point driving is selected. For example, information such as start point, end point time, speed, line direction angle, and preset cut granularity.

In an embodiment of the present application, a process of collecting the path metadata by the edge cloud (i.e., a meta-path travel point simulation process) is shown in fig. 7:

s701: loading self-defined dynamic path metadata;

s702: segmenting the road sections on the path, namely segmenting the road sections according to key points and classifying the road sections;

s703: judging the type of the road section;

if the linear change is detected, combining with speed analysis, and segmenting according to acceleration or segmenting according to distance; if the arc changes, the arc is divided according to speed and angle or according to angle by combining speed analysis;

s704: collecting and summarizing operating points;

s705: the operating points are stored, forming path metadata.

After the whole section of script is calculated, collecting all simulation points and the starting and ending points of each section of road, and storing the simulation points and the starting and ending points into a database, thereby completing the entry of path metadata once.

It should be noted that, in a scene, the driving behavior of the vehicle may change intelligently and in real time according to a scene event, and if there is no influence of other external factors, the vehicle should perform simulation operation according to the path metadata.

In one embodiment of the invention, the simulation basic path metadata (namely the path metadata) is intelligently added into the simulated driving position information points through an algorithm, so that the vehicle running behavior can be smoother and more real.

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

Specifically, as shown in fig. 7, the following four segmentation methods can be classified according to the speed change and the angle change:

the method comprises the following steps of (A) evenly dividing according to the distance between two points: assuming that the vehicle is in straight line driving and assuming that the vehicle is in constant speed driving, the speed of the input time passing through the distance between the two points and the angle of the straight line between the two points relative to the true north of 0 can be calculated, then the current road sections are equally divided according to the set segmentation granularity, and the longitude and latitude of the equally divided points are calculated according to the distance and the angle.

(II) cutting according to the acceleration: assuming that the vehicle runs in a straight line, and the vehicle speeds in the information of the starting position point and the ending position point are different, the acceleration can be calculated according to the speed difference and the time, and the longitude and latitude of each simulation point are obtained by calculating according to the set segmentation granularity, the acceleration, the time and the angle of the straight line between the two points relative to the true north and the driving distance until the ending point.

And (III) cutting according to angles: assuming that the vehicle speed is unchanged, the angle change of the two points in the driving process can be obtained according to the course angle of the current point and the course angle of the end point; the method is applicable to simulating the scene of uniform turning of the vehicle.

And (IV) segmenting according to angles and accelerations: assuming speed change (namely the speed information of the starting point and the ending point is inconsistent), the time difference between the two points can be obtained, and the acceleration is calculated; according to the course angle of the current point and the course angle of the end point, two points are taken as two points on the virtual circle, the distance between the two points is taken as the diameter of the circle, and the longitude and latitude of the running point on the circular arc are calculated according to the set segmentation granularity, the acceleration and the equal division angle.

Optionally, the edge cloud performs scene editing, including:

As shown in fig. 8, optionally, setting, by the edge cloud, a scene event on a path according to the path metadata and the scene metadata includes:

s801: loading self-defined dynamic path metadata;

s802: displaying the planned path through a map interface;

s803: setting a scene event on a path; wherein, the scene event is formed by freely combining basic scenes;

s804: checking the scene event;

s805: if the verification is successful, adding the scene event into a queue to be stored;

s806: judging whether the recording is finished or not; if so, go to step S807; otherwise, S803 is executed;

s807: and after the scene event on the path is recorded, storing the scene event in the queue to be stored.

It should be noted that, setting a scene event of a key point, that is, weaving a behavior of the key point, setting the scene event on a path, may only be used for an interactive fusion simulation scene, and mainly means setting a behavior of a scene to be executed on planned path metadata, and the process has the following characteristics: the method comprises 17 basic standard national standard scene behavior events; a plurality of national standard scene behaviors can be freely combined to a certain degree on the interactive simulation path metadata; the method has the advantages that the method can specify the road planning and range of scene occurrence; real equipment and simulation equipment can be used in a mixed manner in a scene, for example, real roadside equipment can provide data support for automatic driving or behavior decision for a simulation vehicle, and conversely, the simulation roadside equipment can also provide dynamic, credible and standard support data for a real V2X road test vehicle.

Optionally, the verifying the scene event by the edge cloud includes: judging whether behavior mutual exclusion exists between the scene events and the path metadata; if the behavior mutual exclusion does not exist, the verification is passed; otherwise, the check fails.

That is, the following constraints need to be satisfied: the scene events can not have behavior mutual exclusion, such as road construction events and traffic light interaction; the scene events and path metadata may not have behavioral mutual exclusion, e.g., left turn assistance may not be performed on a straight-ahead lane.

In the embodiment of the invention, through a scene simulation engine, data from the report formulation (namely, the online recording of equipment data) of an online equipment SDK, the formulation of custom arrangement metadata (namely, the formulation of the online metadata) and the formulation of template data import (namely, the template import) are arranged into a scene script suitable for the simulation equipment through a certain degree of manual combination, setting and algorithm automatic generation according to 17 basic scenes such as forward collision early warning, intersection collision early warning, left turn assistance and the like defined by a national standard scene, so that the simulation scene arrangement of the road side equipment and the vehicle-mounted equipment is realized, and the simulation scene arrangement is used for verifying the capacities of a vehicle-road cooperation system, the road side equipment and the vehicle-mounted equipment.

Through simulation, events and conditions which are not easy to create in the real world, such as congestion events, vehicle out-of-control early warning events, road construction events, road weather dangerous events such as strong wind, strong fog and road icing, can be provided, conditions which cannot be generated by the events during scene verification are avoided, and scene verification efficiency is improved.

In addition, because the simulation scene can directly generate dangerous events, the danger of drivers, pedestrians, roads and the like caused by the fact that real vehicles verify the simulation scene in the running process is avoided.

In addition, when 17 basic scenes are arranged and fused, a brand new combined scene can be formed, an algorithm model can be further constructed, algorithms such as machine learning are adopted, an algorithm training function is provided for automatic driving behaviors of a specific scene, the method can be applied to machine learning and algorithm training of edge cloud-assisted driving directions, and the method is more widely applied to business.

In the embodiment of the invention, by simulating the vehicle-mounted equipment and the road side equipment, and mixing the vehicle-mounted equipment and the road side equipment with the real equipment accessed to the simulation environment in the edge cloud, and jointly acting on the vehicle-road cooperative scene, the deployment of a large number of real equipment can be reduced to reduce the cost, and scene conditions which are difficult to realize in the real world can be created.

For example, when a Host Vehicle (HV) travels, a simulated vehicle (RV) is located on a road short of the preset front in the scene, and a pedestrian is detected by a real roadside lidar, the host vehicle should decelerate instead of passing from the left as preset in the scene.

The invention can be used alternately with simulation equipment in the aspect of simulation, is easy to expand, has better subsequent data value-added property, application universality, machine learning data diversity, universality and the like, and solves the problems of distributed data fusion and related intelligent algorithm training of people, vehicles and objects caused by the realization of simulation by a single server in the prior art.

