AEB-P system based on vehicle operating condition variable control strategy

Abstract

The application discloses an AEB-P system based on a variable control strategy of a vehicle working condition, acquires vehicle surrounding environment and pedestrian information through an information perception module, matches and fuses the surrounding environment and pedestrian information through a data fusion module to obtain pedestrian data in front of the vehicle, judges the driving condition of the current vehicle through a driving condition judgment module, receives the driving condition of the vehicle and the pedestrian data in front of the vehicle through a control strategy calculation module, outputs a TTC classification threshold according to the pedestrian data in front of the vehicle and the driving condition, calculates a TTC value according to the TTC classification threshold and the pedestrian data in front of the vehicle through a risk assessment decision module, and decides the current risk level, and executes control on the vehicle according to the current risk level through a control execution module. The trigger threshold of the AEB-P system of the application changes continuously according to the current driving state of the vehicle, can effectively avoid the situation that the AEB-P system is invalid under some driving states of a fixed threshold, simultaneously evaluates and corrects the trigger threshold, guarantees the effectiveness of the AEB-P system, and reduces the interference of the AEB-P system on the driver.

Description

Technical Field

[0001] This invention belongs to the field of advanced driver assistance technology for vehicle active safety. More specifically, this invention relates to an AEB-P system based on a variable vehicle operating condition control strategy. Background Technology

[0002] With the development of intelligent vehicles, many automakers have begun to equip their vehicles with Autonomous Emergency Braking System (AEB-P). The AEB-P system uses onboard sensors to detect objects ahead and predicts the degree of collision risk based on internal algorithms. When a collision is deemed possible, the system warns the driver through images and sounds to take evasive action. If the collision risk threshold is reached and the driver has not reacted correctly, the system will actively brake the vehicle to avoid a collision or reduce collision damage. However, research indicates that vehicles equipped with AEB-P cannot completely avoid collisions.

[0003] Research on AEB-P systems for pedestrians mainly involves two issues: first, how to quickly and accurately identify and track pedestrians; and second, how to achieve reasonable and efficient safety assessment and decision-making. With the development of sensing technology, artificial intelligence, and improved computer processing capabilities, the first issue has gradually been resolved. Currently, active emergency braking safety assessment methods are mainly divided into safe distance strategies and Time-to-Collision (TTC) models, relying on safe distance and collision time parameters respectively. The calibration of decision parameter thresholds usually relies on experiments. The inherent drawback of this method is that it makes the system less robust, and its implementation and application are rather cumbersome. Therefore, how to comprehensively consider both pedestrian safety and active safety execution efficiency to conduct a safety assessment of the driving environment and make collision avoidance decisions is the key challenge of the second issue.

[0004] Compared to other safety assessment models, the TTC model has advantages such as fewer output parameters, shorter computation time, and a more balanced linear relationship as vehicle speed increases upon triggering compared to other strategies. Currently, most AEB-P systems use the TTC model as a risk assessment index. AEB-P systems using the TTC model identify hazards by calculating the TTC value in real time. After comparing the TTC value with a pre-defined TTC warning threshold, the pedestrian risk is classified into different levels. Different risk levels correspond to different braking strategies. The brakes receive the braking strategy signal from the AEB-P system and make corresponding controls to achieve the braking effect. The TTC threshold, as a decision parameter of the AEB-P system, determines the timing of system triggering and is the highest decision-making level of the AEB-P system. The setting of the TTC threshold determines the final pedestrian collision avoidance result of the AEB-P system. Currently, most TTC thresholds are based on fixed values ​​calibrated in experiments. In reality, vehicle operating conditions and road environments vary. If a predetermined TTC warning threshold is always used to measure safety, the warning results may be inaccurate. Therefore, a TTC threshold that can adapt to different vehicle driving conditions is needed as the basis for AEB-P system decision-making and control. Summary of the Invention

[0005] The purpose of this invention is to propose an AEB-P system based on a vehicle operating condition variable control strategy. The trigger threshold of the AEB-P system can be continuously changed according to the current driving state of the vehicle, which can effectively avoid the failure of the AEB-P system due to certain driving states under a fixed threshold. At the same time, the trigger threshold is evaluated and corrected, so as to reduce the interference of the AEB-P system to the driver while ensuring the effectiveness of the AEB-P system.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] An AEB-P system based on a vehicle operating condition variable control strategy includes:

[0008] Information sensing module, which acquires information about the vehicle's surrounding environment and pedestrians;

[0009] The data fusion module receives surrounding environment and pedestrian information collected by the information perception module, and matches and fuses the surrounding environment and pedestrian information to obtain pedestrian data in front of the vehicle.

