CN113625685A - Automatic driving test system and method - Google Patents
Automatic driving test system and method Download PDFInfo
- Publication number
- CN113625685A CN113625685A CN202110844003.3A CN202110844003A CN113625685A CN 113625685 A CN113625685 A CN 113625685A CN 202110844003 A CN202110844003 A CN 202110844003A CN 113625685 A CN113625685 A CN 113625685A
- Authority
- CN
- China
- Prior art keywords
- data
- automatic driving
- virtual scene
- upper computer
- vehicle control
- Prior art date
- Legal status (The legal status 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 status listed.)
- Pending
Links
- 238000012360 testing method Methods 0.000 title claims abstract description 167
- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000008447 perception Effects 0.000 claims abstract description 69
- 238000004458 analytical method Methods 0.000 claims abstract description 32
- 238000006243 chemical reaction Methods 0.000 claims description 26
- 238000012545 processing Methods 0.000 claims description 22
- 238000004088 simulation Methods 0.000 claims description 18
- 238000010998 test method Methods 0.000 claims description 8
- 230000004927 fusion Effects 0.000 claims description 4
- 230000006870 function Effects 0.000 description 13
- 238000004590 computer program Methods 0.000 description 6
- 238000012795 verification Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000007499 fusion processing Methods 0.000 description 2
- 230000001953 sensory effect Effects 0.000 description 2
- 101100365794 Schizosaccharomyces pombe (strain 972 / ATCC 24843) sim3 gene Proteins 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The application discloses an automatic driving test system and a method, the application generates virtual scene data through an upper computer, generates position-associated radio frequency signals and relative positioning data, a test bench generates first perception data according to the acquired vehicle control data and the virtual scene data, a global satellite navigation system simulator generates absolute positioning data according to the position-associated radio frequency signals, then a combined navigation module generates second perception data according to the absolute positioning data and the relative positioning data, more comprehensive perception data required by an automatic driving domain controller for automatic driving control analysis can be obtained, the automatic driving domain controller performs automatic driving control analysis based on the first perception data and the second perception data to generate vehicle control data, thereby generating more real vehicle control data and leading the vehicle control data to have more reference value, the test result is more objective, and the safety and the reliability of the automatic driving test are improved.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to an automatic driving test system and method.
Background
Virtual simulation test verification is an important ring in the development process of the advanced automatic driving system, a considerable number of functional scene test verifications are required before the products of related functional modules of the automatic driving system are shaped or put into mass production, and the HIL virtual simulation test technology can effectively identify and find defects and problems existing in the automatic driving system and accelerate the development process of the products.
The expected functional safety SOTIF of the automatic driving automobile refers to a risk identification, analysis and design method aiming at the expected function, which is provided from the whole automobile level, the system level, the software and hardware level and different system component levels such as perception, decision and execution, in order to avoid the safety risk caused by the non-failure, the expected functional limitation and the reasonable and foreseeable misuse of the whole automatic driving automobile and the system. By detecting and discovering and improving the functional deficiencies in different layers and system components based on the expected functional safety verification and confirmation of known unsafe scenes and unknown unsafe scenes, the automatic driving automobile can reach reasonable safety level under the expected use working condition.
However, in the existing loop simulation test system for the automatic driving hardware, a very effective test verification method is not provided for the expected function safety of the positioning function corresponding to the automatic driving system depending on the absolute positioning sensing technology route, and the real-time hardware-in-loop simulation test verification can not be performed under the positioning function scenes of the absolute positioning technology function limitation, such as the urban canyon, the multipath reflection caused by buildings, the reduction of the positioning accuracy caused by the limitation of traffic facilities, geographic conditions and the like, and the loss of the positioning signal.
Disclosure of Invention
In order to solve the above technical problems, the present invention provides an automatic driving test system and method, which can improve the safety and reliability of an automatic driving test.
To achieve the above object, the present application provides an automatic driving test system, comprising:
the system comprises an upper computer, a test bench, an automatic driving area controller, a combined navigation module and a global satellite navigation system simulator;
the upper computer is used for generating virtual scene data and sending the virtual scene data to the test bench; generating a position-associated radio frequency signal according to the virtual scene data, and sending the position-associated radio frequency signal to a global satellite navigation system simulator through a test bench;
the test bench is used for acquiring vehicle control data sent by the automatic driving area controller in real time, performing perception analysis processing according to the virtual scene data and the vehicle control data to generate first perception data, and sending the first perception data to the automatic driving area controller;
the global satellite navigation system simulator is used for generating absolute positioning data and relative positioning data according to the position-associated radio frequency signal and sending the absolute positioning data and the relative positioning data to the combined navigation module;
the combined navigation module is used for generating second sensing data according to the absolute positioning data and the relative positioning data and sending the second sensing data to the automatic driving area controller;
the automatic driving area controller is used for carrying out automatic driving control analysis based on the first perception data and the second perception data, generating latest vehicle control data, sending the latest vehicle control data to the test bench, determining at least one of the current second perception data, the current vehicle control data or the current track data as a test result when a preset condition is met, and adjusting the automatic driving area controller based on the test result.
In one possible implementation, the system further includes a data conversion module;
the upper computer is further used for generating the position correlation radio frequency signal and the relative positioning data according to the virtual scene data; and transmitting the position-correlated radio frequency signal to the global satellite navigation system simulator via the test rig; and sending the relative positioning data to a data conversion module;
the global satellite navigation system simulator is used for generating absolute positioning data and relative positioning data according to the position-associated radio frequency signal, sending the absolute positioning data to the integrated navigation module, and sending the relative positioning data to the data conversion module;
the data conversion module is used for performing data conversion on the relative positioning data to obtain relative positioning data in a target format and sending the relative positioning data in the target format to the integrated navigation module;
and the combined navigation module is used for generating second sensing data according to the absolute positioning data and the relative positioning data of the target format, and sending the second sensing data to the automatic driving domain controller.