In an embodiment of the present application, according to the functional requirements, the simulation scenario can be divided into two types: a historical playback fixed scene and an interactive fusion simulation scene. The historical playback fixed scene mainly refers to the playback of the running condition of a past certain actual vehicle road cooperation area, and is commonly used for display and exhibition; the interactive fusion scene mainly means that real equipment (namely, roadside equipment and vehicle-mounted equipment) and simulation equipment (namely, simulation roadside equipment and simulation vehicle-mounted equipment) are woven, and the real equipment and the simulation equipment are operated in a specific line together to obtain behavior strategy feedback data of a vehicle or an interactive result of the roadside equipment.

Specifically, whether to execute the history scene playback (i.e., execute the history playback fixed scene) may be determined according to parameter configuration or an API call.

As shown in fig. 10, optionally, the edge cloud executes the simulation scenario, including:

s1001: initializing a scene execution engine;

s1002: judging the type of the simulation scene according to parameter configuration or API call; and executing the simulation scene according to the type. When the simulation scene is a historical playback fixed scene, executing S1003; and executing S1004 when the simulation scene is an interactive fusion simulation scene.

It should be noted that, the scene execution (i.e. executing the simulation scene) aims to run the organized vehicle end metadata, road end metadata and simulation event metadata in the specific scene of vehicle-road cooperation, verify the communication capability and data processing capability of the real or simulated road end traffic infrastructure and vehicles under the vehicle-road cooperation, and enhance the behavior decision capability of the vehicle end and road end computing devices through the artificial intelligence algorithm.

When simulation research related to vehicle-road cooperation and automatic driving is carried out, simulated or real vehicle-mounted equipment and road side equipment are connected into a simulation environment on edge clouds, and a simulation scene is executed in the same time period.

When real equipment (namely vehicle-mounted equipment and road side equipment) related to vehicle-road cooperation and automatic driving is received, the real equipment is accessed to a vehicle-road cooperation platform of the edge cloud, and vehicle cooperation preset scenes are executed in the same time period together with simulation equipment metadata and simulation event metadata which are difficult to realize in the real world. Therefore, when a large number of real devices are connected to the MEC edge cloud, the simulation environment can provide events and conditions which are not easy to create in the real world for realizing the vehicle-road cooperation scene, and the cost and the risk of scene operation are reduced.

The simulation library is basic support data of decision making capability of artificial intelligence, is attached to a V2X platform, and performs autonomous learning through behavior data generated by real vehicle-mounted equipment and road side equipment in the operation process so as to achieve the capability of making decisions for the same scene behaviors.

In an optional embodiment of the invention, the edge cloud can establish a thread pool, create threads for main work such as vehicle-mounted equipment (namely vehicle-mounted equipment) broadcasting driving data, event receiving, driving planning, time processing and data reporting network communication, set a data sharing and synchronizing mechanism among the threads, start each thread, and read and execute the automobile driving path script according to a fixed frequency; the edge cloud can also establish a thread pool, broadcast RSI, MAP, SPAT messages or scene events from a vehicle-road cooperative platform for a road end (namely, a road side device), actively generate RSM alarms by the road end, maintain the state of the alarm messages within the validity period, establish threads for main work such as event broadcasting and the like, set a data sharing and synchronizing mechanism among threads, start each thread, and read and execute a script of the road side device (such as a traffic signal lamp) according to the frequency specified by the simulation scene.

It should be noted that, if the device of the current execution scene is a vehicle end (i.e., a vehicle-mounted device), the vehicle end performs preprocessing such as decoding script data, establishing an association relationship with a traffic road network or other device metadata, and the like; if the scene event causes that the automobile must change the driving path, the automobile end plans a new driving path (including GPS point position, steering angle, driving speed and the like) different from the preset script through simulation; the method adopts an algorithm to process scene events, for example, deep learning, reinforcement learning and other methods are adopted to continuously improve the optimal solution of event processing. If the device of the current execution scene is a road end (namely, a road side device), the road end performs preprocessing such as decoding script data, establishing an association relation with a traffic road network or other device metadata, and the like.

initializing a program space required by operation;

loading operation parameters;

connecting a local database, a cache or a message queue;

loading device metadata;

a network communication link is initialized.

In the embodiment of the invention, when the scene execution starts, the scene execution engine is initialized. For example, initializing a program space required for operation, loading operation parameters, connecting middleware such as a local database, a cache, a message queue, and the like, loading necessary vehicle end metadata, road end metadata, and simulation event metadata, and initializing necessary network communication links, edge cloud routing network addresses, and the like.

As shown in fig. 10, optionally, in a case that the type is a history playback fixed scene, the performing, by the edge cloud, the simulation scene includes:

and sending the scene recording data to the equipment.

Under the condition that the type is a historical playback fixed scene, namely a historical scene is executed, selecting equipment (or equipment group) needing to be executed, loading operation data and scene recording data of real (or simulation) equipment which are stored in a historical mode from a database, setting a historical playback mark for the data, and reporting or broadcasting the historical operation data among the equipment in a process or network communication mode; and after receiving the data with the historical playback marks through the vehicle-road cooperation platform, the cloud simulation environment loads the recorded scene event data and broadcasts the scene event data to the road side equipment and the vehicle-mounted equipment.

At the moment, the vehicle-road cooperation platform can monitor the current dynamic driving state of the vehicle and the decision-making behavior in a historical scene on the edge cloud.

matching scripted data for the device.

And under the condition that the type is an interactive fusion simulation scene, namely the instruction obtained by the scene engine is not an execution history scene but an interactive fusion simulation scene, loading associated scene metadata including equipment basic information and a regional traffic road relation network according to the equipment types of the current vehicle-mounted equipment and the road side equipment, and matching scripted data of the equipment.

As shown in fig. 9, a scene is used as basic support data for simulating vehicle-mounted equipment, simulated roadside equipment, and interaction among the equipment, and in order to ensure normal operation of the equipment, data correctness checking needs to be performed, and the following constraint conditions need to be satisfied: multiple simulation devices (namely simulation vehicle-mounted devices and simulation road-side devices) can be bound to one scene, but only one scene can be bound to one simulation device.

Optionally, the edge cloud is further configured to: and sending a dynamic perception map to the vehicle-mounted equipment and/or the simulated vehicle-mounted equipment within the edge cloud coverage range according to a simulation result.

Optionally, the establishing, by the vehicle-mounted device, communication with the edge cloud includes: receiving a network address of the edge cloud sent by the core cloud; and selecting a first edge cloud corresponding to the network address closest to the position of the vehicle-mounted equipment from the network addresses, and establishing connection with the first edge cloud.

The vehicle-mounted SDK in the real automobile or the scene engine in the simulated automobile can select a nearby edge cloud (namely, a first edge cloud) and establish connection according to an edge cloud network address in an area range obtained during initialization, and after the connection is established, an RSU list and a communication address in the proximity range can be periodically obtained.

and uploading the second data to the edge cloud according to the first message.

As shown in fig. 11, it is a work flow diagram of the vehicle SDK:

s1101: configuring loading parameters and a script list of the vehicle SDK;

s1102: the SDK pulls a corresponding script from the cloud platform according to the configuration;

s1103: caching the scripts, and executing the scripts one by one according to the execution sequence and frequency of the scripts one by one in a message manner;

s1104: connecting corresponding road side units according to the configuration;

s1105: judging whether the connection is successful; if the connection is successful, executing S1104; if the connection fails, re-entry is needed, namely, S1106 is executed;

s1106: receiving a message;

s1107: and uploading the required message according to the design.

