Safety planning system for autonomous vehicle and safety planning method thereof

Abstract

The application provides a safety planning system for an automatic driving vehicle and a safety planning method thereof, wherein the method comprises: calculating vehicle related information based on a plurality of sensor signals to obtain a dynamic safety boundary signal; generating a trajectory signal and a wheel speed signal according to the dynamic safety boundary signal and a planning decision signal obtained based on the dynamic safety boundary signal; solving a plurality of sensor signals and a whole vehicle dynamics control signal to obtain a vehicle estimation and prediction signal; performing cooperative control based on the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signal to generate a motion control signal; and performing distribution calculation on the vehicle estimation and prediction signal and the motion control signal to obtain a control signal corresponding to a vehicle related system. The application fully utilizes the partial perception and decision capability of automatic driving to improve the safety performance of an automatic driving domain controller.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobiles, in particular to a safety planning system for an autonomous vehicle and a safety planning method thereof. BACKGROUND

[0002] The development of intelligent and electric autonomous vehicles requires higher control priority for the chassis to fully utilize the advantages of vehicle domain control and autonomous driving intelligent decision-making, thereby improving the safety of autonomous vehicles.

[0003] Currently, when an autonomous vehicle enters extreme dynamic conditions such as low adhesion road surfaces and high-speed side slipping, the vehicle is completely taken over by ABS, ESC, TCS controllers and other extreme dynamic controllers, and the autonomous driving controller loses its control ability over the vehicle until the active safety controller exits. This sudden intervention of the active safety controller mode causes the autonomous driving domain controller to temporarily lose complete control over the vehicle dynamics, which easily leads to unexpected safety accidents. At the same time, the active safety control also fails to fully utilize the more perception information and high computing power of autonomous driving to enhance its potential. SUMMARY

[0004] The present application aims to at least partially solve one of the technical problems in the related art.

[0005] To this end, the first object of the present application is to propose a safety planning system for an autonomous vehicle, which integrates active safety control functions into vehicle path planning control, calculates the dynamics boundary of the vehicle according to the fusion perception information during path planning, and limits the path for safety, and generates wheel speed control commands along with the path, ensuring that the generated trajectory does not trigger ABS and other safety functions during chassis path tracking control and dynamics control, and fully utilizes the perception and decision-making capabilities of the autonomous driving part to improve the safety performance of the autonomous driving domain controller.

[0006] To achieve the above-mentioned object, an embodiment of the present application proposes a safety planning system for an autonomous vehicle, comprising a plurality of sensors, an autonomous driving domain controller and a chassis domain controller; wherein,

[0007] The plurality of sensors are used to collect a plurality of sensor signals of the autonomous vehicle.

[0008] The automatic driving domain controller comprises a fusion perception module, a safety boundary analysis module, a planning decision module and a safety planning module; wherein the fusion perception module fuses a plurality of sensor signal outputs to calculate vehicle related information, the safety boundary analysis module calculates the vehicle related information to output a dynamic safety boundary signal, the planning decision module outputs a planning decision signal based on the dynamic safety boundary signal, and the safety planning module generates and outputs a trajectory signal and a wheel speed signal based on the planning decision signal and the dynamic safety boundary signal;

[0009] The chassis domain controller comprises a state estimation and prediction module, a trajectory / wheel speed tracking controller and a chassis dynamics controller; wherein the state estimation and prediction module calculates a plurality of sensor signals and whole vehicle dynamics control signals to output vehicle estimation and prediction signals; the trajectory / wheel speed tracking controller cooperatively controls based on the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signals to generate a motion control signal; and the chassis dynamics controller distributes and calculates the vehicle estimation and prediction signals and the motion control signal to generate a first control signal of a vehicle related system and sends it to a corresponding actuator.

[0010] The safety planning system for the automatic driving vehicle according to the embodiment of the application fully utilizes more perception information and high computing power of the automatic driving to improve its safety potential, reduces triggering of ABS / ESC / TCS safety functions, and improves the safety performance of the vehicle.