In a possible implementation manner, the upper computer is further configured to acquire target map data within a preset range; and the number of the first and second groups,
performing multipath reflection processing according to the target map data to generate multipath virtual scene data; and the number of the first and second groups,
and matching and fusing the target map data and the multipath virtual scene data to generate the virtual scene data, and sending the virtual scene data to the test bench.
In one possible implementation manner, the upper computer is further configured to acquire current positioning data;
and the automatic driving area controller is further used for taking the current second sensing data as a test result when the current second sensing data and the current positioning data meet a first preset condition, and adjusting the automatic driving area controller based on the test result.
In a possible implementation manner, the automatic driving area controller is further configured to, when the current vehicle control data meets a second preset condition, use the current vehicle control data as a test result, and adjust the automatic driving area controller based on the test result.
In one possible implementation manner, the upper computer comprises a first upper computer and a second upper computer;
the computing power of the second upper computer is higher than that of the first upper computer;
the first upper computer is used for generating virtual scene data and sending the virtual scene data to the test bench;
the second upper computer is used for generating the position-related radio frequency signal according to the virtual scene data in a simulation mode, and sending the position-related radio frequency signal to the global satellite navigation system simulator through the test bench.
In another aspect, the present application further provides an automatic driving test method, including:
the upper computer generates virtual scene data and sends the virtual scene data to the test bench;
the upper computer generates a position-associated radio frequency signal according to the virtual scene data and sends the position-associated radio frequency signal to a global satellite navigation system simulator through a test bench;
the test bench acquires vehicle control data sent by an automatic driving area controller in real time, performs perception analysis processing according to the virtual scene data and the vehicle control data to generate first perception data, and sends the first perception data to the automatic driving area controller;
the global satellite navigation system simulator generates absolute positioning data and relative positioning data according to the position-associated radio frequency signal, and sends the absolute positioning data and the relative positioning data to the combined navigation module;
the combined navigation module generates second sensing data according to the absolute positioning data and the relative positioning data, and sends the second sensing data to the automatic driving area controller;
and the automatic driving area controller performs automatic driving control analysis based on the first sensing data and the second sensing data to generate vehicle control data, sends the vehicle control data to the test bench, determines at least one of the current second sensing data, the current vehicle control data or the current track data as a test result until a preset condition is met, and adjusts the automatic driving area controller based on the test result.
In one possible implementation manner, the generating, by the upper computer, virtual scene data and sending the virtual scene data to the test bench includes:
the upper computer acquires target map data within a preset range;
the upper computer performs multipath reflection processing according to the target map data to generate multipath virtual scene data;
and the upper computer performs matching fusion on the target map data and the multipath virtual scene data to generate the virtual scene data, and sends the virtual scene data to the test bench.
In one possible implementation, the gnss simulator generates absolute positioning data and relative positioning data according to the position-related radio frequency signal, and sends the absolute positioning data and the relative positioning data to the integrated navigation module includes:
the global satellite navigation system simulator generates a satellite radio-frequency signal and relative positioning data according to the position correlation radio-frequency signal, and sends the satellite radio-frequency signal serving as absolute positioning data to the combined navigation module;
the global satellite navigation system simulator sends the relative positioning data to a data conversion module;
and the data conversion module performs data format conversion on the relative positioning data to obtain the relative positioning data in the target format, and sends the relative positioning data in the target format to the combined navigation module.
In one possible implementation, the method further includes:
the upper computer acquires current positioning data;
when the preset condition is met, determining at least one of current second sensing data, current vehicle control data or current track data as a test result, and adjusting the automatic driving area controller based on the test result comprises:
and when the current second perception data and the current positioning data meet a first preset condition, taking the current second perception data as a test result, and adjusting the automatic driving area controller based on the test result.
In one possible implementation manner, when the preset condition is satisfied, determining at least one of current second sensing data, current vehicle control data, or current trajectory data as a test result, and adjusting the automatic driving area controller based on the test result includes:
and when the current vehicle control data meet a second preset condition, taking the current vehicle control data as a test result, and adjusting the automatic driving area controller based on the test result.
In one possible implementation, the first perception data includes: video frame data, bus simulation data, IO signals and fault simulation signals.
In one possible implementation, the bus emulation data includes:
millimeter wave radar data, ultrasonic radar data, and target controller data.
The application has the following beneficial effects:
the upper computer generates a position-associated radio frequency signal and relative positioning data according to the virtual scene data, sends the position-associated radio frequency signal to the global satellite navigation system simulator through the test bench, and sends the relative positioning data to the combined navigation module, so that the virtual scene data including a positioning function limited scene can be obtained, and the environment data for testing is more comprehensive; the test bench acquires vehicle control data sent by the automatic driving domain controller in real time, performs perception analysis processing according to virtual scene data and the vehicle control data to generate first perception data, sends the first perception data to the automatic driving domain controller, the global satellite navigation system simulator generates absolute positioning data according to position-related radio frequency signals, sends the absolute positioning data to the combined navigation module, the combined navigation module generates second perception data according to the absolute positioning data and the relative positioning data, and sends the second perception data to the automatic driving domain controller, so that more comprehensive perception data required by the automatic driving domain controller for automatic driving control analysis can be obtained; the automatic driving domain controller performs automatic driving control analysis based on the first sensing data and the second sensing data to generate vehicle control data, so that more real vehicle control data are generated, the vehicle control data have a reference value, a test result is more objective, and reliability and safety of automatic driving tests are improved.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an automatic driving test system according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an automatic driving test system according to another embodiment of the present application;
fig. 3 is a schematic flowchart of an automatic driving test method according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a method for generating virtual scene data by an upper computer according to an embodiment of the present application;
fig. 5 is a flowchart illustrating a method for generating absolute positioning data and relative positioning data according to an embodiment of the present application;
FIG. 6 is a schematic flow chart illustrating an automatic driving test method according to another embodiment of the present disclosure;
fig. 7 is a schematic flowchart of an automatic driving test method according to another embodiment of the present application.