It should be noted that, in the embodiment of the present invention, the SDK may trigger national standard 17-class basic demonstration scenes (such as forward collision warning, intersection collision prediction, forward congestion reminding, and the like) according to the parameter configuration interface, and select a policy for switching the nearby edge clouds according to the positions of the vehicle itself and the edge clouds. After the V2X vehicle-road cooperative platform in the edge cloud is connected, the event and early warning data of the simulated or real road-side equipment for demonstration can be acquired, and the verification of the equipment capacity is completed. When a simulation scene is displayed by a simulation platform and a vehicle-road cooperation platform running in an edge cloud, data of a vehicle-mounted device in the scene needs to be acquired according to a standardized coding format, communication frequency, communication mode and scene processing behavior, and the vehicle-mounted SDK defines a consistent program standard flow and behavior for realizing the vehicle-road cooperation scene, so that a large number of vehicle-mounted devices of different types have standardized scene processing capability for the vehicle-road cooperation platform service, the complexity brought by devices of different types is reduced, the realization cost of the vehicle-road cooperation platform is reduced, and a standardized quick verification entrance can be provided for verifying the vehicle-road cooperation capability or automatic driving capability of a vehicle.

As shown in fig. 10, optionally, the in-vehicle device executes the script to perform the following steps in a loop:

processing the scene event;

That is, during the execution of the script by the vehicle-mounted device, the following steps may be executed in a loop: receiving a scene event of messages such as RSI (remote vehicle identifier), RSM (road side equipment) and the like broadcasted and encapsulated by a remote vehicle (other vehicle-mounted equipment) or road side equipment, and simulating dynamic event driving data; processing the event; and reporting the driving data and the event processing result.

That is, each time the in-vehicle device completes execution of one travel script and completes processing of a scene event, a path of the execution script or a result of the scene event processing is asynchronously transmitted through the thread.

Optionally, the roadside apparatus is further configured to: selecting a second edge cloud corresponding to the network address closest to the position of the road side equipment through the built-in or configured network address of the edge cloud, and establishing connection with the second edge cloud; periodically acquiring a list of the vehicle-mounted devices in a second preset range and a communication address corresponding to each vehicle-mounted device, and establishing an association relation with a traffic road network or other device metadata.

Specifically, the scene engine in the real roadside SDK or the simulated roadside unit may select a nearby edge cloud and establish a connection according to an edge cloud network address within the area range obtained during initialization; after the connection is established, a list of vehicles and communication addresses in close range may be periodically obtained.

As shown in fig. 10, optionally, the roadside apparatus is further configured to cyclically execute the following steps within a preset period:

and broadcasting the alarm event to vehicles within a third preset range.

That is, within a preset period of the scene, the roadside device may execute the following steps by the main thread in a loop: receiving an alarm event of a vehicle-road cooperative platform in an edge cloud or autonomously generating the alarm event; judging the validity period of the event, and marking and deleting if the validity period is expired; broadcasting the event to in-proximity vehicles.

Optionally, the roadside apparatus is further configured to: periodically checking the validity of the alarm event; discarding the alarm event if the alarm event has expired.

As shown in fig. 12, it is a flowchart of the roadside SDK:

s1201: and the SDK is guided and loaded when the road side equipment unit is powered on, and initialization work inside the SDK is carried out. For example, operating space allocation, memory space checking, roadside equipment unit communication module checking, etc.;

s1202: the SDK continues to boot load according to the built-in parameters or modifies the operating parameters according to the remote interface configuration. For example, soft reset is performed through interface configuration to empty stored messages, edge cloud vehicle-road cooperation V2X platform addresses and login authentication information which need to be connected are set through configuration of edge cloud node parameters, and the like;

s1203: the SDK can trigger national standard 17-class basic demonstration scenes, such as road dangerous condition prompting, speed limit early warning, green wave vehicle speed guiding and the like, according to the parameter configuration interface;

s1204: the SDK collects events and data of road-side traffic facilities, such as the states of traffic signal lamps, identification sign information, camera data, hygrothermograph data and the like, through a device communication module of the road-side device unit; temporarily arriving at a device storage space, and preparing to report to a V2X platform;

s1205: the SDK selects a routing strategy of a nearby edge cloud according to a built-in edge cloud communication address table, and connects a V2X vehicle-road cooperation platform in the edge cloud with a simulated or real vehicle for demonstration;

s1206: the SDK tries to connect a V2X platform in the edge cloud node through a built-in or configured edge cloud connection address and authentication information; if the connection is unsuccessful, re-connecting after retrying for N seconds, namely executing S1205; if the connection is successful, executing S1207, periodically reporting heartbeat data packets, and keeping the online state of the equipment;

s1207: the SDK reports the collected data from the road side traffic facilities to an edge cloud V2X platform in the approaching range;

s1208: the SDK receives an event reminding message (RSI) and a safety message (RSM) from a V2X platform through the connection established with the edge cloud, and caches the messages in a device memory space after the messages are analyzed;

it should be noted that the vehicle-road cooperation platform generates a road event or early warning information after calculation, and finally pushes the road event or early warning information to the vehicle-mounted device to complete verification of the capability of the road-side device.

S1209: periodically checking the validity of the message; if yes, go to S1210; if not, discarding the message; for example, whether an intersection congestion event expires, and the like, and if so, the message is discarded;

s1210: the SDK periodically broadcasts the cached message to nearby running vehicles through a wireless network after the message is coded, and if the vehicle receives the message, the message is reported to the V2X platform, so that the V2X platform can perform statistical analysis on the aspects of message receiving, message utilization rate and the like;

it should be noted that when the simulation scene is displayed by the simulation platform and the vehicle-road cooperation platform running in the edge cloud, data of the road side device in the scene needs to be obtained according to a standardized encoding format, communication frequency, communication mode and scene processing behavior. The roadside SDK defines consistent program standard flows and behaviors for realizing a vehicle-road cooperation scene, so that a large number of roadside devices of different types have standardized scene processing capacity for the vehicle-road cooperation platform service, the complexity brought by the devices of different types is reduced, the cost for realizing the vehicle-road cooperation platform is reduced, and meanwhile, a standardized quick verification entrance is provided for verifying the vehicle-road cooperation capacity of the roadside devices or assisting in verifying the automatic driving vehicle.

In addition, the roadside device can continuously optimize the efficiency of information delivery of the vehicle event information and the vehicle event information in the edge cloud cooperative platform and the running vehicle in the scene execution process. For example, the detection, tracking and monitoring of the road end to the traffic participants can be optimized through a deep learning algorithm, and the judgment time delay of scene events such as road congestion and danger is reduced.

