Vehicle-side safety protection systems and methods for autonomous vehicles

Abstract

This invention relates to the field of autonomous driving technology, and particularly to a vehicle-side safety protection system and method for autonomous vehicles. Connected to the original vehicle system, the vehicle-side safety protection system includes: a risk identification module, a safety and defect analysis module, and an emergency response module. The risk identification module obtains vehicle safety information from the original vehicle system to identify anticipated functional safety risks and functional safety risks. The safety and defect analysis module performs fault analysis and source tracing based on the real-time identification results from the risk identification module, and calculates and classifies comprehensive risk values ​​to determine whether emergency response is required based on the classification results. If so, an emergency response strategy is formulated based on the vehicle safety information and classification results. The emergency response module generates emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and sends it to the vehicle's execution system for emergency control of the autonomous vehicle.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, and in particular to a vehicle-side safety protection system and method for autonomous vehicles. Background Technology

[0002] The widespread application of artificial intelligence (AI) technology has led to the rapid development of vehicle intelligence, particularly in autonomous driving. Autonomous vehicles consist of various sensors, computing units, actuators, and other types of devices. These devices communicate with each other and their functions are interdependent, forming a vast and complex system. Currently, autonomous driving systems are still in the development stage, and ensuring vehicle safety is a pressing issue. Besides functional safety issues caused by system malfunctions, the extensive application of AI technology in the perception systems of autonomous vehicles increases the unpredictability of system output, making the anticipated functional safety of autonomous vehicles also crucial. Anticipated functional safety issues refer to the hazards and risks arising from deficiencies in the perception, decision-making, and control performance of autonomous driving systems in complex traffic scenarios, as well as the hazards and risks caused by reasonably foreseeable human misuse. However, currently, there is a lack of a comprehensive safety protection system that can simultaneously address both of these safety issues.

[0003] Therefore, there is an urgent need for a vehicle-side safety protection system and method for autonomous vehicles. Summary of the Invention

[0004] To address the current lack of a comprehensive safety protection system that can simultaneously consider functional safety issues and anticipated functional safety issues, embodiments of the present invention provide a vehicle-side safety protection system and method for autonomous vehicles.

[0005] In a first aspect, embodiments of the present invention provide a vehicle-side safety protection system for autonomous vehicles, which is installed on the vehicle side and connected to the original vehicle system. The original vehicle system includes a vehicle networking system, a vehicle autonomous driving system, and a vehicle execution system. The vehicle-side safety protection system includes: a risk identification module, a safety and defect analysis module, and an emergency response module.

[0006] The risk identification module is connected to the original vehicle system and is used to obtain vehicle safety information from the original vehicle system to perform expected functional safety risk identification and functional safety risk identification. The vehicle safety information includes the vehicle state vector and the state vectors of surrounding traffic participants for scenario risk assessment, operation data for monitoring the driver's human-machine interaction behavior, and the state signals of the sensors, communications, and controllers of the vehicle's autonomous driving system.

[0007] The safety and defect analysis module is used to perform fault analysis and source tracing based on the real-time identification results of the risk identification module, and to perform comprehensive risk value calculation and classification, so as to determine whether to take emergency measures based on the classification results. If so, an emergency response strategy is formulated based on the vehicle safety information and classification results.

[0008] The emergency response module is used to generate emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and send it to the vehicle execution system for emergency control of the autonomous vehicle.

[0009] Secondly, embodiments of the present invention also provide a vehicle-side safety protection method for autonomous vehicles, applied to the vehicle side, the method comprising:

[0010] The risk identification module is used to obtain vehicle safety information from the original vehicle system in order to identify expected functional safety risks and functional safety risks. The vehicle safety information includes the vehicle state vector and the state vector of surrounding traffic participants for scenario risk assessment, the operation data for monitoring the driver's human-machine interaction behavior, and the state signals of the sensors, communications and controllers of the vehicle's autonomous driving system in the original vehicle system.

[0011] The safety and defect analysis module uses the real-time identification results of the risk identification module to perform fault analysis and source tracing, and performs comprehensive risk value calculation and classification. Based on the classification results, it is determined whether emergency response should be carried out. If so, an emergency response strategy is formulated based on the vehicle safety information and classification results.

[0012] The emergency response module generates emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and sends it to the vehicle execution system in the original vehicle system to perform emergency control of the autonomous vehicle.