Fig. 8 is a block diagram of an upper computer for an automatic driving test according to an embodiment of the present disclosure.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to implement the technical solution of the present application, so that more engineering workers can easily understand and apply the present application, the working principle of the present application will be further described with reference to specific embodiments.
The embodiment in the application provides an automatic driving test system and sets an automatic driving test method aiming at the problems that the test result of the test method in the prior art is inaccurate, and the test verification is not carried out on the automatic driving control function corresponding to the vehicle depending on the absolute positioning sensing technology in the automatic driving hardware-in-loop test system.
An automatic driving test system provided by the embodiment of the present application is described first below. As shown in fig. 1, the test system may include:
the system comprises an upper computer 10, a test bench 20, an automatic driving area controller 30, a combined navigation module 40 and a global satellite navigation system simulator 50.
Specifically, the upper computer 10 and the test bench 20, the test bench 20 and the autopilot domain controller 30, the autopilot domain controller 30 and the integrated navigation module 40, and the integrated navigation module 40 and the global satellite navigation system simulator 50 are respectively in communication connection, wherein the test bench 20 and the autopilot domain controller 30 CAN be connected through board wiring, the autopilot domain controller 30 and the integrated navigation module 40 CAN be connected through a CAN line, the upper computer 10 and the test bench 20 CAN be connected through an ethernet, and the integrated navigation module 40 and the global satellite navigation system simulator 50 CAN be connected through a hard line.
The upper computer 10 may be installed with upper computer management software, and is configured to generate virtual scene data and send the virtual scene data to the test bench 20; a position-related radio frequency signal and relative positioning data are generated from the virtual scene data and sent to the global satellite navigation system simulator 50 via the test rig 20, and the relative positioning data is sent to the integrated navigation module.
In this embodiment of the present description, the virtual scene data may include a non-special scene and a special scene, where the non-special scene refers to a scene without multipath reflection; the special scene refers to a scene under the condition of multipath reflection, satellite signal obstruction or deceptive interference, for example, a scene in which the multipath reflection is caused by urban canyons, tunnels and buildings and the positioning function is limited due to the limitation of traffic facilities and geographic conditions. The position-associated radio frequency signal refers to a signal which is subjected to multipath reflection, satellite signal shielding or satellite signal deception and can be received by the simulated vehicle position in the virtual scene. The relative positioning data refers to simulated data with a function similar to that of an Inertial Measurement Unit (IMU), and can replace Inertial navigation data generated when a vehicle runs in an actual road condition through the simulation of IMU data.
The test bench 20 may be configured to obtain vehicle control data sent by the autonomous driving area controller 30 in real time, perform sensing analysis according to the virtual scene data and the vehicle control data, generate first sensing data, and send the first sensing data to the autonomous driving area controller 30. Specifically, the first perception data may include video perception data, radar perception data, and the like.
In the embodiment of the present disclosure, a vehicle dynamics model may be configured in the test rack 20, and the vehicle control data may be used as an input of the vehicle dynamics model, and the vehicle dynamics model simulates real vehicle controlled output driving state data according to the vehicle control data and the virtual scene data.
The gnss simulator 50 may be configured to generate absolute positioning data according to the position-related radio frequency signal, and transmit the absolute positioning data to the integrated navigation module 40. The GNSS simulator 50 may employ a multi-frequency multi-mode GNSS (Global Navigation Satellite System) simulator.
Combined navigation module 40 may be configured to generate second sensory data based on the absolute positioning data and the relative positioning data, and send the second sensory data to autonomous driving area controller 30.
The autopilot domain controller 30 is configured to perform autopilot control analysis based on the first sensing data and the second sensing data, generate current vehicle control data, send the current vehicle control data to the test bench 20, determine at least one of the current second sensing data, the current vehicle control data, or the current trajectory data as a test result until a preset condition is satisfied, and adjust the autopilot domain controller 30 based on the test result.
In a possible implementation manner, as shown in fig. 2, the system may further include a data conversion module 60, and the data conversion module 60 may employ a TS1823 FPGA (Field Programmable gate array) board. The gnss simulator 50 is configured to generate absolute positioning data and relative positioning data according to the position-related radio frequency signal, send the absolute positioning data to the integrated navigation module 40, and send the relative positioning data to the data conversion module 60. The data conversion module 60 is configured to perform data conversion on the relative positioning data to obtain the relative positioning data in the target format, and send the relative positioning data in the target format to the integrated navigation module 40. And the integrated navigation module 40 is configured to generate second sensing data according to the absolute positioning data and the relative positioning data in the target format, and send the second sensing data to the autopilot domain controller 30.
In one possible implementation, the upper computer 10 is further configured to generate a position-related radio frequency signal and relative positioning data according to the virtual scene data; and transmitting the position-related radio frequency signal to the global satellite navigation system simulator 50 through the test rig 20; and, sends the relative positioning data to the data conversion module 60.
In a possible implementation manner, the upper computer 10 is further configured to obtain target map data within a preset range; performing multipath reflection processing according to the target map data to generate multipath virtual scene data; and matching and fusing the target map data and the multipath virtual scene data to generate virtual scene data, and sending the virtual scene data to the test bench 20.
