Intelligent automobile path tracking system for urgent danger prevention

Abstract

The invention discloses an intelligent automobile path tracking system for urgent danger avoidance, and particularly relates to the technical field of intelligent automobiles, the system comprises an environment sensing module, the output end of the environment sensing module is connected with a danger assessment module, and the output end of the danger assessment module is connected with a path planning module. The output end of the path planning module is connected with a decision planning module, the output end of the decision planning module is connected with a vehicle control module, and the output end of the vehicle control module is connected with a communication and interaction module. Through cooperative work of all the modules, perception of the surrounding environment of the vehicle, danger assessment, path planning, decision making, vehicle control and communication interaction with the outside are achieved, under the dangerous condition, the system can make a response rapidly, effective danger avoiding measures are taken, the driving safety of the vehicle and the accuracy of path tracking are ensured, and the driving safety of the vehicle is improved. And a comprehensive and reliable guarantee is provided for safe driving of the intelligent automobile.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent automobiles, and more specifically, to an intelligent automobile path tracking system for emergency avoidance of danger. Background Art

[0002] The intelligent vehicle path tracking system is an important component of intelligent vehicles. Its main function is to track the planned trajectory in real time by controlling the vehicle's steering angle, etc., to ensure that the vehicle can travel along the desired path accurately, stably and comfortably.

[0003] The fusion effect of multiple sensors used in traditional smart car path tracking systems is not ideal. Differences in data format and accuracy lead to fusion errors. The data processing algorithm is not optimal and there are delays, which affect real-time and accuracy. Some smart cars lack a systematic evaluation mechanism. Drivers rely on experience to make judgments and find it difficult to accurately quantify potential risks, such as rollover and road deviation risks. When driving at high speeds, they may not be able to detect vehicle status changes and potential dangers in time, leading to accidents; they rely on memory and simple navigation and cannot dynamically adjust according to real-time conditions. When encountering danger, drivers lack information and decision-making support and find it difficult to make the best risk avoidance decision, which may lead to accidents due to blind operations; manual control is limited by the driver's skills and reactions, and the control accuracy and stability are insufficient in emergency situations, such as long braking distance or steering out of control; they have poor adaptability under complex road conditions and cannot find the optimal path or make adjustments in time. The decision-making algorithm does not integrate multiple factors, and the results are not optimized enough. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an intelligent automobile path tracking system for emergency avoidance of danger to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a smart car path tracking system for emergency avoidance of danger, comprising an environment perception module, an output end of the environment perception module is connected to a danger assessment module, an output end of the danger assessment module is connected to a path planning module, an output end of the path planning module is connected to a decision planning module, an output end of the decision planning module is connected to a vehicle control module, and an output end of the vehicle control module is connected to a communication and interaction module; The environment perception module includes a laser radar, a millimeter-wave radar and a camera, the output ends of the laser radar, the millimeter-wave radar and the camera are connected to a sensor data acquisition module, the output end of the sensor data acquisition module is connected to a multimodal sensor fusion enhancement module, and the output end of the multimodal sensor fusion enhancement module is connected to a data preprocessing module; The output end of the danger assessment module is connected to a dangerous target detection module, and the output ends of the dangerous target detection module are respectively connected to a collision risk assessment module, a rollover risk assessment module and a road departure risk assessment module, and the output ends of the collision risk assessment module, the rollover risk assessment module and the road departure risk assessment module are all connected to a dynamic risk monitoring module.

[0006] Preferably, the output end of the path planning module is respectively connected to the target path generation module, the obstacle avoidance path planning module and the path optimization algorithm module, the output ends of the target path generation module, the obstacle avoidance path planning module and the path optimization algorithm module are all connected to the emergency lane and special channel utilization planning module, and the output end of the emergency lane and special channel utilization planning module is connected to the dynamic path adjustment module.

[0007] Preferably, the output end of the decision planning module is connected to a hedging strategy selection, the output end of the hedging strategy selection is connected to a decision execution module, and the output ends of the decision execution module are respectively connected to a decision execution monitoring module and a decision record optimization module.

[0008] Preferably, the output ends of the vehicle control module are respectively connected to the steering control module, the acceleration control module, the braking control module and the vehicle stability control module, the output ends of the vehicle stability control modules are all connected to the control instruction execution, the output ends of the communication and interaction module are respectively connected to the vehicle-to-vehicle communication module, the vehicle-road communication module and the human-computer interaction module, the output ends of the communication and interaction module are also connected to the remote monitoring and emergency rescue interaction module, and the output ends of the remote monitoring and emergency rescue interaction module are connected to the data transmission and communication protocol module.