[0010] The driving condition judgment module obtains the vehicle's driving speed and maximum deceleration; and judges the current driving condition of the vehicle based on the driving speed and maximum deceleration.

[0011] The control strategy calculation module receives vehicle driving conditions and pedestrian data in front of the vehicle; it outputs a TTC (Traffic Troubleshooting) classification threshold based on the pedestrian data and driving conditions; the method for obtaining the TTC classification threshold is as follows:

[0012] S1. Calculate the shortest braking TTC threshold corresponding to different driving conditions based on the vehicle's driving conditions.

[0013] S2. Based on the shortest braking TTC threshold, calculate the current braking distance and compare it with the braking distance threshold. If the braking distance is less than the braking distance threshold, the current vehicle driving braking section is divided into a normal braking section; otherwise, the braking section is divided into a long braking section.

[0014] S3. Set the corresponding TTC classification threshold according to the type of braking range and the current driving conditions; if it is in the normal braking range, set the TTC classification threshold to level 2; if it is in the long braking range, set the TTC classification threshold to level 3.

[0015] The risk assessment and decision-making module receives the TTC classification threshold and pedestrian data in front of the vehicle; it calculates the TTC value based on the TTC classification threshold and pedestrian data in front of the vehicle, and compares the calculated TTC value with the TTC classification threshold to determine the current risk level.

[0016] The control execution module receives the current risk level determined by the risk assessment and decision-making module and then executes control on the vehicle.

[0017] Furthermore, if the vehicle is in the normal braking range and traveling at a constant speed, the TTC classification thresholds include the warning TTC threshold and the full braking TTC threshold, calculated as follows:

[0018]

[0019]

[0020] If the vehicle is in the normal braking range and the acceleration is not zero, the TTC classification thresholds include the warning TTC threshold and the full braking TTC threshold, and the calculation formula is as follows:

[0021]

[0022]

[0023] Among them, TTC n1 To provide early warning of TTC thresholds, TTC n2 For full braking, the TTC threshold is given, where v1 represents the vehicle speed, v2 represents the pedestrian's longitudinal velocity, and a maxa represents the maximum achievable deceleration at present. n t2 represents the vehicle's current acceleration, d represents the safe distance between the vehicle and the pedestrian, t3 represents the system delay, and Δt is a fixed value.

[0024] If the vehicle is in a long braking range and traveling at a constant speed, the TTC (Traction Control) grading thresholds include the warning TTC threshold, the partial braking TTC threshold, and the full braking TTC threshold. The calculation formula is as follows:

[0025]

[0026]

[0027]

[0028] If the vehicle is in a long braking range and the acceleration is not zero, the TTC classification threshold includes TTC. l1 TTC l2 and TTC l3 The calculation formula is as follows:

[0029]

[0030]

[0031]

[0032] Among them, TTC l1 For early warning TTC threshold, TTC l2 For partial braking TTC threshold, TTC l3 For full braking, the TTC threshold is given, where v1 represents the vehicle speed, v2 represents the pedestrian's longitudinal velocity, and a max a represents the maximum achievable deceleration at present. n t1 represents the vehicle's current acceleration, d represents the safe distance between the vehicle and the pedestrian, t2 represents the system delay, t3 represents the deceleration increase time, Δt is a fixed value, and k is the driver comfort adjustment coefficient.

[0033] Furthermore, the driver comfort adjustment coefficient k is expressed as:

[0034]

[0035] In the formula, v1 is the vehicle speed and d0 is the safe distance.

