CN110736627A - automatic driving test vehicle and remote control system and method thereof - Google Patents

Abstract

The invention discloses an automatic driving test vehicle and a remote control system and method thereof. The automatic driving test vehicle includes a casing, a power chassis connected to the bottom of the casing, and a vehicle environment perception device; the vehicle environment perception device includes: a positioning device , video acquisition device, environmental perception device, bus controller and on-board processor; the system includes an autonomous driving test vehicle, a communication base station, a remote control center and a driving simulator; the remote control center receives the test vehicle operation data, as well as the test vehicle and the tested vehicle. The relative position information of the vehicle and the running status data of the vehicle under test are used for multi-faceted fusion processing and targeted processing of the received data, so as to monitor whether the running status of the test vehicle is normal or not; the user manually operates the driving simulator uploaded by receiving the driving simulator. state data or receive the driving track data input by the user, analyze it, generate control commands, and send the control commands to the automatic test vehicle through the communication base station.

Description

An automatic driving test vehicle and its remote control system and method

technical field

The present disclosure relates to the technical field of test vehicles, and features an automatic driving test vehicle for behavior testing of unmanned vehicles, and a remote control system and method thereof.

Background technique

With the continuous deepening of research on the automation, intelligence and networking of autonomous vehicles, more and more companies have begun to make breakthroughs in this field, and the testing of autonomous vehicles has become a must for many developers. An issue that is not considered. However, in China, due to the lack of relevant laws, self-driving cars are not yet allowed to be tested on public roads, so companies that have the need for self-driving car testing may choose places that have opened road tests in the United States, Germany, and Japan. To test, either can only be achieved through domestic demonstration areas. Therefore, in the past two years, a large number of intelligent network connection or autonomous driving demonstration areas have been built successively in China.

The autonomous driving demonstration area provides a wealth of static traffic scenes within a certain range, but how to create dynamic traffic scenes, while achieving the test effect and ensuring the safety of testers, is a more difficult problem. Some test sites use manual remote control to create traffic scenes, such as moving dummies, animals, vehicles, etc. However, this kind of test method can only evaluate the test performance of a single scene of a car. Due to the complexity and randomness of the traffic environment, there is currently a lack of flexible and flexible test methods and equipment covering a wide range of scenes.

SUMMARY OF THE INVENTION

In order to overcome the above-mentioned deficiencies of the prior art, the present disclosure provides an automatic driving test vehicle and a remote control system and method thereof.

An aspect of the present disclosure provides a technical solution for an autonomous driving test vehicle:

An automatic driving test vehicle, comprising a casing, a power chassis connected at the bottom of the casing, and a vehicle environment perception device;

The in-vehicle environment perception equipment includes:

The positioning device is used to collect the position information of the test vehicle, including latitude and longitude, speed and heading information, and transmit it to the on-board processor;

Video acquisition device, used to collect video information of road conditions ahead of the test vehicle and transmit it to the on-board processor;

The environmental perception device is used to collect environmental data around the test vehicle, including static obstacle data, moving obstacle data and obstacle image information, and transmit it to the on-board processor;

The bus controller is used to collect the running status data and fault status data of the test vehicle, and transmit them to the vehicle-mounted processor; receive the control signal output by the vehicle-mounted controller, and control the test vehicle to perform corresponding actions;

The on-board processor is used to receive the position information of the test vehicle, the video information of the road conditions ahead, the surrounding environment data, the running status data and the fault status data, and upload it to the remote control center through the communication device; The control instructions are parsed, converted into control signals for the test vehicle, and output to the power chassis through the bus controller to control the automatic test vehicle to complete corresponding actions.

Further, the positioning device includes a GPS receiver and an IMU inertial navigation device installed in the cavity formed between the casing and the power chassis, and a GPS positioning antenna installed in the front and rear of the casing; the GPS receiver is used to receive GPS The position information of the test vehicle and the relative position information with the tested vehicle collected by the positioning antenna; the IMU inertial navigation device is used to collect the attitude information of the test vehicle.

