A vehicle safety control method and apparatus

Abstract

This invention discloses a vehicle safety control method and apparatus. The method includes detecting whether a collision or speeding is possible based on vehicle information, road information, and obstacle information provided by an information acquisition unit, using a judgment and decision-making method or a deep learning decision-making method in an intelligent decision-making unit. If the intelligent decision-making unit detects a potential collision or speeding, an execution unit implements a collision avoidance speed limit strategy or a warning strategy for the vehicle. This invention uses two decision-making methods to implement warning strategies or collision avoidance speed limit strategies for the driver's actions of accidentally accelerating rapidly or continuously accelerating, thereby preventing accidents.

Description

Technical Field

[0001] This invention relates to the field of vehicle safety technology, and in particular to a vehicle safety control method and device. Background Technology

[0002] Currently, with the continuous improvement of people's living standards and the rapid growth of car ownership, more and more people are choosing to travel by car. For a long time, accidents caused by drivers accidentally pressing the accelerator have been frequent. Even during normal driving, there are instances where drivers accidentally press the accelerator or continuously accelerate, causing the vehicle speed to exceed the maximum speed limit on the road; this can lead to quite serious accidents, causing not only significant economic losses but also injuries or fatalities. Summary of the Invention

[0003] The purpose of this invention is to provide a vehicle safety control method and device that uses two decision-making methods to implement a warning strategy or a collision avoidance speed limit strategy for the driver's mistaken acceleration by pressing the accelerator or continuous acceleration, so as to avoid accidents.

[0004] To achieve the above objectives, the present invention provides a vehicle safety control method, the method comprising:

[0005] Based on the vehicle information, road information, and obstacle information provided by the information acquisition unit, the system uses the judgment and decision-making methods or deep learning decision-making methods in the intelligent decision-making unit to detect whether the vehicle may collide or exceed the speed limit.

[0006] If the intelligent decision-making unit detects that a collision may occur or that the vehicle is speeding, it will use the execution unit to implement a collision avoidance speed limit strategy or a warning strategy for the vehicle.

[0007] Furthermore, the information acquisition unit includes an environmental perception unit, an obstacle information acquisition unit, and a vehicle information acquisition unit;

[0008] The environmental perception unit determines and acquires the road information based on a high-definition map of the current vehicle driving environment;

[0009] The vehicle information acquisition unit acquires the vehicle information based on the vehicle's own sensors;

[0010] The obstacle information acquisition unit acquires obstacle information based on the sensing devices on the vehicle.

[0011] Furthermore, the vehicle information includes: accelerator pedal depth, vehicle speed, vehicle acceleration, steering wheel rotation angle, and accelerator pedal depressing rate;

[0012] The road information includes: number of lanes, road speed limit information, gradient information, and road curvature;

[0013] The obstacle information includes: the relative distance between the vehicle and the obstacle, the type of obstacle, the volume of the obstacle, the speed of the obstacle, and the acceleration of the obstacle.

[0014] Furthermore, the intelligent decision-making unit uses a judgment and decision-making method to detect whether a collision or speeding is possible, including:

[0015] Step P1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit;

[0016] Step P2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the relative distance between the vehicle and the obstacle is less than the threshold OD.

[0017] If the relative distance between the vehicle and the obstacle is less than the threshold OD, then the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle.

[0018] If the relative distance between the vehicle and the obstacle is not less than the threshold OD, the intelligent decision-making unit determines whether the accelerator pedal depth is greater than the threshold THR1; where...

[0019] When the accelerator pedal depth is greater than the threshold THR1, the intelligent decision unit determines whether the accelerator pedal depth is greater than the threshold THR2.

[0020] When the accelerator pedal depth is not greater than the threshold THR1, the intelligent decision unit determines whether the vehicle speed exceeds the maximum speed limit of the road.

[0021] If the vehicle is not speeding, return to step 1;

[0022] If a vehicle exceeds the speed limit and the speeding time exceeds the first threshold, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle.

[0023] If a vehicle exceeds the speed limit but the speeding time does not exceed the first threshold, the execution unit will be used to implement a warning strategy for the vehicle.