[0013] This invention provides a vehicle-side safety protection system and method for autonomous vehicles. It identifies anticipated functional safety risks and functional safety risks in real time, including identifying complex and dangerous traffic scenarios, driver errors, and malfunctions in the vehicle's autonomous driving system. The system assesses the overall risk value and risk level. When the risk level is high, an emergency response strategy is formulated based on vehicle safety information and the classification results. An emergency response module generates emergency response information for the vehicle's execution system, prioritizing control over the autonomous driving system, and performs emergency control on the vehicle. Therefore, this solution can simultaneously consider both functional safety issues and anticipated functional safety issues to provide comprehensive safety protection for autonomous vehicles, offering a solid guarantee for their safe operation. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the composition of a vehicle-side safety protection system for autonomous vehicles provided in an embodiment of the present invention;

[0016] Figure 2 This is a flowchart of a vehicle-side safety protection method for autonomous vehicles provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] Please refer to Figure 1 This invention provides a vehicle-side safety protection system for autonomous vehicles, which is installed on the vehicle and connected to the original vehicle system. The original vehicle system includes a vehicle networking system, an autonomous driving system, and a vehicle execution system. The vehicle-side safety protection system includes a risk identification module, a safety and defect analysis module, and an emergency response module.

[0019] The risk identification module connects to the original vehicle system to obtain vehicle safety information from the original vehicle system for the purpose of identifying expected functional safety risks and functional safety risks. The vehicle safety information includes the vehicle's state vector and the state vectors of surrounding traffic participants for scenario risk assessment, operational data for monitoring the driver's human-machine interaction behavior, and the state signals of the vehicle's autonomous driving system's sensors, communications, and controllers.

[0020] The safety and defect analysis module is used to perform fault analysis and source tracing based on the real-time identification results of the risk identification module, and to calculate and classify the comprehensive risk value. Based on the classification results, it is determined whether emergency response should be carried out. If so, an emergency response strategy is formulated based on vehicle safety information and classification results.

[0021] The emergency response module is used to generate emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and send it to the vehicle execution system for emergency control of autonomous vehicles.

[0022] In this embodiment of the invention, anticipated functional safety risks and functional safety risks are identified in real time, including identifying complex and dangerous traffic scenarios, driver misoperation, and malfunctions of the vehicle's autonomous driving system. The comprehensive risk value and risk level are assessed. When the risk level is high, an emergency response strategy is formulated based on vehicle safety information and classification results. The emergency response module generates emergency response information to the vehicle execution system, which takes precedence over the control of the vehicle's autonomous driving system, and performs emergency control on the vehicle. Therefore, this solution can simultaneously consider functional safety issues and anticipated functional safety issues to provide comprehensive safety protection for autonomous vehicles, and can provide a solid guarantee for the safe operation of autonomous vehicles.

[0023] In some implementations, the risk identification module includes a vehicle driving risk identification module, a human-machine interaction monitoring module, and a vehicle functional safety risk identification module;

[0024] The vehicle driving risk identification module is used to assess the driving risk value in the current traffic scenario based on the risk model, the vehicle's state vector, and the state vectors of surrounding traffic participants.

[0025] The human-machine interaction monitoring module is used to monitor the operation data of the driver's human-machine interaction behavior in order to identify the driver's misuse or improper operation behavior and determine the factors of human misuse.

[0026] The vehicle functional safety risk identification module is used to detect the status signals of sensors, communications, and controllers in the vehicle's autonomous driving system, and to determine the fault results and functional safety risk values.

[0027] In this embodiment, the vehicle driving risk identification module analyzes the vehicle's state vector and the state vectors of surrounding traffic participants collected by the vehicle's original system for scenario risk assessment. The vehicle's state vector includes information such as position, heading angle, speed, and acceleration. Simultaneously, it collects similar information from surrounding traffic participants, forming multiple state vectors. Then, based on a risk model, it assesses the driving risk value of factors such as relative distance, speed, and potential collision points between vehicles in the current traffic scenario, identifying potential dangers or abnormal behaviors. Once the driving risk value exceeds a safety threshold, it immediately issues a warning to the safety and defect analysis module. Furthermore, this module also considers environmental factors such as weather conditions, road type, traffic signs, and traffic lights, making risk identification more comprehensive. The human-machine interaction monitoring module monitors the actions of drivers and passengers operating vehicle controls, including the timing, force, and duration of pressing the accelerator and brake pedals; the timing, torque, and direction of steering wheel operation; and actions operating the vehicle's infotainment system, including button force, button frequency, and operation duration, to identify driver misuse or improper operation behaviors and determine the factors contributing to human misuse. The Vehicle Functional Safety Risk Identification Module is responsible for diagnosing sensor, communication, and controller faults in the autonomous driving system and transmitting the information in real time to the Safety and Defect Analysis Module to ensure system stability and reliability. Sensor fault detection involves reading and analyzing fault signals emitted by sensors, including monitoring for communication errors, state failures, state blockages, and over-temperature conditions. For communication and controller fault detection, the Vehicle Functional Safety Risk Identification Module uses advanced communication technology to monitor CAN signals in real time. When a CAN fault occurs, the system can quickly identify the error state in the CAN network and accurately locate the fault using LabVIEW signal processing. Simultaneously, the LabVIEW program uses Virtual Instruments (VIs) to further detect and diagnose errors in the CAN signals, ensuring the stability and reliability of the communication network. These three modules work closely together to perform comprehensive risk identification for both anticipated and functional safety.

