Vehicle emergency braking method, device, vehicle, storage medium and program product

Abstract

The application relates to the technical field of vehicles, in particular to a vehicle emergency braking method and device, a vehicle, a storage medium and a program product, wherein the method comprises the following steps: acquiring environment information around the vehicle and vehicle state information; identifying lane line information, at least one obstacle and corresponding state information in the environment information; determining a current working condition of the vehicle according to at least one of the vehicle state information, the lane line information and the state information of the at least one obstacle; determining a target obstacle around the vehicle based on the current working condition; calculating a collision time of the vehicle and the target obstacle according to the state information of the target obstacle and the vehicle state information; and controlling the vehicle to perform emergency braking based on the collision time. Therefore, the problems of insufficient adaptability of emergency braking in the prior art under complex working conditions and high collision risk are solved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a vehicle emergency braking method, device, vehicle, storage medium, and program product. Background Technology

[0002] The Automotive Emergency Braking (AEB) system was developed to address this need. AEB is an advanced driver assistance system that uses sensors to detect obstacles ahead of the vehicle. When a collision risk is detected, it issues an early warning and automatically applies the brakes to avoid a collision or mitigate the damage. Currently, AEB systems are used in many vehicle models and have achieved good safety results.

[0003] Most AEB systems in related technologies focus on automatic emergency obstacle avoidance schemes for vehicles traveling straight and encountering dangerous obstacles within their own lane. Few address scenarios involving collisions with obstacles in other conditions. This results in insufficient adaptability of AEB systems under complex conditions, making it difficult to accurately detect obstacles moving laterally outside the lane (such as pedestrians and electric vehicles), thus posing a collision risk. Summary of the Invention

[0004] This application provides a vehicle emergency braking method, device, vehicle, storage medium, and program product to solve the problems in related technologies such as insufficient adaptability of emergency braking under complex working conditions, resulting in a higher risk of collision.

[0005] The first aspect of this application provides a vehicle emergency braking method, comprising the following steps: acquiring environmental information surrounding the vehicle and vehicle status information; identifying lane line information, at least one obstacle, and corresponding status information in the environmental information; determining the current operating condition of the vehicle based on at least one of the vehicle status information, lane line information, and status information of at least one obstacle; determining a target obstacle surrounding the vehicle based on the current operating condition; calculating the collision time between the vehicle and the target obstacle based on the status information of the target obstacle and the vehicle status information; and controlling the vehicle to perform emergency braking based on the collision time.

[0006] Optionally, in one embodiment of this application, the obstacle's state information includes at least one of position, speed, heading angle, and acceleration, and the vehicle's state information includes at least one of vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration.

[0007] Optionally, in one embodiment of this application, calculating the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle includes: calculating the moment when the longitudinal positions of the vehicle and the target obstacle overlap based on the state information of the target obstacle and the state information of the vehicle; calculating the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the arc model, and calculating the lateral position of the vehicle at the moment of overlap based on the state information of the vehicle and the arc model; setting a first target time range with the moment of overlap as the initial point, and progressively filtering the first collision moments that meet preset conditions within the first target time range with a first target step size, wherein the preset conditions are that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; setting a second target time range centered on the first collision moment, and progressively filtering the second collision moments that meet preset conditions within the second target time range with a second target step size, and using the second collision moment as the collision time between the vehicle and the target obstacle.

[0008] Optionally, in one embodiment of this application, the formula for calculating the overlap time of the longitudinal position is: ; in, The moment of overlap in the longitudinal position. The relative speed between this vehicle and the target obstacle. The relative acceleration between the vehicle and the target obstacle. This is the shortest longitudinal distance between the vehicle and the target obstacle. This is the safe stopping distance between the vehicle and the target obstacle.

[0009] Optionally, in one embodiment of this application, the operating conditions include following, crossing, and turning. The current operating condition of the vehicle is determined based on at least one of the vehicle status information, lane line information, and at least one obstacle status information, including: if the lane line information indicates that no lane line has been identified and the obstacle is located within the current driving trajectory of the vehicle, or if the lane line information indicates that a lane line has been identified and the obstacle is located within the current driving lane of the vehicle, then the current operating condition of the vehicle is determined to be following; if the steering wheel angle of the vehicle is greater than a first preset angle and the obstacle is located within the future driving trajectory of the vehicle, then the current operating condition of the vehicle is determined to be turning; if the steering wheel angle of the vehicle is less than a second preset angle and the absolute value of the heading angle of the obstacle and the heading angle of the vehicle is a preset value, then the current operating condition of the vehicle is determined to be crossing, wherein the second preset angle is less than the first preset angle.

