WO2023236562A1 - 基于数字孪生DaaS平台的自动驾驶安全方法及*** - Google Patents

基于数字孪生DaaS平台的自动驾驶安全方法及*** Download PDF

Info

Publication number
WO2023236562A1
WO2023236562A1 PCT/CN2023/074633 CN2023074633W WO2023236562A1 WO 2023236562 A1 WO2023236562 A1 WO 2023236562A1 CN 2023074633 W CN2023074633 W CN 2023074633W WO 2023236562 A1 WO2023236562 A1 WO 2023236562A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
driving
digital twin
obstacle
passenger
Prior art date
Application number
PCT/CN2023/074633
Other languages
English (en)
French (fr)
Inventor
刘天琼
Original Assignee
深圳市爱云信息科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市爱云信息科技有限公司 filed Critical 深圳市爱云信息科技有限公司
Publication of WO2023236562A1 publication Critical patent/WO2023236562A1/zh

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0011—Planning or execution of driving tasks involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • B60W60/0016—Planning or execution of driving tasks specially adapted for safety of the vehicle or its occupants
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

Definitions

  • the present invention relates to the field of artificial intelligence technology, and in particular to an autonomous driving safety method and system based on a digital twin DaaS platform.
  • Existing self-driving cars use sensors installed on the periphery to obtain the road conditions around the self-driving car to drive the self-driving car.
  • the sensors on the periphery of the self-driving car have certain area restrictions and can only obtain the road conditions around the self-driving car.
  • Self-driving cars are controlled by road conditions.
  • Self-driving cars are unable to obtain longer-distance road conditions, which leaves less time for self-driving cars to respond in the event of an emergency.
  • the safety of passengers in self-driving cars is compromised. Therefore, how to improve the safety of passengers in self-driving cars, reduce traffic congestion and improve efficiency is an urgent problem.
  • the main purpose of the present invention is to propose an autonomous driving safety method and system based on the digital twin DaaS platform, aiming to solve the problems of how to improve the safety of passengers in autonomous vehicles, reduce traffic congestion, and improve efficiency.
  • the present invention provides an automatic driving safety method based on the digital twin DaaS platform.
  • the automatic driving safety method based on the digital twin DaaS platform includes the following steps:
  • the information and the dynamic target route generate driving instructions, and the driving is carried out according to the driving instructions.
  • the step of determining the dynamic target route includes:
  • Obtain the current traffic information issued by the satellite system update the traffic conditions in the electronic map according to the current traffic information, modify the dynamic planning route according to the updated electronic map and the destination information, and determine the dynamic target route.
  • the artificial intelligence digital twin DaaS platform generates driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route.
  • the step of driving according to the driving instructions includes:
  • driving parameters are adjusted to generate driving instructions, and driving is performed according to the driving instructions.
  • the artificial intelligence digital twin DaaS platform generates driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route.
  • the step includes:
  • the passenger's current mental state information is obtained through the virtual reality device, and the passenger's mental state report is generated based on the current mental state information through the artificial intelligence digital twin DaaS platform;
  • the artificial intelligence digital twin DaaS platform is used to generate driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route.
  • the step further includes:
  • the passenger's current physical status information is obtained through the virtual reality device, and the passenger's physical status report is generated based on the current physical status information through the artificial intelligence digital twin DaaS platform;
  • Driving is performed based on the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route.
  • the step of driving according to the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route includes:
  • the dynamic target route is modified according to the optimal treatment location information, and the vehicle is driven according to the modified target route, the first obstacle information and the second obstacle information.
  • the step includes:
  • the alarm information and the best treatment location information are sent to the preset alarm person, so that the preset alarm person can determine the passenger's location and respond in time.
  • the present invention also provides an automatic driving safety device based on the digital twin DaaS platform.
  • the automatic driving safety device based on the digital twin DaaS platform includes:
  • An acquisition module used to acquire destination information and generate a dynamically planned route based on the destination information
  • Modification module used to obtain the current road condition information issued by the satellite system, and perform the dynamic planning according to the current road condition information. Modify the route and determine the dynamic target route;
  • the driving module is used to obtain the first obstacle information issued by the satellite system, and collect the second obstacle information through the artificial intelligence Internet of Things platform, and use the artificial intelligence digital twin DaaS platform according to the first obstacle information and all the obstacles.
  • the second obstacle information and the dynamic target route are used to generate driving instructions, and driving is performed according to the driving instructions.
  • modification module is also used to:
  • Obtain the current traffic information issued by the satellite system update the traffic conditions in the electronic map according to the current traffic information, modify the dynamic planning route according to the updated electronic map and the destination information, and determine the dynamic target route.
  • the driving module is also used for:
  • driving parameters are adjusted to generate driving instructions, and driving is performed according to the driving instructions.
  • the driving module is also used for:
  • the passenger's current mental state information is obtained through the virtual reality device, and the passenger's mental state report is generated based on the current mental state information through the artificial intelligence digital twin DaaS platform;
  • the driving module is also used for:
  • the passenger's current physical status information is obtained through the virtual reality device, and the passenger's physical status report is generated based on the current physical status information through the artificial intelligence digital twin DaaS platform;
  • Driving is performed based on the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route.
  • the driving module is also used for:
  • the dynamic target route is modified according to the optimal treatment location information, and the vehicle is driven according to the modified target route, the first obstacle information and the second obstacle information.
  • the driving module is also used for:
  • the present invention also provides an autonomous driving safety system based on the digital twin DaaS platform.
  • the autonomous driving safety system based on the digital twin DaaS platform includes: a memory, a processor and a device stored on the memory.
  • An autonomous driving program can be run on the processor. When the autonomous driving program is executed by the processor, the steps of the autonomous driving safety method based on the digital twin DaaS platform are implemented as described above.
  • the present invention also provides a computer-readable storage medium, the computer-readable storage medium stores an automatic driving program, and when the automatic driving program is executed by the processor, the above-mentioned digital-based Steps in the Twin DaaS platform’s autonomous driving safety approach.
  • the autonomous driving safety method proposed by this invention based on the digital twin DaaS platform obtains destination information and generates dynamically planned routes based on the destination information; obtains current road condition information issued by the satellite system, and modifies the dynamically planned route based on the current road condition information.
  • Determine the dynamic target route obtain the first obstacle information issued by the satellite system, and collect the second obstacle information through the artificial intelligence IoT platform, and use the artificial intelligence digital twin DaaS platform according to the first obstacle information and the second obstacle information.
  • the dynamic target route to generate driving instructions, and drive according to the driving instructions; the present invention determines the dynamic target route based on the destination information and the current road condition information issued by the satellite system, and then obtains the longer-distance first obstacle information issued by the satellite system.
  • the artificial intelligence IoT platform collects the second obstacle information at a closer distance, generates driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route through the artificial intelligence digital twin DaaS platform, and drives according to the driving instructions. Improved safety for passengers in autonomous vehicles, reduced traffic congestion and improved efficiency.
  • Figure 1 is a schematic diagram of the equipment structure of the hardware operating environment involved in the embodiment of the present invention.
  • Figure 2 is a schematic flowchart of the first embodiment of the autonomous driving safety method based on the digital twin DaaS platform of the present invention.
  • Figure 1 is a schematic diagram of the equipment structure of the hardware operating environment involved in the embodiment of the present invention.
  • the device in this embodiment of the present invention may be a PC or a server device.
  • the device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002.
  • the communication bus 1002 is used to realize connection communication between these components.
  • the user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard).
  • the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • Network interface 1004 may optionally include standard Wired interface, wireless interface (such as WI-FI interface).
  • the memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory.
  • the memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.
  • the device structure shown in Figure 1 does not constitute a limitation of the device, and may include more or fewer components than shown, or combine certain components, or arrange different components.