According to the embodiment of the invention, edge cloud cooperation and vehicle-road cooperation are realized, and the equipment simulation environment is realized on the MEC edge cloud so as to provide simulation interaction of road side equipment and vehicle-mounted equipment close to a real environment for a vehicle-road cooperation platform. The edge cloud is cooperated, an MEC multi-access edge cloud operation simulation environment close to the road side equipment and the vehicle-mounted equipment is adopted, messages such as BSM, MAP, SPAT, RSI and RSM can be interacted with the road side equipment and the vehicle-mounted equipment at a high speed with low time delay, and if a 5G NR technology is combined, millions of real equipment access and message processing capabilities can be supported at an edge cloud. The method comprises the following steps that (1) vehicle-road cooperation, an MEC multi-access edge cloud provides shared infrastructure, configuration information and a simulation behavior library required by simulation for equipment and vehicle-road cooperation application in an area range; and accessing simulation (or real) equipment data on the MEC edge cloud according to the configuration information, designing and operating a simulation scene, dynamically loading according to scene configuration in the operation process and simulating by combining corresponding behaviors in the simulation behavior library so as to verify the data collection capacity, the communication capacity, the data fusion processing capacity, the behavior decision capacity and the cooperation capacity with different platforms or applications of the vehicle-mounted equipment, the road side equipment, the vehicle-road cooperation platform and the three-party platform in each scene of vehicle-road cooperation. The embodiment of the invention supports the cooperative data processing of simulation and real equipment, provides the capabilities of elastic expansion, distributed clustering, caching, artificial intelligence and big data processing, enhances the support to various places and local services, can effectively reduce network delay, and provides certain help and support for better developing intelligent traffic services in the follow-up process.

In the embodiment of the invention, the multilateral and multiple dependencies of the system are subjected to architecture layering, and complete closed-loop service logic and multi-device SDK are provided for various external dependencies to be subjected to a solution which can be split, simulated and truly interacted. The business entities (such as roadside equipment and vehicle-mounted equipment) depended by any party can be simulated and embedded into the whole vehicle-road cooperative system through single or all the business entities to ensure the stable operation of the system, so that the problems of overlong links, complex data sources, different data formats, difficult positioning problem and strong dependence on external environment and conditions in project development, deployment and testing are solved, and the communication noise in the process of butting equipment is solved. Decoupling of each layer in the vehicle-road cooperative overall environment realizes characteristics of rapid development, transparent data, high customization and high availability.

As shown in fig. 13, an embodiment of the present invention provides an analog simulation method applied to an edge cloud, including:

s1301: the method comprises the steps of collecting first data of road side equipment and second data of vehicle-mounted equipment, and carrying out simulation of a vehicle-road cooperative environment according to configuration information, the first data and the second data to obtain a simulation result.

According to the simulation method of the embodiment, the data of the road side equipment and the data of the vehicle-mounted equipment are collected, the simulation of the vehicle-road coordination environment is carried out on the edge cloud, events and conditions which are not easy to create in the real world can be provided, the problem that a conventional vehicle-road coordination platform needs to intervene in the butt joint of a large number of real equipment in the development process can be solved, and therefore debugging time and cost are saved.

Optionally, the simulation method further includes: and sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

executing the simulation scene to obtain at least one of the following:

Optionally, the simulation method further includes: and verifying the service capability of the vehicle-road cooperative system according to the simulation result.

Optionally, the simulation method further includes: collecting the configuration information;

wherein the configuration information comprises:

device metadata;

scene metadata;

path metadata.

Optionally, the edge cloud collecting the device metadata includes:

collecting device initial metadata;

verifying the initial metadata of the equipment;

Optionally, the device initial metadata comprises at least one of:

Optionally, the checking the device initial metadata includes:

and if the vehicle information data is unique, the verification is passed.

Optionally, the checking the device initial metadata includes:

checking the path end metadata;

Optionally, the checking the device initial metadata includes:

setting parameters and mutual exclusion conditions of the simulation events;

verifying the simulation event;

the simulation event is accurate;

Optionally, the scene metadata is collected, including at least one of:

editing and inputting third scripted data on the visual operation interface;

Optionally, collecting the path metadata comprises:

segmenting the path on the path to form a running point;

Optionally, the path is segmented, including at least one of:

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

Optionally, performing scene composition, including:

checking the scene event;

Optionally, the checking the scene event includes:

Optionally, executing the simulation scenario includes:

initializing a scene execution engine;

judging the type of the simulation scene according to parameter configuration or API call;

and executing the simulation scene according to the type.

Optionally, a scenario execution engine initialization is performed, including at least one of:

initializing a program space required by operation;

loading operation parameters;

connecting a local database, a cache or a message queue;

loading device metadata;

a network communication link is initialized.

Optionally, in a case that the type is a history playback fixed scene, executing the simulation scene includes:

and sending the scene recording data to the equipment.

Optionally, in a case that the type is an interactive fusion simulation scene, executing the simulation scene includes:

matching scripted data for the device.

Optionally, the simulation method further includes: and sending a dynamic perception map to the vehicle-mounted equipment and/or the simulated vehicle-mounted equipment within the edge cloud coverage range according to a simulation result.

To sum up, the simulation method of the embodiment implements the device simulation environment on the edge cloud to provide simulation interaction of the roadside device and the vehicle-mounted device close to the real environment for the vehicle-road cooperation platform, supports the simulation and real device cooperation data processing, can provide events and conditions which are not easy to create in the real world for the vehicle-road cooperation scene, and reduces the cost and risk of scene operation.

It should be noted that, when the method is applied to the edge cloud in the vehicle-road coordination system, each process can be realized, and the same technical effect can be achieved.

As shown in fig. 14, an embodiment of the present invention provides an analog simulation method applied to a core cloud, including:

s1401: and providing routing information for access of roadside equipment and vehicle-mounted equipment in each area range to the edge cloud.

The simulation method of the embodiment can provide routing information, so that the road side equipment and the vehicle-mounted equipment can be quickly and nearby accessed to the edge cloud.

Optionally, the simulation method further includes:

In summary, the simulation method according to the embodiment establishes communication with the edge cloud, and can provide functions such as edge collaborative computing scheduling and multi-level computing capability scheduling in corresponding ranges in an area and a global range. By performing fusion calculation on the traffic events generated by the simulation (or real) equipment accessing the edge cloud, analysis and prediction of traffic service scenes with relatively low service delay requirements can be realized, thereby guiding the planning of traffic infrastructure.

It should be noted that, when the method is applied to the core cloud in the vehicle-road coordination system, each process that can be realized can achieve the same technical effect, and for avoiding repetition, the method is not described herein again.

As shown in fig. 15, an embodiment of the present invention provides an analog simulation method applied to roadside equipment, including:

s1501: establishing communication with an edge cloud, and providing first data for the edge cloud;

s1502: making a behavior decision according to the simulation result of the edge cloud;

According to the simulation method of the embodiment, the roadside SDK which is consistent with the behavior and communication mode of the simulation roadside device is adopted, so that the roadside device can inherit the capability of realizing the simulation of the roadside device, and a behavior decision can be made according to the simulation result of the edge cloud.

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the simulation method further includes:

in a preset period, circularly executing the following steps:

and broadcasting the alarm event to vehicles within a third preset range.

Optionally, the simulation method further includes:

periodically checking the validity of the alarm event;

discarding the alarm event if the alarm event has expired.

To sum up, in the analog simulation method of this embodiment, by using the roadside SDK that is consistent with the behavior and communication mode of the simulated roadside device, the roadside device can inherit the capability of implementing the simulated roadside device, such as the simulated scene capability, the edge cloud communication capability, the vehicle-end broadcasting capability, and the like, thereby solving the problem that the communication process is tedious and full of noise due to numerous participants in the design and development process of the common vehicle-road cooperative system, and saving the development cost and the development cycle.