Further, the environment perception device includes a lidar mounted on the top of the casing, a camera, and a millimeter-wave radar mounted on the front of the test vehicle, the laser sensor is used to detect the distance between the test vehicle and a stationary obstacle; The millimeter-wave radar is used to detect the number, distance and speed of moving obstacles; the camera is used to collect image information of the obstacles.

One aspect of the present disclosure provides a technical solution for a remote control system for an autonomous driving test vehicle:

A remote control system for an automatic driving test vehicle, the system comprising the above automatic driving test vehicle, a communication base station, a remote control center and a driving simulator;

The automatic test vehicle is used to collect the location information of the test vehicle, the video information of the road conditions ahead, the surrounding environment data, the running status data and the fault status data, and upload them to the remote control center; receive and execute the control instructions sent by the remote control center;

The communication base station is used to complete the data interaction between the automatic test vehicle and the remote control center;

The remote control center is used to receive location information of the test vehicle, video information of road conditions ahead, surrounding environment data, operating status data, and fault status data, as well as relative position information between the test vehicle and the vehicle under test and the running status data of the vehicle under test. , perform multi-faceted fusion processing on the received data, classify and store the received data, and carry out targeted processing of different types of data to monitor the normal operation status of the test vehicle; build a simulated driving environment, and use the The received running status data of the test vehicle and the running status data of the tested vehicle are updated in real time to simulate the simulated driving environment; at the same time, the status data of the user's manual operation of the driving simulator uploaded by the driving simulator or the driving trajectory data input by the user are received, and the It parses, generates control commands, and sends the control commands to the automatic test vehicle via the communication base station.

Further, the specific implementation method that the remote control center performs multi-faceted fusion processing on the received data is:

Introduce a time synchronization mechanism to synchronously obtain the road condition video data, surrounding environment information, location information, and motion status information of the test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test;

Combine the position information of the test vehicle, the relative position information of the vehicle under test and the test task information to determine whether the driving track of the automatic test vehicle is normal;

Combined with the motion state information of the test vehicle, the motion state information of the tested vehicle and the test task information, the task completion status of the test node is comprehensively judged.

Further, the specific implementation method that the remote control center performs targeted processing on different types of data is:

Set the operating state threshold of the automatic test vehicle, and compare the received operating state data of the automatic test vehicle with the set threshold to determine whether the automatic test vehicle is in a normal operating state;

Set the fault threshold of the automatic test vehicle, compare the received fault state data of the automatic test vehicle with the set fault threshold, and judge whether the test vehicle has a fault;

Determine the driving trajectory of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, and speed relative to the vehicle under test, determine whether the vehicle is driving normally according to the position relative to the road, and determine whether the vehicle is driving normally according to the position relative to the vehicle under test. and speed to determine whether to adjust the current speed and heading of the test vehicle, and whether the set action needs to be performed within the predetermined range;

Record the running status data of the vehicle under test, and simultaneously record the relative position and speed of the test vehicle at the test node.

One aspect of the present disclosure provides a technical solution for a remote control method for an autonomous driving test vehicle:

A remote control method for an automatic driving test vehicle, the method is realized based on the above-mentioned remote control system of the automatic driving test vehicle, and the method comprises the following steps:

The autonomous driving test vehicle collects its own running status data, road condition video data, surrounding environment information and location information, and transmits it to the remote control center;

The remote control center receives the automatic test vehicle running status data, road condition video data, surrounding environment information and location information, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running status data of the vehicle under test, and conducts various aspects of the received data. Integrate processing, classify and store the received data, and process different types of data in a targeted manner to monitor the normal running status of the test vehicle; at the same time, receive the status data of the user's manual operation of the driving simulator uploaded by the driving simulator Or receive the driving track data input by the user, analyze it, generate control commands, and send the control commands to the automatic test vehicle through the communication base station.

Further, it also includes:

The remote control center builds a simulated driving environment, and uses the received operating data of the automatic test vehicle and the running state data of the tested vehicle to update the simulated driving environment.

Further, the specific implementation method for performing multi-faceted fusion processing on the received data is:

Introduce a time synchronization mechanism to synchronously obtain the road condition video data, surrounding environment information, location information, and motion status information of the test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test;

Combine the position information of the test vehicle, the relative position information of the vehicle under test and the test task information to determine whether the driving track of the automatic test vehicle is normal;

Combined with the motion state information of the test vehicle, the motion state information of the tested vehicle and the test task information, the task completion status of the test node is comprehensively judged.