[0011] In addition, the safety planning system for the automatic driving vehicle according to the above embodiment of the application can also have the following additional technical features:

[0012] Further, in an embodiment of the application, the chassis domain controller further comprises a safety state recognition module and an ABS / ESC / TCS function module; wherein,

[0013] The safety state recognition module is configured to check the vehicle related physical quantity according to the dynamic safety boundary signal, to check whether the vehicle related physical quantity meets the dynamic safety boundary constraint condition, and if not, to activate the ABS / ESC / TCS function module and send a check failure signal to the automatic driving domain controller;

[0014] The ABS / ESC / TCS function module is configured to perform whole vehicle dynamics control after being activated, and generate a second control signal of a vehicle related system and send it to a corresponding actuator.

[0015] Further, in an embodiment of the present application, the safety boundary analysis module is further configured to calculate the vehicle-related information using a vehicle dynamics model and a tire model to obtain a dynamics safety boundary signal, and send the dynamics safety boundary signal to a safety planning module and a safety state recognition module.

[0016] Further, in an embodiment of the present application, the safety planning module is further configured to calculate the planning decision signal and the dynamics safety boundary signal to obtain a trajectory signal and a wheel speed signal when a current vehicle dynamics state satisfies a dynamics safety boundary constraint condition.

[0017] Further, in an embodiment of the present application, the safety state recognition module is further configured to recognize the vehicle estimation and prediction signal to estimate the current vehicle dynamics state, and judge whether the current vehicle dynamics state satisfies the dynamics safety boundary constraint condition based on the received dynamics safety boundary signal of the safety boundary analysis module.

[0018] Further, in an embodiment of the present application, the vehicle-related system includes a vehicle driving system, a braking system, a steering system, and a suspension system; the planning decision signal includes a lane changing, straight driving, and obstacle avoidance decision signal; the dynamics safety boundary signal includes a yaw rate limit value and a slip rate limit value; the trajectory signal satisfies a road boundary limit, a yaw rate limit, an acceleration limit, and a lateral acceleration limit; the wheel speed signal satisfies a slip rate limit; and the vehicle dynamics control signal includes a feedback signal of the driving system, the braking system, the steering system, and the suspension system.

[0019] Further, in an embodiment of the present application, the vehicle-related information includes multiple types of obstacle information, road information, attitude signals, vehicle position and speed signals; and the multiple sensor signals include multiple types of laser radar signals, camera signals, combined inertial navigation signals, and wheel speed signals of the autonomous vehicle.

[0020] A second object of the present application is to provide a safety planning method of a safety planning system for an autonomous vehicle.

[0021] To achieve the above object, in one aspect, an embodiment of the present application provides a safety planning method of a safety planning system for an autonomous vehicle, comprising:

[0022] calculating vehicle-related information obtained based on multiple sensor signals to obtain a dynamics safety boundary signal;

[0023] generating a trajectory signal and a wheel speed signal according to the dynamics safety boundary signal and a planning decision signal obtained based on the dynamics safety boundary signal;

[0024] solving the plurality of sensor signals and the whole vehicle dynamics control signals to obtain vehicle estimation and prediction signals;

[0025] cooperatively controlling based on the trajectory signals and the wheel speed signals and the vehicle estimation and prediction signals to generate motion control signals, and distributing and calculating the vehicle estimation and prediction signals and the motion control signals to obtain control signals corresponding to vehicle related systems.

[0026] The safety planning method of the safety planning system for the autonomous vehicle in the embodiment of the application fully utilizes more perception information and high computing power of the autonomous vehicle to improve the safety potential, reduce the triggering of safety functions such as ABS / ESC / TCS, and improve the safety performance of the vehicle.

[0027] A third object of the application is to propose a computer device comprising a processor and a memory;

[0028] The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, to implement the safety planning method of the safety planning system for the autonomous vehicle.

[0029] A fourth object of the application is to propose a non-transitory computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the safety planning method of the safety planning system for the autonomous vehicle.

[0030] Additional aspects and advantages of the application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above and / or additional aspects and advantages of the application will become apparent and be readily appreciated from the following description, including the appended drawings.

[0032] Figure 1 Structure diagram of a safety planning system for an autonomous vehicle according to an embodiment of the application;

[0033] Figure 2 Flow chart of a safety planning method of a safety planning system for an autonomous vehicle according to an embodiment of the application;

[0034] Figure 3 Flow chart of another safety planning method of a safety planning system for an autonomous vehicle according to an embodiment of the application;

[0035] Figure 4 Computer device according to an embodiment of the application. DETAILED DESCRIPTION

[0036] Embodiments of the present application are described below in detail with reference to the accompanying drawings, wherein the same or similar components or components having the same or similar functions are denoted by the same or similar reference numerals throughout. The embodiments described below by reference to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application.