  • memory 1005 which is a computer storage medium, may include an operating system, a network communication module, a user interface module and an automatic driving program.
  • the operating system is a program that manages and controls portable storage devices and software resources, and supports the operation of network communication modules, user interface modules, automatic driving programs, and other programs or software;
  • the network communication module is used to manage and control the network interface 1002;
  • user The interface module is used to manage and control the user interface 1003.
  • the storage device calls the automatic driving program stored in the memory 1005 through the processor 1001, and performs the following operations in various embodiments of the automatic driving safety method based on the digital twin DaaS platform.
  • Figure 2 is a schematic flow chart of the first embodiment of the autonomous driving safety method based on the digital twin DaaS platform of the present invention.
  • the method includes:
  • Step S10 Obtain destination information and generate a dynamically planned route based on the destination information
  • Step S20 Obtain the current road condition information issued by the satellite system, modify the dynamically planned route according to the current road condition information, and determine the dynamic target route;
  • Step S30 Obtain the first obstacle information issued by the satellite system, collect the second obstacle information through the artificial intelligence Internet of Things platform, and use the artificial intelligence digital twin DaaS platform according to the first obstacle information and the third obstacle information.
  • the obstacle information and the dynamic target route are used to generate driving instructions, and the vehicle is driven according to the driving instructions.
  • the autonomous driving safety method based on the digital twin DaaS platform in this embodiment is applied to the autonomous driving safety system of the autonomous vehicle based on the digital twin DaaS platform.
  • the autonomous driving safety system based on the digital twin DaaS platform is in conjunction with the artificial intelligence Internet of Things platform and artificial intelligence.
  • the intelligent digital twin DaaS platform communicates with the satellite system; for the convenience of description, the autonomous driving safety system based on the digital twin DaaS platform, referred to as the autonomous driving safety system, is used as an example; the autonomous driving safety system obtains the passenger information when the passengers get on the bus.
  • the input destination information generates a dynamically planned route based on the destination information; the autonomous driving safety system obtains the current road condition information issued by the satellite system, updates the road conditions in the electronic map based on the current road condition information, and based on the updated electronic map and Destination information is used to modify dynamically planned routes. Change to determine the dynamic target route; the autonomous driving safety system obtains the first obstacle information issued by the satellite system, and collects the second obstacle information through the acquisition equipment, and uses the artificial intelligence digital twin DaaS platform according to the first obstacle information and the second obstacle information. Obstacle information, predict the first movement information of the first obstacle and the second movement information of the second obstacle; adjust the driving parameters according to the first movement information, the second movement information and the dynamic target route to generate driving instructions, and Drive according to driving instructions.
  • the artificial intelligence digital twin DaaS platform is a DaaS digital twin platform, including an interconnected business middle platform and a data middle platform; the data middle platform is used to collect, calculate, store, and process data collected through DaaS.
  • the formed standard data is stored on the one hand and transmitted to the business middle platform on the other hand; the business middle platform is used to combine the standard data transmitted based on the data middle platform with industry applications to form models and products for industry applications, so that users can The middle office quickly encapsulates business products.
  • the artificial intelligence digital twin DaaS platform is mainly used to process the acquired data.
  • the artificial intelligence Internet of Things platform is an AIOT PaaS Internet of Things platform, which includes AI edge computing, digital chips, edge storage computing and module technology.
  • the artificial intelligence Internet of Things platform is mainly used to transmit the acquired data.
  • the autonomous driving safety method in this embodiment obtains destination information, generates a dynamically planned route based on the destination information; obtains the current road condition information issued by the satellite system, modifies the dynamically planned route based on the current road condition information, and determines the dynamic target route; obtains The first obstacle information is sent by the satellite system, and the second obstacle information is collected through the artificial intelligence IoT platform, and the driving is generated based on the first obstacle information, the second obstacle information and the dynamic target route through the artificial intelligence digital twin DaaS platform instructions, and drive according to the driving instructions; the present invention determines the dynamic target route based on the destination information and the current road condition information issued by the satellite system, and then obtains the longer-distance first obstacle information and the artificial intelligence Internet of Things platform issued by the satellite system Collect the second obstacle information at a closer distance, generate driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route through the artificial intelligence digital twin DaaS platform, and drive according to the driving instructions, which improves the accuracy of the autonomous vehicle. Passenger safety
  • Step S10 Obtain destination information and generate a dynamically planned route based on the destination information
  • the autonomous driving safety system when the autonomous driving safety system detects that a passenger enters the autonomous vehicle, it reminds the passenger to enter the destination information through a voice prompt.
  • the autonomous driving safety system obtains the destination information input by the passenger and calculates the destination information based on the current location information and destination information.
  • the self-driving safety system collects the passenger's facial information, fingerprint information, iris information and other biological information, and compares the biological information with the biological information stored in advance.
  • the self-driving safety system uses a prompt sound such as "Please enter the destination", etc. Prompt passengers to enter destination information. After obtaining the destination information entered by passengers, autonomous driving is safe.
  • the system sends positioning instructions to the ground receiving station of the satellite system connected to it through the artificial intelligence Internet of Things platform. After receiving the positioning instruction, the ground receiving station sends the positioning instruction to the satellite of the satellite system. The satellite receives the positioning instruction to the ground based on the received positioning instruction.
  • the station sends the corresponding current location information, and the ground receiving station sends the current location information to the autonomous driving safety system through the artificial intelligence IoT platform.
  • the autonomous driving safety system After receiving the current positioning information, the autonomous driving safety system generates dynamic information based on the current location information and destination information. Plan your route.
  • satellite systems include but are not limited to Beidou system, Starlink system, GPS system, etc.
  • Step S20 Obtain the current road condition information issued by the satellite system, modify the dynamically planned route according to the current road condition information, and determine the dynamic target route;
  • the autonomous driving safety system can directly drive the autonomous vehicle to drive according to the dynamically planned route, and send real-time traffic acquisition instructions to the satellite system during the driving process.
  • the satellite system receives the When obtaining instructions for road conditions, the instructions are obtained according to the road conditions to determine the current road condition information outside the sensing area of the autonomous vehicle and send it to the autonomous driving safety system.
  • the autonomous driving safety system will determine the current road condition information and destination information outside the sensing area. , modify the dynamic planning route to obtain the dynamic target route; further, after generating the dynamic planning route, the autonomous driving safety system directly sends the road condition acquisition instruction to the satellite system.
  • the satellite system receives the road condition acquisition instruction, it obtains the instruction according to the road condition.
  • the autonomous driving safety system modifies the dynamically planned route based on the current road condition information and destination information outside the sensing area, and we get Dynamic target route, the autonomous driving safety system then drives the autonomous vehicle to drive according to the dynamic target route; it is understandable that there are various sensors in autonomous vehicles that sense surrounding things, but the sensing area of the sensor is limited.
  • the current road condition information needs to be obtained through the satellite system, which enables autonomous vehicles to obtain current road condition information outside the sensing area and improves the safety of autonomous driving.
  • the self-driving car while it is driving, it obtains the current road condition information issued by the satellite system that there is a congestion two kilometers ahead. At this time, the self-driving safety system based on the current road condition information and destination information, Modify the dynamic planning route to avoid the congested road section ahead, obtain the dynamic target route, and continue driving according to the dynamic target route.
  • step S20 includes:
  • Step a obtain the current traffic information issued by the satellite system, update the traffic conditions in the electronic map according to the current traffic information, and modify the dynamically planned route according to the updated electronic map and the destination information, Determine dynamic target routes.