Further, the specific implementation method for targeted processing of different types of data is as follows:

Set the operating state threshold of the automatic test vehicle, and compare the received operating state data of the automatic test vehicle with the set threshold to determine whether the automatic test vehicle is in a normal operating state;

Set the fault threshold of the automatic test vehicle, compare the received fault state data of the automatic test vehicle with the set fault threshold, and judge whether the test vehicle has a fault;

Determine the driving trajectory of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, and speed relative to the vehicle under test, determine whether the vehicle is driving normally according to the position relative to the road, and determine whether the vehicle is driving normally according to the position relative to the vehicle under test. and speed to determine whether to adjust the current speed and heading of the test vehicle, and whether the set action needs to be performed within the predetermined range;

Record the running status data of the vehicle under test, and simultaneously record the relative position and speed of the test vehicle at the test node.

Through the above technical solutions, the beneficial effects of the present disclosure are:

(1) The present disclosure realizes the field test verification of the unmanned vehicle in the closed test field, improves the work efficiency, and enriches the test scene;

(2) The present disclosure helps to improve test security and scenario construction flexibility;

(3) The present disclosure adopts two ways to control the automatic test vehicle, one is remote control through a driving simulator, and the other is automatic control according to the input predetermined trajectory, which improves the work efficiency.

Description of drawings

The accompanying drawings, which constitute a part of the present disclosure, are used to provide further understanding of the present disclosure, and the exemplary embodiments of the present disclosure and their descriptions are used to explain the present application and do not constitute an improper limitation of the present disclosure.

Fig. 1 is the structure diagram of the automatic driving test vehicle of Embodiment 1;

2 is a structural block diagram of a vehicle-mounted environment perception device in Embodiment 1;

FIG. 3 is a structural block diagram of the remote control system of the automatic driving test vehicle in the second embodiment.

Detailed ways

The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless otherwise defined, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

Example 1

This embodiment provides an automatic driving test vehicle, please refer to FIG. 1 , the automatic driving test vehicle includes a casing, a power chassis and a vehicle-mounted environment sensing device, and the casing is connected to the chassis by a mechanical connector.

In this embodiment, the casing is integrally formed, the material of the casing is epoxy resin, and the style of the casing can be designed according to requirements, and the purpose of simulating different vehicle models can be achieved by replacing the casing.

The power chassis includes a chassis, wheels and a power system arranged on the chassis, and the casing and the chassis are fixed by screws.

In this embodiment, the power system adopts a direct drive powertrain, including a vehicle controller, a battery, a battery management system, a drive motor and a motor controller, and the vehicle controller is connected to the motor controller through an internal CAN bus And the battery management system, the vehicle controller issues commands to the motor controller and receives the status feedback from the motor controller and the battery management system; the battery provides power for the motor controller and the motor; the motor controller is connected to the motor to connect the DC power It is converted into AC power required by the motor, and the rotation of the motor is controlled by the speed or torque, so that the motor can execute according to the command requirements; the motor adopts a permanent magnet synchronous motor and is connected to the wheel drive shaft to provide power for the vehicle.

Please refer to FIG. 2, the vehicle environment perception equipment includes a positioning device, a video capture device, a communication device, an environment perception device, a bus controller and a vehicle-mounted processor; the vehicle-mounted processor is connected to the positioning device, the video capture device, and the communication device. , an environmental awareness device, and a bus controller, wherein:

The positioning device is used to collect the position information of the test vehicle, including latitude and longitude, speed and heading information, and transmit it to the on-board processor;

The video collection device is used to collect video information of road conditions ahead of the test vehicle and transmit it to the vehicle-mounted processor;

The environment perception device is used to collect surrounding environment data of the test vehicle, including static obstacle data, moving obstacle data, and image information of obstacles, and transmit the data to the vehicle-mounted processor.