[0010] Optionally, in one embodiment of this application, determining target obstacles around the vehicle based on the current operating conditions includes: determining corresponding obstacle screening conditions and obstacle suppression strategies based on the current operating conditions; and determining target obstacles around the vehicle based on the obstacle screening conditions and obstacle suppression strategies.

[0011] A second aspect of this application provides a vehicle emergency braking device, comprising: an acquisition module for acquiring environmental information surrounding the vehicle and vehicle status information; an identification module for identifying lane line information, at least one obstacle, and corresponding status information in the environmental information; a determination module for determining the current operating condition of the vehicle based on at least one of the vehicle status information, lane line information, and status information of at least one obstacle, and determining a target obstacle surrounding the vehicle based on the current operating condition; and a control module for calculating the collision time between the vehicle and the target obstacle based on the status information of the target obstacle and the vehicle status information, and controlling the vehicle to perform emergency braking based on the collision time.

[0012] Optionally, in one embodiment of this application, the obstacle's state information includes at least one of position, speed, heading angle, and acceleration, and the vehicle's state information includes at least one of vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration.

[0013] Optionally, in one embodiment of this application, the control module is further configured to: calculate the moment of overlap between the longitudinal positions of the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle; calculate the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the arc model, and calculate the lateral position of the vehicle at the moment of overlap based on the state information of the vehicle and the arc model; set a first target time range with the moment of overlap as the initial point, and gradually filter the first collision moment that meets the preset conditions within the first target time range with a first target step size, wherein the preset conditions are that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; set a second target time range with the first collision moment as the center, and gradually filter the second collision moment that meets the preset conditions within the second target time range with a second target step size, and use the second collision moment as the collision time between the vehicle and the target obstacle.

[0014] Optionally, in one embodiment of this application, the formula for calculating the overlap time of the longitudinal position is: ; in, The moment of overlap in the longitudinal position. The relative speed between this vehicle and the target obstacle. The relative acceleration between the vehicle and the target obstacle. This is the shortest longitudinal distance between the vehicle and the target obstacle. This is the safe stopping distance between the vehicle and the target obstacle.

[0015] Optionally, in one embodiment of this application, the working conditions include following, crossing, and turning.

[0016] Optionally, in one embodiment of this application, the determining module is further configured to: if the lane line information is that no lane line is identified and the obstacle is located within the current driving trajectory of the vehicle, or if the lane line information is that a lane line is identified and the obstacle is located within the current driving lane line range of the vehicle, then the current operating condition of the vehicle is determined to be a following operating condition; if the steering wheel angle of the vehicle is greater than a first preset angle and the obstacle is located within the future driving trajectory of the vehicle, then the current operating condition of the vehicle is determined to be a turning operating condition; if the steering wheel angle of the vehicle is less than a second preset angle and the absolute value of the heading angle of the obstacle and the heading angle of the vehicle is a preset value, then the current operating condition of the vehicle is determined to be a crossing operating condition, wherein the second preset angle is less than the first preset angle.

[0017] Optionally, in one embodiment of this application, the determining module is further configured to: determine the corresponding obstacle screening conditions and obstacle suppression strategy based on the current operating conditions; and determine the target obstacles around the vehicle based on the obstacle screening conditions and obstacle suppression strategy.

[0018] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the vehicle emergency braking method as described above.

[0019] A fourth aspect of this application provides a computer-readable storage medium having a computer program or instructions stored thereon, which are executed by a processor to perform the vehicle emergency braking method as described above.

[0020] A fifth aspect of this application provides a computer program product, including a computer program or instructions, which, when executed, implement the vehicle emergency braking method as described in the above embodiments.

[0021] Therefore, this application has at least the following beneficial effects: This application embodiment can determine the current operating condition of the vehicle based on at least one of the following: lane line information around the vehicle, obstacle status information, and vehicle status information. It breaks down complex operating conditions and identifies target obstacles around the vehicle based on the current operating condition. For different types of operating conditions, it selects corresponding target obstacles, improving the adaptability of the vehicle's emergency braking to complex operating conditions and reducing collision risk. Furthermore, it calculates the collision time between the vehicle and the target obstacle based on the obstacle's status information and the vehicle's status information, and promptly controls the vehicle to perform emergency braking based on the collision time, thus improving the vehicle's emergency braking performance. Therefore, it solves the technical problem in related technologies where insufficient adaptability of emergency braking under complex operating conditions leads to a higher collision risk.