[0028] In some implementations, the driving risk value is assessed in the following manner:

[0029] Determine the Time-of-Collision (TTC) based risk indicator value (ITTC):

[0030]

[0031] In the formula, D x D is the lateral distance between the vehicle and other vehicles. y L is the longitudinal distance between the vehicle and other vehicles. w For the width of the vehicle, L l For the length of the vehicle, V rx V is the lateral relative velocity between the vehicle and other vehicles. ry Let A be the longitudinal relative velocity between the vehicle and another vehicle.rx Let A be the lateral relative acceleration between the vehicle and the other vehicle. ry Let be the longitudinal relative acceleration of the vehicle and the other vehicle, and 'a' be the influence coefficient of the relative acceleration of the vehicle and the other vehicle.

[0032] The ratio of the vehicle's speed to the road speed limit is used as the correlation coefficient λ in the calculation of driving risk value. The calculation formula is as follows:

[0033]

[0034] In the formula, v is the speed of the vehicle. l To limit speed on roads, such as a maximum speed of 120 km / h on highways, then v l The value is 120. The larger the value of λ, the faster the vehicle's speed is relative to the road speed limit, and the greater the impact on the driving risk value.

[0035] The driving risk value r under the current traffic scenario is:

[0036] r = exp(-λ·ITTC).

[0037] In some implementations, the human misuse factor is determined as follows: if the human-machine interaction monitoring module identifies that the driver has misused or improper operation behavior in the current detection cycle, the human misuse factor is determined to be 2; if no human misuse occurs, the human misuse factor is 1.

[0038] In some implementations, the functional safety risk value is determined by referring to the ASIL vehicle safety integrity level and assessing the functional safety risk value based on three factors: severity, exposure, and controllability of the fault determined by the vehicle functional safety risk identification module in the current inspection cycle. The functional safety risk value can be rated as 1, 2, 3, or 4 from low to high.

[0039] In some implementations, the vehicle functional safety risk identification module is also used to adjust the fault detection priority based on the high-risk traffic scenario when the vehicle driving risk identification module assesses a high-risk traffic scenario, so as to more quickly pinpoint the source of the fault and prioritize the determination of the operating status of key safety components in the current traffic scenario.

[0040] In some implementations, the security and defect analysis module includes at least a fault tracing analysis module, a defect analysis module, a security calculation and classification module, and an emergency response strategy module;

[0041] The input end of the fault tracing analysis module is connected to the vehicle functional safety risk identification module. It is used to establish a system fault propagation model by using a hybrid algorithm based on physical models and data-driven approaches. It uses an artificial intelligence algorithm based on long short-term memory networks (LSTM) to infer the causal relationship between time series, locate the fault location and type, and complete the fault tracing.

[0042] The input end of the defect analysis module is connected to the vehicle functional safety risk identification module. It is used to collect vehicle defect clues through multiple channels and use artificial intelligence technology based on supervised learning to perform defect correlation analysis. It classifies the same or similar faults that occur in different safety events of the vehicle. Then, it uses correlation analysis to mine and summarize the patterns with common attributes in multi-source data to determine the root cause of the fault.

[0043] The safety calculation and classification module is used to determine the comprehensive risk value based on the driving risk value output by the vehicle driving risk identification module, the human misuse factor output by the human-machine interaction monitoring module, and the functional safety risk value output by the vehicle functional safety risk identification module, and to complete the safety classification based on fuzzy theory and clustering algorithm.

[0044] The emergency response strategy module is used to formulate driving routes based on vehicle safety information and determine the braking urgency of the driving routes based on the classification results.