[0009] Preferably, the environmental perception module comprehensively collects information about the vehicle's surrounding environment through multiple sensors such as lidar, millimeter-wave radar and camera; the risk assessment module receives data from the environmental perception module and assesses the risks that the vehicle may face during driving; the path planning module plans a safe and reasonable driving path based on the risk assessment results and the vehicle's current position and destination information; the decision planning module selects an appropriate risk avoidance strategy based on the results of risk assessment and path planning; the vehicle control module receives instructions from the decision planning module and accurately controls the steering, acceleration and braking of the vehicle; and the communication and interaction module realizes communication and interaction functions between the vehicle and other vehicles, road infrastructure and the driver.

[0010] Preferably, the sensor data acquisition module is responsible for collecting data output by lidar, millimeter-wave radar and camera sensors, the multimodal sensor fusion enhancement module fuses data from different sensors, the data preprocessing module is used to preprocess the fused sensor data, including filtering, denoising and calibration operations, the dangerous target detection module identifies target objects that may pose a threat to vehicle driving safety based on the data provided by the environmental perception module, the collision risk assessment module calculates the possibility and time of a collision between the two, and assesses the severity of the collision, the rollover risk assessment module is used to determine the risk of a vehicle rolling over during driving, the road deviation risk assessment module is used to assess the impact of road deviation on driving safety, and the dynamic risk monitoring module monitors changes in dangerous conditions during vehicle driving in real time.

[0011] Preferably, the target path generation module is used to generate an initial driving target path, the obstacle avoidance path planning module is used to plan a specific path to avoid obstacles, the path optimization algorithm module uses the Dijkstra algorithm to optimize the generated path, the emergency lane and special channel utilization planning module is used to evaluate whether the emergency lane or other special channels can be used to achieve faster risk avoidance or passage, and the dynamic path adjustment module is used to dynamically adjust the planned path according to real-time changing environmental information, vehicle status and hazard assessment results.

[0012] Preferably, the hedging strategy selection is used to select the most suitable strategy for the current situation from a plurality of preset hedging strategies, the decision execution module is used to convert the selected hedging strategy into specific operation instructions, the decision execution monitoring module is used to monitor the execution process of the decision in real time, and the decision record optimization module is used to record the relevant information of each decision and optimize and improve the decision algorithm and strategy.

[0013] Preferably, the steering control module is used to accurately control the steering angle of the vehicle, the acceleration control module is used to control the acceleration of the vehicle, the braking control module is used to control the braking system of the vehicle, the vehicle stability control module is used to control the suspension system and wheel torque distribution method of the vehicle to maintain the stability of the vehicle, and the control instructions execute the received instructions and accurately transmit them to the vehicle's actuator.

[0014] Preferably, the vehicle-to-vehicle communication module is used to exchange vehicle position, speed, and driving direction information in real time; the vehicle-road communication module is used to obtain traffic light status, road construction information, and road condition information; the human-computer interaction module realizes human-computer collaborative control, improves the driver's understanding of the vehicle's driving status and ability to respond to dangerous situations; the remote monitoring and emergency rescue interaction module communicates with a remote monitoring center or emergency rescue agency; and the data transmission and communication protocol module is responsible for data transmission between various modules within the system and between external devices, ensuring the stability and reliability of data transmission.