The bus controller is used to collect vehicle running state data and fault state data, including brake pedal, accelerator pedal, steering range, battery power, battery abnormal state, etc., and transmit it to the on-board processor; receive control output from the on-board controller Signals to control the chassis to perform driving, braking and steering operations.

The vehicle-mounted processor is used to receive the position information of the test vehicle collected by the positioning device, the video information of the road conditions in front of the test vehicle collected by the video collection device, the surrounding environment data of the test vehicle collected by the environment perception device, and the running state data of the vehicle collected by the bus controller. and fault status data, and upload it to the remote control center through the communication device; receive the control command sent by the remote control center, parse the command, convert it into a control signal for the automatic test vehicle, and output it to the power system through the bus controller. The automatic test vehicle completes the corresponding actions.

In this embodiment, the positioning device includes a GPS receiver and an IMU inertial navigation device installed in the cavity formed between the casing and the chassis, and a GPS positioning antenna installed in the front and rear of the casing; the GPS receiver is used for Receive the position information of the test vehicle and the relative position information of the vehicle under test collected by the GPS positioning antenna; the IMU inertial navigation device is used to collect the attitude information of the test vehicle.

In this embodiment, the video collection device includes a camera installed at the windshield of the housing, and the camera is used to collect video information of road conditions ahead.

In this embodiment, the environment perception device includes a lidar mounted on the top of the casing, a camera, and a millimeter-wave radar mounted on the front of the test vehicle. The laser sensor is used to detect the distance between the test vehicle and stationary obstacles. distance; the millimeter-wave radar is used to detect the number, distance and speed of moving obstacles; the camera is used to collect image information of obstacles and provide it to the pattern recognition module for identifying different objects.

In this embodiment, a vehicle processor, a communication device and a bus controller are arranged in the cavity formed between the casing and the chassis.

Embodiment 2

This embodiment provides a remote control system for an automatic driving test vehicle, please refer to FIG. 3 , the system includes an automatic test vehicle, a communication base station, a remote control center and a driving simulator.

The automatic test vehicle is used to collect its operation data and execute the control instructions of the remote control center, and upload the collected operation data of the test vehicle to the remote control center, which is convenient for the remote control center to analyze and decide the next action. The data includes the location information of the test vehicle, the video information of the road conditions in front of the test vehicle, the surrounding environment data of the test vehicle, the vehicle running status data and the fault status data.

Wherein, for the specific structure of the automatic test vehicle of this embodiment, please refer to the relevant descriptions of the previous embodiments, which will not be repeated here.

The communication base station provides a wireless network for completing the data interaction between the automatic test vehicle and the remote control center. The communication base station in the test field receives the video data of the surrounding environment and its own operation data collected by the on-board environment perception equipment of the automatic test vehicle, and transmits it to the remote control center server through the Ethernet.

The remote control center is used to receive the road condition video data, surrounding environment information, location information and its own operation data collected by the vehicle-mounted environment perception device of the automatic test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, The running status data of the vehicle is collected, and the received automatic test vehicle running data is processed in various aspects, and the data is classified and stored, and different types of data are processed in a targeted manner. The road condition video data is transmitted to the display device for display, and the road condition video data, surrounding environment information, location information and its own operation data, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test Transmit to the driving simulator; build a simulated driving environment, and update the simulated driving environment with the received operating data of the automatic test vehicle and the running state data of the tested vehicle; at the same time, receive the user's manual operation of the driving simulator uploaded by the driving simulator state data or receive the driving track data input by the user, and analyze it to generate control commands, which are sent to the automatic test vehicle through the communication base station to complete the corresponding actions.

Specifically, the specific implementation process of the multi-faceted fusion processing of the received automatic test vehicle data by the remote control center is as follows:

(1) Time synchronization fusion, in order to achieve data synchronization between different sensor data, and between the test vehicle and the vehicle under test, a time synchronization mechanism needs to be introduced, so that the data message sent by the sensor node has a time stamp, and in a The fusion node compares the time recorded by the data packet with the local time, and if the two are within a given error range, it is regarded as a set of synchronization data.