It should be noted that, when the method is applied to the roadside device in the vehicle-road cooperation system, each process can be realized, and the same technical effect can be achieved.

As shown in fig. 16, an embodiment of the present invention provides an analog simulation method applied to a vehicle-mounted device, including:

s1601: establishing communication with an edge cloud, providing second data for the edge cloud, and making a behavior decision according to a simulation result of the edge cloud;

According to the simulation method of the embodiment, the vehicle-mounted SDK which is consistent with the behavior and communication mode of the simulation vehicle-mounted equipment is adopted, so that the vehicle-mounted equipment can inherit the capability of realizing the simulation vehicle-mounted equipment, and a behavior decision can be made according to the simulation result of the edge cloud.

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

Optionally, the establishing communication with the edge cloud includes:

receiving a network address of the edge cloud sent by a core cloud;

Optionally, the providing second data for the edge cloud includes:

and uploading the second data to the edge cloud according to the first message.

processing the scene event;

To sum up, in the simulation method of this embodiment, by using the vehicle-mounted SDK that is consistent with the behavior and communication mode of the simulated vehicle-mounted device, the vehicle-mounted device can inherit the capability of implementing the simulated vehicle-mounted device, such as the simulated scene capability, the early warning decision capability, and the like, and can ensure that the real device can implement 17 vehicle-road collaborative typical application scenes defined by the national standard, thereby avoiding the too complicated network environment influence and hardware requirements, and better solving the cost problems in various aspects in the life cycle of the vehicle-road simulation system.

It should be noted that, when the method is applied to the vehicle-mounted device in the vehicle-road coordination system, each process can be realized, and the same technical effect can be achieved.

As shown in fig. 17, an embodiment of the present invention provides an analog simulation apparatus applied to an edge cloud, including:

the simulation module 1701 is configured to collect first data of the road side device and second data of the vehicle-mounted device, and perform simulation of the vehicle-road collaborative environment according to the configuration information, the first data, and the second data to obtain a simulation result.

Optionally, the analog simulation apparatus further includes:

and the first sending module is used for sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

Optionally, the simulation module 1701 includes:

the scene arrangement submodule is used for arranging scenes according to the configuration information, the first data and the second data to form a simulation scene;

a scene execution submodule, configured to execute the simulation scene, and obtain at least one of:

Optionally, the analog simulation apparatus further includes:

and the second sending module is used for sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

Optionally, the analog simulation apparatus further includes:

and the verification module is used for verifying the service capability of the vehicle-road cooperative system according to the simulation result.

Optionally, the verification module comprises:

and the verification sub-module is used for verifying the service capability of the vehicle-road cooperative system by comparing whether the first data and the first simulation data under the same simulation scene are the same or not and comparing whether the second data and the second simulation data under the same simulation scene are the same or not.

Optionally, the analog simulation apparatus further includes:

a collecting module for collecting the configuration information;

wherein the configuration information comprises:

device metadata;

scene metadata;

path metadata.

Optionally, the collection module comprises:

a first collecting submodule for collecting device initial metadata;

the first checking submodule is used for checking the initial metadata of the equipment;

and the first storage submodule is used for storing the initial metadata of the equipment into a database as the metadata of the equipment under the condition that the verification is passed.

Optionally, the device initial metadata comprises at least one of:

Optionally, the collection module further comprises:

the second checking sub-module is used for carrying out uniqueness checking on the vehicle information data in the vehicle-end metadata under the condition that the initial metadata of the equipment is the vehicle-end metadata;

and the result determination submodule is used for passing the verification if the vehicle information data is unique.

Optionally, the first check submodule includes:

a first setting unit, configured to set an action range of roadside traffic equipment in the roadside equipment information when the equipment initial metadata is roadside metadata;

the second setting unit is used for setting the GPS coordinates of the road side traffic equipment or setting the position relation between the road side traffic equipment and roads on a map;

the first checking unit is used for checking the road end metadata;

a first result determining unit, configured to pass the verification if the route end metadata satisfies a first preset condition;

Optionally, the first check submodule further includes:

a first selecting unit, configured to select, when the device initial metadata is simulation event metadata, a device associated with the simulation event; wherein the equipment comprises the roadside equipment, the on-board equipment, the simulation roadside equipment and the simulation on-board equipment;

the second selection unit is used for selecting the type of the simulation event; the types of different simulation events correspond to different simulation scenes;

the setting unit is used for setting parameters and mutual exclusion conditions of the simulation events;

the second verification unit is used for verifying the simulation event;

and the second result determining unit is used for passing the verification under the condition that the simulation event meets a second preset condition.

the simulation event is accurate;

Optionally, the first collection submodule comprises at least one of:

the first collection unit is used for receiving first scripted data uploaded manually; the first scripted data are scripted data formed by screening and processing third data uploaded by the road side equipment and the vehicle-mounted equipment; the third data includes behavior data of a vehicle and roadside device data related to the vehicle;

the second collection unit is used for acquiring fourth data of the road side equipment and the vehicle-mounted equipment through a vehicle-road cooperative platform on the edge cloud, and processing the fourth data to form second scripted data; wherein the fourth data includes all vehicles and roadside device data related to the vehicles;

the third collection unit is used for editing and inputting third scripted data on the visual operation interface;

Optionally, the first collection submodule further includes:

the loading unit is used for loading the self-defined dynamic path metadata and displaying the planned path through a map interface;

the segmentation unit is used for segmenting the path to form an operation point;

and the fourth collecting unit is used for collecting and summarizing the operating points and storing the operating points to form path metadata.

Optionally, the path is segmented, including at least one of:

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

Optionally, the scene orchestration submodule includes:

a first setting unit, configured to set a scene event on a path according to the path metadata and the scene metadata;

and the third selection unit is used for selecting a simulation vehicle and binding the path metadata with the simulation vehicle.

Optionally, the first setting unit includes:

the first processing subunit is used for loading self-defined dynamic path metadata and displaying a planned path through a map interface;

the second processing subunit is used for setting the scene event on the path; wherein, the scene event is formed by freely combining basic scenes;

the checking subunit is used for checking the scene event;

a result confirmation subunit, configured to add the scene event to the queue to be stored if the verification is successful;

and the storage subunit is used for storing the scene events in the queue to be stored after the scene events on the path are recorded.

Optionally, the checking the scene event includes:

Optionally, the scene execution sub-module includes:

the initialization unit is used for initializing a scene execution engine;

the judging unit is used for judging the type of the simulation scene according to parameter configuration or application program interface API calling;

and the execution unit is used for executing the simulation scene according to the type.

initializing a program space required by operation;

loading operation parameters;

connecting a local database, a cache or a message queue;

loading device metadata;

a network communication link is initialized.

Optionally, the execution unit includes:

the selection subunit is used for selecting the equipment which needs to execute the simulation scene; the equipment comprises the road side equipment, the vehicle-mounted equipment, the simulation road side equipment and the simulation vehicle-mounted equipment;

the first loading subunit is used for loading the stored historical scene metadata from the database; wherein the historical scene metadata comprises device operation data and scene recording data;

and the sending subunit is used for sending the scene recording data to the equipment.

Optionally, the execution unit further includes:

the second loading subunit is used for loading the associated scene metadata according to the type of the current equipment; the scene metadata comprise equipment basic information and a regional traffic road relation network; the equipment comprises the road side equipment, the vehicle-mounted equipment, the simulation road side equipment and the simulation vehicle-mounted equipment;

a matching subunit, configured to match scripted data for the device.