[0015] Technical effects and advantages of the present invention: 1. Through multi-sensor fusion, it can realize comprehensive and accurate perception of the vehicle's surrounding environment and accurately identify various potential dangers, such as obstacles, abnormal road conditions, etc. The hazard assessment module can accurately calculate the risks of collision, rollover, road deviation, etc., provide solid data support for risk avoidance decisions, greatly reduce the probability of accidents, quickly detect sudden situations of pedestrians or vehicles under complex road conditions and accurately judge the degree of risk, timely warn and provide a basis for risk avoidance operations, the decision-making and planning module formulates the best risk avoidance strategy based on real-time conditions, and the vehicle control module accurately performs steering, acceleration, braking and other operations to ensure that the vehicle responds quickly and accurately at dangerous moments, effectively avoids or reduces the harm of accidents, and can quickly and accurately control the vehicle to achieve safe avoidance or braking in the face of emergencies to ensure driving safety; 2. By comprehensively planning the optimal route based on multiple factors, the driving time and distance can be reduced, the energy utilization efficiency can be improved, and the vehicles can be helped to reach the destination quickly and energy-efficiently. According to real-time traffic information, congested sections can be avoided, and efficient and energy-saving routes can be selected to improve travel efficiency. In emergency situations, special channels such as emergency lanes can be scientifically evaluated and used to achieve rapid risk avoidance or passage, reduce traffic jams and delays, and improve the passing efficiency in special scenarios. Vehicle-to-vehicle and vehicle-to-road communication can realize information sharing, and vehicles can obtain real-time traffic and other information, make decisions in advance, promote vehicle collaborative risk avoidance, improve traffic smoothness and safety, optimize driving experience, communicate with rescue agencies in emergency situations, obtain rescue in time, enhance the driver's sense of security, improve emergency rescue efficiency, and reduce accident losses. The data sharing of vehicle-to-vehicle and vehicle-to-road communication provides valuable information for traffic management, helps optimize traffic control and planning, and improves the overall operation efficiency and management level of the transportation system; 3. In summary, through the mutual influence of the above-mentioned multiple effects, the intelligent car path tracking system for emergency avoidance of danger realizes the perception of the vehicle's surrounding environment, danger assessment, path planning, decision-making and vehicle control, as well as communication and interaction with the outside world through the collaborative work between various modules. In dangerous situations, the system can respond quickly and take effective avoidance measures to ensure the vehicle's driving safety and the accuracy of path tracking, providing comprehensive and reliable protection for the safe driving of intelligent vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0017] Figure 2 It is a functional structure diagram of the environment perception of the present invention.

[0018] Figure 3 It is a functional structure diagram of the risk assessment of the present invention.

[0019] Figure 4 It is a functional structure diagram of the path planning of the present invention.

[0020] Figure 5 A schematic diagram of the functional structure of the decision-making planning of the present invention.

[0021] Figure 6 It is a functional structure diagram of the vehicle control of the present invention.

[0022] Figure 7 It is a schematic diagram of the functional structure of communication and interaction of the present invention.

[0023] The accompanying drawings are marked as follows: 1. Environmental perception module; 2. Hazard assessment module; 3. Path planning module; 4. Decision planning module; 5. Vehicle control module; 6. Communication and interaction module; 7. LiDAR; 8. Millimeter wave radar; 9. Camera; 10. Sensor data acquisition module; 11. Multimodal sensor fusion enhancement module; 12. Data preprocessing module; 13. Dangerous target detection module; 14. Collision risk assessment module; 15. Rollover risk assessment module; 16. Road departure risk assessment module; 17. Dynamic risk monitoring module; 18. Target path generation module; 19. Obstacle avoidance path planning Module; 20. Path optimization algorithm module; 21. Emergency lane and special channel utilization planning module; 22. Dynamic path adjustment module; 23. Risk avoidance strategy selection; 24. Decision execution module; 25. Decision execution monitoring module; 26. Decision record optimization module; 27. Steering control module; 28. Acceleration control module; 29. ​​Braking control module; 30. Vehicle stability control module; 31. Control instruction execution; 32. Vehicle-to-vehicle communication module; 33. Vehicle-to-road communication module; 34. Human-computer interaction module; 35. Remote monitoring and emergency rescue interaction module; 36. Data transmission and communication protocol module. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] As attached Figure 1-7 The intelligent automobile path tracking system for emergency avoidance of danger shown in the figure comprises an environment perception module 1, an output end of the environment perception module 1 is connected to a danger assessment module 2, an output end of the danger assessment module 2 is connected to a path planning module 3, an output end of the path planning module 3 is connected to a decision planning module 4, an output end of the decision planning module 4 is connected to a vehicle control module 5, and an output end of the vehicle control module 5 is connected to a communication and interaction module 6; The environment perception module 1 includes a laser radar 7, a millimeter wave radar 8 and a camera 9. The output ends of the laser radar 7, the millimeter wave radar 8 and the camera 9 are connected to a sensor data acquisition module 10. The output end of the sensor data acquisition module 10 is connected to a multimodal sensor fusion enhancement module 11. The output end of the multimodal sensor fusion enhancement module 11 is connected to a data preprocessing module 12. The output end of the danger assessment module 2 is connected to the dangerous target detection module 13, and the output end of the dangerous target detection module 13 is respectively connected to the collision risk assessment module 14, the rollover risk assessment module 15 and the road departure risk assessment module 16, and the output ends of the collision risk assessment module 14, the rollover risk assessment module 15 and the road departure risk assessment module 16 are all connected to the dynamic risk monitoring module 17.