[0037] A safety planning system, method, device and storage medium for an autonomous vehicle according to an embodiment of the present application are described below with reference to the accompanying drawings.

[0038] Figure 1 is a structural schematic diagram of a safety planning system for an autonomous vehicle according to an embodiment of the present application.

[0039] As shown in Figure 1 , the system comprises a plurality of sensors 10, an autonomous driving domain controller 20 and a chassis domain controller 30; wherein,

[0040] The plurality of sensors 10 (a sensor combination supporting high-level autonomous driving) are used to collect a plurality of sensor signals of the autonomous vehicle;

[0041] The autonomous driving domain controller 20 comprises a fusion perception module, a safety boundary analysis module, a planning decision module and a safety planning module; wherein the fusion perception module fuses a plurality of sensor signals to output vehicle-related information, the safety boundary analysis module calculates the vehicle-related information to output a dynamic safety boundary signal, the planning decision module outputs a planning decision signal based on the dynamic safety boundary signal, and the safety planning module generates and outputs a trajectory signal and a wheel speed signal based on the planning decision signal and the dynamic safety boundary signal;

[0042] The chassis domain controller 30 comprises a state estimation and prediction module, a trajectory / wheel speed tracking controller and a chassis dynamics controller; wherein the state estimation and prediction module calculates a plurality of sensor signals and whole vehicle dynamics control signals to output vehicle estimation and prediction signals; the trajectory / wheel speed tracking controller cooperatively controls based on the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signals to generate a motion control signal; and the chassis dynamics controller distributes and calculates the vehicle estimation and prediction signals and the motion control signal to generate a first control signal of a vehicle-related system and sends it to the corresponding actuator.

[0043] It can be understood that the plurality of sensors 10 (a sensor combination supporting high-level autonomous driving) comprise a laser radar, a camera, a combined inertial navigation system and a wheel speed sensor of the chassis domain of the autonomous driving sensor.

[0044] In one embodiment of the present invention, the autonomous driving domain controller 20 includes a fusion perception module 21, a safety boundary analysis module 22, a planning and decision module 23, and a safety planning module 24.

[0045] The fusion perception module 21 receives multiple sensor signals of the autonomous driving vehicle, and obtains obstacle information, road information, vehicle position, and speed signals through fusion calculation. At the same time, it sends the road safety boundary signal, including obstacle information and road information, to the safety boundary analysis module 22 and the planning and decision module 23. The multiple types of sensor signals include lidar signals, camera signals, combined inertial navigation signals, and wheel speed signals in the chassis domain for autonomous driving sensing.

[0046] The safety boundary analysis module 23 combines the road adhesion signal, posture signal, and speed signal calculated by the fusion perception module 21 with the vehicle dynamics model and tire model to calculate a dynamic safety boundary signal, where the dynamic safety boundary signal includes the yaw angular velocity limit and slip rate limit in this state, and sends the safety boundary signal to the safety planning module 24 and the safety state identification module 34 of the chassis domain controller 30.

[0047] The planning and decision module 23 makes intelligent decisions for autonomous driving based on the received safety boundary information, including decisions on lane changing, straight driving, and obstacle avoidance, and sends decision signals to the safety planning module 24.

[0048] The safety planning module 24 calculates an optimized trajectory signal constrained by the dynamic safety boundary based on the received planning decision signal and dynamic safety boundary information when the vehicle dynamic state does not exceed the dynamic safety boundary limit, and generates a wheel speed command along with the path to ensure that the generated trajectory is within the vehicle safety dynamic boundary during execution. At the same time, the trajectory signal and wheel speed signal are sent to the chassis domain controller 30, where the commands of the trajectory signal and wheel speed signal can adopt an optimization method, such as model predictive control, or an intelligent learning method, such as reinforcement learning. The generated trajectory signal must ensure that the road boundary limit, yaw angular velocity limit, acceleration limit, and lateral acceleration limit are met, and the generated wheel speed signal must meet the slip rate limit to ensure that the planned path and wheel speed of the vehicle meet the dynamic safety requirements.

[0049] In one embodiment of the present invention, the chassis domain controller 30 includes a state estimation and prediction module 31 , a trajectory / wheel speed tracking controller 32 , a chassis dynamics controller 33 , a safety state identification module 34 and an ABS / ESC / TCS functional module 35 .