[0024] Furthermore, when the accelerator pedal depth exceeds the threshold THR1, the intelligent decision-making unit determines whether the accelerator pedal depth exceeds the threshold THR2, including:

[0025] If the accelerator pedal depth is greater than the threshold THR2, the execution unit will be used to implement a collision avoidance speed limiting strategy for the vehicle.

[0026] If the accelerator pedal depth is not greater than the threshold THR2, the intelligent decision unit determines whether the accelerator pedal pressing time exceeds the threshold TTC.

[0027] When the accelerator pedal is depressed for a duration exceeding the threshold TTC, the execution unit is used to implement a collision avoidance speed limiting strategy for the vehicle.

[0028] If the accelerator pedal is depressed for no more than the threshold TTC, the intelligent decision-making unit determines whether the vehicle is speeding based on the maximum speed limit on the road; whereby...

[0029] If the vehicle is not speeding, return to step 1;

[0030] If a vehicle exceeds the speed limit and the speeding time exceeds the first threshold, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle.

[0031] If a vehicle exceeds the speed limit but the speeding time does not exceed the first threshold, the execution unit will be used to implement a warning strategy for the vehicle.

[0032] Furthermore, the deep learning decision-making method in the intelligent decision-making unit is used to detect whether a collision or speeding is possible, including...

[0033] The intelligent decision-making unit inputs the received vehicle information, road information, and obstacle information into the deep learning network, outputs the probability value of the vehicle colliding with the obstacle and the speeding danger value of the vehicle, and determines whether the vehicle may collide or exceed the speed limit.

[0034] Furthermore, the deep learning decision-making method in the intelligent decision-making unit determines whether a collision or speeding is possible, including:

[0035] Step D1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit;

[0036] Step D2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1.

[0037] If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T1, the intelligent decision unit then determines whether the speeding hazard of the vehicle exceeds the threshold OS_T1.

[0038] If the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1, the intelligent decision-making unit then determines whether the probability of a collision between the vehicle and the obstacle exceeds the threshold CC_T2; whereby...

[0039] When the probability of a vehicle colliding with an obstacle exceeds the threshold CC_T2, the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle.

[0040] If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T2, the execution unit will be used to implement a warning strategy for the vehicle.

[0041] Furthermore, if the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T1, the intelligent decision-making unit determines whether the vehicle's speeding hazard exceeds the threshold OS_T1, including:

[0042] If the speeding hazard of the vehicle does not exceed the threshold OS_T1, return to step D1;

[0043] When the speeding hazard of a vehicle exceeds the threshold OS_T1, the intelligent decision unit determines whether the speeding hazard exceeds the threshold OS_T2:

[0044] If the speeding risk of a vehicle exceeds the threshold OS_T2, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle.

[0045] If the speeding risk of the vehicle does not exceed the threshold OS_T2, then the execution unit will be used to implement a warning strategy for the vehicle.

[0046] Furthermore, the warning strategy includes: a voice device broadcasting a warning message, steering wheel vibration, and seatbelt tightening;

[0047] The collision avoidance speed limiting strategy includes: cutting off the acceleration request from the vehicle to the ESP and sending a request for appropriate deceleration, so that the ESP controls the power control device to decelerate the vehicle.

[0048] Based on a unified inventive concept, the present invention also provides a vehicle safety control device, including an information acquisition unit, an intelligent decision-making unit, and an execution unit.

[0049] The information acquisition unit is used to acquire vehicle information, road information, and obstacle information;

[0050] The intelligent decision-making unit is used to detect whether a vehicle may collide or speed based on vehicle information, road information, and obstacle information, using a judgment decision-making method or a deep learning decision-making method.

[0051] The execution unit is used to implement collision avoidance speed limit strategy or warning strategy for the vehicle when a collision may occur or the vehicle is speeding.

[0052] The technical effects and advantages of this invention are as follows: This invention addresses two situations (① the relative distance between the vehicle and the obstacle is less than the safe distance, ② continuous acceleration on the road exceeding the maximum speed limit) by implementing warning or collision avoidance speed limiting strategies to prevent accidents and improve the personal safety of the driver.