In one possible implementation, the upper computer 10 is further configured to obtain current positioning data. The automatic driving area controller 30 is further configured to take the current second sensing data as a test result when the current second sensing data and the current positioning data satisfy a first preset condition, and adjust the automatic driving area controller 30 based on the test result.
In one possible implementation, the autopilot domain controller 30 is further configured to take the current vehicle control data as a test result when the current vehicle control data satisfies a second preset condition, and to adjust the autopilot domain controller based on the test result.
In one possible implementation, the upper computer 10 may include a first upper computer and a second upper computer. The computing power of the second upper computer is higher than that of the first upper computer. The first host computer is used for generating virtual scene data and sending the virtual scene data to the test bench 20. The second upper computer is used for generating a position-related radio frequency signal according to the virtual scene data in a simulation mode, and sending the position-related radio frequency signal to the global satellite navigation system simulator 50 through the test bench 20.
In practical application, the first upper computer may deploy VTD (Virtual Test Drive) software for constructing original Virtual scene data according to the high-precision map, where the original Virtual data may include element data such as roads, buildings, bridges, traffic signs, and the like. The second upper computer can be provided with a sim3D multipath simulation model generator and sim3 simulation model generator, the first upper computer imports the original virtual data into the second upper computer, and the second upper computer performs data processing on the original virtual data by using the sim3D multipath simulation model generator and the sim3D multipath simulation model generator to generate virtual scene data. And the second upper computer generates a position-associated radio frequency signal according to the virtual scene data. The original virtual data are subjected to data processing by the aid of the high-computing-power second upper computer to generate virtual scene data, and the position-associated radio frequency signals are generated according to the virtual scene data, so that the virtual scene generation efficiency can be improved.
The present application additionally provides an embodiment of an automatic driving test method, as shown in fig. 3, the method may include:
s101: the upper computer generates virtual scene data and sends the virtual scene data to the test bench.
In this embodiment of the present description, the virtual scene data may include a non-special scene and a special scene, where the non-special scene refers to a scene without multipath reflection; the special scene refers to a scene under the condition of multipath reflection, satellite signal obstruction or deceptive interference, for example, a scene in which the multipath reflection is caused by urban canyons, tunnels and buildings and the positioning function is limited due to the limitation of traffic facilities and geographic conditions. The upper computer can construct original virtual scene data according to the high-precision map, and multipath simulation is carried out on the original virtual scene data to generate virtual scene data. The upper computer can send the generated virtual scene data to the test bench through the Ethernet.
S103: the upper computer generates position-associated radio frequency signals and relative positioning data according to the virtual scene data, sends the position-associated radio frequency signals to the global satellite navigation system simulator through the test bench, and sends the relative positioning data to the combined navigation module.
In this embodiment of the present description, the position-related radio frequency signal refers to a signal that is received by a simulated vehicle position in a virtual scene and that has undergone a process of multipath reflection, satellite signal occlusion, or satellite signal deception, and the upper computer may send the position-related radio frequency signal to the global satellite navigation system simulator through a TCP (Transmission Control Protocol). The upper computer can generate radio frequency signals received at the simulated vehicle position in the virtual scene, and the radio frequency signals are used as position-related radio frequency signals to be sent to the test bench. Specifically, the upper computer may send the position-related radio frequency signal to the test bench through the ethernet, and the test bench may send the position-related radio frequency signal to the global satellite navigation system simulator through the ethernet. The relative positioning data refers to simulated data with functions similar to those of IMU data, and can replace inertial navigation data generated when a vehicle runs in an actual road condition through simulation of the IMU data.
S105: the test bench acquires vehicle control data sent by the automatic driving area controller in real time, performs perception analysis processing according to the virtual scene data and the vehicle control data, generates first perception data, and sends the first perception data to the automatic driving area controller.
In this embodiment of the present specification, the first sensing data refers to a part of sensing data required by the autopilot domain controller for sensing analysis, and the part of sensing data may include one or more of video stream data, bus simulation data, IO signals, and fault signals. The vehicle control data sent by the automatic driving area controller and acquired by the test bench is vehicle control data generated by the automatic driving area controller based on first perception data at a previous moment and second perception data at the previous moment and performing automatic driving control analysis. The test bench acquires vehicle control data sent by the automatic driving area controller in real time, and performs perception analysis processing according to the virtual scene data and the vehicle control data to generate first perception data.
In practical application, time t1 is referred to as previous time, time t2 is referred to as current time, an automatic driving domain controller performs automatic driving control analysis based on first perception data at time t1 and second perception data at time t1 to generate vehicle control data at time t2, a test bench obtains vehicle control data at current time t2, and perception analysis processing is performed according to virtual scene data at time t2 and the vehicle control data at time t2 to generate the first perception data at time t 2.
S107: and the global satellite navigation system simulator generates absolute positioning data according to the position correlation radio frequency signal and sends the absolute positioning data to the combined navigation module.
In the embodiment of the present description, after the GNSS simulator obtains the position-related radio frequency signal, the GNSS simulator may perform control such as satellite constellation and GNSS deception jamming on the position-related radio frequency signal, calculate an RF signal data stream result, and use the RF signal data stream result as absolute positioning data. And the global satellite navigation system simulator sends the absolute positioning data to the integrated navigation module.
S109: and the combined navigation module generates second sensing data according to the absolute positioning data and the relative positioning data and sends the second sensing data to the automatic driving area controller.
In this specification, the integrated navigation module may perform fusion processing of the positioning data on the absolute positioning data and the relative positioning data, and generate second sensing data. And the combined navigation module sends second sensing data to the automatic driving domain controller, wherein the second sensing data are positioning data required by the automatic driving domain controller during sensing analysis.