[0036] Furthermore, the method for determining the risk level of the current vehicle's driving within the risk assessment decision module is as follows:

[0037] S1. Calculate the current TTC value;

[0038] S2. Under different braking zone types, different risk levels are classified according to the relationship between the current TTC value and the TTC classification threshold;

[0039] When the vehicle is operating within the normal braking range, the current TTC value is greater than the TTC. n1 The risk level is Level 1; the current TTC value is less than the TTC. n1 And greater than TTC n2 The risk level is Level 2, which is the collision warning zone; the current TTC value is less than the TTC. n2 The risk level is currently at level four.

[0040] When the vehicle is operating in a long braking range, the current TTC value is greater than the TTC. l1 The risk level is Level 1; the current TTC value is less than the TTC. l1 And greater than TTC l2 The risk level is Level 2; the current TTC value is less than the TTC. l2 And greater than TTC l3 The risk level is currently level three; the current TTC value is less than the TTC. l3 The risk level is level four.

[0041] Furthermore, when the pedestrian risk level reaches level three or four, the calculation of the TTC threshold will automatically stop, and the shortest braking TTC threshold obtained at the moment will be saved as a fixed trigger threshold until the dangerous state is eliminated.

[0042] Furthermore, different risk levels correspond to different signal values, and AEB-P sends the signal values ​​to the control execution module.

[0043] Furthermore, when the risk level is one, two, or three, once the driver makes a braking operation, AEB-P will exit the risk level and transfer driving control to the driver; when the risk level is four, even if the driver makes an operation, the AEB-P system will continue to apply full braking force to achieve the maximum braking force currently achievable.

[0044] Furthermore, the vehicle execution control module performs corresponding control on the vehicle based on the signal value sent by AEB-P, realizing vehicle deceleration, braking and alarm operations.

[0045] Furthermore, the information perception module acquires information about the vehicle's external environment and pedestrians in front of the vehicle through onboard camera sensors and millimeter-wave radar sensors.

[0046] Furthermore, the vehicle execution module includes an audible and visual alarm, an LED display, a brake-by-wire system, an electronic stability system (ESC), and an engine (EMS) or motor controller.

[0047] Beneficial effects

[0048] 1. The AEB-P system using variable TTC threshold control can select the most appropriate trigger threshold according to different vehicle operating conditions, which solves the problem of system failure and collision caused by excessive braking distance at high vehicle speed and low maximum deceleration, and minimizes the occurrence of accidents caused by driver distraction or untimely reaction.

[0049] 2. Compared to the traditional AEB-P system which uses a fixed threshold triggering control method, the variable TTC threshold control method based on vehicle operating conditions can select the optimal TTC threshold to control the AEB-P system under different operating conditions. This achieves the characteristics of reasonable triggering timing, less interference to the driver, and improved collision avoidance rate in certain situations, thus better meeting the trade-off between safety and comfort in the AEB-P system.

[0050] The purpose of this invention is to propose an AEB-P system based on a vehicle operating condition variable control strategy. The trigger threshold of the AEB-P system can be continuously calculated based on the vehicle's driving state to obtain the optimal TTC threshold. This can effectively avoid the failure of the AEB-P system due to certain driving states under a fixed threshold. At the same time, the obtained TTC trigger threshold is evaluated and corrected, thereby reducing the interference of the AEB-P system on the driver while ensuring the effectiveness of the AEB-P system. Attached Figure Description

[0051] Figure 1 This is a block diagram of an AEB-P system based on a variable vehicle operating condition control strategy according to the present invention.

[0052] Figure 2 This is a schematic diagram illustrating the risk level classification of the present invention;

[0053] Figure 3 This is a schematic diagram of the judgment process of the AEB-P system based on the variable vehicle operating condition control strategy of the present invention;

[0054] Figure 4 This is a schematic diagram illustrating the signal values ​​emitted by AEB-P under different risk levels within the normal braking range.

[0055] Figure 5 This is a schematic diagram showing the signal values ​​emitted by AEB-P under different risk levels within the long braking range. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0057] This invention relates to the fields of advanced driver assistance systems (ADAS), automatic emergency pedestrian braking systems (AEB-P), multi-sensor fusion, and multi-level control strategies for AEB-P systems. Addressing the problem that current AEB-P systems fail under certain conditions and cannot effectively avoid pedestrian collisions, this invention proposes an AEB-P system based on a variable control strategy for vehicle operating conditions. It also introduces a minimum braking TTC threshold and a driving comfort adjustment coefficient, allowing the activation threshold of the AEB-P system to be continuously adjusted to the optimal threshold according to the current operating conditions. This ensures that the activation timing of the AEB-P system fully considers driver comfort while guaranteeing pedestrian safety, reducing interference with the driver and improving the overall comfort of the AEB-P system.