[0053] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart illustrating the steps of a vehicle safety control method according to an embodiment of the present invention;

[0056] Figure 2 This is a flowchart of the decision-making method in an embodiment of the present invention;

[0057] Figure 3 This is a flowchart of the deep learning decision-making method in an embodiment of the present invention;

[0058] Figure 4 This is a schematic diagram of the structure of a vehicle safety control device according to an embodiment of the present invention. Detailed Implementation

[0059] 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 only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] To address the shortcomings of existing technologies, embodiments of the present invention disclose a vehicle safety control method, such as... Figure 1 As shown, it includes:

[0061] When the driver is detected pressing the accelerator to control the vehicle to accelerate, the intelligent decision-making unit uses the judgment and decision-making methods or deep learning decision-making methods in the intelligent decision-making unit to detect whether the vehicle may collide or exceed the speed limit, based on the vehicle information, road information and obstacle information provided by the information acquisition unit;

[0062] If the intelligent decision-making unit detects that a collision may occur or that the vehicle is speeding, it will use the execution unit to implement collision avoidance speed limit strategies or warning strategies to avoid accidents.

[0063] In some specific embodiments, the information acquisition unit includes an environmental perception unit, an obstacle information acquisition unit, and a vehicle information acquisition unit;

[0064] The vehicle information acquisition unit acquires vehicle information based on the vehicle's own sensors; the vehicle information includes: accelerator pedal depth, vehicle speed, vehicle acceleration, steering wheel rotation angle, accelerator pedal depressing rate, etc.

[0065] The environmental perception unit determines and acquires road information based on a high-definition map of the current vehicle driving environment; the road information includes: number of lanes, road speed limit information, slope information, and road curvature.

[0066] The obstacle information acquisition unit acquires obstacle information based on the vehicle's sensing devices (such as a forward-facing camera, millimeter-wave radar, etc.); the obstacle information includes: the relative distance between the vehicle and the obstacle, the obstacle type, the obstacle volume, the obstacle speed, and the obstacle acceleration.

[0067] In some specific embodiments, the intelligent decision-making unit uses a judgment and decision-making method to detect whether a collision or speeding is possible, such as... Figure 2 As shown, it includes the following steps:

[0068] Step P1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit;

[0069] Step P2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the relative distance between the vehicle and the obstacle is less than the threshold OD.

[0070] ①If the relative distance between the vehicle and the obstacle is less than the threshold OD, then the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle;

[0071] ② If the relative distance between the vehicle and the obstacle is not less than the threshold OD, the intelligent decision-making unit determines whether the accelerator pedal depth is greater than the threshold THR1; wherein,

[0072] When the accelerator pedal depth is greater than the threshold THR1, the intelligent decision unit determines whether the accelerator pedal depth is greater than the threshold THR2.

[0073] When the accelerator pedal depth is not greater than the threshold THR1, the intelligent decision unit determines whether the vehicle speed exceeds the maximum speed limit of the road.

[0074] If the vehicle is not speeding, return to step 1; if the vehicle is speeding and the speeding time is greater than the first threshold (e.g., 5 seconds), then use the execution unit to implement a collision avoidance speed limit strategy for the vehicle; if the vehicle is speeding but the speeding time is not greater than the first threshold (e.g., 5 seconds), then use the execution unit to implement a warning strategy for the vehicle.

[0075] In some specific embodiments, when the accelerator pedal depth is greater than the threshold THR1, the intelligent decision unit determines whether the accelerator pedal depth is greater than the threshold THR2, including:

[0076] ①If the accelerator pedal depth is greater than the threshold THR2, then the execution unit is used to implement a collision avoidance speed limiting strategy for the vehicle;

[0077] ②If the accelerator pedal depth is not greater than the threshold THR2, the intelligent decision unit determines whether the accelerator pedal pressing time exceeds the threshold TTC:

[0078] When the accelerator pedal is depressed for a duration exceeding the threshold TTC, the execution unit is used to implement a collision avoidance speed limiting strategy for the vehicle.