  • the autonomous driving safety system obtains the current road condition information issued by the satellite system, and The information updates the road conditions in the electronic map, and modifies the dynamic planning route based on the updated electronic map and destination information to determine the dynamic target route; for example: the autonomous driving safety system stores the corresponding electronic map, and after obtaining the dynamic After planning the route, the self-driving car is driven by combining the dynamic planning route and the electronic map.
  • the current road condition information issued by the satellite system is obtained, the road conditions in the electronic map are updated according to the current road condition information.
  • the current road condition information is This includes modifying the dynamic planning route based on the updated electronic map and destination information to obtain a dynamic target route when there are abnormal road conditions that are not conducive to the passage of autonomous vehicles.
  • the dynamic target route bypasses the abnormal road conditions. Routes to prevent self-driving cars from entering roads with abnormal road conditions that are not conducive to traffic, and improve the safety of self-driving cars.
  • Step S30 Obtain the first obstacle information issued by the satellite system, collect the second obstacle information through the artificial intelligence Internet of Things platform, and use the artificial intelligence digital twin DaaS platform according to the first obstacle information and the third obstacle information.
  • the obstacle information and the dynamic target route are used to generate driving instructions, and the vehicle is driven according to the driving instructions.
  • the self-driving safety system sends obstacle acquisition instructions to the satellite system in real time.
  • the satellite system receives the obstacle acquisition instructions, it determines the self-driving car based on the location information of the self-driving car.
  • the first obstacle information outside the sensing area is sent to the autonomous driving safety system.
  • the autonomous driving safety system collects the first obstacle information within the sensing area of the autonomous driving vehicle through the collection device on the autonomous driving vehicle. second obstacle information, and then control the self-driving car to drive based on the first obstacle information, the second obstacle information and the dynamic target route.
  • the step of driving according to the first obstacle information, the second obstacle information and the dynamic target route includes:
  • Step b Predict the first movement information of the first obstacle and the second movement information of the second obstacle based on the first obstacle information and the second obstacle information through the artificial intelligence digital twin DaaS platform;
  • the autonomous driving safety system predicts the first movement information of the first obstacle based on the first obstacle information through the artificial intelligence digital twin DaaS platform connected to it, and predicts the second movement information of the second obstacle based on the second obstacle information.
  • the first obstacle and the second obstacle can be pedestrians on the road, vehicles on the road, fixed objects on the road, etc.; the first obstacle information and the second obstacle information include obstacles The moving speed, the distance between the obstacle and the self-driving car, the type of obstacle, etc.; the first movement information and the second movement information include the movement route, movement speed, etc. of the obstacle.
  • Step c Adjust driving parameters according to the first movement information, the second movement information and the dynamic target route to generate driving instructions, and drive according to the driving instructions.
  • the automatic driving safety system determines the first movement information and the second movement information. Movement information, second movement information and dynamic target routes are used to adjust driving parameters to generate driving instructions and drive according to the driving instructions.
  • the automatic driving safety system based on the digital twin DaaS platform uses the first movement information and the second movement information. and dynamic target route, adjust the driving speed, driving lane and other driving parameters of the autonomous vehicle, generate driving instructions based on the adjusted driving parameters, and drive according to the driving instructions to avoid accidents caused by collision with obstacles.
  • the automatic driving safety system in this embodiment obtains the destination information input by the passengers when they get on the bus, and generates a dynamically planned route based on the destination information; the automatic driving safety system obtains the current road condition information issued by the satellite system, and generates a dynamically planned route based on the current road condition information.
  • the autonomous driving safety system obtains the first obstacle information issued by the satellite system and passes The collection device collects the second obstacle information, and predicts the first movement information of the first obstacle and the second movement information of the second obstacle based on the first obstacle information and the second obstacle information through the artificial intelligence digital twin DaaS platform; According to the first movement information, the second movement information and the dynamic target route, the driving parameters are adjusted to generate a driving instruction, and the driving is performed according to the driving instruction.
  • the invention determines the dynamic target route based on the destination information and the current road condition information issued by the satellite system, and then obtains the first obstacle information at a greater distance issued by the satellite system and the second obstacle at a closer distance collected by the artificial intelligence Internet of Things platform.
  • the artificial intelligence digital twin DaaS platform Based on the object information, the artificial intelligence digital twin DaaS platform generates driving instructions based on the first obstacle information, the second obstacle information and the dynamic target route, and drives according to the driving instructions, which improves the safety of passengers in autonomous vehicles and reduces traffic congestion. and improve efficiency.
  • step S30 includes:
  • Step d when receiving manual driving instructions, obtain the passenger's current mental state information through the virtual reality device, and generate a passenger's mental state report based on the current mental state information through the artificial intelligence digital twin DaaS platform;
  • Step e If it is determined based on the passenger's mental state report that the passenger's current mental state meets the preset driving mental state, switch to manual driving according to the manual driving instruction.
  • the autonomous driving safety system when it receives a manual driving instruction input by a passenger during the driving of the autonomous vehicle, it scans the passenger's face through a virtual reality device (MR device) to obtain the passenger's face. Micro-expressions, and determine the passenger's current mental state information based on the passenger's facial micro-expressions, and then generate a passenger's mental state report based on the current mental state information through the artificial intelligence digital twin DaaS platform. The autonomous driving safety system makes judgments based on the passenger's mental state report. Whether the passenger's current mental state matches the preset driving mental state.
  • MR device virtual reality device
  • the manual driving instruction will be used to switch to manual driving.
  • driving if it is determined based on the passenger's mental state report that the passenger's current mental state matches the preset driving mental state, the manual driving instruction will be rejected and the vehicle will continue driving in the autonomous driving mode.
  • the self-driving safety system of this embodiment determines the current psychological state of passengers and prevents passengers whose current psychological state does not meet the preset driving psychological state from manually driving self-driving cars, which is beneficial to improving the safety of passengers in self-driving cars.
  • step S30 the difference between the third embodiment of the automatic driving safety method based on the digital twin DaaS platform of the present invention and the first and second embodiments of the automatic driving safety method based on the digital twin DaaS platform is that after step S30, it also includes:
  • Step f obtain the passenger's current physical status information through the virtual reality device, and generate the passenger's physical status report based on the current physical status information through the artificial intelligence digital twin DaaS platform;
  • Step g Driving according to the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route.
  • the autonomous driving safety system obtains the passenger's current physical status information through the virtual reality device according to the preset period, and generates the passenger's physical status report based on the current physical status information through the artificial intelligence digital twin DaaS platform; based on the digital twin DaaS If the platform's autonomous driving safety system determines that the passenger's current physical condition requires treatment based on the passenger's physical condition report, it will determine the best treatment location information, change the dynamic target route, and determine the first obstacle based on the changed target route. information and second obstacle information to drive to the best treatment location; if the autonomous driving safety system determines that the passenger's current physical condition does not require treatment based on the passenger's physical status report, it will continue to maintain the original dynamic target route Carry on driving. When it is determined based on the passenger's current physical condition that the passenger needs immediate treatment, the best treatment location information is determined and the passenger is sent to the best treatment location so that the passenger can receive timely treatment, further ensuring the safety of the passenger's life.