[0022] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0023] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a vehicle emergency braking method provided according to an embodiment of this application; Figure 2 This is an architecture diagram of the AEB system provided according to an embodiment of this application; Figure 3 This is a diagram showing the components of the AEB module provided according to an embodiment of this application; Figure 4 This is a flowchart illustrating the collision time calculation according to an embodiment of this application; Figure 5 This is an example diagram of a vehicle emergency braking device provided according to an embodiment of this application; Figure 6 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application. Detailed Implementation

[0024] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0025] The following description, with reference to the accompanying drawings, outlines a vehicle emergency braking method, apparatus, vehicle, storage medium, and program product according to embodiments of this application. Addressing the issue mentioned in the background art regarding the insufficient adaptability of AEB systems under complex conditions, which leads to the difficulty in accurately identifying obstacles moving laterally outside the vehicle's lane (such as pedestrians and electric vehicles) and posing a collision risk, this application provides a vehicle emergency braking method. In this method, the current operating condition of the vehicle can be determined based on at least one of lane line information, obstacle state information, and vehicle state information. The complex operating condition is broken down, and target obstacles around the vehicle are identified based on the current operating condition. Corresponding target obstacles are selected for different types of operating conditions, improving the adaptability of vehicle emergency braking to complex conditions and reducing collision risk. Furthermore, the collision time between the vehicle and the target obstacle is calculated based on the state information of the target obstacle and the vehicle state information. Based on the collision time, the vehicle is promptly controlled to perform emergency braking, improving the vehicle's emergency braking performance. This solves the problem in related technologies where emergency braking is insufficiently adaptable to complex conditions, leading to a high collision risk.

[0026] Specifically, Figure 1 This is a schematic flowchart of a vehicle emergency braking method provided in an embodiment of this application.

[0027] like Figure 1 As shown, the emergency braking method for this vehicle includes the following steps: In step S101, environmental information surrounding the vehicle and vehicle status information are obtained.

[0028] The vehicle status information includes at least one of the following: vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration.

[0029] Among them, the vehicle's position can be obtained through the vehicle positioning system, the current driving trajectory can be obtained based on the vehicle's navigation system, the steering wheel angle, heading angle, speed, and acceleration can be obtained based on the vehicle's sensors (such as millimeter-wave radar, cameras, etc.), and the future driving trajectory can be determined based on information such as vehicle speed and heading angle.

[0030] In step S102, lane line information, at least one obstacle, and corresponding status information in the environmental information are identified.

[0031] The obstacle's status information includes at least one of its position, speed, heading angle, and acceleration, which can be obtained through the vehicle's perception system and sensors.

[0032] It is understood that the embodiments of this application can identify lane line information, at least one obstacle and corresponding status information in the environmental information, so as to subsequently determine the current operating condition of the vehicle.

[0033] Furthermore, it should be noted that the obstacle categories in this application embodiment include vehicles and vulnerable road users (VRUs). When the obstacle is a vulnerable road user (VRU), the heading angle is not included in the status information.

[0034] In step S103, the current operating condition of the vehicle is determined based on at least one of the vehicle status information, lane line information, and status information of at least one obstacle, and target obstacles around the vehicle are determined based on the current operating condition.

[0035] The operating conditions include following, crossing, and turning.

[0036] It is understood that the embodiments of this application can determine the current working condition of the vehicle based on the vehicle status information, lane line information and the status information of at least one obstacle, abstract different types of simple working conditions from the complex scene in which the vehicle is currently located, and determine the surrounding target obstacles based on the current working condition.

[0037] In some embodiments of this application, the current operating condition of the vehicle is determined based on at least one of the vehicle status information, lane line information, and at least one obstacle status information, including: if the lane line information indicates that no lane line has been identified and the obstacle is located within the current driving trajectory of the vehicle, or if the lane line information indicates that a lane line has been identified and the obstacle is located within the current driving lane of the vehicle, then the current operating condition of the vehicle is determined to be a following condition; if the steering wheel angle of the vehicle is greater than a first preset angle and the obstacle is located within the future driving trajectory of the vehicle, then the current operating condition of the vehicle is determined to be a turning condition; if the steering wheel angle of the vehicle is less than a second preset angle and the absolute value of the heading angle of the obstacle and the heading angle of the vehicle is a preset value, then the current operating condition of the vehicle is determined to be a crossing condition, wherein the second preset angle is less than the first preset angle.

[0038] The first preset angle, the second preset angle, and the preset value can all be set according to specific circumstances, without any specific limitations. For example, the first preset angle can be set to 30°, the second preset angle can be set to 5°, and the preset value can be set to 90°.