[0079] If the accelerator pedal is depressed for no more than the threshold TTC, the intelligent decision-making unit determines whether the vehicle is speeding based on the maximum speed limit on the road; whereby...

[0080] If the vehicle is not speeding, return to step 1; if the vehicle is speeding and the speeding time is greater than the first threshold (e.g., 5 seconds), then use the execution unit to implement a collision avoidance speed limit strategy for the vehicle; if the vehicle is speeding but the speeding time is not greater than the first threshold (e.g., 5 seconds), then use the execution unit to implement a warning strategy for the vehicle.

[0081] In some specific embodiments, the deep learning decision-making method in the intelligent decision-making unit is used to detect whether a collision or speeding is possible, including...

[0082] The intelligent decision-making unit inputs the received vehicle information, road information, and obstacle information into the deep learning network, outputs the probability value of the vehicle colliding with the obstacle and the speeding danger value of the vehicle, and determines whether the vehicle may collide or exceed the speed limit.

[0083] The parameters in the deep learning network can be optimized based on the driver's driving habits and specific road conditions.

[0084] In some specific embodiments, the deep learning decision-making method in the intelligent decision-making unit is used to determine whether a collision or speeding is possible, such as... Figure 3 As shown, it includes:

[0085] Step D1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit;

[0086] Step D2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1.

[0087] ①If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T1, the intelligent decision unit then determines whether the speeding risk of the vehicle exceeds the threshold OS_T1.

[0088] If the speeding hazard of the vehicle does not exceed the threshold OS_T1, return to step D1;

[0089] When the speeding hazard of a vehicle exceeds the threshold OS_T1, the intelligent decision unit determines whether the speeding hazard exceeds the threshold OS_T2:

[0090] If the speeding risk of a vehicle exceeds the threshold OS_T2, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle.

[0091] If the speeding risk of the vehicle does not exceed the threshold OS_T2, then the execution unit will be used to implement a warning strategy for the vehicle.

[0092] ② If the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1, the intelligent decision-making unit determines whether the probability of a collision between the vehicle and the obstacle exceeds the threshold CC_T2; wherein,

[0093] When the probability of a vehicle colliding with an obstacle exceeds the threshold CC_T2, the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle.

[0094] If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T2, the execution unit will be used to implement a warning strategy for the vehicle.

[0095] In some specific embodiments, determining whether a vehicle is likely to collide with an obstacle can be aided by auxiliary information such as accelerator pedal speed, obstacle speed, and obstacle acceleration; determining whether speeding is in progress can be aided by auxiliary information such as steering wheel rotation angle, turn signals, and road lane information.

[0096] In some specific embodiments, the warning strategy includes: a voice device broadcasting a warning message, steering wheel vibration, and seat belt tightening;

[0097] The collision avoidance speed limiting strategy includes: cutting off the vehicle's acceleration request to the ESP (Electronic Stability Program) and sending an appropriate deceleration request, so that the ESP controls the power control device to decelerate the vehicle.

[0098] Based on the same inventive concept, embodiments of the present invention also provide a vehicle safety control device, such as... Figure 4 As shown, it includes an information acquisition unit, an intelligent decision-making unit, and an execution unit.

[0099] The information acquisition unit is used to acquire vehicle information, road information, and obstacle information;

[0100] The intelligent decision-making unit is used to detect whether a vehicle may collide or speed based on vehicle information, road information, and obstacle information, using a judgment decision-making method or a deep learning decision-making method.

[0101] The execution unit is used to implement collision avoidance speed limit strategy or warning strategy for the vehicle when a collision may occur or the vehicle is speeding.

[0102] This invention addresses two scenarios (① the relative distance between the vehicle and an obstacle is less than the safe distance, ② continuous acceleration on the road exceeding the maximum speed limit) by implementing warning or collision avoidance speed limiting strategies to prevent accidents and improve driver safety.