Optionally, the analog simulation apparatus further includes:

and the third sending module is used for sending a dynamic perception map to the vehicle-mounted equipment and/or the simulated vehicle-mounted equipment within the edge cloud coverage range according to a simulation result.

The device realizes the simulation interaction of the equipment simulation environment on the edge cloud so as to provide roadside equipment and vehicle-mounted equipment which are close to the real environment for the vehicle-road cooperative platform, supports the simulation and real equipment cooperative data processing, can provide events and conditions which are not easy to create in the real world for the vehicle-road cooperative scene realization, and reduces the cost and risk of scene operation.

The simulation device provided in the embodiment of the present application can implement each process implemented in the method embodiment of fig. 13, and can achieve the same technical effect, and is not described here again to avoid repetition.

As shown in fig. 18, an embodiment of the present invention provides an analog simulation apparatus applied to a core cloud, including:

the routing module 1801 is configured to provide routing information for access of roadside devices and vehicle-mounted devices in each area range to the edge cloud.

Optionally, the analog simulation apparatus further includes:

and the first processing module is used for establishing communication with the edge cloud in the whole area range and carrying out big data comprehensive analysis and prediction on the traffic road condition in the whole area range.

The device establishes communication with the edge cloud, and can provide functions of edge collaborative computing scheduling, multi-level computing capability scheduling and the like in corresponding ranges in a region and a global range. By performing fusion calculation on the traffic events generated by the simulation (or real) equipment accessing the edge cloud, analysis and prediction of traffic service scenes with relatively low service delay requirements can be realized, thereby guiding the planning of traffic infrastructure.

The simulation device provided in the embodiment of the present application can implement each process implemented by the method embodiment of fig. 14, and can achieve the same technical effect, and for avoiding repetition, details are not repeated here.

As shown in fig. 19, an embodiment of the present invention provides an analog simulation apparatus applied to roadside devices, including:

a first communication module 1901, configured to establish communication with an edge cloud and provide first data for the edge cloud;

a first decision module 1902, configured to make a behavior decision according to a simulation result of the edge cloud;

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the analog simulation apparatus further includes:

the second processing module is used for selecting a second edge cloud corresponding to the network address closest to the position of the road side equipment through the built-in or configured network address of the edge cloud, and establishing connection with the second edge cloud;

and the third processing module is used for periodically acquiring a list of the vehicle-mounted equipment in a second preset range and a communication address corresponding to each vehicle-mounted equipment, and establishing an association relation with a traffic road network or other equipment metadata.

Optionally, the analog simulation apparatus further includes:

the execution module is used for circularly executing the following steps in a preset period:

and broadcasting the alarm event to vehicles within a third preset range.

Optionally, the analog simulation apparatus further includes:

a detection module for periodically checking the validity of the alarm event;

and the fourth processing module is used for discarding the alarm event under the condition that the alarm event is expired.

The device adopts the roadside SDK consistent with the behavior and the communication mode of the simulation roadside equipment, so that the roadside equipment can inherit the capability of realizing the simulation of the roadside equipment, such as the simulation scene capability, the edge cloud communication capability, the vehicle-end broadcasting capability and the like, the problems that the communication process is long and is full of noise due to numerous participants in the design and development process of a common vehicle-road cooperative system are solved, and the development cost and the development cycle can be saved.

The simulation device provided in the embodiment of the present application can implement each process implemented in the method embodiment of fig. 15, and can achieve the same technical effect, and for avoiding repetition, details are not repeated here.

As shown in fig. 20, an embodiment of the present invention provides an analog simulation apparatus applied to an in-vehicle device, including:

a second communication module 2001, configured to establish communication with an edge cloud and provide second data for the edge cloud;

a second decision module 2002, configured to make a behavior decision according to the simulation result of the edge cloud;

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

Optionally, the second communication module 2001 includes:

the receiving submodule is used for receiving the network address of the edge cloud sent by the core cloud;

and the first processing submodule is used for selecting a first edge cloud corresponding to the network address closest to the position of the vehicle-mounted equipment from the network addresses and establishing connection with the first edge cloud.

Optionally, the second communication module 2001 further includes:

the second processing submodule is used for pulling corresponding scripted data from the edge cloud according to the SDK configuration, connecting corresponding road side equipment according to the SDK configuration, and receiving a first message from the road side equipment after the connection is successful;

the third processing submodule is used for decoding the scripted data and sequentially executing the first message and the script according to the execution sequence and the frequency of the script;

and the uploading sub-module is used for uploading the second data to the edge cloud according to the first message.

Optionally, when the third processing sub-module is used for the vehicle-mounted device to execute the script, the following steps are executed in a loop:

processing the scene event;

The device, through adopting the on-vehicle SDK consistent with the behavior and the communication mode of the simulation vehicle-mounted equipment, enables the vehicle-mounted equipment to inherit the capability of realizing the simulation vehicle-mounted equipment, such as simulation scene capability, early warning decision capability and the like, can ensure that the real equipment can realize 17 vehicle-road cooperative typical application scenes defined by national standards, avoids excessively complicated network environment influence and hardware requirements, and better solves the cost problems of all aspects in the life cycle of the vehicle-road simulation system.

The simulation device provided in the embodiment of the present application can implement each process implemented in the method embodiment of fig. 16, and can achieve the same technical effect, and for avoiding repetition, details are not repeated here.

As shown in fig. 21, an embodiment of the present invention provides a communication device, which is an edge cloud 2100, including a processor 2110; the processor 2110 is configured to collect first data of road side equipment and second data of vehicle-mounted equipment, and perform simulation of a vehicle-road collaborative environment according to configuration information, the first data and the second data to obtain a simulation result.

Optionally, a transceiver 2120 is further included, the transceiver 2120 being configured to: and sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

Optionally, when performing simulation of the vehicle-road collaborative environment according to the configuration information, the first data, and the second data to obtain a simulation result, the processor 2110 is specifically configured to:

executing the simulation scene to obtain at least one of the following:

Optionally, the transceiver 2120 is further configured to: and sending the first data, the second data and the road condition data obtained through the edge cloud computing to a core cloud.

Optionally, the processor 2110 is further configured to: and verifying the service capability of the vehicle-road cooperative system according to the simulation result.

Optionally, the processor 2110, according to the simulation result, verifies a service capability of the vehicle-road cooperative system, and is specifically configured to:

Optionally, the processor 2110 is further configured to: collecting the configuration information;

wherein the configuration information comprises:

device metadata;

scene metadata;

path metadata.

Optionally, when the processor 2110 is used for cloud collection of the device metadata, the processor 2110 is specifically configured to:

collecting device initial metadata;

verifying the initial metadata of the equipment;

Optionally, the device initial metadata comprises at least one of:

Optionally, when the processor 2110 is configured to check the device initial metadata, the packet is specifically configured to:

and if the vehicle information data is unique, the verification is passed.