  • the autonomous driving safety system based on the digital twin DaaS platform obtains the passenger's current physical status information through the virtual reality device, it uses the artificial intelligence digital twin DaaS platform to obtain the passenger's historical physical status information based on the passenger's personal information, and combines it with Passengers' current physical status information and historical physical status information are used to generate passenger physical status reports to improve the accuracy of passenger physical status reports and further ensure the safety of passengers.
  • the step of driving according to the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route includes:
  • Step g1 If it is determined that the passenger's current physical condition requires treatment based on the passenger's physical condition report, report to the passenger
  • the satellite system sends a search command and obtains the best treatment location information issued by the satellite system according to the search command; in this step, if the autonomous driving safety system determines that the passenger's current physical status requires treatment based on the passenger's physical status report
  • the autonomous driving safety system determines that the passenger's current physical status requires treatment based on the passenger's physical status report
  • the system is running, it sends a search command to the satellite system and obtains the best treatment location information issued by the satellite system according to the search command; for example, if the autonomous driving safety system determines that the passenger's current physical status requires treatment based on the passenger's physical status report, it will send a search command to the satellite system.
  • the system sends a search command, and the satellite system determines the current location of the self-driving car based on the search command, searches for the nearest hospital based on the current location of the self-driving car, and then determines the best treatment location information and sends the best treatment location information to the automatic in the driving safety system.
  • Step g2 Modify the dynamic target route based on the best treatment location information, and drive based on the modified target route, the first obstacle information, and the second obstacle information.
  • the autonomous driving safety system changes the dynamic target route based on the optimal treatment location information, and controls the autonomous vehicle to drive based on the changed target route, and during the driving process
  • the autonomous driving safety system sends obstacle acquisition instructions to the satellite system in real time.
  • the satellite system receives the obstacle acquisition instructions, it determines the first obstacle information outside the sensing area of the autonomous vehicle based on the position information of the autonomous vehicle. , and sends the first obstacle information to the self-driving safety system.
  • the self-driving safety system collects the second obstacle information within the sensing area of the self-driving car through the collection device on the self-driving car, and then based on the first obstacle Information, second obstacle information and dynamic target routes control the autonomous vehicle to drive.
  • the autonomous driving safety system controls the autonomous vehicle to stop at a safe location, obtains the current location information issued by the satellite system, and transmits the current location information to the nearest The patient will be sent to the best treatment location, and other vehicles dispatched from the best treatment location will be sent to the current location to treat the passengers.
  • the step of driving according to the modified target route, the first obstacle information and the second obstacle information includes:
  • Step h Send the alarm information and the best treatment location information to the preset alarm person, so that the preset alarm person can determine the passenger's location and respond in time.
  • the self-driving safety system sends warning information and the best treatment location information to the preset warning person, so that the preset warning person can determine the passenger's location and Respond promptly and arrive at the best treatment location in time.
  • the self-driving car when it takes passengers to the best treatment location, it can also alert the traffic management system and send the dynamic target route to the best treatment location to the traffic management system, so that the traffic management system can respond in a timely manner.
  • Dynamic target routes adjust traffic lights, etc., allowing autonomous vehicles to transport passengers to the best treatment location as quickly as possible, further ensuring the safety of passengers.
  • the autonomous driving safety system of this embodiment obtains the passenger's current physical status information through the virtual reality device according to the preset period, and generates the passenger's physical status report based on the current physical status information through the artificial intelligence digital twin DaaS platform; body status report, first obstacle information, second obstacle information and dynamic target route for driving.
  • the best treatment location information is determined and the passenger is sent to the best treatment location so that the passenger can receive timely treatment, further ensuring the safety of the passenger's life.
  • the autonomous driving safety system can obtain the current road condition information and the first obstacle information issued by the satellite system in real time.
  • the first obstacle information cannot be collected by the sensors in the autonomous vehicle equipped with the autonomous driving safety system.
  • Obstacle information the autonomous driving safety system also collects obstacle information that can be collected by the sensors in the autonomous vehicle through the artificial intelligence IoT platform, that is, the second obstacle information, and uses the artificial intelligence digital twin DaaS platform based on the first obstacle information.
  • the automatic driving safety system controls the automatic driving vehicle to drive according to the driving instructions to ensure the travel safety of passengers; at the same time, the automatic driving safety system obtains real-time
  • the passenger's current mental state information and current physical state information are analyzed, and when the passenger's current mental state information or current physical state information is abnormal, further rescue actions are taken to ensure the safety of the passenger. physical and mental safety;
  • the autonomous driving safety system can not only ensure the travel safety of passengers, but also ensure the physical and mental safety of passengers when traveling, protect the safety of passengers in an all-round way, and provide better safety guarantee for passengers.
  • the present invention also provides an automatic driving safety device based on the digital twin DaaS platform.
  • the automatic driving safety device based on the digital twin DaaS platform of the present invention includes:
  • An acquisition module used to acquire destination information and generate a dynamically planned route based on the destination information
  • a modification module used to obtain the current traffic information issued by the satellite system, modify the dynamic planning route according to the current traffic information, and determine the dynamic target route;
  • the driving module is used to obtain the first obstacle information issued by the satellite system, and collect the second obstacle information through the artificial intelligence Internet of Things platform, and use the artificial intelligence digital twin DaaS platform according to the first obstacle information and all the obstacles.
  • the second obstacle information and the dynamic target route are used to generate driving instructions, and driving is performed according to the driving instructions.
  • modification module is also used to:
  • Obtain the current traffic information issued by the satellite system update the traffic conditions in the electronic map according to the current traffic information, modify the dynamic planning route according to the updated electronic map and the destination information, and determine the dynamic target route.
  • the driving module is also used for:
  • driving parameters are adjusted to generate driving instructions, and driving is performed according to the driving instructions.
  • the driving module is also used for:
  • the passenger's current mental state information is obtained through the virtual reality device, and the passenger's mental state report is generated based on the current mental state information through the artificial intelligence digital twin DaaS platform;
  • the driving module is also used for:
  • the passenger's current physical status information is obtained through the virtual reality device, and the passenger's physical status report is generated based on the current physical status information through the artificial intelligence digital twin DaaS platform;
  • Driving is performed based on the passenger physical status report, the first obstacle information, the second obstacle information and the dynamic target route.
  • the driving module is also used for:
  • the dynamic target route is modified according to the optimal treatment location information, and the vehicle is driven according to the modified target route, the first obstacle information and the second obstacle information.
  • the driving module is also used for:
  • the alarm information and the best treatment location information are sent to the preset alarm person, so that the preset alarm person can determine the passenger's location and respond in time.
  • the present invention also provides an automatic driving safety system based on the digital twin DaaS platform.
  • the autonomous driving safety system based on the digital twin DaaS platform includes: a memory, a processor, and an autonomous driving program stored on the memory and executable on the processor.
  • the autonomous driving program is implemented when executed by the processor. The steps of the autonomous driving safety method based on the digital twin DaaS platform as mentioned above.
  • the invention also provides a computer-readable storage medium.
  • the computer-readable storage medium stores an automatic driving program.
  • the automatic driving program is executed by the processor, Steps to implement the autonomous driving safety method based on the digital twin DaaS platform as described above.
  • the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation.
  • the technical solution of the present invention can be embodied in the form of a software product that is essentially or contributes to the existing technology.
  • the computer software product is stored in a storage medium (such as ROM/RAM) as mentioned above. , magnetic disk, optical disk), including several instructions to cause a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the method described in various embodiments of the present invention.