[0103] Regarding the apparatus in the above embodiments, the specific manner in which each unit module performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0104] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A vehicle safety control method characterized by, The method includes: Based on the vehicle information, road information, and obstacle information provided by the information acquisition unit, the system uses the judgment and decision-making methods or deep learning decision-making methods in the intelligent decision-making unit to detect whether the vehicle may collide or exceed the speed limit. If the intelligent decision-making unit detects that a collision may occur or that the vehicle is speeding, it will use the execution unit to implement a collision avoidance speed limit strategy or a warning strategy for the vehicle. The vehicle information includes: accelerator pedal depth, vehicle speed, vehicle acceleration, steering wheel rotation angle, and accelerator pedal depress rate; The road information includes: number of lanes, road speed limit information, gradient information, and road curvature; The obstacle information includes: the relative distance between the vehicle and the obstacle, the type of obstacle, the volume of the obstacle, the speed of the obstacle, and the acceleration of the obstacle; The intelligent decision-making unit uses a judgment and decision-making method to detect whether a vehicle may collide or exceed the speed limit, including: Step P1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit; Step P2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the relative distance between the vehicle and the obstacle is less than the threshold OD. If the relative distance between the vehicle and the obstacle is less than the threshold OD, then the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle. If the relative distance between the vehicle and the obstacle is not less than the threshold OD, the intelligent decision-making unit determines whether the accelerator pedal depth is greater than the threshold THR1; where... When the accelerator pedal depth is greater than the threshold THR1, the intelligent decision unit determines whether the accelerator pedal depth is greater than the threshold THR2. When the accelerator pedal depth is not greater than the threshold THR1, the intelligent decision unit determines whether the vehicle speed exceeds the maximum speed limit of the road. If the vehicle is not speeding, return to step P1; If a vehicle exceeds the speed limit and the speeding time exceeds the first threshold, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle. If a vehicle exceeds the speed limit but the speeding time does not exceed the first threshold, the execution unit will be used to implement a warning strategy for the vehicle. The warning strategy includes: a voice device broadcasting a warning message, steering wheel vibration, and seat belt tightening; The collision avoidance speed limiting strategy includes: cutting off the acceleration request from the vehicle to the ESP and sending a request for appropriate deceleration, so that the ESP controls the power control device to decelerate the vehicle.

2. The vehicle safety control method according to claim 1, characterized in that, The information acquisition unit includes an environmental perception unit, an obstacle information acquisition unit, and a vehicle information acquisition unit; The environmental perception unit determines and acquires the road information based on a high-definition map of the current vehicle driving environment; The vehicle information acquisition unit acquires the vehicle information based on the vehicle's own sensors; The obstacle information acquisition unit acquires obstacle information based on the sensing devices on the vehicle.

3. The vehicle safety control method according to claim 1, characterized in that, When the accelerator pedal depth exceeds the threshold THR1, the intelligent decision unit then determines whether the accelerator pedal depth exceeds the threshold THR2, including: If the accelerator pedal depth is greater than the threshold THR2, the execution unit will be used to implement a collision avoidance speed limiting strategy for the vehicle. If the accelerator pedal depth is not greater than the threshold THR2, the intelligent decision unit determines whether the accelerator pedal pressing time exceeds the threshold TTC. When the accelerator pedal is depressed for a duration exceeding the threshold TTC, the execution unit is used to implement a collision avoidance speed limiting strategy for the vehicle. If the accelerator pedal is depressed for no more than the threshold TTC, the intelligent decision-making unit determines whether the vehicle is speeding based on the maximum speed limit on the road; whereby... If the vehicle is not speeding, return to step P1; If a vehicle exceeds the speed limit and the speeding time exceeds the first threshold, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle. If a vehicle exceeds the speed limit but the speeding time does not exceed the first threshold, the execution unit will be used to implement a warning strategy for the vehicle.

4. The vehicle safety control method according to claim 1, characterized in that, The intelligent decision-making unit uses deep learning decision-making methods to detect whether a vehicle may collide or exceed speed limits, including... The intelligent decision-making unit inputs the received vehicle information, road information, and obstacle information into the deep learning network, outputs the probability value of the vehicle colliding with the obstacle and the speeding danger value of the vehicle, and determines whether the vehicle may collide or exceed the speed limit.