[0039] It is understood that the embodiments of this application determine the current operating condition of the vehicle based on at least one of the vehicle status information, lane line information, and the status information of at least one obstacle. Specifically, the operating condition is mainly divided into three types. When there are no lane lines and the obstacle is within the vehicle's current driving trajectory, or when no lane lines are detected and the obstacle is within the range of the vehicle's current driving lane, the vehicle's current operating condition is determined to be following condition. When the steering wheel angle of this vehicle is greater than the first preset angle, it indicates that the steering wheel of this vehicle has a large angle and the driver has a clear intention to turn. If the obstacle is within the future driving trajectory of this vehicle, then the current working condition of this vehicle is determined to be a turning condition. When the steering wheel angle of this vehicle is less than the second preset angle, it indicates that the vehicle is traveling straight. When the absolute value of the heading angle of the obstacle and the heading angle of this vehicle is a preset value, the current working condition of this vehicle is determined to be a traversing working condition.

[0040] Furthermore, it should be noted that the operating conditions of the embodiments of this application are not limited to the above-described operating conditions, and may be continuously supplemented as the functional requirements of AEB increase.

[0041] In some embodiments of this application, determining target obstacles around the vehicle based on the current operating conditions includes: determining corresponding obstacle screening conditions and obstacle suppression strategies based on the current operating conditions; and determining target obstacles around the vehicle based on the obstacle screening conditions and obstacle suppression strategies.

[0042] It is understood that the embodiments of this application can determine the corresponding obstacle screening bar and obstacle suppression strategy according to the current working conditions, determine the target obstacles around the vehicle based on the obstacle screening conditions and obstacle suppression strategy, and adapt to more complex scenarios by determining the corresponding obstacle screening conditions for different types of working conditions. In addition, there will be corresponding obstacle suppression strategies for different types of working conditions to prevent the occurrence of accidental triggering of scenarios.

[0043] For example, in straight-ahead or following driving conditions, lane line information can be used to avoid the problem of not being able to select objects when shaking the steering wheel at high speeds. In crossing driving conditions, curb information can be used to suppress alarms for obstacles crossing outside the fence. At the same time, during emergency braking road test data reinjection analysis, if a false emergency braking trigger occurs, the trigger source condition can be recorded to quickly locate the cause of the false trigger and formulate strategies to suppress the false trigger without affecting other driving conditions.

[0044] Specifically, the methods for screening target obstacles under different types of working conditions in this application are as follows: The filtering logic for following the working conditions is as follows: when there are no lane lines, the target in the lane is filtered out according to the vehicle's trajectory (assuming the vehicle is moving in an arc, then the obstacles in the two arc trajectories formed by the left and right wheels of the vehicle are regarded as target obstacles). When there are lane lines, the target vehicle in the lane is regarded as the target obstacle. The selection logic for turning conditions is as follows: when the vehicle's steering wheel has a large angle and the driver clearly intends to turn, the target is an obstacle within the vehicle's future trajectory (the future trajectory is determined by information such as the vehicle's speed and heading angle). The selection logic for traversing the working conditions is as follows: the vehicle is traveling straight, and there are obstacles with an absolute value of the heading angle between the vehicle and the vehicle within approximately 90 degrees (the specific value is determined based on the actual sensor accuracy calibration).

[0045] In step S104, the collision time between the vehicle and the target obstacle is calculated based on the state information of the target obstacle and the state information of the vehicle, and the vehicle is controlled to perform emergency braking based on the collision time.

[0046] The collision time can be ETC (enhanced distance-collision time).

[0047] It is understood that, in the embodiments of this application, the collision time between the vehicle and the target obstacle can be calculated based on the state information of the target obstacle and the state information of the vehicle, and the vehicle can be controlled to perform emergency actions based on the collision time in order to avoid a collision accident.

[0048] In some embodiments of this application, calculating the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle includes: calculating the moment when the longitudinal positions of the vehicle and the target obstacle overlap based on the state information of the target obstacle and the state information of the vehicle; calculating the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the arc model, and calculating the lateral position of the vehicle at the moment of overlap based on the state information of the vehicle and the arc model; setting a first target time range with the moment of overlap as the initial point, and progressively filtering the first collision moments that meet preset conditions within the first target time range with a first target step size, wherein the preset conditions are that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; setting a second target time range with the first collision moment as the center, and progressively filtering the second collision moments that meet the preset conditions within the second target time range with a second target step size, and using the second collision moment as the collision time between the vehicle and the target obstacle.

[0049] It is understood that the embodiments of this application can calculate the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle. Taking the vehicle as an example, the following steps are included: 1. Calculate the moment when the longitudinal positions of the vehicle and the target obstacle overlap based on the state information of the target obstacle and the state information of the vehicle.