[0050] The state estimation and prediction module 31 mainly calculates the current vehicle body dynamics state, and calculates a plurality of automatic driving sensor signals and vehicle dynamics control signals based on a vehicle dynamics model to obtain vehicle position, speed, attitude, and tire force signals, which are sent to the safety state recognition module 34, the chassis dynamics control module 33, and the trajectory / wheel speed tracking control module 32. The sensor signals include combined inertial navigation signals and wheel speed signals, and the vehicle dynamics control signals include feedback signals of the driving system, the braking system, the steering system, and the suspension system.

[0051] The trajectory / wheel speed tracking controller 32 receives the trajectory signal of the safety planning module 24, the wheel speed signal, and the estimated and predicted signal of the state estimation and prediction module 31, performs longitudinal-lateral-vertical collaborative control on the chassis dynamics motion state, generates longitudinal-lateral motion control commands for tracking the trajectory and the wheel speed, including lateral force, longitudinal force, and yaw moment commands, and sends them to the chassis dynamics controller 33.

[0052] The chassis dynamics controller 33 receives the motion control commands generated by the trajectory / wheel speed tracking controller 32 and the estimated and predicted signals of the state estimation and prediction module 31, performs execution distribution of the drive-by-wire actuators according to the vehicle dynamics control algorithm, generates control signals of the vehicle driving system 41, the braking system 42, the steering system 43, and the suspension system 44, and sends them to the corresponding actuators.

[0053] The safety state recognition module 34 receives the dynamic safety boundary signal calculated by the safety boundary analysis module 22 and the current vehicle body dynamics state estimated and predicted by the state estimation and prediction module 31, and checks selected physical quantities related to vehicle body stability such as wheel speed, yaw rate, and lateral acceleration. When the related physical quantities are within the dynamic safety boundary threshold, the safety planning and dynamics control are continued according to the safety planning method of the automatic driving domain control; when the related physical quantities exceed the dynamic safety boundary threshold, it means that the vehicle motion state is in a critical state and the current planned path and wheel speed cannot guarantee safety, and the ABS / ESC / TCS function module 35 is activated, and a check failure signal is sent to the automatic driving domain controller 20, which temporarily gives up vehicle body control and restores the vehicle body state to within the safety boundary.

[0054] The ABS / ESC / TCS function module 35 is activated when the vehicle dynamics state exceeds the dynamic safety boundary limit, temporarily takes over the vehicle dynamics control, generates control signals of the vehicle driving system 41, the braking system 42, the steering system 43, and the suspension system 44, and sends them to the corresponding actuators, and exits after controlling the vehicle state to within the safety boundary.

[0055] The safety planning system for the autonomous vehicle according to the embodiment of the present application integrates the active safety control function into the vehicle path planning control, calculates the dynamics boundary of the vehicle according to the fused perception information in the path planning process, limits the path, generates the wheel speed control command along with the path, and ensures that the generated trajectory is in the process of chassis path tracking control and dynamics control, so that the vehicle does not trigger the ABS safety function, fully utilizes the perception and decision-making ability of the autonomous driving part, and improves the safety performance of the autonomous driving domain controller.

[0056] Secondly, the safety planning method of the safety planning system for the autonomous vehicle according to the embodiment of the present application is described with reference to the accompanying drawings.

[0057] Figure 2 The flowchart of the safety planning method of the safety planning system for the autonomous vehicle according to the embodiment of the present application is shown in FIG. 1.

[0058] As shown in FIG. 1, the method comprises the following steps: Figure 2

[0059] S1, calculating the dynamics safety boundary signal from the vehicle related information obtained based on the plurality of sensor signals;

[0060] S2, generating the trajectory signal and the wheel speed signal according to the dynamics safety boundary signal and the planning decision signal obtained based on the dynamics safety boundary signal;

[0061] S3, calculating the vehicle estimation and prediction signal from the plurality of sensor signals and the whole vehicle dynamics control signal;

[0062] S4, performing the cooperative control based on the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signal to generate the motion control signal, and performing the distribution calculation on the vehicle estimation and prediction signal and the motion control signal to obtain the control signal corresponding to the vehicle related system.