[0058] Combined with appendix Figure 1 The system shown in this invention is an AEB-P system based on a vehicle operating condition variable control strategy; the system includes:

[0059] The information perception module uses onboard sensors to acquire information about the surrounding environment and pedestrians.

[0060] The data fusion module receives surrounding environment and pedestrian information collected by the information perception module, and matches and fuses the surrounding environment and pedestrian information to obtain more accurate pedestrian data in front of the vehicle.

[0061] The driving condition judgment module obtains the vehicle's driving speed and maximum deceleration through the vehicle's own sensors; and judges the current driving condition of the vehicle based on the driving speed and maximum deceleration.

[0062] The control strategy calculation module receives vehicle driving conditions and pedestrian data in front of the vehicle; it outputs TTC classification thresholds based on the pedestrian data in front of the vehicle and driving conditions.

[0063] The risk assessment and decision-making module receives the TTC classification threshold and pedestrian data in front of the vehicle; it calculates the TTC value based on the TTC classification threshold and pedestrian data in front of the vehicle, and compares the calculated TTC value with the TTC classification threshold to determine the current risk level.

[0064] The control execution module receives the current risk level determined by the risk assessment and decision-making module and executes corresponding controls on the vehicle.

[0065] The specific implementation steps of each module in this invention are as follows:

[0066] 1. Information Sensing Module

[0067] The information perception module primarily acquires information about the vehicle's external environment and pedestrians ahead of the vehicle through multi-sensor fusion perception. More specifically, the multi-sensor mainly includes a monocular camera sensor and a millimeter-wave radar sensor.

[0068] The monocular camera sensor captures the scene in front of the vehicle in real time, extracts features of pedestrians in front by calculating the directional gradient histogram in the image, and then uses a support vector machine to classify the pedestrian features extracted from the image. If it is determined that there are pedestrians in front, the camera needs to be used to obtain pedestrian information in real time.

[0069] The aforementioned acquisition of pedestrian information refers to the acquisition of relevant and valid information about pedestrians through a monocular camera after pedestrians are identified. After camera calibration and image correction, the identified pedestrians are marked with a rectangular box, and the center point of the pedestrian rectangle is obtained. The pedestrian center point and the left and right edges of the pedestrian are recorded in two consecutive frames. By calculation, the world coordinates of the pedestrian center point, the pedestrian width, and the edge angle can be obtained. The pedestrian speed can be obtained by differentiating the pedestrian center point coordinates of two consecutive frames.

[0070] The millimeter-wave radar adopts an all-weather working mode, continuously transmitting signals to scan all targets (i.e. pedestrians) within a 40m range and a 60° field of view in real time, and returning data such as relative distance, relative speed, and azimuth angle between the radar and the target.

[0071] More specifically, the camera is installed on the windshield of the car to capture video images of the road ahead in real time; the millimeter-wave radar is installed in the middle of the vehicle's bumper to acquire relevant information about targets ahead in real time.

[0072] 2. Data Fusion Module

[0073] The data fusion module integrates pedestrian data acquired by the information perception module. Specifically, after the camera sensor detects a pedestrian, it matches the pedestrian data returned by the camera sensor with that returned by the millimeter-wave radar sensor in terms of time, location, and space to achieve precise positioning of the pedestrian in the world coordinate system, thereby obtaining more accurate pedestrian data. The fused pedestrian data is then sent to the control strategy calculation module and the risk assessment decision module. If no pedestrian target is detected ahead, it indicates that the current driving status is safe.

[0074] The pedestrian data includes pedestrian lateral velocity v. xp Pedestrian longitudinal velocity v yp The relative distance d between the vehicle and the pedestrian rel Pedestrian azimuth angle θ; further, the relative lateral and longitudinal distances d between the vehicle and the pedestrian. rx d ry It can be obtained from the following two formulas.