(2) The data fusion of the driving trajectory, combined with the vehicle status information, the relative position information with the tested vehicle and the test task information, comprehensively judge whether the driving trajectory of the automatic test vehicle is normal. The information specifically includes positioning information, attitude information, speed information from the GPS receiver, distance and relative position from the target vehicle under test, and the type and number of test tasks.

In this embodiment, the comprehensive judgment method is to define the logical relationship between the normal driving and abnormal driving of the automatic test vehicle.

(3) Data fusion of test nodes, combined with test vehicle motion information, tested vehicle motion information and test tasks, comprehensively judge the task completion status of test nodes. The test vehicle motion information includes the automatic test vehicle trajectory, speed, and relative position information to the tested vehicle, and the tested vehicle motion information includes the tested vehicle trajectory, accelerator, brake, steering status, task action type and number of times, and the like.

Specifically, the specific implementation process of the remote control center for targeted processing of different types of data is as follows:

For the running status data of the automatic test vehicle, including the speed, position, brake pedal, accelerator pedal, and steering status data of the test vehicle, set the normal operating thresholds of the speed, position, brake pedal, accelerator pedal, and steering of the test vehicle, and the test vehicle will be The speed, position, brake pedal, accelerator pedal, and steering are compared with the corresponding thresholds to judge whether the running state of the automatic test vehicle is normal.

For automatic test vehicle fault status data, including battery remaining power, total battery voltage, battery undervoltage/overvoltage status, motor temperature, motor voltage status, etc., the fault status data sent by the automatic test vehicle is consistent with the set fault threshold. Compare and judge whether the test vehicle is faulty.

For the driving trajectory data of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, speed relative to the vehicle under test, etc., determine whether the vehicle is driving normally by the position relative to the road, and determine whether the vehicle is driving normally by the position relative to the vehicle under test. The position and speed of the device determine whether to adjust the current speed and heading, and whether to reach the predetermined range requires a predetermined action.

For the running state data of the tested vehicle, including speed, position, brake pedal, accelerator pedal, and steering state, record the state data of the tested vehicle during driving, and simultaneously record the relative position and speed of the test vehicle at the test node.

The driving simulator is used for acquiring the state data of the user's manual operation of the driving simulator and transmitting it to the remote control.

In this embodiment, the driving simulator includes a steering wheel, a brake pedal, an accelerator pedal, a clutch pedal, a gear lever, and a number of custom buttons; the driving simulator and the remote control center are connected through a communication line, when the user manually When operating the driving simulator, a set of status messages will be generated and sent to the remote control center; the remote control center will receive and parse the driving simulator data, obtain the status of the steering wheel, brake, accelerator pedal, gear position, etc., and generate control commands.

The remote control center also receives the driving track data input by the user, parses the driving track data, generates control commands, and transmits them to the automatic test vehicle through the communication base station.

There are two ways to control the automatic test vehicle in this embodiment, one is to directly manipulate the simulated driver, and the other is to input a set of trajectory data to the remote control center. The command is sent to the automatic test vehicle to make it complete the corresponding action.

The communication device of the automatic test vehicle receives the control command, converts it into a control signal of the vehicle through the on-board processor, and sends it to the vehicle execution mechanism by the bus controller to complete the corresponding action.

Compared with the existing methods that require on-site operation of dummies and vehicles, it is difficult to create random traffic scenes, it is difficult to reproduce the same scene, and the test scenes under different working conditions need to be repeatedly operated. The remote control system, through the driving simulator, will manually define the driving trajectory to generate control commands, issue control commands and receive status feedback through the remote control center, and create a real traffic environment through automatic test vehicles. Test scenarios and test plans help to simulate extreme situations that rarely occur in reality, and some scenarios that rarely occur in actual road conditions can be repeatedly constructed by using automatic test vehicles to help improve test safety and scene construction flexibility.

Embodiment 3

This embodiment provides a remote control method for an autonomous driving test vehicle, which is implemented based on the remote control system for the autonomous driving test vehicle described in Embodiment 2, and the method includes the following steps:

Step 1: The automatic test vehicle sends the vehicle running status data, road condition video data, surrounding environment information and location information to the remote control center.

In this embodiment, the vehicle running state data includes brake pedal, accelerator pedal, steering range, battery power, battery abnormal state, etc.; the location information includes latitude and longitude, speed and heading, and is transmitted to the on-board processor.