[0063] It can be understood that the current safety control scheme of the autonomous vehicle is mainly that the chassis dynamics controller tracks the path calculated by the autonomous driving controller, and the ABS / ESC / TCS safety function is directly triggered in the case of low adhesion and emergency braking. However, this scheme causes the emergency condition to be more likely to trigger, the autonomous driving domain controller cannot completely control the whole vehicle dynamics temporarily, and unexpected safety accidents are prone to occur. In view of this, the present application fully utilizes more perception information and high computing power of the autonomous driving to improve the safety potential, reduces the triggering of the ABS / ESC / TCS safety function, and improves the safety performance of the vehicle.

[0064] In one embodiment of the present application, Figure 3 The logic diagram of the safety planning method of the safety planning system for the autonomous vehicle according to the embodiment of the present application is shown in FIG. 2.​Figure 3 as shown:

[0065] Fusion perception S10 is used to accept automatic driving multiple sensor signals, fusion calculation obtains obstacle information, road adhesion information, vehicle position, attitude, speed signal;

[0066] Safety boundary analysis S20 is used to combine the road adhesion signal, attitude signal and speed signal calculated by the fusion perception calculation, the vehicle dynamics model and the tire model to calculate the dynamics safety boundary signal, including the yaw rate limit value and the slip rate limit value in this state;

[0067] Safety state recognition S30 recognizes the estimated vehicle state estimation and prediction signal and receives the safety boundary information of the safety boundary analysis module, and judges whether the vehicle dynamics state is within the safety boundary state limit.

[0068] When the vehicle dynamics state does not exceed the dynamics safety boundary limit, safety planning S41 is performed, based on the received planning decision signal and the dynamics safety boundary information, the optimization trajectory signal constrained by the dynamics safety boundary is calculated, and the path generation wheel speed command is accompanied to ensure that the generated trajectory is within the vehicle safety dynamics boundary when executed, and the chassis dynamics fusion control S42 is performed to calculate and distribute the control command of the drive-by-wire actuator, and finally step S50 is performed. The chassis drive-by-wire actuator executes the related control command, including wheel drive braking force command, steering system steering angle command, active suspension active force command, etc.

[0069] When the vehicle dynamics state exceeds the dynamics safety boundary limit, ABS / ESC / TCS function is directly triggered S43, which temporarily takes over the vehicle dynamics control, and the traditional ABS / ESC / TCS safety algorithm quickly restores the vehicle stability and improves the vehicle adhesion utilization, and finally step S50 is performed. The chassis drive-by-wire actuator executes the related control command, including wheel drive braking force command, steering system steering angle command, active suspension active force command, etc.

[0070] In summary, with the rise of automobile intelligence, intelligent vehicles gradually improve the computing power and perception ability, increase the safety demand, and deepen the collaborative interaction between the chassis domain and the automatic driving domain. The present application utilizes the automatic driving perception information and planning ability under the premise of ensuring safety, reduces the risk scene trigger, improves the safety of the automatic driving vehicle, and has a wide application prospect.

[0071] According to the safety planning method of the safety planning system for the autonomous vehicle provided by the embodiment of the present application, the chassis domain controller of the safety planning system for the autonomous vehicle can make full use of the perception ability and the computing ability of the autonomous vehicle, reduce the triggering of ABS / TCS / ESC and other functions that are not expected, improve the body stability of the autonomous vehicle during driving, and retain the active safety ability in the emergency working condition.

[0072] In order to realize the method of the above-mentioned embodiment, the present application further provides a computer device, as shown in the accompanying drawings, which comprises a memory 601 and a processor 602; wherein the processor 602 runs a program corresponding to an executable program code stored in the memory 601 by reading the executable program code, so as to realize each step of the safety planning method of the safety planning system for the autonomous vehicle. Figure 4

[0073] In order to realize the above-mentioned embodiment, the present application further provides a non-temporary computer readable storage medium, which stores a computer program, and the program is executed by a processor to realize the safety planning method of the safety planning system for the autonomous vehicle as described in the above-mentioned embodiment.

[0074] In addition, the terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first", "second" can be explicitly or implicitly included at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise specifically limited.

[0075] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, the skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples without contradiction.