[0075]

[0076] The longitudinal direction is parallel to the vehicle's heading, and the lateral direction is perpendicular to the vehicle's heading.

[0077] 3. Driving Condition Judgment Module

[0078] The driving condition judgment module is used to judge the vehicle's driving condition in real time, including vehicle speed and maximum deceleration. Specifically, it obtains the vehicle's real-time speed information through vehicle speed sensors installed on the vehicle body; it detects real-time tire parameters and slip ratio through vehicle tire sensors, and detects parameters such as sideslip angle through body sensors. Then, the obtained parameters are input into the Kalman filter to estimate the ground friction coefficient estimation model, which outputs the current ground friction coefficient. The obtained ground friction coefficient is then input into the formula to calculate the vehicle's real-time maximum deceleration.

[0079] The calculation formula is as follows:

[0080] a max =μ·g

[0081] In the formula a max Let μ be the maximum deceleration of the vehicle, μ be the coefficient of friction of the ground, and g be the acceleration due to gravity, typically taken as 9.8 m / s². 2 .

[0082] 4. Control Strategy Calculation Module

[0083] Combination Figure 3 The control strategy calculation module has a built-in threshold calculation model. The received pedestrian data and vehicle driving conditions are input into the threshold calculation model to obtain the shortest braking TTC threshold under the current conditions. Based on the shortest braking TTC threshold, different TTC thresholds are set to implement a multi-level control strategy for the AEB-P system. Specifically:

[0084] In this embodiment, the pedestrian data includes the relative speed between the vehicle and the pedestrian, the relative distance between the vehicle and the pedestrian, the pedestrian speed, and the azimuth angle; the vehicle driving conditions include parameters such as vehicle speed and maximum vehicle deceleration.

[0085] In this embodiment, the shortest braking TTC threshold indicates that when there is a hazard ahead, AEB-P can activate the vehicle at this threshold time to completely avoid a collision, and after the vehicle stops, there is a certain safe distance between the vehicle and the pedestrian. The shortest braking TTC threshold is directly proportional to the vehicle speed and inversely proportional to the vehicle's maximum deceleration. When the shortest braking TTC threshold is larger at high speed or low maximum deceleration, the vehicle braking distance is longer.

[0086] A vehicle's braking distance is primarily affected by its speed and maximum deceleration. An AEB-P system with a fixed TTC threshold can effectively avoid collisions at low speeds and high deceleration, reducing the vehicle's speed to zero before reaching pedestrians. However, as speed increases and maximum deceleration decreases, the braking distance increases, and the original TTC threshold becomes inadequate for current vehicle conditions. In such cases, a larger TTC threshold is required for collision avoidance. However, if the TTC threshold is too high, the AEB-P system will be overly sensitive, causing frequent triggers, which can annoy the driver and severely impact the driving experience and comfort. Conversely, if the preset TTC threshold is too low, the AEB-P system will be sluggish, failing to fully utilize its capabilities and making it difficult to avoid hazards in emergencies, thus compromising driving safety.

[0087] Therefore, in this application, for cases where the shortest braking TTC threshold calculated under high vehicle speed and low deceleration operating conditions is large, a driving comfort adjustment coefficient is introduced to constrain and optimize the shortest braking TTC threshold, thereby enabling precise control of the AEB-P system and reducing the system's impact on the driver.

[0088] First, based on the vehicle's current driving conditions, calculate the shortest braking TTC threshold for the corresponding driving conditions, using the following formula:

[0089] When the vehicle is traveling at a constant speed:

[0090]

[0091] When the vehicle is accelerating or decelerating:

[0092]

[0093] Among them, TTC thr This represents the shortest braking TTC threshold, v1 represents the vehicle speed, v2 represents the pedestrian longitudinal velocity, and a n t1 represents the vehicle's current acceleration, t2 represents the system delay, t3 represents the time it takes for the deceleration to increase, and a represents the time it takes for the deceleration to increase. max d represents the maximum deceleration that can be achieved at present, and d represents the safe distance between the vehicle and the pedestrian.