[0045] In this embodiment, when the vehicle functional safety risk identification module identifies a fault in the vehicle's autonomous driving system, the fault tracing analysis module and the defect analysis module trace and analyze the fault. If no fault is identified, the fault tracing analysis module and the defect analysis module do not operate.

[0046] The safety calculation and classification module determines the overall risk value R in the following way:

[0047] R = β × γ × r

[0048] In the formula, β is the functional safety risk value, γ is the personnel misuse factor, and r is the driving risk value. The larger the comprehensive risk value R, the higher the vehicle risk level.

[0049] Furthermore, the emergency response strategy module not only considers the current risk level and fault status but also predicts the risk development trend within a certain forecast time window, thus making a more predictive safety analysis. Based on the analysis and prediction, it determines a safe driving route, as well as measures such as deceleration, lane changing, stopping, or initiating emergency avoidance procedures. In special circumstances, if the system detects a serious fault or an irreversible risk, the emergency response strategy module may also decide to safely guide the vehicle to a stop and initiate emergency assistance procedures.

[0050] In some implementations, the security and defect analysis module also includes a security log generation module;

[0051] The input end of the safety log generation module is connected to the risk identification module, fault tracing and analysis module, defect analysis module, safety calculation and classification module, and emergency response strategy module, while the output end is connected to the safety brain system located in the cloud. The safety log generation module is used to record the vehicle operating status, driver operation data, and vehicle autonomous driving system faults when a safety incident occurs, and reports them to the safety brain system in the cloud to provide basic data for subsequent safety strategy optimization.

[0052] In some implementations, the emergency response module includes at least: a lateral response module and a longitudinal response module;

[0053] The lateral response module is used to generate emergency response information for the vehicle steering system based on emergency response strategies in order to control the direction of the vehicle.

[0054] The longitudinal response module is used to generate emergency response information on vehicle speed and acceleration based on emergency response strategies, in order to control the vehicle's power output and braking force output.

[0055] In this embodiment, the lateral response module is responsible for the vehicle's direction and path following, including steering, lane changing, and lane keeping. By controlling the vehicle's steering system, it ensures that the vehicle accurately follows the safe driving path defined by the emergency response strategy module, thereby maintaining vehicle stability and good handling performance even in emergency avoidance or complex road conditions. The longitudinal response module mainly adjusts the vehicle's speed and acceleration, including acceleration, deceleration, and emergency braking. When the emergency response strategy module determines that a speed change or stopping is necessary, the longitudinal control intervenes and controls the vehicle's power output and braking force output.

[0056] In some implementations, the emergency response module also includes a safety warning module; the safety warning module obtains risk information from the safety and defect analysis module and provides safety warnings and feedback to the driver in emergency situations through head-up display (HUD) information prompts, steering wheel and seat vibrations, and in-vehicle voice prompts.

[0057] In some implementations, the emergency response module is also used to: generate emergency response information using the vehicle safety information at the last moment before the failure, and control the vehicle when a fault causes communication data between systems to fail.

[0058] In this embodiment, the emergency response module serves as the last line of defense in the safety protection system. Besides executing the conventional functions of the emergency response strategy output from the safety and defect analysis module, it exhibits strong fault tolerance and robustness in extreme situations. Even without critical data from the safety and defect analysis module, it can achieve a safe vehicle response solely based on the vehicle's own status information. When a malfunction in the autonomous driving system or an internal fault in the system of this embodiment causes communication data between systems to fail, the vehicle safety information at the last moment before the malfunction occurs is used to predict the surrounding environment based on a kinematic model and control the vehicle.

[0059] In this embodiment of the invention, when a malfunction in the autonomous driving system causes communication data between systems to fail, the longitudinal response module is used to calculate the safe driving distance in real time using a deceleration model and to decelerate based on a sliding mode control algorithm to stop within a safe distance; the lateral response module uses the last valid expected path issued by the vehicle's autonomous driving system to control the vehicle's steering system, thereby ensuring basic safety response functions.