Landscapes

  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Navigation (AREA)

Abstract

基于数字孪生DaaS平台的自动驾驶安全方法及***，该方法包括：获取目的地信息，根据目的地信息生成动态规划路线；获取卫星***下发的当前路况信息，根据当前路况信息对动态规划路线进行修改，确定动态目标路线；获取卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶。

Description

基于数字孪生DaaS平台的自动驾驶安全方法及*** 技术领域
本发明涉及人工智能技术领域，尤其涉及基于数字孪生DaaS平台的自动驾驶安全方法及***。
背景技术
现有的自动驾驶汽车是通过安装在***的传感器，获取自动驾驶汽车周围的道路情况从而驱动自动驾驶汽车，但是自动驾驶汽车***的传感器的具有一定的区域限制，只能获取自动驾驶汽车周围的道路情况来控制自动驾驶汽车，自动驾驶汽车无法获取更远距离的道路情况，使得在出现紧急事件时，留给自动驾驶汽车做出反应的时间较短，导致自动驾驶汽车的乘客的安全得不到较好的保障，因此，如何提高自动驾驶汽车的乘客的安全保障，减少交通拥堵和提高效率是急需解决的问题。
发明内容
本发明的主要目的在于提出基于数字孪生DaaS平台的自动驾驶安全方法及***，旨在解决如何提高自动驾驶汽车的乘客的安全保障，减少交通拥堵和提高效率问题。
为实现上述目的，本发明提供一种基于数字孪生DaaS平台的自动驾驶安全方法，所述基于数字孪生DaaS平台的自动驾驶安全方法包括如下步骤：
获取目的地信息，根据所述目的地信息生成动态规划路线；
获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶。
可选地，获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线的步骤包括：
获取卫星***下发的当前路况信息，根据所述当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和所述目的地信息对所述动态规划路线进行修改，确定动态目标路线。
可选地，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶的步骤包括：
通过人工智能数字孪生DaaS平台根据所述第一障碍物信息和所述第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；
根据所述第一移动信息、所述第二移动信息和所述动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。
可选地，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶的步骤之后，包括：
在接收到手动驾驶指令时，通过虚拟现实设备获取乘客的当前心理状态信息，并通过人工智能数字孪生DaaS平台根据所述当前心理状态信息生成乘客心理状态报告；
若根据所述乘客心理状态报告确定所述乘客当前心理状态符合预设驾车心理状态时，则根据所述手动驾驶指令切换为手动驾驶。
可选地，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶步骤之后，还包括：
根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据所述当前身体状态信息生成乘客身体状态报告；
根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶。
可选地，根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶的步骤包括：
若根据所述乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向所述卫星***发送搜索指令，并获取所述卫星***根据所述搜索指令下发的最佳治疗地点信息；
根据所述最佳治疗地点信息，对所述动态目标路线进行更改，并根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶。
可选地，根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶的步骤之后，包括：
向预设告警人发送告警信息和所述最佳治疗地点信息，以使所述预设告警人确定乘客位置并及时响应。
此外，为实现上述目的，本发明还提供一种基于数字孪生DaaS平台的自动驾驶安全装置，所述基于数字孪生DaaS平台的自动驾驶安全装置包括：
获取模块，用于获取目的地信息，根据所述目的地信息生成动态规划路线；
修改模块，用于获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划 路线进行修改，确定动态目标路线；
行驶模块，用于获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶
进一步地，所述修改模块还用于：
获取卫星***下发的当前路况信息，根据所述当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和所述目的地信息对所述动态规划路线进行修改，确定动态目标路线。
进一步地，所述行驶模块还用于：
通过人工智能数字孪生DaaS平台根据所述第一障碍物信息和所述第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；
根据所述第一移动信息、所述第二移动信息和所述动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。
进一步地，所述行驶模块还用于：
在接收到手动驾驶指令时，通过虚拟现实设备获取乘客的当前心理状态信息，并通过人工智能数字孪生DaaS平台根据所述当前心理状态信息生成乘客心理状态报告；
若根据所述乘客心理状态报告确定所述乘客当前心理状态符合预设驾车心理状态时，则根据所述手动驾驶指令切换为手动驾驶。
进一步地，所述行驶模块还用于：
根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据所述当前身体状态信息生成乘客身体状态报告；
根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶。
进一步地，所述行驶模块还用于：
若根据所述乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向所述卫星***发送搜索指令，并获取所述卫星***根据所述搜索指令下发的最佳治疗地点信息；
根据所述最佳治疗地点信息，对所述动态目标路线进行更改，并根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶。
进一步地，所述行驶模块还用于：
向预设告警人发送告警信息和所述最佳治疗地点信息，以使所述预设告警人确定乘客位置并 及时响应。
此外，为实现上述目的，本发明还提供一种基于数字孪生DaaS平台的自动驾驶安全***，所述基于数字孪生DaaS平台的自动驾驶安全***包括：存储器、处理器及储存在所述存储器上并可在所述处理器上运行的自动驾驶程序，所述自动驾驶程序被所述处理器执行时实现如上所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
此外，为实现上述目的，本发明还提供一种计算机可读存储介质，所述计算机可读储存介质上储存有自动驾驶程序，所述自动驾驶程序被处理器执行时实现如上所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
本发明提出的基于数字孪生DaaS平台的自动驾驶安全方法，获取目的地信息，根据目的地信息生成动态规划路线；获取卫星***下发的当前路况信息，根据当前路况信息对动态规划路线进行修改，确定动态目标路线；获取卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶；本发明根据目的地息和卫星***下发的当前路况信息确定动态目标路线，再获取卫星***下发的较远距离的第一障碍物信息和人工智能物联网平台采集较近距离的第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶，提高了自动驾驶汽车的乘客的安全保障，减少交通拥堵和提高效率。
附图说明
图1是本发明实施例方案涉及的硬件运行环境的设备结构示意图；
图2为本发明基于数字孪生DaaS平台的自动驾驶安全方法第一实施例的流程示意图。
本发明目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
如图1所示，图1是本发明实施例方案涉及的硬件运行环境的设备结构示意图。
本发明实施例设备可以是PC机或服务器设备。
如图1所示，该设备可以包括：处理器1001，例如CPU，网络接口1004，用户接口1003，存储器1005，通信总线1002。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏(Display)、输入单元比如键盘(Keyboard)，可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的 有线接口、无线接口(如WI-FI接口)。存储器1005可以是高速RAM存储器，也可以是稳定的存储器(non-volatile memory)，例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的储存装置。
本领域技术人员可以理解，图1中示出的设备结构并不构成对设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
如图1所示，作为一种计算机储存介质的存储器1005中可以包括操作***、网络通信模块、用户接口模块以及自动驾驶程序。
其中，操作***是管理和控制便携储存设备与软件资源的程序，支持网络通信模块、用户接口模块、自动驾驶程序以及其他程序或软件的运行；网络通信模块用于管理和控制网络接口1002；用户接口模块用于管理和控制用户接口1003。
在图1所示的储存设备中，所述储存设备通过处理器1001调用存储器1005中储存的自动驾驶程序，并执行下述基于数字孪生DaaS平台的自动驾驶安全方法各个实施例中的操作。
基于上述硬件结构，提出本发明基于数字孪生DaaS平台的自动驾驶安全方法实施例。
参照图2，图2为本发明基于数字孪生DaaS平台的自动驾驶安全方法第一实施例的流程示意图，所述方法包括：
步骤S10，获取目的地信息，根据所述目的地信息生成动态规划路线；
步骤S20，获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
步骤S30，获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶。