S111: and the automatic driving domain controller performs automatic driving control analysis based on the first sensing data and the second sensing data to generate vehicle control data, sends the vehicle control data to the test bench, determines at least one of the current second sensing data, the current vehicle control data or the current track data as a test result until a preset condition is met, and adjusts the automatic driving domain controller based on the test result.
In the embodiment of the present specification, the vehicle control data is control data required for driving a simulated vehicle in an automatic driving test, and for example, the vehicle control data may be command data for controlling acceleration. And the automatic driving domain controller performs perception fusion processing based on the first perception data and the second perception data, and performs data analysis aiming at specific functions of automatic driving control so as to generate vehicle control data. After the automatic driving area controller sends the vehicle control data to the test bench, the test bench can continue to use the vehicle control data as the input of the vehicle dynamics model, and performs perception analysis processing by combining the virtual scene data of the simulated vehicle to generate first perception data. The application does not limit the termination time of the test. And when the preset conditions are met, determining at least one of the current second sensing data, the current vehicle control data or the current track data as a test result, and adjusting the automatic driving area controller based on the test result.
In the embodiment, the upper computer generates the virtual scene data and sends the virtual scene data to the test bench, the upper computer generates the position-associated radio frequency signal and the relative positioning data according to the virtual scene data, sends the position-associated radio frequency signal to the global satellite navigation system simulator through the test bench, and sends the relative positioning data to the combined navigation module, so that the virtual scene data including the positioning function limited scene can be obtained, and the environment data for testing is more comprehensive; the test bench acquires vehicle control data sent by the automatic driving domain controller in real time, performs perception analysis processing according to virtual scene data and the vehicle control data to generate first perception data, sends the first perception data to the automatic driving domain controller, the global satellite navigation system simulator generates absolute positioning data according to position-related radio frequency signals, sends the absolute positioning data to the combined navigation module, the combined navigation module generates second perception data according to the absolute positioning data and the relative positioning data, and sends the second perception data to the automatic driving domain controller, so that more comprehensive perception data required by the automatic driving domain controller for automatic driving control analysis can be obtained; the automatic driving domain controller performs automatic driving control analysis based on the first sensing data and the second sensing data to generate vehicle control data, so that more real vehicle control data are generated, the vehicle control data have a higher reference value, and a test result is more objective.
In one possible implementation manner, as shown in fig. 4, in step S101, the generating, by the upper computer, virtual scene data and sending the virtual scene data to the test bench may include:
s1011: the upper computer obtains target map data in a preset range.
Specifically, the preset range refers to an overall range in which the simulated vehicle needs to operate in the target map for the automatic driving test. The target map data refers to map data which can describe the position of a simulated vehicle and the environment where the simulated vehicle is located, the target map data can include high-precision map data, and the target map data can include data of roads, buildings, bridges, traffic signs and the like.
S1013: and the upper computer performs multipath reflection processing according to the target map data to generate multipath virtual scene data.
And the upper computer determines the full-scale target points in the map and the associated data of each object according to the target map data, and performs multipath reflection processing on the full-scale target points according to the corresponding associated data of the objects to generate multipath virtual scene data. The total target point refers to a position point to which the simulated vehicle may travel. The object association data refers to data describing the position of an object such as a building, a tree, or the like.
S1015: and the upper computer performs matching fusion on the target map data and the multipath virtual scene data to generate virtual scene data, and sends the virtual scene data to the test bench.
In the embodiment of the present specification, the target map data and the multipath virtual scene data have a correspondence relationship between position points, and the upper computer performs matching fusion on the target map data and the multipath virtual scene data according to the correspondence relationship, so as to generate the virtual scene data.
In the embodiment, target map data within a preset range is acquired through an upper computer, multipath reflection processing is performed according to the target map data to generate multipath virtual scene data, the target map data and the multipath virtual scene data are matched and fused to generate virtual scene data, the virtual scene data are sent to a test bench, and a virtual scene comprising functional scenes such as satellite signal shielding, multipath reflection and diffraction can be obtained.
In one possible implementation manner, as shown in fig. 5, in step S107, the gnss simulator may generate absolute positioning data and relative positioning data according to the position-related radio frequency signal, and send the absolute positioning data and the relative positioning data to the integrated navigation module, which may include:
s1071: the global satellite navigation system simulator generates satellite radio-frequency signals and relative positioning data according to the position correlation radio-frequency signals, and sends the satellite radio-frequency signals serving as absolute positioning data to the combined navigation module.
S1073: the global satellite navigation system simulator sends the relative positioning data to the data conversion module.
S1075: and the data conversion module performs data format conversion on the relative positioning data to obtain the relative positioning data in the target format, and sends the relative positioning data in the target format to the combined navigation module.
In this embodiment, the data conversion module may convert the relative positioning data sent by the gnss simulator into a target format, for example, convert the relative positioning data in UDP (User Datagram Protocol) format into SPI bus data, so that the relative positioning data can be used by the integrated navigation module.
In one possible implementation, as shown in fig. 6, the method may include:
s101: the upper computer generates virtual scene data and sends the virtual scene data to the test bench.
S103: and the upper computer generates a position-associated radio frequency signal according to the virtual scene data, and sends the position-associated radio frequency signal to the global satellite navigation system simulator through the test bench.
S105: the test bench acquires vehicle control data sent by the automatic driving area controller in real time, performs perception analysis processing according to the virtual scene data and the vehicle control data, generates first perception data, and sends the first perception data to the automatic driving area controller.
S107: and the global satellite navigation system simulator generates absolute positioning data and relative positioning data according to the position correlation radio frequency signal, and sends the absolute positioning data and the relative positioning data to the combined navigation module.