[0050] Based on the collision model formula, the longitudinal overlap time t between the obstacle and the vehicle is roughly calculated. Assuming the shortest longitudinal distance between the two vehicles is s (m), the safe stopping distance is d (m), the travel time is t (s), the vehicle's speed and acceleration are v1 (m / s) and a1 (m / s²), and the speed and acceleration of the vehicle in front are v2 (m / s) and a2 (m / s²), the safe stopping distance is generally taken as 0.5~3m, the relative speed is vrel (vehicle speed minus vehicle speed), and the relative acceleration is arel (vehicle speed minus vehicle speed). The calculation formula is as follows: , ( ; ; 2. Calculate the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the circular arc model, and calculate the lateral position of the vehicle at the moment of overlap based on the state information of the vehicle and the circular arc model; take the moment of overlap as the initial point, set a first target time range, and gradually filter the first collision moment that meets the preset conditions within the first target time range with a first target step size, wherein the preset conditions are that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle.

[0051] The first step can calculate the collision time for the following conditions. However, for other complex conditions, the result may not be the collision time. This is because longitudinal overlap does not necessarily mean that the vehicle and the obstacle will collide. For example, in the traversing condition, there may be a situation where the longitudinal position of the vehicle and the obstacle is on the same horizontal line, but the lateral position does not overlap. Therefore, in this embodiment, after roughly obtaining the longitudinal collision time, the vehicle uses this time as the initial point and calculates the position of the obstacle and the vehicle in an arc using yaw rate and velocity information. The vehicle uses this time as the basic origin point and sets a time threshold range, such as t-0.3s, t+0.5s, with a time step of 0.1s, which can be adjusted. The vehicle calculates the collision time t2 (i.e., the first collision time) between the obstacle and the vehicle within this time range, and the accuracy of the calculated collision time is the set time step.

[0052] 3. Taking the first collision moment as the center, set a second target time range, and within the second target time range, gradually filter the second collision moments that meet the preset conditions with the second target step size, and take the second collision moment as the collision time between the vehicle and the target obstacle.

[0053] Based on the collision time t2 with an accuracy of 0.1s, we can search for a more accurate collision time within two steps, such as t2-0.1s to t2+0.1s, and set the calculation accuracy, such as 0.01s. Generally, a collision time with an accuracy of 0.01s is sufficient to meet the requirements, thus obtaining the final second collision time, which is used as the collision time between the vehicle and the target obstacle.

[0054] Based on the above implementation, the collision time calculation method of this application can cope with more complex scene conditions and has higher calculation accuracy. In addition, through the design of two-stage step-by-step calculation and controllable time step, that is, first coarse screening to narrow down the range and then fine screening to improve accuracy, high-precision calculation over the entire time range is avoided, the amount of calculation is reduced, and the calculation time is reduced. Therefore, it can be embedded in a lower computing power platform to implement the method of porting the algorithm.

[0055] In some embodiments of this application, the formula for calculating the overlap time of the longitudinal position is as follows: ; in, The moment of overlap in the longitudinal position. The relative speed between this vehicle and the target obstacle. The relative acceleration between the vehicle and the target obstacle. This is the shortest longitudinal distance between the vehicle and the target obstacle. This is the safe stopping distance between the vehicle and the target obstacle.

[0056] In some embodiments of this application, the method of controlling the vehicle to perform emergency braking based on collision time can be to determine the alarm level based on the collision time, and determine the triggering time and deceleration magnitude of emergency braking based on the alarm level.

[0057] Specifically, methods for controlling the vehicle to perform emergency braking based on collision time include: 1. Set the threshold for collision time classification.

[0058] For example, if the collision time is greater than 5 seconds, there will be no alarm; if the collision time is greater than 3 seconds and less than or equal to 5 seconds, the alarm level is 1, indicating a potential risk; if the collision time is greater than 1.5 seconds and less than or equal to 3 seconds, the alarm level is 2, indicating a high collision risk; if the collision time is less than or equal to 1.5 seconds, the alarm level is 3, indicating an extremely high collision risk.

[0059] 2. Based on the collision time, match the alarm level and issue preliminary instructions.

[0060] Level 1 alarm provides visual and auditory cues, but the vehicle itself does not apply the brakes; the driver must operate the brakes. Level 2 alarm, in addition to Level 1 alarm, sends a braking preparation command to the actuator (such as pre-pressurizing the brake line to reduce braking response delay), while continuously monitoring changes in collision time; Level 3 alarm, automatically after an emergency, sends an AEB (Autonomous Emergency Braking) trigger command to the actuator, specifying the braking deceleration requirement.

[0061] 3. Dynamically adjust braking deceleration based on collision time to execute emergency braking.

[0062] (1) With the goal of avoiding a collision, combined with the current speed of the vehicle The collision time (ettc) is used to preliminarily calculate the required braking deceleration using a formula. : ; in, For safe vehicle speed (based on scenario settings, following operating conditions) Take the speed of the vehicle in front and cross the working conditions. Set the value to 0 to avoid collisions with vulnerable road users.