Step 2: The remote control center receives the road condition video data, surrounding environment information, location information and its own operation data collected by the vehicle-mounted environment perception device of the automatic test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the relative position information of the vehicle under test. Running status data, classify and store the data, carry out targeted processing of different types of data, analyze whether the running status of the vehicle is normal by monitoring the running data of the vehicle, transmit the road condition video data to the display device for display, and convert the road condition video data, The surrounding environment information, position information and its own operation data, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test are transmitted to the driving simulator.

Specifically, the specific implementation process for the targeted processing of different types of data is as follows:

For the running status data of the automatic test vehicle, including the speed, position, brake pedal, accelerator pedal, and steering status data of the test vehicle, set the normal operating thresholds of the speed, position, brake pedal, accelerator pedal, and steering of the test vehicle, and the test vehicle will be The speed, position, brake pedal, accelerator pedal, and steering are compared with the corresponding thresholds to judge whether the running state of the automatic test vehicle is normal.

For automatic test vehicle fault status data, including battery remaining power, total battery voltage, battery undervoltage/overvoltage status, motor temperature, motor voltage status, etc., the fault status data sent by the automatic test vehicle is consistent with the set fault threshold. Compare and judge whether the test vehicle is faulty.

For the driving trajectory data of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, speed relative to the vehicle under test, etc., determine whether the vehicle is driving normally by the position relative to the road, and determine whether the vehicle is driving normally by the position relative to the vehicle under test. The position and speed of the device determine whether to adjust the current speed and heading, and whether to reach the predetermined range requires a predetermined action.

For the running state data of the tested vehicle, including speed, position, brake pedal, accelerator pedal, and steering state, record the state data of the tested vehicle during driving, and simultaneously record the relative position and speed of the test vehicle at the test node.

Step 3: The driving simulator obtains the status data of the user manually operating the driving simulator and uploads it to the remote control center; or the remote control center receives the driving trajectory data input by the user; the remote control center obtains the status data of the user manually operating the driving simulator or The driving track data is analyzed to generate control commands. The control command signals are broadcasted by the communication base station and received by the data communication device in the automatic test vehicle, converted into control signals by the on-board processor, and sent by the bus controller to the vehicle actuator to complete the corresponding actions. , to realize the remote control of the automatic test vehicle.

When the automatic test vehicle receives the automatic mode switching command and the vehicle is in the standby state, the automatic test vehicle switches to the automatic control mode. When the automatic test vehicle receives the automatic mode switching instruction and the vehicle is in the remote control state, the automatic test vehicle remains remote. Control mode; when the automatic test vehicle receives a remote control command, no matter what state the vehicle is in, it immediately switches to the remote control mode.

It also includes that the remote control center builds a simulated driving environment, and the realization process of building the simulated driving environment is:

The remote control center uses simulation software to build a simulated driving environment, receives the running data of the automatic test vehicle and the running data of the tested vehicle, and updates the data of the automatic test vehicle in the simulated driving environment;

The remote control center builds a simulated driving environment, which can synchronously reflect the running state of the test vehicle; after receiving the control signal of the simulated driver, the remote control center packages it and sends it to the communication base station of the test site, and then the communication of the test vehicle is automatically tested. The terminal receives the message, and the on-board processor unpacks the message, and controls the vehicle to perform corresponding actions according to the control command; the running status of the automatic test vehicle and the target vehicle under test is transmitted to the remote control center in real time, and displayed synchronously in the simulated driving environment.

In this embodiment, the realization process of generating the control instruction is:

When the user manually operates the driving simulator, the driving simulator will generate a set of status messages and send them to the remote control center; the remote control center will receive and parse the driving simulator data to obtain the status of the steering wheel, brake, accelerator pedal, gear, etc. Generate control commands and transmit them to the automatic test vehicle through the communication base station.

Or, the remote control center receives the driving track data input by the user, and uploads it to the remote control center, and the remote control center parses the driving track data, generates control commands, and transmits it to the automatic test vehicle through the communication base station.