S109: and the combined navigation module generates second sensing data according to the absolute positioning data and the relative positioning data and sends the second sensing data to the automatic driving area controller.
S201: and the automatic driving domain controller performs automatic driving control analysis based on the first sensing data and the second sensing data, generates vehicle control data and sends the vehicle control data to the test bench.
S203: the upper computer obtains current positioning data.
In the embodiment of the present specification, the current positioning data refers to real positioning data of a simulated vehicle obtained from virtual environment data.
S205: and when the current second sensing data and the current positioning data meet a first preset condition, taking the current second sensing data as a test result, and adjusting the automatic driving area controller based on the test result.
In practical application, when the difference value between the second sensing data and the current positioning data meets a preset threshold value, the current second sensing data is used as a test result, and the automatic driving area controller is adjusted based on the test result.
In one possible implementation, as shown in fig. 7, the method may include:
s101: the upper computer generates virtual scene data and sends the virtual scene data to the test bench.
S103: and the upper computer generates a position-associated radio frequency signal according to the virtual scene data, and sends the position-associated radio frequency signal to the global satellite navigation system simulator through the test bench.
S105: the test bench acquires vehicle control data sent by the automatic driving area controller in real time, performs perception analysis processing according to the virtual scene data and the vehicle control data, generates first perception data, and sends the first perception data to the automatic driving area controller.
S107: and the global satellite navigation system simulator generates absolute positioning data and relative positioning data according to the position correlation radio frequency signal, and sends the absolute positioning data and the relative positioning data to the combined navigation module.
S109: and the combined navigation module generates second sensing data according to the absolute positioning data and the relative positioning data and sends the second sensing data to the automatic driving area controller.
S301: and the automatic driving domain controller performs automatic driving control analysis based on the first sensing data and the second sensing data, generates vehicle control data and sends the vehicle control data to the test bench.
S303: and when the current vehicle control data meet a second preset condition, taking the current vehicle control data as a test result, and adjusting the automatic driving area controller based on the test result.
In practical application, reference vehicle control data can be obtained, when the current vehicle control data and the reference vehicle control data exceed a preset control threshold, the current vehicle control data is used as a test result, and the automatic driving area controller is adjusted based on the test result, wherein the reference vehicle control data can be vehicle control data corresponding to a road condition of a simulated vehicle in a current virtual scene, which is preset by experts or technicians in the field.
In one possible implementation, when the automatic driving test reports an error and stops running, the driving track data of the simulated vehicle before the error is reported may be obtained, the driving track data is used as a test result, and the automatic driving area controller is adjusted based on the test result.
In one possible implementation, the first perception data may include: video stream data, bus emulation data, IO signals, and fault simulation signals.
In one possible implementation, the bus emulation data may include:
millimeter wave radar data, ultrasonic radar data, and target controller data.
Specifically, the target controller data refers to data generated by a target controller on the vehicle, such as data simulating a window controller, which is simulated or acquired.
According to the two embodiments, the sensing data corresponding to the real-world automatic driving is generated, so that the safety and the reliability of the automatic driving test can be greatly improved.
Fig. 8 is a block diagram illustrating an upper computer for an automatic driving test according to an exemplary embodiment, an internal structure diagram of which may be as shown in fig. 8. The upper computer may include a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein, the processor of the upper computer is used for providing calculation and control capability. The memory of the upper computer comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the electronic device is used for communicating with an external device through network connection. The computer program is executed by a processor to implement a method of automatic driving testing. The display screen of the upper computer can be a liquid crystal display screen or an electronic ink display screen, and the input device of the upper computer can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the electronic equipment, an external keyboard, a touch pad or a mouse and the like.
In an exemplary embodiment, a computer-readable storage medium is also provided, in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform an autopilot testing method in embodiments of the present disclosure. The computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, a computer program product containing instructions that, when executed on a computer, cause the computer to perform an autopilot testing method in embodiments of the present disclosure is also provided.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that although embodiments described herein include some features included in other embodiments, not other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims of the present invention, any of the claimed embodiments may be used in any combination.
The present invention may also be embodied as apparatus or system programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps or the like not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several systems, several of these systems may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering and these words may be interpreted as names.
Claims (13)
1. An automated driving test system, the system comprising:
the system comprises an upper computer, a test bench, an automatic driving area controller, a combined navigation module and a global satellite navigation system simulator;
the upper computer is used for generating virtual scene data and sending the virtual scene data to the test bench; generating a position-associated radio frequency signal and relative positioning data according to the virtual scene data, sending the position-associated radio frequency signal to a global satellite navigation system simulator through a test bench, and sending the relative positioning data to a combined navigation module;
the test bench is used for acquiring vehicle control data sent by the automatic driving area controller in real time, performing perception analysis processing according to the virtual scene data and the vehicle control data to generate first perception data, and sending the first perception data to the automatic driving area controller;
the global satellite navigation system simulator is used for generating absolute positioning data according to the position-associated radio frequency signal and sending the absolute positioning data to the combined navigation module;
the combined navigation module is used for generating second sensing data according to the absolute positioning data and the relative positioning data and sending the second sensing data to the automatic driving area controller;
the automatic driving area controller is used for carrying out automatic driving control analysis based on the first perception data and the second perception data, generating current vehicle control data, sending the current vehicle control data to the test bench, determining at least one of the current second perception data, the current vehicle control data or the current track data as a test result until a preset condition is met, and adjusting the automatic driving area controller based on the test result.