[0060] Therefore, the vehicle-side safety protection system for autonomous vehicles in this embodiment of the invention covers three key aspects: risk identification, safety and defect analysis, and emergency response. In the risk identification section, this system implements a comprehensive risk identification strategy, capable of accurately and in real-time detecting and assessing safety risks in traffic scenarios, monitoring human-machine interaction behavior, and diagnosing faults in various functions of the autonomous driving system. The safety and defect analysis module comprehensively analyzes traffic scenario data, human-machine interaction behavior data, and vehicle fault conditions obtained from the risk identification module. Based on this information, it performs comprehensive analysis, calculates the comprehensive risk value and safety level, intelligently selects the most appropriate safety strategy, and generates a safety log to address the current traffic environment and system status. Furthermore, the safety and defect analysis module can also trace the source of faults by identifying fault location, type, and other factors. It uses artificial intelligence technology for correlation analysis to accurately identify the factors associated with the occurrence of defects. The generated safety log records vehicle operation data, event information, and occupant behavior, providing a reliable data source for accident reconstruction. In terms of emergency response, in addition to its standard functions, the system can maintain effective control of the vehicle even when the autonomous driving system and safety and defect analysis module fail. This is thanks to the reference model embedded in the emergency response module, which enables safe control even in extreme situations. Furthermore, a safety warning module is included to issue safety warnings in emergencies, prompting occupants to take necessary actions and protective measures to ensure driving safety.

[0061] like Figure 2 As shown, this embodiment of the invention also provides a vehicle-side safety protection method for autonomous vehicles, applied to the vehicle side, the method including:

[0062] Step 200: Use the risk identification module to obtain vehicle safety information from the original vehicle system to perform expected functional safety risk identification and functional safety risk identification; vehicle safety information includes the vehicle state vector and the state vectors of surrounding traffic participants for scenario risk assessment, operation data for monitoring driver human-machine interaction behavior, and the state signals of sensors, communications and controllers of the vehicle's autonomous driving system in the original vehicle system.

[0063] Step 202: The safety and defect analysis module performs fault analysis and source tracing based on the real-time identification results of the risk identification module, and performs comprehensive risk value calculation and classification to determine whether emergency response should be carried out based on the classification results. If so, an emergency response strategy is formulated based on vehicle safety information and classification results.

[0064] Step 204: The emergency response module generates emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and sends it to the vehicle execution system in the original vehicle system to carry out emergency control of the autonomous vehicle.

[0065] Since the above method is based on the same concept as the system embodiment of the present invention, the specific details can be found in the description of the system embodiment of the present invention, and will not be repeated here.

[0066] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0067] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle-side safety protection system for autonomous vehicles, characterized in that, The vehicle-side security system is installed on the vehicle end and connected to the original vehicle system, which includes a vehicle networking system, an autonomous driving system, and a vehicle execution system. The vehicle-side security protection system includes: a risk identification module, a security and defect analysis module, and an emergency response module. The risk identification module is connected to the original vehicle system and is used to obtain vehicle safety information from the original vehicle system to perform expected functional safety risk identification and functional safety risk identification. The vehicle safety information includes the vehicle state vector and the state vectors of surrounding traffic participants for scenario risk assessment, operation data for monitoring the driver's human-machine interaction behavior, and the state signals of the sensors, communications, and controllers of the vehicle's autonomous driving system. The safety and defect analysis module is used to perform fault analysis and source tracing based on the real-time identification results of the risk identification module, and to perform comprehensive risk value calculation and classification, so as to determine whether to take emergency measures based on the classification results. If so, an emergency response strategy is formulated based on the vehicle safety information and classification results. The emergency response module is used to generate emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and send it to the vehicle execution system for emergency control of the autonomous vehicle. The risk identification module includes a vehicle driving risk identification module, a human-machine interaction monitoring module, and a vehicle functional safety risk identification module. The vehicle driving risk identification module is used to assess the driving risk value in the current traffic scenario based on the risk model, the vehicle's state vector, and the state vectors of surrounding traffic participants. The human-machine interaction monitoring module is used to monitor the operation data of the driver's human-machine interaction behavior in order to identify the driver's misuse or improper operation behavior and determine the factor of human misuse. The vehicle functional safety risk identification module is used to detect the status signals of the sensors, communications and controllers of the vehicle's autonomous driving system, and to determine the fault results and functional safety risk values. The driving risk value is assessed in the following manner: Determine the time-of-collision risk index value (ITTC): In the formula, The lateral distance between your vehicle and other vehicles. The longitudinal distance between your vehicle and other vehicles. For the width of the vehicle, For the length of the vehicle, The relative speed between the vehicle and other vehicles in the lateral direction. The longitudinal relative speed between the vehicle and other vehicles. The relative acceleration in the lateral direction between the vehicle and the other vehicle. Let be the longitudinal relative acceleration between the vehicle and the other vehicle. The coefficient representing the influence of the relative acceleration between the vehicle and other vehicles; The ratio of the vehicle's speed to the road speed limit is used as the correlation coefficient in calculating the driving risk value. The calculation formula is: In the formula, The vehicle's speed. Speed ​​limits on roads; The driving risk value r under the current traffic scenario is: ； The safety calculation and classification module determines the comprehensive risk value in the following manner. of: In the formula, This represents the functional safety risk value. For personnel misuse factors, This represents the driving risk value.