[0076] Although the embodiments of the present application have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.​

Claims

1. A safety planning system for autonomous vehicles, the system comprising: The application relates to an automatic driving system. The automatic driving system comprises a plurality of sensors, an automatic driving domain controller and a chassis domain controller. The plurality of sensors are used for collecting a plurality of sensor signals of an automatic driving vehicle. The automatic driving domain controller comprises a fusion perception module, a safety boundary analysis module, a planning decision module and a safety planning module. The fusion perception module fuses the plurality of sensor signals to output vehicle-related information. The safety boundary analysis module calculates the vehicle-related information to output a dynamic safety boundary signal. The planning decision module outputs a planning decision signal based on the dynamic safety boundary signal. The safety planning module generates and outputs a trajectory signal and a wheel speed signal based on the planning decision signal and the dynamic safety boundary signal. The chassis domain controller comprises a state estimation and prediction module, a trajectory / wheel speed tracking controller and a chassis dynamics controller. The state estimation and prediction module calculates the plurality of sensor signals and the whole-vehicle dynamics control signal to output vehicle estimation and prediction signals. The trajectory / wheel speed tracking controller cooperatively controls the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signals to generate a motion control signal. The chassis dynamics controller distributes and calculates the vehicle estimation and prediction signals and the motion control signal to generate a first control signal of a vehicle-related system and sends the first control signal to a corresponding execution mechanism. The chassis domain controller further comprises a safety state identification module and an ABS / ESC / TCS function module. The safety state identification module checks vehicle-related physical quantities according to the dynamic safety boundary signal to check whether the vehicle-related physical quantities meet dynamic safety boundary constraint conditions. If not, the ABS / ESC / TCS function module is activated, and a check failure signal is sent to the automatic driving domain controller. The ABS / ESC / TCS function module controls the whole-vehicle dynamics and generates a second control signal of a vehicle-related system and sends the second control signal to a corresponding execution mechanism. The safety boundary analysis module calculates the vehicle-related information by using a whole-vehicle dynamics model and a tire model to obtain a dynamic safety boundary signal and sends the dynamic safety boundary signal to the safety planning module and the safety state identification module. The safety planning module calculates the planning decision signal and the dynamic safety boundary signal to obtain the trajectory signal and the wheel speed signal when the current whole-vehicle dynamics state meets the dynamic safety boundary constraint conditions. The safety state identification module identifies the vehicle estimation and prediction signals to estimate the current whole-vehicle dynamics state and judges whether the current whole-vehicle dynamics state meets the dynamic safety boundary constraint conditions based on the received dynamic safety boundary signal of the safety boundary analysis module.

2. The safety planning system for autonomous vehicles of claim 1, wherein, The vehicle-related system includes a vehicle driving system, a braking system, a steering system, and a suspension system; the planning decision signal includes a lane-changing, straight-ahead, and obstacle-avoiding decision signal; the dynamics safety boundary signal includes a yaw rate limit and a slip ratio limit; the trajectory signal satisfies a road boundary limit, a yaw rate limit, an acceleration limit, and a lateral acceleration limit; the wheel speed signal satisfies a slip ratio limit; and the vehicle dynamics control signal includes feedback signals of the driving system, the braking system, the steering system, and the suspension system.

3. The safety planning system for autonomous vehicles of claim 1, wherein, The vehicle-related information includes multiple types of obstacle information, road information, attitude signals, vehicle position, and speed signals; and the multiple sensor signals include multiple types of laser radar signals, camera signals, combined inertial navigation signals, and wheel speed signals of the autonomous vehicle.

4. A safety planning method applied to the safety planning system for autonomous vehicles according to any one of claims 1 to 3, characterized in that, The method comprises the following steps: calculating vehicle-related information based on multiple sensor signals to obtain a dynamics safety boundary signal; generating a trajectory signal and a wheel speed signal according to the dynamics safety boundary signal and a planning decision signal obtained based on the dynamics safety boundary signal; solving the multiple sensor signals and a vehicle dynamics control signal to obtain vehicle estimation and prediction signals; performing collaborative control based on the trajectory signal and the wheel speed signal and the vehicle estimation and prediction signals to generate a motion control signal, and performing distribution calculation on the vehicle estimation and prediction signals and the motion control signal to obtain control signals corresponding to vehicle-related systems.

5. A computer device, comprising: The method comprises a processor and a memory; The processor runs a program corresponding to executable program code stored in the memory by reading the executable program code, to implement the safety planning method of claim 4.

6. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the safety planning method of claim 4.

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