5. A vehicle safety control method according to claim 4, characterized in that, The intelligent decision-making unit uses a deep learning decision-making method to determine whether a vehicle is likely to collide or exceed the speed limit, including: Step D1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit; Step D2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1. If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T1, the intelligent decision unit then determines whether the speeding hazard of the vehicle exceeds the threshold OS_T1. If the probability of a collision between the vehicle and an obstacle exceeds the threshold CC_T1, the intelligent decision-making unit then determines whether the probability of a collision between the vehicle and the obstacle exceeds the threshold CC_T2; whereby... When the probability of a vehicle colliding with an obstacle exceeds the threshold CC_T2, the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle. If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T2, the execution unit will be used to implement a warning strategy for the vehicle.

6. A vehicle safety control method according to claim 5, characterized in that, If the probability of a collision between the vehicle and an obstacle does not exceed the threshold CC_T1, the intelligent decision-making unit then determines whether the vehicle's speeding hazard exceeds the threshold OS_T1, including: If the speeding hazard of the vehicle does not exceed the threshold OS_T1, return to step D1; When the speeding hazard of a vehicle exceeds the threshold OS_T1, the intelligent decision unit determines whether the speeding hazard exceeds the threshold OS_T2: If the speeding risk of a vehicle exceeds the threshold OS_T2, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle. If the speeding risk of the vehicle does not exceed the threshold OS_T2, then the execution unit will be used to implement a warning strategy for the vehicle.

7. A vehicle safety control device, characterized in that, It includes an information acquisition unit, an intelligent decision-making unit, and an execution unit. The information acquisition unit is used to acquire vehicle information, road information, and obstacle information; The intelligent decision-making unit is used to detect whether a vehicle may collide or speed based on vehicle information, road information, and obstacle information, using a judgment decision-making method or a deep learning decision-making method. The execution unit is used to execute a collision avoidance speed limit strategy or a warning strategy for the vehicle when a collision may occur or the vehicle is speeding. The vehicle information includes: accelerator pedal depth, vehicle speed, vehicle acceleration, steering wheel rotation angle, and accelerator pedal depress rate; The road information includes: number of lanes, road speed limit information, gradient information, and road curvature; The obstacle information includes: the relative distance between the vehicle and the obstacle, the type of obstacle, the volume of the obstacle, the speed of the obstacle, and the acceleration of the obstacle; The intelligent decision-making unit uses a judgment and decision-making method to detect whether a vehicle may collide or exceed the speed limit, including: Step P1: Obtain vehicle information, road information, and obstacle information from the information acquisition unit; Step P2: When the driver is detected pressing the accelerator, the intelligent decision-making unit is triggered to determine whether the relative distance between the vehicle and the obstacle is less than the threshold OD. If the relative distance between the vehicle and the obstacle is less than the threshold OD, then the execution unit is used to implement a collision avoidance speed limit strategy for the vehicle. If the relative distance between the vehicle and the obstacle is not less than the threshold OD, the intelligent decision-making unit determines whether the accelerator pedal depth is greater than the threshold THR1; where... When the accelerator pedal depth is greater than the threshold THR1, the intelligent decision unit determines whether the accelerator pedal depth is greater than the threshold THR2. When the accelerator pedal depth is not greater than the threshold THR1, the intelligent decision unit determines whether the vehicle speed exceeds the maximum speed limit of the road. If the vehicle is not speeding, return to step P1; If a vehicle exceeds the speed limit and the speeding time exceeds the first threshold, the execution unit will be used to implement a collision avoidance speed limit strategy for the vehicle. If a vehicle exceeds the speed limit but the speeding time does not exceed the first threshold, the execution unit will be used to implement a warning strategy for the vehicle. The warning strategy includes: a voice device broadcasting a warning message, steering wheel vibration, and seat belt tightening; The collision avoidance speed limiting strategy includes: cutting off the acceleration request from the vehicle to the ESP and sending a request for appropriate deceleration, so that the ESP controls the power control device to decelerate the vehicle.

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