[0026] The output ends of the path planning module 3 are respectively connected to the target path generation module 18, the obstacle avoidance path planning module 19 and the path optimization algorithm module 20; the output ends of the target path generation module 18, the obstacle avoidance path planning module 19 and the path optimization algorithm module 20 are all connected to the emergency lane and special channel utilization planning module 21; the output end of the emergency lane and special channel utilization planning module 21 is connected to the dynamic path adjustment module 22.

[0027] The output end of the decision planning module 4 is connected to the risk hedging strategy selection 23, the output end of the risk hedging strategy selection 23 is connected to the decision execution module 24, and the output ends of the decision execution module 24 are respectively connected to the decision execution monitoring module 25 and the decision record optimization module 26.

[0028] The output ends of the vehicle control module 5 are respectively connected to the steering control module 27 , the acceleration control module 28 , the braking control module 29 and the vehicle stability control module 30 , and the output ends of the vehicle stability control module 30 are all connected to the control instruction execution 31 .

[0029] The output ends of the communication and interaction module 6 are respectively connected to the vehicle-to-vehicle communication module 32, the vehicle-road communication module 33 and the human-computer interaction module 34. The output ends of the communication and interaction module 6 are also connected to the remote monitoring and emergency rescue interaction module 35. The output ends of the remote monitoring and emergency rescue interaction module 35 are connected to the data transmission and communication protocol module 36.

[0030] The environment perception module 1 comprehensively collects information about the vehicle's surrounding environment through multiple sensors such as laser radar 7, millimeter wave radar 8 and camera 9. The risk assessment module 2 receives data from the environment perception module and assesses the risks that the vehicle may face during driving. The path planning module 3 plans a safe and reasonable driving path based on the risk assessment results and the vehicle's current position and destination information. The decision planning module 4 selects an appropriate risk avoidance strategy based on the results of risk assessment and path planning. The vehicle control module 5 receives instructions from the decision planning module and accurately controls the steering, acceleration and braking of the vehicle. The communication and interaction module 6 realizes the communication and interaction functions between the vehicle and other vehicles, road infrastructure and the driver.

[0031] The sensor data acquisition module 10 is responsible for collecting data output by the laser radar, millimeter wave radar and camera sensors. The multimodal sensor fusion enhancement module 11 fuses the data from different sensors. The data preprocessing module 12 is used to preprocess the fused sensor data, including filtering, denoising and calibration operations. The dangerous target detection module 13 identifies target objects that may pose a threat to the driving safety of the vehicle based on the data provided by the environmental perception module. The collision risk assessment module 14 calculates the possibility and time of a collision between the two and assesses the severity of the collision. The rollover risk assessment module 15 is used to determine the risk of the vehicle rolling over during driving. The road deviation risk assessment module 16 is used to assess the impact of road deviation on driving safety. The dynamic risk monitoring module 17 monitors the changes in dangerous conditions during vehicle driving in real time.

[0032] The target path generation module 18 is used to generate the initial driving target path, the obstacle avoidance path planning module 19 is used to plan a specific path to avoid obstacles, the path optimization algorithm module 20 uses the Dijkstra algorithm to optimize the generated path, the emergency lane and special channel utilization planning module 21 is used to evaluate whether the emergency lane or other special channels can be used to achieve faster risk avoidance or passage, and the dynamic path adjustment module 22 is used to dynamically adjust the planned path according to real-time changing environmental information, vehicle status and hazard assessment results.

[0033] The hedging strategy selection 23 is used to select the most suitable strategy for the current situation from a variety of preset hedging strategies. The decision execution module 24 is used to convert the selected hedging strategy into specific operation instructions. The decision execution monitoring module 25 is used to monitor the execution process of the decision in real time. The decision record optimization module 26 is used to record the relevant information of each decision and optimize and improve the decision algorithm and strategy.

[0034] The steering control module 27 is used to accurately control the steering angle of the vehicle, the acceleration control module 28 is used to control the acceleration of the vehicle, the braking control module 29 is used to control the braking system of the vehicle, the vehicle stability control module 30 is used to control the suspension system and wheel torque distribution method of the vehicle to maintain the stability of the vehicle, and the control instruction execution 31 receives instructions and accurately transmits them to the vehicle's actuator.