[0094] Secondly, based on the shortest braking TTC threshold calculated under the current driving conditions, the current braking distance is calculated, and the calculated braking distance is compared with the braking distance threshold, where the braking distance threshold is set to 20m. If the braking distance is less than the braking distance threshold, the current vehicle driving braking section is divided into the normal braking section; otherwise, the braking section is divided into the long braking section.

[0095] The formula for calculating the vehicle braking distance based on the shortest braking TTC threshold is shown below:

[0096]

[0097] In the formula d TTC v0 represents the current braking distance, v0 represents the initial velocity of the vehicle before braking, and t represents the initial braking distance. delay Indicates the total delay of the braking system, a max Indicates the maximum deceleration a vehicle can achieve, TTC thr Indicates the shortest braking TTC threshold.

[0098] Finally, based on the type of braking range and the current driving conditions, the corresponding TTC (Traction Control Point) thresholds are set. A Level 2 TTC threshold is set when in a normal braking range; a Level 3 TTC threshold is set when in a long braking range. The specific method for calculating the TTC thresholds under different driving conditions is as follows:

[0099] (1) If the vehicle is in the normal braking range and traveling at a constant speed, the TTC classification threshold includes the warning TTC threshold (denoted as TTC). n1 ) and full braking TTC threshold (denoted as TTC) n2 The calculation formula is as follows:

[0100]

[0101]

[0102] (2) If the vehicle is in the normal braking range and the acceleration is not zero, the TTC grading threshold includes TTC. n1 and TTC n2 The calculation formula is as follows:

[0103]

[0104]

[0105] (3) If the vehicle is in a long braking range and traveling at a constant speed, the TTC classification threshold includes the warning TTC threshold (denoted as TTC). l1 ), partial braking TTC threshold (denoted as TTC) l2 ) and full braking TTC threshold (denoted as TTC) l3 The calculation formula is as follows:

[0106]

[0107]

[0108]

[0109] (4) If the vehicle is in a long braking range and the acceleration is not zero, the TTC grading threshold includes TTC. l1 TTC l2 and TTC l3 The calculation formula is as follows:

[0110]

[0111]

[0112]

[0113] Where Δt is a fixed value and k is the driver comfort adjustment coefficient.

[0114] The value of Δt is 1 second, and the value of k is a variable that varies with the vehicle speed. The calculation formula is shown below:

[0115]

[0116] In the formula, v1 is the vehicle speed and d0 is the safe distance.

[0117] 5. Risk Assessment and Decision-Making Module

[0118] The risk assessment and decision-making module calculates the current TTC value based on the received pedestrian fusion data and compares it with the control threshold under the current vehicle operating conditions output by the control strategy calculation module to determine the risk level of the current vehicle driving.

[0119] First, the risk assessment decision module uses the following formula to calculate the current TTC value:

[0120]

[0121] In the formula D rel v represents the relative distance between a vehicle and a pedestrian. rel a represents the relative speed between vehicles and pedestrians. r Let v1(t) represent the relative acceleration between the vehicle and the pedestrian, v2(t) represent the vehicle speed at time t, and v2(t) represent the pedestrian speed at time t.

[0122] Secondly, since different braking section types correspond to different TTC (Total Risk Charge) grading thresholds, different risk levels are assigned based on the relationship between the current TTC value and the TTC grading threshold under different braking section types. Specifically:

[0123] like Figure 2 and 5 When the vehicle is operating within the normal braking range, the AEB-P system uses Level 2 threshold control, meaning that if the current TTC value is greater than the TTC threshold... n1The risk level is Level 1, i.e., pedestrian safe zone; the current TTC value is less than the TTC. n1 And greater than TTC n2 The risk level is Level 2, which is the collision warning zone; the current TTC value is less than the TTC. n2 The risk level is level four, which is a collision hazard zone.

[0124] like Figure 4 When the vehicle is operating in a long braking range, the AEB-P system uses a 3-level threshold control. The current TTC value is greater than the TTC. l1 The risk level is Level 1, i.e., pedestrian safe zone; the current TTC value is less than the TTC. l1 And greater than TTC l2 The risk level is Level 2, which is the collision warning zone; the current TTC value is less than the TTC. l2 And greater than TTC l3 The risk level is currently Level 3, i.e., the collision braking zone; the current TTC value is less than the TTC. l3 The risk level is level four, which is a collision hazard zone.