2. The system of claim 1, further comprising a data conversion module;
the upper computer is further used for generating the position correlation radio frequency signal and the relative positioning data according to the virtual scene data; and transmitting the position-correlated radio frequency signal to the global satellite navigation system simulator via the test rig; and sending the relative positioning data to a data conversion module;
the global satellite navigation system simulator is used for generating absolute positioning data and relative positioning data according to the position-associated radio frequency signal, sending the absolute positioning data to the integrated navigation module, and sending the relative positioning data to the data conversion module;
the data conversion module is used for performing data conversion on the relative positioning data to obtain relative positioning data in a target format and sending the relative positioning data in the target format to the integrated navigation module;
and the combined navigation module is used for generating second sensing data according to the absolute positioning data and the relative positioning data of the target format, and sending the second sensing data to the automatic driving domain controller.
3. The system of claim 1, wherein the upper computer is further configured to obtain target map data within a preset range; and the number of the first and second groups,
performing multipath reflection processing according to the target map data to generate multipath virtual scene data; and the number of the first and second groups,
and matching and fusing the target map data and the multipath virtual scene data to generate the virtual scene data, and sending the virtual scene data to the test bench.
4. The system of claim 1, wherein the upper computer is further configured to obtain current location data;
and the automatic driving area controller is further used for taking the current second sensing data as a test result when the current second sensing data and the current positioning data meet a first preset condition, and adjusting the automatic driving area controller based on the test result.
5. The system of claim 1, wherein the autopilot domain controller is further configured to take the current vehicle control data as a test result when the current vehicle control data meets a second predetermined condition, and to adjust the autopilot domain controller based on the test result.
6. The system of claim 1, wherein the upper computer comprises a first upper computer and a second upper computer;
the computing power of the second upper computer is higher than that of the first upper computer;
the first upper computer is used for generating virtual scene data and sending the virtual scene data to the test bench;
the second upper computer is used for generating the position-related radio frequency signal according to the virtual scene data in a simulation mode, and sending the position-related radio frequency signal to the global satellite navigation system simulator through the test bench.
7. An automated driving test method, the method comprising:
the upper computer generates virtual scene data and sends the virtual scene data to the test bench;
the upper computer generates a position-associated radio frequency signal and relative positioning data according to the virtual scene data, sends the position-associated radio frequency signal to a global satellite navigation system simulator through a test bench and sends the relative positioning data to an integrated navigation module;
the test bench acquires vehicle control data sent by an automatic driving area controller in real time, performs perception analysis processing according to the virtual scene data and the vehicle control data to generate first perception data, and sends the first perception data to the automatic driving area controller;
the global satellite navigation system simulator generates absolute positioning data according to the position-associated radio frequency signal and sends the absolute positioning data to the integrated navigation module;
the combined navigation module generates second sensing data according to the absolute positioning data and the relative positioning data, and sends the second sensing data to the automatic driving area controller;
and the automatic driving area controller performs automatic driving control analysis based on the first sensing data and the second sensing data to generate vehicle control data, sends the vehicle control data to the test bench, determines at least one of the current second sensing data, the current vehicle control data or the current track data as a test result until a preset condition is met, and adjusts the automatic driving area controller based on the test result.
8. The method of claim 7, wherein the upper computer generating virtual scene data and sending the virtual scene data to a test bench comprises:
the upper computer acquires target map data within a preset range;
the upper computer performs multipath reflection processing according to the target map data to generate multipath virtual scene data;
and the upper computer performs matching fusion on the target map data and the multipath virtual scene data to generate the virtual scene data, and sends the virtual scene data to the test bench.
9. The method of claim 7, wherein the upper computer generates a position-associated radio frequency signal and relative positioning data from the virtual scene data and sends the position-associated radio frequency signal to a global satellite navigation system simulator via a test rig, and sending the relative positioning data to a combined navigation module comprises:
the upper computer generates the position-associated radio frequency signal and the relative positioning data according to the virtual scene data;
the upper computer sends the position-associated radio frequency signal to the global satellite navigation system simulator through the test bench;
the global satellite navigation system simulator generates a satellite radio-frequency signal according to the position-associated radio-frequency signal, and sends the satellite radio-frequency signal to the integrated navigation module as absolute positioning data;
the upper computer sends the relative positioning data to a data conversion module;
and the data conversion module performs data format conversion on the relative positioning data to obtain the relative positioning data in the target format, and sends the relative positioning data in the target format to the combined navigation module.
10. The method of claim 7, further comprising:
the upper computer acquires current positioning data;
when the preset condition is met, determining at least one of current second sensing data, current vehicle control data or current track data as a test result, and adjusting the automatic driving area controller based on the test result comprises:
and when the current second perception data and the current positioning data meet a first preset condition, taking the current second perception data as a test result, and adjusting the automatic driving area controller based on the test result.
11. The method of claim 7, wherein determining at least one of current second perception data, current vehicle control data, or current trajectory data as a test result when a preset condition is satisfied, and adjusting the autopilot domain controller based on the test result comprises:
and when the current vehicle control data meet a second preset condition, taking the current vehicle control data as a test result, and adjusting the automatic driving area controller based on the test result.
12. The method of claim 7, wherein the first perception data comprises: video frame data, bus simulation data, IO signals and fault simulation signals.