There are two ways to control the automatic test vehicle in this embodiment, one is remote control through a driving simulator, and the other is automatic control according to the input predetermined trajectory. For the first method, the control command comes from the manual operation of the driving simulator, and the control command is remotely sent to the automatic test vehicle through the remote control center host, and the on-board processor translates it into the vehicle's control signal to realize the control of the vehicle. control. For the second method, the staff input the predetermined trajectory to the remote control center host, and remotely transmit the trajectory data to the automatic test vehicle. The on-board processor inputs the predetermined trajectory and the current position into the trajectory tracking algorithm to obtain the next steering angle. , and then translate the steering angle into a control signal for the vehicle to control the vehicle.

Although the specific embodiments of the present disclosure have been described above in conjunction with the accompanying drawings, they do not limit the protection scope of the present disclosure. Those skilled in the art should understand that on the basis of the technical solutions of the present disclosure, those skilled in the art do not need to pay creative efforts. Various modifications or variations that can be made are still within the protection scope of the present disclosure.

Claims (10)

1. A self-driving test vehicle, characterized in that it comprises a casing, a power chassis connected at the bottom of the casing and a vehicle-mounted environment perception device; The in-vehicle environment perception equipment includes: The positioning device is used to collect the position information of the test vehicle, including latitude and longitude, speed and heading information, and transmit it to the on-board processor; Video acquisition device, used to collect video information of road conditions ahead of the test vehicle and transmit it to the on-board processor; The environmental perception device is used to collect environmental data around the test vehicle, including static obstacle data, moving obstacle data and obstacle image information, and transmit it to the on-board processor; The bus controller is used to collect the running status data and fault status data of the test vehicle, and transmit them to the vehicle-mounted processor; receive the control signal output by the vehicle-mounted controller, and control the test vehicle to perform corresponding actions; The on-board processor is used to receive the position information of the test vehicle, the video information of the road conditions ahead, the surrounding environment data, the running status data and the fault status data, and upload it to the remote control center through the communication device; The control instructions are parsed, converted into control signals for the test vehicle, and output to the power chassis through the bus controller to control the automatic test vehicle to complete corresponding actions. 2. The self-driving test vehicle according to claim 1, wherein the positioning device comprises a GPS receiver and an IMU inertial navigation device installed in the cavity formed between the casing and the power chassis, and an inertial navigation device installed in the front and rear of the casing. The GPS positioning antenna; the GPS receiver is used to receive the position information of the test vehicle and the relative position information with the tested vehicle collected by the GPS positioning antenna; the IMU inertial navigation device is used to collect the attitude information of the test vehicle. 3. The self-driving test vehicle according to claim 1, wherein the environment perception device comprises a lidar mounted on the top of the casing, a camera, and a millimeter-wave radar mounted on the front of the test vehicle, and the laser sensor, It is used to detect the distance between the test vehicle and stationary obstacles; the millimeter wave radar is used to detect the number, distance and speed of moving obstacles; the camera is used to collect image information of obstacles. 4. The remote control system of a self-driving test vehicle, comprising the self-driving test vehicle described in any one of claims 1 to 3, a communication base station, a remote control center and a driving simulator; The automatic test vehicle is used to collect the location information of the test vehicle, the video information of the road conditions ahead, the surrounding environment data, the running status data and the fault status data, and upload them to the remote control center; receive and execute the control instructions sent by the remote control center; The communication base station is used to complete the data interaction between the automatic test vehicle and the remote control center; The remote control center is used to receive location information of the test vehicle, video information of road conditions ahead, surrounding environment data, operating status data, and fault status data, as well as relative position information between the test vehicle and the vehicle under test and the running status data of the vehicle under test. , perform multi-faceted fusion processing on the received data, classify and store the received data, and carry out targeted processing of different types of data to monitor the normal operation status of the test vehicle; build a simulated driving environment, and use the The received running status data of the test vehicle and the running status data of the tested vehicle are updated in real time to simulate the simulated driving environment; at the same time, the status data of the user's manual operation of the driving simulator uploaded by the driving simulator or the driving trajectory data input by the user are received, and the It parses, generates control commands, and sends the control commands to the automatic test vehicle via the communication base station. 