Optionally, when the processor 2110 is configured to check the device initial metadata, specifically, to:

checking the path end metadata;

setting parameters and mutual exclusion conditions of the simulation events;

verifying the simulation event;

the simulation event is accurate;

Optionally, the processor 2110, when configured to collect the scene metadata, includes at least one of:

editing and inputting third scripted data on the visual operation interface;

Optionally, the processor 2110, when configured to collect the path metadata, includes:

segmenting the path on the path to form a running point;

Optionally, the processor 2110, when used for segmenting a segment on a path, comprises at least one of:

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

Optionally, the processor 2110, when configured to perform scene programming, includes:

Optionally, when the processor 2110 is configured to set a scene event on a path according to the path metadata and the scene metadata, the processor 2110 includes:

checking the scene event;

Optionally, when the processor 2110 is configured to check the scene event, the processor 2110 includes:

Optionally, the processor 2110, when configured to execute the simulation scenario, includes:

initializing a scene execution engine;

and executing the simulation scene according to the type.

Optionally, the processor 2110, when configured to perform the scenario execution engine initialization, includes at least one of:

initializing a program space required by operation;

loading operation parameters;

connecting a local database, a cache or a message queue;

loading device metadata;

a network communication link is initialized.

Optionally, the processor 2110, when executing the simulation scenario when the type is a history playback fixed scenario, includes:

and sending the scene recording data to the equipment.

Optionally, the processor 2110, when the type is an interactive fusion simulation scenario, is configured to execute the simulation scenario, including:

matching scripted data for the device.

Optionally, the processor 2110 is further configured to: and sending a dynamic perception map to the vehicle-mounted equipment and/or the simulated vehicle-mounted equipment within the edge cloud coverage range according to a simulation result.

The communication equipment realizes the simulation interaction of the equipment simulation environment on the edge cloud so as to provide roadside equipment and vehicle-mounted equipment which are close to the real environment for the vehicle-road cooperative platform, supports the simulation and real equipment cooperative data processing, can provide events and conditions which are not easy to create in the real world for the vehicle-road cooperative scene realization, and reduces the cost and risk of scene operation.

The embodiment of the invention provides communication equipment, which is a core cloud and comprises a processor; the processor is used for providing routing information for access edge clouds of the road side equipment and the vehicle-mounted equipment in each area range.

Optionally, the processor is further configured to:

It should be noted that the structure of the core cloud in this embodiment is similar to that of the edge cloud shown in fig. 21.

The communication equipment establishes communication with the edge cloud, and can provide functions of edge collaborative computing scheduling, multi-level computing capability scheduling and the like in corresponding ranges in regions and global ranges. By performing fusion calculation on the traffic events generated by the simulation (or real) equipment accessing the edge cloud, analysis and prediction of traffic service scenes with relatively low service delay requirements can be realized, thereby guiding the planning of traffic infrastructure.

As shown in fig. 22, an embodiment of the present invention provides a communication apparatus, which is an in-vehicle apparatus 2200, including: a transceiver 2210 and a processor 2220;

wherein the transceiver 2210 is configured to establish communication with an edge cloud, providing second data for the edge cloud;

the processor 2220 is configured to make a behavior decision according to a simulation result of the edge cloud;

Optionally, the second data comprises at least one of:

vehicle geographic location information;

a basic safety message BSM of the vehicle driving state;

vehicle sensor data.

Optionally, the processor 2220, when configured to establish communication with an edge cloud, includes:

receiving a network address of the edge cloud sent by a core cloud;

Optionally, the processor 2220, when configured to provide the second data for the edge cloud, includes:

and uploading the second data to the edge cloud according to the first message.

Optionally, the processor 2220, when configured to execute the script, loops back to:

processing the scene event;

According to the communication equipment, the vehicle-mounted SDK which is consistent with the behavior and the communication mode of the simulation vehicle-mounted equipment is adopted, so that the vehicle-mounted equipment can inherit the capability of realizing the simulation vehicle-mounted equipment, such as simulation scene capability, early warning decision capability and the like, the fact that the real equipment can realize 17 vehicle-road cooperative typical application scenes defined by national standards can be guaranteed, the excessively complex network environment influence and hardware requirements are avoided, and the cost problems in all aspects of the life cycle of a vehicle-road simulation system are better solved.

The embodiment of the invention provides communication equipment, which is roadside equipment and comprises a processor and a transceiver;

Optionally, the first data comprises at least one of:

roadside traffic device data;

MAP message MAP;

traffic light phase and timing messages SPAT;

roadside traffic time messages;

road side information RSI;

roadside safety messages RSM.

Optionally, the processor is further configured to:

in a preset period, circularly executing the following steps:

and broadcasting the alarm event to vehicles within a third preset range.

Optionally, the processor is further configured to:

periodically checking the validity of the alarm event;

discarding the alarm event if the alarm event has expired.

According to the communication equipment, the roadside SDK which is consistent with the behavior and the communication mode of the simulation roadside equipment is adopted, so that the roadside equipment can inherit the capability of realizing the simulation roadside equipment, such as simulation scene capability, edge cloud communication capability, vehicle-end broadcasting capability and the like, the problems that in the design and development process of a common vehicle-road cooperative system, due to the fact that the number of participants is large, the communication process is long and noise is full are solved, and the development cost and the development cycle can be saved.

Note that the structure of the roadside apparatus in this embodiment is similar to that of the vehicle-mounted apparatus shown in fig. 22.

An edge cloud according to another embodiment of the present invention, as shown in fig. 23, includes a transceiver 2310, a processor 2300, a memory 2320, and a program or instructions stored in the memory 2320 and executable on the processor 2300; when the processor 2300 executes the program or the instructions, the above-mentioned simulation method applied to the edge cloud is implemented.

The transceiver 2310 is used for receiving and transmitting data under the control of the processor 2300.

In FIG. 23, among other things, the bus architecture may include any number of interconnected buses and bridges, with one or more processors, represented by processor 2300, and various circuits, represented by memory 2320, being linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface. The transceiver 2310 may be a number of elements including a transmitter and a receiver that provide a means for communicating with various other apparatus over a transmission medium. The processor 2300 is responsible for managing the bus architecture and general processing, and the memory 2320 may store data used by the processor 2300 in performing operations.

The core cloud according to another embodiment of the present invention has a structure similar to that of the edge cloud shown in fig. 23, and includes a transceiver 2310, a processor 2300, a memory 2320, and a program or instructions stored in the memory 2320 and executable on the processor 2300; when the processor 2300 executes the program or the instructions, the above-mentioned simulation method applied to the core cloud is implemented.

An in-vehicle device according to another embodiment of the present invention, as shown in fig. 24, includes a transceiver 2410, a processor 2400, a memory 2420, and a program or instructions stored in the memory 2420 and executable on the processor 2400; when the processor 2400 executes the program or the instruction, the above-described analog simulation method applied to the vehicle-mounted device is implemented.

The transceiver 2410 for receiving and transmitting data under the control of the processor 2400.

Where in fig. 24, the bus architecture may include any number of interconnected buses and bridges, with one or more processors, represented by the processor 2400, and various circuits, represented by the memory 2420, being linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface. The transceiver 2410 may be a plurality of elements including a transmitter and a receiver that provide a means for communicating with various other apparatus over a transmission medium. The user interface 2430 may also be an interface capable of interfacing with a desired device externally, for different user devices, including but not limited to a keypad, a display, a speaker, a microphone, a joystick, etc.

The processor 2400 is responsible for managing a bus architecture and general processing, and the memory 2420 may store data used by the processor 2400 in performing operations.