13. The method of claim 12, wherein the bus emulation data comprises:
millimeter wave radar data, ultrasonic radar data, and target controller data.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110351732 | 2021-03-31 | ||
CN2021103517325 | 2021-03-31 |
Publications (1)
Publication Number | Publication Date |
---|---|
CN113625685A true CN113625685A (en) | 2021-11-09 |
Family
ID=78380868
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110844003.3A Pending CN113625685A (en) | 2021-03-31 | 2021-07-26 | Automatic driving test system and method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113625685A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114185330A (en) * | 2021-12-12 | 2022-03-15 | 蜂联智能(深圳)有限公司 | Control method and control device based on multi-scene interaction |
CN117434916A (en) * | 2022-07-15 | 2024-01-23 | 小米汽车科技有限公司 | Vehicle function test system, method and storage medium |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108931260A (en) * | 2018-07-04 | 2018-12-04 | 山东省科学院自动化研究所 | Automatic driving vehicle positioning security test macro and method when GPS is cheated |
CN110243610A (en) * | 2019-05-13 | 2019-09-17 | 北京航空航天大学 | A kind of the multidimensional interference automatic Pilot test macro and method of movement and fixed Combination |
CN110307995A (en) * | 2019-05-28 | 2019-10-08 | 同济大学 | A kind of test method for autonomous driving vehicle marginal test |
CN111949544A (en) * | 2020-08-19 | 2020-11-17 | 腾讯科技(深圳)有限公司 | Test method and related device for positioning module of automatic driving vehicle |
US20200378870A1 (en) * | 2019-05-29 | 2020-12-03 | Pony Ai Inc. | Driving emulation system for an autonomous vehicle |
CN112130472A (en) * | 2020-10-14 | 2020-12-25 | 广州小鹏自动驾驶科技有限公司 | Automatic driving simulation test system and method |
CN112182748A (en) * | 2020-09-18 | 2021-01-05 | 苏州星越智能科技有限公司 | Automatic driving sensor simulation test system and application method thereof |
CN112180892A (en) * | 2020-09-11 | 2021-01-05 | 苏州智行众维智能科技有限公司 | Intelligent driving vehicle testing method based on field-in-loop |
-
2021
- 2021-07-26 CN CN202110844003.3A patent/CN113625685A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108931260A (en) * | 2018-07-04 | 2018-12-04 | 山东省科学院自动化研究所 | Automatic driving vehicle positioning security test macro and method when GPS is cheated |
CN110243610A (en) * | 2019-05-13 | 2019-09-17 | 北京航空航天大学 | A kind of the multidimensional interference automatic Pilot test macro and method of movement and fixed Combination |
CN110307995A (en) * | 2019-05-28 | 2019-10-08 | 同济大学 | A kind of test method for autonomous driving vehicle marginal test |
US20200378870A1 (en) * | 2019-05-29 | 2020-12-03 | Pony Ai Inc. | Driving emulation system for an autonomous vehicle |
CN111949544A (en) * | 2020-08-19 | 2020-11-17 | 腾讯科技(深圳)有限公司 | Test method and related device for positioning module of automatic driving vehicle |
CN112180892A (en) * | 2020-09-11 | 2021-01-05 | 苏州智行众维智能科技有限公司 | Intelligent driving vehicle testing method based on field-in-loop |
CN112182748A (en) * | 2020-09-18 | 2021-01-05 | 苏州星越智能科技有限公司 | Automatic driving sensor simulation test system and application method thereof |
CN112130472A (en) * | 2020-10-14 | 2020-12-25 | 广州小鹏自动驾驶科技有限公司 | Automatic driving simulation test system and method |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114185330A (en) * | 2021-12-12 | 2022-03-15 | 蜂联智能(深圳)有限公司 | Control method and control device based on multi-scene interaction |
CN114185330B (en) * | 2021-12-12 | 2024-06-11 | 深圳市集智创新信息技术有限公司 | Control method and control device based on multi-scene interaction |
CN117434916A (en) * | 2022-07-15 | 2024-01-23 | 小米汽车科技有限公司 | Vehicle function test system, method and storage medium |
CN117434916B (en) * | 2022-07-15 | 2024-06-11 | 小米汽车科技有限公司 | Vehicle function test system, method and storage medium |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN112965466B (en) | Reduction test method, device, equipment and program product of automatic driving system | |
US11400928B2 (en) | Driverless vehicle testing method and apparatus, device and storage medium | |
US10579512B2 (en) | Method and apparatus for testing software for autonomous vehicles | |
Szalay | Next generation X-in-the-loop validation methodology for automated vehicle systems | |
CN112783006B (en) | Hardware-in-loop simulation test system for vehicle-mounted computing unit of automatic driving vehicle | |
US10885240B2 (en) | Deterministic simulation framework for autonomous vehicle testing | |
CN113625685A (en) | Automatic driving test system and method | |
CN109596145B (en) | Dynamic test method and system for vehicle navigation | |
CN113419518B (en) | VIL test platform based on VTS | |
CN218332314U (en) | HIL simulation test platform based on intelligent driving area controller | |
Song et al. | Development and validation of a distance measurement system in metro lines | |
CN112671487B (en) | Vehicle testing method, server and testing vehicle | |
CN111699449A (en) | Simulation test method and system for automatic driving vehicle, storage medium and vehicle | |
Sovani | Simulation accelerates development of autonomous driving | |
Gowdu et al. | System architecture for installed-performance testing of automotive radars over-the-air | |
Passchier et al. | An integral approach to autonomous and cooperative vehicles development and testing | |
US11327878B2 (en) | Method for rating a software component of an SiL environment | |
CN117193041A (en) | Unmanned collection card is at ring test platform based on digit twin | |
CN117131589A (en) | Simulation test method and device for intelligent network-connected vehicle cooperative algorithm | |
EP3618013A1 (en) | System for generating vehicle sensor data | |
CN115657494A (en) | Virtual object simulation method, device, equipment and storage medium | |
CN115576296A (en) | Vehicle in-loop test system, method and device and storage medium | |
CN106842151B (en) | Based on the Passive Positioning test method that guinea pig system interference source azimuth angle is constant | |
CN115956190A (en) | Method and apparatus for providing high resolution digital map | |
Lu et al. | Methods for certification of GNSS-based safe vehicle localisation in driving assistance systems |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211109 |