[0035] The vehicle-to-vehicle communication module 32 is used to exchange vehicle position, speed, and driving direction information in real time. The vehicle-road communication module 33 is used to obtain traffic light status, road construction information, and road condition information. The human-computer interaction module 34 realizes human-computer collaborative control, improves the driver's understanding of the vehicle's driving status and the ability to respond to dangerous situations. The remote monitoring and emergency rescue interaction module 35 communicates with the remote monitoring center or emergency rescue agency. The data transmission and communication protocol module 36 is responsible for data transmission between various modules within the system and between external devices to ensure the stability and reliability of data transmission.

[0036] The working principle of the present invention is as follows: the laser radar 7 measures the information of surrounding objects, the millimeter wave radar 8 detects the target motion state, the camera 9 identifies the object and provides visual information, the sensor data acquisition module 10 collects and organizes the data, the multimodal sensor fusion enhancement module 11 fuses the data and gives full play to the advantages, the data preprocessing module 12 processes the data, the dangerous target detection module 13 identifies the dangerous target, the collision risk assessment module 14 assesses the possibility and severity of the collision, the rollover risk assessment module 15 determines the rollover risk, the road deviation risk assessment module 16 assesses the deviation risk, the dynamic risk monitoring module 17 monitors the risk change, the target path generation module 18 generates the initial path, the obstacle avoidance path planning module 19 plans the obstacle avoidance path, the path optimization algorithm module 20 optimizes the path, and the emergency lane and special channel are utilized. The planning module 21 plans the use of special channels, the dynamic path adjustment module 22 adjusts the path, the risk avoidance strategy selection 23 selects the risk avoidance strategy, the decision execution module 24 converts the strategy into instructions and executes it, the decision execution monitoring module 25 monitors the execution process, the decision record optimization module 26 records the optimization decision, the steering control module 27 controls the steering, the acceleration control module 28 adjusts the acceleration, the braking control module 29 controls the braking, the vehicle stability control module 30 maintains the stability of the vehicle, the control instruction execution 31 transmits the instruction to the actuator, the vehicle-to-vehicle communication module 32 realizes vehicle-to-vehicle communication, the vehicle-to-road communication module 33 realizes vehicle-to-road communication, the human-computer interaction module 34 interacts with the driver, the remote monitoring and emergency rescue interaction module 35 interacts with relevant departments, and the data transmission and communication protocol module 36 ensures data transmission and communication.

[0037] Finally, it should be noted that the drawings of the embodiments disclosed in the present invention only involve structures related to the embodiments disclosed in the present invention, and other structures can refer to common designs. In the absence of conflicts, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent automobile path tracking system for emergency avoidance of danger, comprising an environment perception module (1), characterized in that: The output end of the environment perception module (1) is connected to a risk assessment module (2), the output end of the risk assessment module (2) is connected to a path planning module (3), the output end of the path planning module (3) is connected to a decision planning module (4), the output end of the decision planning module (4) is connected to a vehicle control module (5), and the output end of the vehicle control module (5) is connected to a communication and interaction module (6); The environment perception module (1) comprises a laser radar (7), a millimeter wave radar (8) and a camera (9); the output ends of the laser radar (7), the millimeter wave radar (8) and the camera (9) are connected to a sensor data acquisition module (10); the output end of the sensor data acquisition module (10) is connected to a multimodal sensor fusion enhancement module (11); the output end of the multimodal sensor fusion enhancement module (11) is connected to a data preprocessing module (12); The output end of the danger assessment module (2) is connected to a dangerous target detection module (13); the output end of the dangerous target detection module (13) is respectively connected to a collision risk assessment module (14), a rollover risk assessment module (15) and a road departure risk assessment module (16); and the output ends of the collision risk assessment module (14), the rollover risk assessment module (15) and the road departure risk assessment module (16) are all connected to a dynamic risk monitoring module (17).

2. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 1 is characterized by: The output end of the path planning module (3) is respectively connected to a target path generation module (18), an obstacle avoidance path planning module (19) and a path optimization algorithm module (20); the output ends of the target path generation module (18), the obstacle avoidance path planning module (19) and the path optimization algorithm module (20) are all connected to an emergency lane and special channel utilization planning module (21); and the output end of the emergency lane and special channel utilization planning module (21) is connected to a dynamic path adjustment module (22).

3. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 1 is characterized by: The output end of the decision planning module (4) is connected to a risk hedging strategy selection (23), the output end of the risk hedging strategy selection (23) is connected to a decision execution module (24), and the output end of the decision execution module (24) is respectively connected to a decision execution monitoring module (25) and a decision record optimization module (26).

4. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 1 is characterized by: The output end of the vehicle control module (5) is respectively connected to a steering control module (27), an acceleration control module (28), a braking control module (29) and a vehicle stability control module (30); the output end of the vehicle stability control module (30) is connected to a control instruction execution module (31); the output end of the communication and interaction module (6) is respectively connected to a vehicle-to-vehicle communication module (32), a vehicle-to-road communication module (33) and a human-computer interaction module (34); the output end of the communication and interaction module (6) is also connected to a remote monitoring and emergency rescue interaction module (35); the output end of the remote monitoring and emergency rescue interaction module (35) is connected to a data transmission and communication protocol module (36).

5. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 1 is characterized by: The environment perception module (1) comprehensively collects information about the vehicle's surrounding environment through multiple sensors such as a laser radar (7), a millimeter wave radar (8) and a camera (9); the risk assessment module (2) receives data from the environment perception module and assesses the risks that the vehicle may face during driving; the path planning module (3) plans a safe and reasonable driving path based on the risk assessment result and the vehicle's current position and destination information; the decision planning module (4) selects a suitable risk avoidance strategy based on the risk assessment and path planning results; the vehicle control module (5) receives instructions from the decision planning module and accurately controls the steering, acceleration and braking of the vehicle; and the communication and interaction module (6) realizes communication and interaction functions between the vehicle and other vehicles, road infrastructure and the driver.

6. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 1 is characterized by: The sensor data acquisition module (10) is responsible for collecting data output by laser radar, millimeter wave radar and camera sensors. The multimodal sensor fusion enhancement module (11) performs fusion processing on data from different sensors. The data preprocessing module (12) is used to preprocess the fused sensor data, including filtering, denoising and calibration operations. The dangerous target detection module (13) identifies target objects that may pose a threat to the driving safety of the vehicle based on the data provided by the environmental perception module. The collision risk assessment module (14) calculates the possibility and time of a collision between the two and assesses the severity of the collision. The rollover risk assessment module (15) is used to determine the risk of the vehicle rolling over during driving. The road deviation risk assessment module (16) is used to assess the impact of road deviation on driving safety. The dynamic risk monitoring module (17) monitors changes in dangerous conditions during vehicle driving in real time.

7. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 2 is characterized by: The target path generation module (18) is used to generate an initial driving target path, the obstacle avoidance path planning module (19) is used to plan a specific path to avoid obstacles, the path optimization algorithm module (20) uses the Dijkstra algorithm to optimize the generated path, the emergency lane and special channel utilization planning module (21) is used to evaluate whether the emergency lane or other special channels can be used to achieve faster risk avoidance or passage, and the dynamic path adjustment module (22) is used to dynamically adjust the planned path according to real-time changing environmental information, vehicle status and risk assessment results.

8. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 3 is characterized by: The hedging strategy selection module (23) is used to select the most suitable strategy for the current situation from a plurality of preset hedging strategies; the decision execution module (24) is used to convert the selected hedging strategy into specific operation instructions; the decision execution monitoring module (25) is used to monitor the execution process of the decision in real time; and the decision record optimization module (26) is used to record the relevant information of each decision and optimize and improve the decision algorithm and strategy.

9. The intelligent automobile path tracking system for emergency avoidance of danger according to claim 4 is characterized by: The steering control module (27) is used to accurately control the steering angle of the vehicle, the acceleration control module (28) is used to control the acceleration of the vehicle, the braking control module (29) is used to control the braking system of the vehicle, the vehicle stability control module (30) is used to control the suspension system and wheel torque distribution mode of the vehicle to maintain the stability of the vehicle, and the control instruction execution (31) receives instructions and accurately transmits them to the vehicle's actuator.

10. The intelligent vehicle path tracking system for emergency avoidance of danger according to claim 4 is characterized by: The vehicle-to-vehicle communication module (32) is used to exchange vehicle position, speed, and driving direction information in real time; the vehicle-to-road communication module (33) is used to obtain traffic light status, road construction information, and road condition information; the human-machine interaction module (34) implements human-machine collaborative control to improve the driver's understanding of the vehicle's driving status and the ability to respond to dangerous situations; the remote monitoring and emergency rescue interaction module (35) communicates with a remote monitoring center or an emergency rescue agency; and the data transmission and communication protocol module (36) is responsible for data transmission between various modules within the system and between the system and external devices, ensuring the stability and reliability of data transmission.

Images