2. The system according to claim 1, characterized in that, The vehicle functional safety risk identification module is also used to adjust the fault detection priority based on the high-risk traffic scenario when the vehicle driving risk identification module assesses a high-risk traffic scenario, so as to prioritize the determination of the operating status of key safety components in the current traffic scenario.

3. The system according to claim 1, characterized in that, The security and defect analysis module includes at least a fault tracing analysis module, a defect analysis module, a security calculation and classification module, and an emergency response strategy module; The input end of the fault tracing analysis module is connected to the vehicle functional safety risk identification module. It is used to establish a system fault propagation model by using a hybrid algorithm based on physical models and data-driven methods, and to use an artificial intelligence algorithm based on long short-term memory networks to infer the causal relationship between time series, locate the fault location and type, and complete the fault tracing. The input end of the defect analysis module is connected to the vehicle functional safety risk identification module. It is used to collect vehicle defect clues through multiple channels, and use clustering methods to perform defect correlation analysis. It classifies the same or similar faults that occur in different safety events of the vehicle. Then, it uses correlation analysis to mine and summarize the patterns with common attributes in multi-source data to determine the root cause of the fault. The safety calculation and classification module is used to determine a comprehensive risk value based on the driving risk value output by the vehicle driving risk identification module, the personnel misuse factor output by the human-machine interaction monitoring module, and the functional safety risk value output by the vehicle functional safety risk identification module, and to complete the safety classification based on fuzzy theory and clustering algorithm. The emergency response strategy module is used to formulate a driving route based on the vehicle safety information and determine the braking urgency of the driving route based on the classification results.

4. The system according to claim 3, characterized in that, The security and defect analysis module also includes a security log generation module; The input end of the safety log generation module is connected to the risk identification module, the fault tracing and analysis module, the defect analysis module, the safety calculation and classification module, and the emergency response strategy module, and the output end is connected to the safety brain system located in the cloud. The safety log generation module is used to record the vehicle operating status, driver operation data, and faults of the vehicle's autonomous driving system when a safety incident occurs, and to report them to the safety brain system in the cloud.

5. The system according to claim 1, characterized in that, The emergency response module includes at least: a horizontal response module and a vertical response module; The lateral response module is used to generate emergency response information for the vehicle steering system based on emergency response strategies in order to control the direction of the vehicle. The longitudinal response module is used to generate emergency response information on vehicle speed and acceleration based on emergency response strategies, so as to control the vehicle's power output and braking force output.

6. The system according to claim 5, characterized in that, The emergency response module is also used to: when a fault causes communication data between systems to fail, generate emergency response information using the vehicle safety information at the last moment before the fault occurred, and control the vehicle.

7. The system according to claim 6, characterized in that, When a fault causes communication data between systems to fail, the longitudinal response module is used to calculate the safe driving distance in real time using a deceleration model and decelerate based on a sliding mode control algorithm to stop within a safe distance. The lateral response module is used to control the vehicle steering system using the last valid expected path issued by the vehicle's autonomous driving system.

8. A vehicle-side safety protection method for autonomous vehicles based on the system described in any one of claims 1-7, characterized in that, Applied to the vehicle end, the method includes: The risk identification module is used to obtain vehicle safety information from the original vehicle system in order to identify expected functional safety risks and functional safety risks. The vehicle safety information includes the vehicle state vector and the state vector of surrounding traffic participants for scenario risk assessment, the operation data for monitoring the driver's human-machine interaction behavior, and the state signals of the sensors, communications and controllers of the vehicle's autonomous driving system in the original vehicle system. The safety and defect analysis module uses the real-time identification results of the risk identification module to perform fault analysis and source tracing, and performs comprehensive risk value calculation and classification. Based on the classification results, it is determined whether emergency response should be carried out. If so, an emergency response strategy is formulated based on the vehicle safety information and classification results. The emergency response module generates emergency response information based on the emergency response strategy formulated by the safety and defect analysis module and sends it to the vehicle execution system in the original vehicle system to perform emergency control of the autonomous vehicle.

Images