本实施例基于数字孪生DaaS平台的自动驾驶安全方法运用于自动驾驶汽车的基于数字孪生DaaS平台的自动驾驶安全***中，该基于数字孪生DaaS平台的自动驾驶安全***与人工智能物联网平台、人工智能数字孪生DaaS平台和卫星***进行通信连接；为了方便描述，以基于数字孪生DaaS平台的自动驾驶安全***简称为自动驾驶安全***为例进行说明；自动驾驶安全***在乘客上车时，获取乘客输入的目的地信息，根据目的地信息生成动态规划路线；自动驾驶安全***获取卫星***下发的当前路况信息，根据当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和目的地信息对动态规划路线进行修 改，确定动态目标路线；自动驾驶安全***获取卫星***下发的第一障碍物信息，并通过采集设备采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息和第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；根据第一移动信息、第二移动信息和动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。需要说明的是，人工智能数字孪生DaaS平台为DaaS数字孪生平台，包括相互连接的业务中台和数据中台；数据中台用于对通过DaaS方式收集的数据进行采集、计算、存储、加工，形成的标准数据一方面进行储存一方面传送至业务中台；业务中台用于将基于数据中台传送的标准数据并结合行业应用，形成针对行业应用的模型及产品，以使用户能够基于业务中台快速封装出业务产品，在本发明中主要利用人工智能数字孪生DaaS平台对获取到的数据进行处理。人工智能物联网平台为AIOT PaaS物联网平台，其中包括AI边缘计算，数字芯片，边缘存储计算和模组技术，在本发明中主要利用人工智能物联网平台传输获取到的数据。
本实施例中的自动驾驶安全方法获取目的地信息，根据目的地信息生成动态规划路线；获取卫星***下发的当前路况信息，根据当前路况信息对动态规划路线进行修改，确定动态目标路线；获取卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶；本发明根据目的地息和卫星***下发的当前路况信息确定动态目标路线，再获取卫星***下发的较远距离的第一障碍物信息和人工智能物联网平台采集较近距离的第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶，提高了自动驾驶汽车的乘客的安全保障，减少交通拥堵和提高效率。
以下将对各个步骤进行详细说明：
步骤S10，获取目的地信息，根据所述目的地信息生成动态规划路线；
在本实施例中，自动驾驶安全***在检测到乘客进入自动驾驶汽车时，通过语音提示提醒乘客输入目的地信息，自动驾驶安全***获取乘客输入的目的地信息，根据当前位置信息和目的地信息生成动态规划路线，可以理解的是，当乘客需要进入自动驾驶汽车模式时，自动驾驶安全***采集乘客的脸部信息、指纹信息、虹膜信息等生物信息，将生物信息与提前储存的生物信息进行对比，当采集的乘客的生物信息与提前储存的生物信息相同时，允许乘客进入自动驾驶汽车；在乘客进入到自动驾驶汽车时，自动驾驶安全***通过提示音如“请输入目的地”等，提示乘客输入目的地信息，在获取到乘客输入的目的地信息后，自动驾驶安全 ***通过人工智能物联网平台向与其连接的卫星***的地面接收站发送定位指令，地面接收站接收到定位指令后，将定位指令发送到卫星***的卫星，卫星根据接收到的定位指令向地面接收站发送对应的当前位置信息，地面接收站通过人工智能物联网平台向自动驾驶安全***下发当前位置信息，自动驾驶安全***在接收到当前定位信息后，根据当前位置信息和目的地信息生成动态规划路线。需要说明的是，卫星***包括但不限于北斗***、星链***、GPS***等。
步骤S20，获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
在本实施例中，自动驾驶安全***在生成动态规划路线后，可直接根据动态规划路线驱动自动驾驶汽车进行行驶，并在行驶的过程中向卫星***实时发送路况获取指令，卫星***在接收到路况获取指令时，根据路况获取指令，确定自动驾驶汽车的感知区域范围外的当前路况信息，并发送到自动驾驶安全***中，自动驾驶安全***根据感知区域范围外的当前路况信息和目的地信息，对动态规划路线进行修改，得到动态目标路线；进一步地，自动驾驶安全***在生成动态规划路线后，直接向卫星***发送路况获取指令，卫星***在接收到路况获取指令时，根据路况获取指令，确定自动驾驶汽车的感知区域范围外的当前路况信息，并发送到自动驾驶安全***中，自动驾驶安全***根据感知区域范围外的当前路况信息和目的地信息，对动态规划路线进行修改，得到动态目标路线，自动驾驶安全***再根据动态目标路线驱动自动驾驶汽车进行行驶；可以理解的是，自动驾驶汽车中存在各种感知周边事物的传感器，但是传感器的感知区域有限，对于感知区域范围外的当前路况信息则需要通过卫星***获取，这使得自动驾驶汽车能够获取感知区域范围外的当前路况信息，提高自动驾驶的安全性。
在一可行的实施例中，自动驾驶汽车在行驶过程中，获取到卫星***下发的当前路况信息为前方两公里处发生拥堵，此时，自动驾驶安全***根据当前路况信息和目的地信息，对动态规划路线进行修改，绕开前方拥堵路段，得到动态目标路线，根据动态目标路线继续行驶。
具体地，步骤S20包括：
步骤a，获取卫星***下发的当前路况信息，根据所述当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和所述目的地信息对所述动态规划路线进行修改，确定动态目标路线。
在该步骤中，自动驾驶安全***获取卫星***下发的当前路况信息，根据当前路况 信息对电子地图中的路况进行更新，并根据更新后的电子地图和目的地信息对动态规划路线进行修改，确定动态目标路线；如：自动驾驶安全***中储存有对应的电子地图，在得到动态规划路线后，结合动态规划路线和电子地图驱动自动驾驶汽车进行行驶，当获取到卫星***下发的当前路况信息时，根据当前路况信息对电子地图中的路况进行更新，当确定当前路况信息中包括了在动态规划路线上存在不利于自动驾驶汽车通行的异常路况时，根据更新后的电子地图和目的地信息对动态规划路线进行修改，得到动态目标路线，动态目标路线是绕过异常路况的路线，避免自动驾驶汽车进入到存在不利于通行的异常路况的道路，提高自动驾驶汽车的安全性。
步骤S30，获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶。
在本实施例中，自动驾驶汽车在行驶过程中，自动驾驶安全***实时向卫星***发送障碍物获取指令，卫星***接收到障碍物获取指令时，根据自动驾驶汽车的位置信息，确定自动驾驶汽车的感知区域范围外的第一障碍物信息，并将第一障碍物信息发送到自动驾驶安全***中，自动驾驶安全***通过自动驾驶汽车上的采集设备采集自动驾驶汽车的感知区域范围内的第二障碍物信息，进而根据第一障碍物信息、第二障碍物信息和动态目标路线控制自动驾驶汽车进行行驶。
具体地，根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶的步骤包括：
步骤b，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息和所述第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；
在该步骤中，自动驾驶安全***通过与其连接的人工智能数字孪生DaaS平台根据第一障碍物信息预测第一障碍物的第一移动信息，根据第二障碍物信息预测第二障碍物的第二移动信息，可以理解的是，第一障碍物和第二障碍物可以是道路上的行人、道路上的车辆、道路上固定的物体等；第一障碍物信息和第二障碍物信息包括障碍物的移动速度、障碍物与自动驾驶汽车的距离、障碍物的类型等；第一移动信息和第二移动信息包括障碍物的移动路线、移动速度等。
步骤c，根据所述第一移动信息、所述第二移动信息和所述动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。
在该步骤中，自动驾驶安全***在确定第一移动信息和第二移动信息后，根据第一 移动信息、第二移动信息和动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶，如：基于数字孪生DaaS平台的自动驾驶安全***根据第一移动信息、第二移动信息和动态目标路线，调整自动驾驶汽车的行驶速度、行驶车道等行驶参数，并根据调整后的行驶参数生成行驶指令，并根据行驶指令进行行驶，避免与障碍物碰撞发生事故。
本实施例中的自动驾驶安全***在乘客上车时，获取乘客输入的目的地信息，根据目的地信息生成动态规划路线；自动驾驶安全***获取卫星***下发的当前路况信息，根据当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和目的地信息对动态规划路线进行修改，确定动态目标路线；自动驾驶安全***获取卫星***下发的第一障碍物信息，并通过采集设备采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息和第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；根据第一移动信息、第二移动信息和动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。本发明根据目的地息和卫星***下发的当前路况信息确定动态目标路线，再获取卫星***下发的较远距离的第一障碍物信息和人工智能物联网平台采集较近距离的第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息和动态目标路线生成行驶指令，根据行驶指令进行行驶，提高了自动驾驶汽车的乘客的安全保障，减少交通拥堵和提高效率。
进一步地，基于本发明基于数字孪生DaaS平台的自动驾驶安全方法第一实施例，提出本发明基于数字孪生DaaS平台的自动驾驶安全方法第二实施例。
本发明基于数字孪生DaaS平台的自动驾驶安全方法的第二实施例与基于数字孪生DaaS平台的自动驾驶安全方法的第一实施例的区别在于，步骤S30之后包括：
步骤d，在接收到手动驾驶指令时，通过虚拟现实设备获取乘客的当前心理状态信息，并通过人工智能数字孪生DaaS平台根据所述当前心理状态信息生成乘客心理状态报告；
步骤e，若根据所述乘客心理状态报告确定所述乘客当前心理状态符合预设驾车心理状态时，则根据所述手动驾驶指令切换为手动驾驶。
在本实施例中，自动驾驶安全***在自动驾驶车辆的行驶过程中，接收到乘客输入的手动驾驶指令时，通过虚拟现实设备(MR设备)对乘客的脸部进行扫描，获取乘客的脸部微表情，并根据乘客的脸部微表情，确定乘客的当前心理状态信息，再通过人工智能数字孪生DaaS平台根据当前心理状态信息生成乘客心理状态报告，自动驾驶安全***根据乘客心理状态报告，判断乘客的当前心理状态是否符合预设驾车心理状态，若根据乘客心理状态报告确定乘客当前心理状态符合预设驾车心理状态时，则根据手动驾驶指令切换为手动驾 驶，若根据乘客心理状态报告确定乘客当前心理状态不符合预设驾车心理状态时，则拒绝手动驾驶指令，继续进行自动驾驶模式进行行驶。