[0125] When the pedestrian risk level reaches level three or four, the calculation of the TTC threshold will automatically stop, and the shortest braking TTC threshold obtained at the moment will be saved as a fixed trigger threshold until the dangerous state is eliminated.

[0126] In this embodiment, AEB-P will send different signal values ​​to the control execution module under different risk levels, specifically: Level 1 sends signal value 0, Level 2 sends signal value 1, Level 3 sends signal value 2, and Level 4 sends signal value 3. In safety levels 1, 2, and 3, once the driver makes a braking operation, AEB-P will exit the risk level and transfer driving control to the driver. However, in safety level 4, even if the driver makes an operation, the AEB-P system will continue to brake at full force to achieve the maximum braking force currently achievable.

[0127] 6. Vehicle control execution module

[0128] The vehicle execution control module controls the vehicle according to the signal values ​​sent by AEB-P, realizing operations such as vehicle deceleration, braking and alarm.

[0129] More specifically, the vehicle execution module includes an audible and visual alarm, an LED display, a brake-by-wire system, an electronic stability system (ESC), and an engine (EMS) or motor controller.

[0130] The control corresponding to the different signal values ​​are as follows: Signal value 0: No action is taken; Signal value 1: Text and image prompts are issued and accompanied by 3 beeps to remind the driver that there is a pedestrian ahead and a collision hazard; Signal value 2: A continuous emergency alarm signal is issued and accompanied by a constant beeping of the buzzer, while the braking system is partially braked and the engine or motor control is cut off; Signal value 3: A continuous emergency alarm signal is issued and accompanied by a constant beeping of the buzzer, while the braking system is fully braked.

[0131] In summary, this system overcomes the shortcomings of existing technologies, realizes a variable threshold AEB-P system, and better meets the technical and security requirements of AEB-P systems.

[0132] The above embodiments are only used to illustrate the design concept and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed in the present invention are within the protection scope of the present invention.

Claims

1. An AEB-P system based on a variable control strategy according to a vehicle operating condition, characterized by, The application relates to a vehicle risk assessment and control method, which comprises the following steps: An information perception module acquires vehicle surrounding environment and pedestrian information; A data fusion module receives the surrounding environment and pedestrian information collected by the information perception module, and matches and fuses the surrounding environment and pedestrian information to obtain pedestrian data in front of the vehicle; A driving condition judgment module acquires the driving speed and maximum deceleration of the vehicle, and judges the driving condition of the current vehicle according to the driving speed and maximum deceleration; A control strategy calculation module receives the driving condition of the vehicle and the pedestrian data in front of the vehicle, and outputs a TTC classification threshold value according to the pedestrian data in front of the vehicle and the driving condition; the method for obtaining the TTC classification threshold value is as follows: S1. According to the driving condition of the vehicle, the shortest braking TTC threshold value corresponding to different driving conditions is calculated; S2. Based on the shortest braking TTC threshold value, the current braking distance is calculated, and the braking distance is compared with a braking distance threshold value; if the braking distance is smaller than the braking distance threshold value, the current vehicle driving braking interval is divided into a normal braking interval; otherwise, the braking interval is divided into a long braking interval; S3. According to the type of the braking interval and the current driving condition, a corresponding TTC classification threshold value is set; if the current vehicle is in the normal braking interval, a two-level TTC classification threshold value is set; if the current vehicle is in the long braking interval, a three-level TTC classification threshold value is set; A risk assessment and decision module receives the TTC classification threshold value and the pedestrian data in front of the vehicle; According to the TTC classification threshold value and the pedestrian data in front of the vehicle, a TTC value is calculated, and the calculated TTC value is compared with the TTC classification threshold value to decide the current risk level; A control execution module receives the current risk level decided by the risk assessment and decision module, and executes control on the vehicle; If the vehicle is in the normal braking interval and uniformly travels, the TTC classification threshold value comprises a warning TTC threshold value and a full braking TTC threshold value, and the calculation formula is as follows: If the vehicle is in the normal braking interval and the acceleration is not 0, the TTC classification threshold value comprises a warning TTC threshold value and a full braking TTC threshold value, and the calculation formula is as follows: wherein TTC n1 is the pre-warning TTC threshold, TTC n2 is the full braking TTC threshold, v1 represents the vehicle speed, v2 represents the longitudinal speed of the pedestrian, a max represents the maximum deceleration currently available, a n represents the current acceleration of the vehicle, d represents the safety distance between the vehicle and the pedestrian, t2 represents the system delay, t3 represents the deceleration increase time, Δ t is a fixed value; If the vehicle is in the long braking interval and uniformly travels, the TTC classification threshold value comprises a warning TTC threshold value, a partial braking TTC threshold value and a full braking TTC threshold value, and the calculation formula is as follows: If the vehicle is in the long braking interval and the acceleration is not 0, the TTC classification thresholds include TTC l1 , TTC l2 , and TTC l3 , with the following calculation formula: wherein TTC l1 is the pre-warning TTC threshold, TTC l2 is the partial braking TTC threshold, TTC l3 is the full braking TTC threshold, v1 represents the vehicle speed, v2 represents the longitudinal speed of the pedestrian, a max represents the maximum deceleration currently available, a n represents the current acceleration of the vehicle, d represents the safety distance between the vehicle and the pedestrian, t2 represents the system delay, t3 represents the deceleration increase time, Δ t is a fixed value, and k is a driver comfort adjustment coefficient.