A roadside apparatus according to another embodiment of the present invention, which has a structure similar to that of the vehicle-mounted apparatus shown in fig. 24, includes a transceiver 2410, a processor 2400, a memory 2420, and a program or instructions stored in the memory 2420 and executable on the processor 2400; when the processor 2400 executes the program or the instruction, the analog simulation method applied to the roadside device is implemented.

The readable storage medium of the embodiment of the present invention stores a program or an instruction thereon, and the program or the instruction when executed by the processor implements the steps in the analog simulation method described above, and can achieve the same technical effects, and the details are not repeated here to avoid repetition. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

It is further noted that the terminals described in this specification include, but are not limited to, smart phones, tablets, etc., and that many of the functional components described are referred to as modules in order to more particularly emphasize their implementation independence.

In embodiments of the present invention, modules may be implemented in software for execution by various types of processors. An identified module of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions which may, for instance, be constructed as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may comprise disparate instructions stored in different bits which, when joined logically together, comprise the module and achieve the stated purpose for the module.

Indeed, a module of executable code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Likewise, operational data may be identified within the modules and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network.

When a module can be implemented by software, considering the level of existing hardware technology, a module implemented by software may build a corresponding hardware circuit to implement a corresponding function, without considering cost, and the hardware circuit may include a conventional Very Large Scale Integration (VLSI) circuit or a gate array and an existing semiconductor such as a logic chip, a transistor, or other discrete components. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like.

The exemplary embodiments described above are described with reference to the drawings, and many different forms and embodiments of the invention may be made without departing from the spirit and teaching of the invention, therefore, the invention is not to be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In the drawings, the size and relative sizes of elements may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Unless otherwise indicated, a range of values, when stated, includes the upper and lower limits of the range and any subranges therebetween.

While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A vehicle-road coordination system, comprising:

2. The vehicle-road coordination system according to claim 1, wherein the performing, by the edge cloud according to the configuration information, the first data, and the second data, simulation of the vehicle-road coordination environment includes:

executing the simulation scene to obtain at least one of the following:

3. The vehicle-road coordination system according to claim 2, wherein said edge cloud is further configured to:

verifying the service capability of the vehicle-road cooperative system according to the simulation result; wherein, the verifying the service capability of the vehicle-road cooperative system according to the simulation result comprises:

4. The vehicle-road coordination system according to claim 2, wherein said edge cloud is further configured to collect said configuration information;

wherein the configuration information comprises:

device metadata;

scene metadata;

path metadata.

5. The vehicle road coordination system according to claim 4, wherein said edge cloud collects said device metadata, comprising:

collecting device initial metadata;

verifying the initial metadata of the equipment;

under the condition that the verification is passed, storing the initial metadata of the equipment into a database as the metadata of the equipment;

wherein the device initial metadata comprises at least one of:

6. The vehicle-road coordination system according to claim 5, wherein said edge cloud checks said device initial metadata, comprising:

checking the path end metadata;

the roadside traffic device includes at least one of: the system comprises an RSU, a traffic signal lamp, a laser radar, a millimeter wave radar, a high-definition camera and a temperature and humidity sensor;

the method comprises the following steps that the road end metadata meet a first preset condition:

7. The vehicle-road coordination system according to claim 5, wherein said edge cloud checks said device initial metadata, comprising:

setting parameters and mutual exclusion conditions of the simulation events;

verifying the simulation event;

when the simulation event meets a second preset condition, the verification is passed;

wherein the parameters include event level, execution time, period, location, and value;

the simulation event meets a second preset condition, which at least comprises the following three items:

the simulation event is accurate;

8. The vehicle road coordination system according to claim 4, wherein said edge cloud collects said scene metadata, comprising at least one of:

editing and inputting third scripted data on the visual operation interface;

9. The vehicle road coordination system according to claim 4, wherein said edge cloud collects said path metadata, comprising:

segmenting the path on the path to form a running point;

collecting and summarizing the operating points and storing the operating points to form path metadata;

the edge cloud segments the path, and the edge cloud segments the path and comprises at least one of the following items:

equally dividing the road sections according to the distance;

segmenting the road section according to the acceleration;

segmenting the road sections according to the angles;

and segmenting the road section according to the angle and the acceleration.

10. The vehicle-road coordination system according to claim 4, wherein said edge cloud performs scene editing, including:

11. The vehicle-road coordination system according to claim 10, wherein the edge cloud sets a scene event on a path according to the path metadata and the scene metadata, and includes:

checking the scene event;

after the scene event on the path is recorded, storing the scene event in the queue to be stored;

wherein the verifying the scene event by the edge cloud comprises:

12. The vehicle-road coordination system according to claim 2, wherein said simulation scenario comprises a historical playback fixed scenario and an interactive fusion simulation scenario;

wherein the edge cloud executes the simulation scenario, including:

initializing a scene execution engine;

and executing the simulation scene according to the type.

13. The vehicle-road coordination system according to claim 12, wherein in a case where the type is a historical playback fixed scene, the edge cloud executes the simulation scene including:

and sending the scene recording data to the equipment.

14. The vehicle-road coordination system according to claim 12, wherein in a case where the type is an interactive fusion simulation scenario, the executing of the simulation scenario by the edge cloud comprises:

matching scripted data for the device.

15. The vehicle-road coordination system according to claim 1, wherein said vehicle-mounted device provides said second data to said edge cloud, comprising:

pulling corresponding scripted data from the edge cloud according to the SDK configuration, an

Connecting corresponding road side equipment according to the SDK configuration, and receiving a first message from the road side equipment after the connection is successful;

and uploading the second data to the edge cloud according to the first message.

16. An analog simulation method is applied to an edge cloud, and is characterized by comprising the following steps:

17. The simulation method according to claim 16, wherein the performing simulation of the vehicle-road cooperative environment according to the configuration information, the first data, and the second data to obtain a simulation result includes:

executing the simulation scene to obtain at least one of the following:

18. An analog simulation method is applied to road side equipment and is characterized by comprising the following steps:

19. An analog simulation method is applied to vehicle-mounted equipment and is characterized by comprising the following steps:

20. An analog simulation device applied to an edge cloud, comprising:

21. An analog simulation device is applied to road side equipment and is characterized by comprising:

22. An analog simulation device is applied to vehicle-mounted equipment and is characterized by comprising:

23. An edge cloud, comprising: a processor;

the processor is used for collecting first data of the road side equipment and second data of the vehicle-mounted equipment, and carrying out simulation of the vehicle-road cooperative environment according to configuration information, the first data and the second data to obtain a simulation result.

24. A roadside apparatus characterized by comprising: a transceiver and a processor;

25. An in-vehicle apparatus, characterized by comprising: a transceiver and a processor;

the transceiver is used for establishing communication with an edge cloud and providing second data for the edge cloud;

26. A communication device, comprising: a transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; wherein the processor, when executing the program or instructions, implements the simulation method of any of claims 16 to 17; or implementing the simulation method of claim 18; or implementing an analog simulation method according to claim 19.

27. A readable storage medium having stored thereon a program or instructions which, when executed by a processor, carry out the steps in the simulation method of any of claims 16 to 17, or carry out the steps in the simulation method of claim 18, or carry out the steps in the simulation method of claim 19.