[0063] (2) Dynamic correction during braking process; the braking system receives... Then, the actual braking deceleration needs to be fed back every 0.01 seconds (to match the accuracy of ETC calculations). The hazard assessment module corrects the issue by incorporating the new ETC value (recalculated in real time). .

[0064] 4. Determine whether it is necessary to terminate the braking action.

[0065] For example, if the collision time is greater than 5 seconds and the relative distance between the obstacle and the vehicle continues to increase, or the vehicle speed drops to a safe speed and there is no collision wind, or the obstacle becomes smaller, then the braking action will be terminated.

[0066] The vehicle emergency braking method of this application embodiment can be applied to the AEB system on a vehicle. The method of this application embodiment is described below through a specific embodiment, taking its application to the AEB system as an example.

[0067] like Figure 2 As shown, Figure 2 This is a structural diagram of the AEB system, including the sensing system, fusion module, AEB module, etc.

[0068] The perception system is responsible for transmitting external environmental information, while the fusion module is responsible for transmitting the results from multiple sensors to the AEB module through a fusion algorithm. The AEB module makes a comprehensive decision based on the perception system, fusion module, vehicle status information, human-machine interaction module, and actuator information, and finally outputs a braking signal to the actuator to bring the vehicle to a timely stop.

[0069] Furthermore, the AEB module mainly comprises three modules: target screening, hazard assessment, and the AEB state machine module. The components of the AEB module are as follows: Figure 3 As shown.

[0070] The target screening function identifies obstacles that may trigger AEB; the hazard assessment module calculates the collision time (ettc) of the hazard obstacle, determines the alarm level, and then determines the AEB triggering timing and deceleration magnitude; the AEB state machine mainly controls whether AEB should be triggered or whether AEB should be interrupted.

[0071] Furthermore, the target selection module's execution process includes classifying obstacles acquired by the perception system into categories such as vehicles and vulnerable road users (VRUs). This can be expanded to include irregularly shaped obstacles as AEB performance requirements evolve. Based on the current vehicle status and the obstacle's position, speed, and heading angle (which only considers vehicle-type targets), the module categorizes the current operating condition into following, crossing, and turning, allowing for different logical judgments and strategy adjustments based on the obstacle and the corresponding operating condition.

[0072] Specifically, the filtering logic for the following driving condition is as follows: When there are no lane lines, targets within the current lane are selected based on the vehicle's trajectory (assuming the vehicle is moving in an arc, obstacles along the two arcs formed by the left and right wheels are considered target obstacles). When lane lines exist, the target vehicle is considered a target obstacle within the current lane. The filtering logic for the turning driving condition is as follows: When the vehicle's steering wheel has a large angle and the driver clearly intends to turn, obstacles within the vehicle's future trajectory are selected (the future trajectory is determined by information such as vehicle speed and heading angle). The filtering logic for the crossing driving condition is as follows: When the vehicle is moving straight, obstacles with an absolute value of approximately 90 degrees relative to the vehicle's heading angle are selected (the specific value is determined based on the actual sensor accuracy calibration). The target selection scenarios include, but are not limited to, the listed items. These can be continuously expanded as AEB functional requirements increase. Different target selection scenarios will be matched with different AEB trigger suppression strategies to prevent false triggering. For example, in the straight-ahead scenario, lane line information is used to avoid the problem of not being able to select objects when the vehicle is moving the steering wheel at high speed. In the crossing scenario, curb information is used to suppress alarms for obstacles crossing outside the fence. Furthermore, during AEB road test data feedback analysis, if a false AEB trigger occurs, the trigger source scenario can be recorded to quickly locate the cause of the false trigger and formulate strategies to suppress it without affecting other scenarios.