本实施例的自动驾驶安全***通过确定乘客的当前心理状态，避免当前心理状态不符合预设驾车心理状态的乘客手动驾驶自动驾驶汽车，有利于提高自动驾驶汽车的乘客的安全保障。
进一步地，基于本发明基于数字孪生DaaS平台的自动驾驶安全方法第一实施例和第二实施例，提出本发明基于数字孪生DaaS平台的自动驾驶安全方法第三实施例。
本发明基于数字孪生DaaS平台的自动驾驶安全方法的第三实施例与基于数字孪生DaaS平台的自动驾驶安全方法的第一实施例和第二实施例的区别在于，步骤S30之后还包括：
步骤f，根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据所述当前身体状态信息生成乘客身体状态报告；
步骤g，根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶。
在本实施例中，自动驾驶安全***根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据当前身体状态信息生成乘客身体状态报告；基于数字孪生DaaS平台的自动驾驶安全***若根据乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，确定最佳治疗地点信息，并对动态目标路线进行更改，并根据更改后的目标线路、第一障碍物信息和第二障碍物信息进行行驶，以将乘客送往最佳治疗地点；自动驾驶安全***若根据乘客身体状态报告确定乘客的当前身体状态不需要进行治疗时，则继续保持原本的动态目标路线进行行驶。通过乘客的当前身体状态确定乘客需要记性治疗时，确定最佳治疗地点信息，并将乘客送往最佳治疗地点，是的乘客能够及时得到治疗，进一步保证了乘客的生命安全。
进一步地，基于数字孪生DaaS平台的自动驾驶安全***通过虚拟现实设备获取乘客的当前身体状态信息后，通过人工智能数字孪生DaaS平台根据乘客的个人信息，获取该乘客的历史身体状态信息，并结合乘客的当前身体状态信息和历史身体状态信息，生成乘客身体状态报告，以提高乘客身体状态报告的准确性，进一步保证了乘客的生命安全。
具体地，根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶的步骤包括：
步骤g1，若根据所述乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向所述 卫星***发送搜索指令，并获取所述卫星***根据所述搜索指令下发的最佳治疗地点信息；在该步骤中，自动驾驶安全***若根据乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向卫星***发送搜索指令，并获取卫星***根据搜索指令下发的最佳治疗地点信息；如：自动驾驶安全***若根据乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向卫星***发送搜索指令，卫星***根据搜索指令确定自动驾驶汽车的当前位置，并根据自动驾驶汽车的当前位置搜索距离最近的医院，进而确定最佳治疗地点信息，并将最佳治疗地点信息发送到自动驾驶安全***中。
步骤g2，根据所述最佳治疗地点信息，对所述动态目标路线进行更改，并根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶。
在该步骤中，自动驾驶安全***在确定最佳治疗地点信息后，根据最佳治疗地点信息，对动态目标路线进行更改，并根据更改后的目标线路控制自动驾驶汽车进行行驶，并在行驶过程中，的自动驾驶安全***实时向卫星***发送障碍物获取指令，卫星***接收到障碍物获取指令时，根据自动驾驶汽车的位置信息，确定自动驾驶汽车的感知区域范围外的第一障碍物信息，并将第一障碍物信息发送到自动驾驶安全***中，自动驾驶安全***通过自动驾驶汽车上的采集设备采集自动驾驶汽车的感知区域范围内的第二障碍物信息，进而根据第一障碍物信息、第二障碍物信息和动态目标路线控制自动驾驶汽车进行行驶。
可选地，在另一种情况下，自动驾驶安全***在确定最佳治疗地点信息后，控制自动驾驶汽车停止到安全位置，并获取卫星***下发的当前位置信息，将当前位置信息向最佳治疗地点发送，通过最佳治疗地点派出的其他车辆到当前位置对乘客进行治疗。
进一步地，根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶的步骤之后，包括：
步骤h，向预设告警人发送告警信息和所述最佳治疗地点信息，以使所述预设告警人确定乘客位置并及时响应。
在该步骤中，在自动驾驶汽车将乘客送往最佳治疗地点的过程中，自动驾驶安全***向预设告警人发送告警信息和最佳治疗地点信息，以使预设告警人确定乘客位置并及时响应，及时赶到最佳治疗地点。
进一步地，在自动驾驶汽车将乘客送往最佳治疗地点的过程中，还可以向交通管理***告警，将前往最佳治疗地点的动态目标路线发送到交通管理***中，以使交通管理***及时动态目标路线调节交通信号灯等，使得自动驾驶汽车能够尽快将乘客送往最佳治疗地点，进一步保证了乘客的生命安全。
本实施例的自动驾驶安全***根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据当前身体状态信息生成乘客身体状态报告；自动驾驶安全***根据乘客身体状态报告、第一障碍物信息、第二障碍物信息和动态目标路线进行行驶。通过乘客的当前身体状态确定乘客需要记性治疗时，确定最佳治疗地点信息，并将乘客送往最佳治疗地点，是的乘客能够及时得到治疗，进一步保证了乘客的生命安全。
在具体实施时，自动驾驶安全***能够实时获取到卫星***下发的当前路况信息和第一障碍物信息，第一障碍物信息是搭载自动驾驶安全***的自动驾驶汽车中的传感器无法采集到的障碍物信息，自动驾驶安全***同时通过人工智能物联网平台采集自动驾驶汽车中的传感器能够采集到的障碍物信息，即第二障碍物信息，通过人工智能数字孪生DaaS平台根据第一障碍物信息、第二障碍物信息、当前路况信息和乘客输入的目的地信息，生成行驶指令，自动驾驶安全***根据行驶指令控制自动驾驶汽车进行行驶，保障乘客的出行安全；同时，自动驾驶安全***实时获取乘客的当前心理状态信息和当前身体状态信息，分析乘客的当前心理状态信息和当前身体状态信息，在乘客当前心理状态信息或当前身体状态信息出现异常时，采取进一步的救治行动，进而保障乘客的身心安全；
因此，自动驾驶安全***既可以保障乘客的出行安全，也可以保障乘客在出行时的身心安全，全方位保护乘客的安全，为乘客提供更好的安全保障。
本发明还提供一种基于数字孪生DaaS平台的自动驾驶安全装置。本发明基于数字孪生DaaS平台的自动驾驶安全装置包括：
获取模块，用于获取目的地信息，根据所述目的地信息生成动态规划路线；
修改模块，用于获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
行驶模块，用于获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶
进一步地，所述修改模块还用于：
获取卫星***下发的当前路况信息，根据所述当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和所述目的地信息对所述动态规划路线进行修改，确定动态目标路线。
进一步地，所述行驶模块还用于：
通过人工智能数字孪生DaaS平台根据所述第一障碍物信息和所述第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；
根据所述第一移动信息、所述第二移动信息和所述动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。
进一步地，所述行驶模块还用于：
在接收到手动驾驶指令时，通过虚拟现实设备获取乘客的当前心理状态信息，并通过人工智能数字孪生DaaS平台根据所述当前心理状态信息生成乘客心理状态报告；
若根据所述乘客心理状态报告确定所述乘客当前心理状态符合预设驾车心理状态时，则根据所述手动驾驶指令切换为手动驾驶。
进一步地，所述行驶模块还用于：
根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据所述当前身体状态信息生成乘客身体状态报告；
根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶。
进一步地，所述行驶模块还用于：
若根据所述乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向所述卫星***发送搜索指令，并获取所述卫星***根据所述搜索指令下发的最佳治疗地点信息；
根据所述最佳治疗地点信息，对所述动态目标路线进行更改，并根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶。
进一步地，所述行驶模块还用于：
向预设告警人发送告警信息和所述最佳治疗地点信息，以使所述预设告警人确定乘客位置并及时响应。
本发明还提供一种基于数字孪生DaaS平台的自动驾驶安全***。
基于数字孪生DaaS平台的自动驾驶安全***包括：存储器、处理器及储存在所述存储器上并可在所述处理器上运行的自动驾驶程序，所述自动驾驶程序被所述处理器执行时实现如上所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
其中，在所述处理器上运行的自动驾驶程序被执行时所实现的方法可参照本发明基于数字孪生DaaS平台的自动驾驶安全方法各个实施例，此处不再赘述。
本发明还提供一种计算机可读存储介质。
该计算机可读存储介质上储存有自动驾驶程序，所述自动驾驶程序被处理器执行时 实现如上所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
其中，在所述处理器上运行的自动驾驶程序被执行时所实现的方法可参照本发明基于数字孪生DaaS平台的自动驾驶安全方法各个实施例，此处不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者***不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者***所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者***中还存在另外的相同要素。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品储存在如上所述的一个储存介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本发明各个实施例所述的方法。
以上仅为本发明的优选实施例，并非因此限制本发明的专利范围，凡是利用本发明说明书与附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本发明的专利保护范围内。