2. The AEB-P system based on a variable control strategy according to the working condition of the vehicle according to claim 1, characterized in that, The driver comfort adjustment coefficient k is expressed as: In the formula, v1 is the vehicle speed, and d0 is a safety distance. 3.The AEB-P system based on variable control strategy according to vehicle working condition according to claim 1, characterized in that, The method for deciding the risk level of the current vehicle in the risk assessment and decision module is as follows: S1. The current TTC value is calculated; S2. In different braking interval types, different risk levels are divided according to the relationship between the current TTC value and the TTC classification threshold value; When the vehicle is operating in the normal braking zone, the current TTC value is greater than TTC n1 ; the risk level is level one; the current TTC value is less than TTC n1 and greater than TTC n2 ; the risk level is level two, i.e. the collision warning zone; the current TTC value is less than TTC n2 ; the risk level is level four; When the vehicle is operating in a long braking section, the current TTC value is greater than TTC l1 when the risk level is level one; the current TTC value is less than TTC l1 and greater than TTC l2 when the risk level is level two; the current TTC value is less than TTC l2 and greater than TTC l3 when the risk level is level three; the current TTC value is less than TTC l3 when the risk level is level four.

4. The AEB-P system based on a variable control strategy according to the working condition of the vehicle according to claim 3, characterized in that, When the risk level of the pedestrian reaches level three or level four, the calculation of the TTC threshold value is automatically terminated, and the shortest braking TTC threshold value obtained at present is saved as a fixed triggering threshold value until the dangerous state is removed.

5. The AEB-P system based on variable control strategy according to the working condition of the vehicle according to claim 3, characterized in that, Different risk levels correspond to different signal values, and the AEB-P sends the signal values to the control execution module.

6. The AEB-P system based on a variable control strategy according to the working condition of the vehicle according to claim 3, characterized in that, When the risk level is one, two or three, AEB-P will exit the risk level and hand over the driving right to the driver once the driver makes a brake operation; when the risk level is four, AEB-P will continue to brake at full power even if the driver makes an operation, so as to reach the maximum brake force that can be reached at present.

7. The AEB-P system based on variable control strategy according to vehicle working conditions according to claim 1, characterized in that, The vehicle execution control module controls the vehicle according to the signal value sent by AEB-P, so as to realize the operation of vehicle deceleration, braking and alarm. 8.The AEB-P system based on variable control strategy according to vehicle working condition according to claim 1, characterized in that, The information sensing module obtains the vehicle external environment information and the pedestrian information in front of the vehicle through the vehicle camera sensor and the millimeter wave radar sensor. 9.The AEB-P system based on variable control strategy according to vehicle working condition according to claim 1, characterized in that, The vehicle execution module comprises an audible and visual alarm, an LED display, a line control brake system, an electronic stability system and an engine or motor controller.

Images