[0073] After target selection, the collision time of the selected obstacles is calculated. Traditional ETC calculation modules either only consider following conditions, making them too simplistic and unable to calculate collision times for complex scenarios such as turning and crossing, or they suffer from excessive computational load, too many loops, and high time consumption, making them unsuitable for low-performance platforms. The ETC module described in this invention achieves fast collision time calculation while maintaining a certain level of accuracy. It can be embedded in lower-performance platforms, facilitating the porting of the AEB algorithm. The ETC calculation steps are as follows: Figure 4 As shown, it specifically includes: First, based on the collision model formula, roughly calculate the longitudinal overlap time t between the obstacle and the vehicle. Assume the shortest longitudinal distance between the two vehicles is s (m), the safe stopping distance is d (m), the travel time is t (s), the vehicle's speed and acceleration are v1 (m / s) and a1 (m / s²), and the speed and acceleration of the vehicle in front are v2 (m / s) and a2 (m / s²). The safe stopping distance is generally taken as 0.5~3m. The relative vehicle speed is vrel (vehicle speed minus vehicle speed), and the relative acceleration is arel (vehicle speed minus vehicle speed). The calculation formula is as follows: ,( ; ; The above formula can calculate the collision time t under the following conditions. However, for other complex conditions, the result may not be the collision time. This is because longitudinal overlap does not necessarily mean that the vehicle and the obstacle will collide. For example, in the traversing condition, there may be a situation where the longitudinal position of the vehicle and the obstacle is on the same horizontal line, but the lateral position does not overlap. Therefore, after roughly obtaining the longitudinal collision time, this time is used as the initial point. The positions of the obstacle and the vehicle are calculated in an arc using yaw rate and velocity information. This position is used as the basic origin point, and a time threshold range is set, such as t-0.3s, t+0.5s, with a time step of 0.1s (the step size is adjustable). The collision time t2 between the obstacle and the vehicle within this time range is calculated, and the accuracy of the calculated collision time is the set time step.

[0074] Next, after obtaining the collision time t2 with an accuracy of 0.1s, we can search for a higher accuracy collision time within two steps, such as t2-0.1s to t2+0.1s, and set the calculation accuracy, such as 0.01s. In general, a collision time with an accuracy of 0.01s is sufficient to meet the requirements.

[0075] In summary, this application can abstract and decompose complex scene conditions and design different target obstacle screening strategies for different scene conditions, enabling AEB to adapt to more complex scenes and solve the problem of screening target obstacles when the vehicle is turning or in complex conditions. At the same time, by using the ETC calculation scheme for complex conditions, high-precision ETC results can be calculated quickly, reducing the collision risk caused by complex environment or driver reaction delay, thereby significantly improving AEB performance and ensuring the timeliness of AEB triggering.

[0076] According to the vehicle emergency braking method proposed in the embodiments of this application, the current operating condition of the vehicle can be determined based on at least one of the lane line information, obstacle state information and vehicle state information around the vehicle. The complex operating condition is broken down, and the target obstacle around the vehicle is determined according to the current operating condition. The corresponding target obstacle is selected for different types of operating conditions, which improves the adaptability of vehicle emergency braking to complex operating conditions, reduces the risk of collision, and then calculates the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the vehicle state information. Based on the collision time, the vehicle is controlled to perform emergency braking in a timely manner, thereby improving the emergency braking performance of the vehicle.

[0077] Next, the vehicle emergency braking device according to the embodiments of this application is described with reference to the accompanying drawings.

[0078] Figure 5 This is a block diagram of a vehicle emergency braking device according to an embodiment of this application.

[0079] like Figure 5 As shown, the vehicle emergency braking device 10 includes: an acquisition module 100, an identification module 200, a determination module 300, and a control module 400.

[0080] The acquisition module 100 is used to acquire environmental information around the vehicle and vehicle status information; the identification module 200 is used to identify lane line information, at least one obstacle, and its corresponding status information in the environmental information; the determination module 300 is used to determine the current operating condition of the vehicle based on at least one of the vehicle status information, lane line information, and status information of at least one obstacle, and to determine the target obstacle around the vehicle based on the current operating condition; the control module 400 is used to calculate the collision time between the vehicle and the target obstacle based on the status information of the target obstacle and the vehicle status information, and to control the vehicle to perform emergency braking based on the collision time.

[0081] In some embodiments of this application, the obstacle's state information includes at least one of position, speed, heading angle, and acceleration, and the vehicle's state information includes at least one of vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration.

[0082] In some embodiments of this application, the control module 400 is further configured to: calculate the moment of overlap between the longitudinal positions of the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle; calculate the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the arc model, and calculate the lateral position of the vehicle at the moment of overlap based on the state information of the vehicle and the arc model; set a first target time range with the moment of overlap as the initial point, and gradually filter the first collision moment that meets the preset conditions within the first target time range with a first target step size, wherein the preset conditions are that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; set a second target time range with the first collision moment as the center, and gradually filter the second collision moment that meets the preset conditions within the second target time range with a second target step size, and use the second collision moment as the collision time between the vehicle and the target obstacle.

[0083] In some embodiments of this application, the formula for calculating the overlap time of the longitudinal position is as follows: ; in, The moment of overlap in the longitudinal position. The relative speed between this vehicle and the target obstacle. The relative acceleration between the vehicle and the target obstacle. This is the shortest longitudinal distance between the vehicle and the target obstacle. This is the safe stopping distance between the vehicle and the target obstacle.