Claims (10)

  1. 一种基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述基于数字孪生DaaS平台的自动驾驶安全方法包括如下步骤：
    获取目的地信息，根据所述目的地信息生成动态规划路线；
    获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
    获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶。
  2. 如权利要求1所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线的步骤包括：
    获取卫星***下发的当前路况信息，根据所述当前路况信息对电子地图中的路况进行更新，并根据更新后的电子地图和所述目的地信息对所述动态规划路线进行修改，确定动态目标路线。
  3. 如权利要求1所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶的步骤包括：
    通过人工智能数字孪生DaaS平台根据所述第一障碍物信息和所述第二障碍物信息，预测第一障碍物的第一移动信息和第二障碍物的第二移动信息；
    根据所述第一移动信息、所述第二移动信息和所述动态目标路线，调整行驶参数，以生成行驶指令，并根据行驶指令进行行驶。
  4. 如权利要求1所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶的步骤之后，包括：
    在接收到手动驾驶指令时，通过虚拟现实设备获取乘客的当前心理状态信息，并通过人工智能数字孪生DaaS平台根据所述当前心理状态信息生成乘客心理状态报告；
    若根据所述乘客心理状态报告确定所述乘客当前心理状态符合预设驾车心理状态时，则根据所述手动驾驶指令切换为手动驾驶。
  5. 如权利要求1中所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述 动态目标路线生成行驶指令，根据行驶指令进行行驶步骤之后，还包括：
    根据预设周期，通过虚拟现实设备获取乘客的当前身体状态信息，并通过人工智能数字孪生DaaS平台根据所述当前身体状态信息生成乘客身体状态报告；
    根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶。
  6. 如权利要求5所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述根据所述乘客身体状态报告、所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线进行行驶的步骤包括：
    若根据所述乘客身体状态报告确定乘客的当前身体状态需要进行治疗时，向所述卫星***发送搜索指令，并获取所述卫星***根据所述搜索指令下发的最佳治疗地点信息；
    根据所述最佳治疗地点信息，对所述动态目标路线进行更改，并根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶。
  7. 如权利要求6所述的基于数字孪生DaaS平台的自动驾驶安全方法，其特征在于，所述根据更改后的目标线路、所述第一障碍物信息和所述第二障碍物信息进行行驶的步骤之后，包括：
    向预设告警人发送告警信息和所述最佳治疗地点信息，以使所述预设告警人确定乘客位置并及时响应。
  8. 一种基于数字孪生DaaS平台的自动驾驶安全装置，其特征在于，所述基于数字孪生DaaS平台的自动驾驶安全装置包括：
    获取模块，用于获取目的地信息，根据所述目的地信息生成动态规划路线；
    修改模块，用于获取卫星***下发的当前路况信息，根据所述当前路况信息对所述动态规划路线进行修改，确定动态目标路线；
    行驶模块，用于获取所述卫星***下发的第一障碍物信息，并通过人工智能物联网平台采集第二障碍物信息，通过人工智能数字孪生DaaS平台根据所述第一障碍物信息、所述第二障碍物信息和所述动态目标路线生成行驶指令，根据行驶指令进行行驶。
  9. 一种基于数字孪生DaaS平台的自动驾驶安全***，其特征在于，所述基于数字孪生DaaS平台的自动驾驶安全***包括：存储器、处理器及储存在所述存储器上并可在所述处理器上运行的自动驾驶程序，所述自动驾驶程序被所述处理器执行时实现如权利要求1至7中任一项所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上储存有自动驾驶程 序，所述自动驾驶程序被处理器执行时实现如权利要求1至7中任一项所述的基于数字孪生DaaS平台的自动驾驶安全方法的步骤。
PCT/CN2023/074633 2022-06-10 2023-02-06 基于数字孪生DaaS平台的自动驾驶安全方法及*** WO2023236562A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202210649717.3A CN114715197B (zh) 2022-06-10 2022-06-10 基于数字孪生DaaS平台的自动驾驶安全方法及***
CN202210649717.3 2022-06-10

Publications (1)

Publication Number Publication Date
WO2023236562A1 true WO2023236562A1 (zh) 2023-12-14

Family

ID=82232688

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2023/074633 WO2023236562A1 (zh) 2022-06-10 2023-02-06 基于数字孪生DaaS平台的自动驾驶安全方法及***

Country Status (2)

Country Link
CN (1) CN114715197B (zh)
WO (1) WO2023236562A1 (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114715197B (zh) * 2022-06-10 2022-08-30 深圳市爱云信息科技有限公司 基于数字孪生DaaS平台的自动驾驶安全方法及***

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107336711A (zh) * 2017-06-19 2017-11-10 北京汽车股份有限公司 车辆及其自动驾驶***和方法
CN110716558A (zh) * 2019-11-21 2020-01-21 上海车右智能科技有限公司 一种基于数字孪生技术的非公开道路用自动驾驶***
CN111016927A (zh) * 2014-12-12 2020-04-17 索尼公司 自动驾驶控制设备以及自动驾驶控制方法和程序
CN112305573A (zh) * 2020-10-23 2021-02-02 上海伯镭智能科技有限公司 一种基于北斗的无人驾驶汽车路线选择***
CN112339776A (zh) * 2019-08-09 2021-02-09 丰田自动车株式会社 车辆行驶***
KR20210117030A (ko) * 2020-03-18 2021-09-28 인하대학교 산학협력단 자율주행 가상화를 위한 디지털 트윈 장치 및 방법
CN114153220A (zh) * 2022-02-10 2022-03-08 深圳市爱云信息科技有限公司 基于人工智能物联网平台用于自动驾驶的远程控制方法
CN114715197A (zh) * 2022-06-10 2022-07-08 深圳市爱云信息科技有限公司 基于数字孪生DaaS平台的自动驾驶安全方法及***

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103383265B (zh) * 2013-07-04 2016-12-07 宁波吉利汽车研究开发有限公司 汽车自动驾驶***
CN106935053A (zh) * 2015-12-29 2017-07-07 天津华方科技有限公司 云计算平台优化行车路线的物联网自驾汽车装置
CN108008727A (zh) * 2017-12-11 2018-05-08 梁金凤 一种能够高速行驶的无人驾驶汽车
CN113359709B (zh) * 2021-05-19 2022-07-05 中山大学 一种基于数字孪生的无人驾驶运动规划方法

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111016927A (zh) * 2014-12-12 2020-04-17 索尼公司 自动驾驶控制设备以及自动驾驶控制方法和程序
CN107336711A (zh) * 2017-06-19 2017-11-10 北京汽车股份有限公司 车辆及其自动驾驶***和方法
CN112339776A (zh) * 2019-08-09 2021-02-09 丰田自动车株式会社 车辆行驶***
CN110716558A (zh) * 2019-11-21 2020-01-21 上海车右智能科技有限公司 一种基于数字孪生技术的非公开道路用自动驾驶***
KR20210117030A (ko) * 2020-03-18 2021-09-28 인하대학교 산학협력단 자율주행 가상화를 위한 디지털 트윈 장치 및 방법
CN112305573A (zh) * 2020-10-23 2021-02-02 上海伯镭智能科技有限公司 一种基于北斗的无人驾驶汽车路线选择***
CN114153220A (zh) * 2022-02-10 2022-03-08 深圳市爱云信息科技有限公司 基于人工智能物联网平台用于自动驾驶的远程控制方法
CN114715197A (zh) * 2022-06-10 2022-07-08 深圳市爱云信息科技有限公司 基于数字孪生DaaS平台的自动驾驶安全方法及***

Also Published As

Publication number Publication date
CN114715197A (zh) 2022-07-08
CN114715197B (zh) 2022-08-30

Similar Documents

Publication Publication Date Title
JP7406215B2 (ja) 自律走行車動作管理のための方向調整アクション
KR20210108381A (ko) 다양한 레벨들의 자율성을 갖는 차량들 사이의 상호작용들을 관리하기 위한 방법들 및 시스템들
KR102548697B1 (ko) 승객 건강 검진 및 모니터링
US11822327B2 (en) Safety of autonomous vehicles by remote support request
JP6963158B2 (ja) 集中型共有自律走行車動作管理
US9075416B2 (en) Mobile body
CN109521764A (zh) 车辆远程辅助模式
JP7010048B2 (ja) 移動体、業務支援方法、業務支援プログラムおよび業務支援システム
US20190306779A1 (en) Vehicle communication control method and vehicle communication device
WO2023236562A1 (zh) 基于数字孪生DaaS平台的自动驾驶安全方法及***
US11735041B2 (en) Route-specific services for connected automated vehicle highway systems
JP2020521978A (ja) 安全ルート決定のためのシステムと方法
WO2021066863A1 (en) Map prior layer
JP2021530039A (ja) 貨物を輸送するための自律走行車の盗難防止技術
US10885785B2 (en) Network-controllable physical resources for vehicular transport system safety
US20230324188A1 (en) Autonomous vehicle fleet scheduling to maximize efficiency
CN106710273A (zh) 一种道路交通管理方法及其中控***
US20220128371A1 (en) Information processing apparatus, information processing method, and vehicle
JP2018114913A (ja) 運転支援装置
US20230300877A1 (en) Dynamic allocation of communication network resources for autonomous vehicles
US20230199450A1 (en) Autonomous Vehicle Communication Gateway Architecture
US20240218911A1 (en) Brake pad wear detection and warning for autonomous driving vehicles
US20240173179A1 (en) Apparatus and method for guiding the transportation vulnerable
JP2022142860A (ja) 運転支援装置、運転支援方法及びプログラム
WO2023122586A1 (en) Autonomous vehicle communication gateway architecture

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23818730

Country of ref document: EP

Kind code of ref document: A1