5. The remote control system of automatic driving test vehicle according to claim 4, is characterized in that, the concrete realization method that described remote control center carries out multifaceted fusion processing to the data received is: Introduce a time synchronization mechanism to synchronously obtain the road condition video data, surrounding environment information, location information, and motion status information of the test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test; Combine the position information of the test vehicle, the relative position information of the vehicle under test and the test task information to determine whether the driving track of the automatic test vehicle is normal; Combined with the motion state information of the test vehicle, the motion state information of the tested vehicle and the test task information, the task completion status of the test node is comprehensively judged. 6. The remote control system of automatic driving test vehicle according to claim 4, is characterized in that, the concrete realization method that described remote control center carries out targeted processing to the data of different categories is: Set the operating state threshold of the automatic test vehicle, and compare the received operating state data of the automatic test vehicle with the set threshold to determine whether the automatic test vehicle is in a normal operating state; Set the fault threshold of the automatic test vehicle, compare the received fault state data of the automatic test vehicle with the set fault threshold, and judge whether the test vehicle has a fault; Determine the driving trajectory of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, and speed relative to the vehicle under test, determine whether the vehicle is driving normally according to the position relative to the road, and determine whether the vehicle is driving normally according to the position relative to the vehicle under test. and speed to determine whether to adjust the current speed and heading of the test vehicle, and whether the set action needs to be performed within the predetermined range; Record the running status data of the vehicle under test, and simultaneously record the relative position and speed of the test vehicle at the test node. 7. A remote control method of an automatic driving test vehicle, the method is realized based on the remote control system of the automatic driving test vehicle described in any one of claims 4 to 6, and is characterized in that, comprises the following steps: The autonomous driving test vehicle collects its own running status data, road condition video data, surrounding environment information and location information, and transmits it to the remote control center; The remote control center receives the automatic test vehicle running status data, road condition video data, surrounding environment information and location information, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running status data of the vehicle under test, and conducts various aspects of the received data. Integrate processing, classify and store the received data, and process different types of data in a targeted manner to monitor the normal running status of the test vehicle; at the same time, receive the status data of the user's manual operation of the driving simulator uploaded by the driving simulator Or receive the driving trajectory data input by the user, analyze it, generate control commands, and send the control commands to the automatic test vehicle through the communication base station. 8. The remote control method of automatic driving test vehicle according to claim 7, is characterized in that, also comprises: The remote control center builds a simulated driving environment, and uses the received operating data of the automatic test vehicle and the running state data of the tested vehicle to update the simulated driving environment. 9. The remote control method of the self-driving test vehicle according to claim 7, wherein the specific implementation method of performing multi-faceted fusion processing on the received data is: Introduce a time synchronization mechanism to synchronously obtain the road condition video data, surrounding environment information, location information, and motion status information of the test vehicle, as well as the relative position information of the automatic test vehicle and the vehicle under test, and the running state data of the vehicle under test; Combine the position information of the test vehicle, the relative position information of the vehicle under test and the test task information to determine whether the driving track of the automatic test vehicle is normal; Combined with the motion state information of the test vehicle, the motion state information of the tested vehicle and the test task information, the task completion status of the test node is comprehensively judged. 10. The remote control method of the self-driving test vehicle according to claim 7, wherein the specific implementation method of carrying out targeted processing to the data of different categories is: Set the operating state threshold of the automatic test vehicle, and compare the received operating state data of the automatic test vehicle with the set threshold to determine whether the automatic test vehicle is in a normal operating state; Set the fault threshold of the automatic test vehicle, compare the received fault state data of the automatic test vehicle with the set fault threshold, and judge whether the test vehicle has a fault; Determine the driving trajectory of the automatic test vehicle, including speed, position, position relative to the road, position relative to the vehicle under test, and speed relative to the vehicle under test, determine whether the vehicle is driving normally according to the position relative to the road, and determine whether the vehicle is driving normally according to the position relative to the vehicle under test. and speed to determine whether to adjust the current speed and heading of the test vehicle, and whether the set action needs to be performed within the predetermined range; Record the running status data of the vehicle under test, and simultaneously record the relative position and speed of the test vehicle at the test node.

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