[0084] In some embodiments of this application, the working conditions include following working conditions, crossing working conditions, and turning working conditions.

[0085] In some embodiments of this application, the determining module 300 is further configured to: if the lane line information is that no lane line is identified and the obstacle is located within the current driving trajectory of the vehicle, or if the lane line information is that a lane line is identified and the obstacle is located within the current driving lane line range of the vehicle, then the current operating condition of the vehicle is determined to be a following operating condition; if the steering wheel angle of the vehicle is greater than a first preset angle and the obstacle is located within the future driving trajectory of the vehicle, then the current operating condition of the vehicle is determined to be a turning operating condition; if the steering wheel angle of the vehicle is less than a second preset angle and the absolute value of the heading angle of the obstacle and the heading angle of the vehicle is a preset value, then the current operating condition of the vehicle is determined to be a crossing operating condition, wherein the second preset angle is less than the first preset angle.

[0086] In some embodiments of this application, the determining module 300 is further configured to: determine the corresponding obstacle screening conditions and obstacle suppression strategy based on the current operating conditions; and determine the target obstacles around the vehicle based on the obstacle screening conditions and obstacle suppression strategy.

[0087] It should be noted that the foregoing explanation of the vehicle emergency braking method embodiment also applies to the vehicle emergency braking device of this embodiment, and will not be repeated here.

[0088] According to the vehicle emergency braking device proposed in the embodiments of this application, the current operating condition of the vehicle can be determined based on at least one of the lane line information, obstacle status information and vehicle status information around the vehicle. The complex operating condition is broken down, and the target obstacles around the vehicle are determined according to the current operating condition. The corresponding target obstacles are selected for different types of operating conditions, thereby improving the adaptability of vehicle emergency braking to complex operating conditions and reducing the risk of collision. Then, the collision time between the vehicle and the target obstacle is calculated based on the status information of the target obstacle and the vehicle status information. Based on the collision time, the vehicle is controlled to perform emergency braking in a timely manner, thereby improving the emergency braking performance of the vehicle.

[0089] Figure 6 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0090] When the processor 602 executes the program, it implements the vehicle emergency braking method provided in the above embodiments.

[0091] Furthermore, the vehicle also includes: Communication interface 603 is used for communication between memory 601 and processor 602.

[0092] The memory 601 is used to store computer programs that can run on the processor 602.

[0093] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0094] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0095] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0096] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0097] This application also provides a computer-readable storage medium storing a computer program or instructions thereon, which, when executed by a processor, implements the above-described vehicle emergency braking method.

[0098] This application also provides a computer program product, including a computer program or instructions, which, when executed, implement the above-described vehicle emergency braking method.

[0099] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0101] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0102] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0103] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A method for emergency braking of a vehicle, characterized in that, Includes the following steps: Acquire environmental information surrounding the vehicle and vehicle status information, wherein the vehicle status information includes at least one of the following: vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration; Identify lane line information, at least one obstacle, and corresponding status information in the environmental information, wherein the status information of the obstacle includes at least one of position, speed, heading angle, and acceleration; The current operating condition of the vehicle is determined based on at least one of the vehicle status information, the lane line information, and the status information of at least one obstacle, and the target obstacles around the vehicle are determined based on the current operating condition. Calculate the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle, and control the vehicle to perform emergency braking based on the collision time; the calculation of the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle includes: calculating the moment of overlap of the longitudinal positions of the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle; calculating the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the arc model; and calculating the collision time between the vehicle and the target obstacle based on the state information of the vehicle and the arc model. At the lateral position of the overlapping moment; taking the overlapping moment as the initial point, a first target time range is set, and within the first target time range, a first collision moment that meets the preset conditions is gradually filtered with a first target step size, wherein the preset condition is that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; taking the first collision moment as the center, a second target time range is set, and within the second target time range, a second collision moment that meets the preset conditions is gradually filtered with a second target step size, and the second collision moment is taken as the collision time between the vehicle and the target obstacle.

2. The vehicle emergency braking method according to claim 1, characterized in that, The formula for calculating the overlap time of the longitudinal positions is: ； in, The moment of overlap in the longitudinal position. The relative speed between this vehicle and the target obstacle. The relative acceleration between the vehicle and the target obstacle. This is the shortest longitudinal distance between the vehicle and the target obstacle. This is the safe stopping distance between the vehicle and the target obstacle.

3. The vehicle emergency braking method according to claim 1, characterized in that, The operating conditions include following, crossing, and turning. Determining the current operating condition of the vehicle based on at least one of the vehicle status information, lane line information, and at least one obstacle status information includes: If the lane line information indicates that no lane line has been identified and the obstacle is located within the current driving trajectory of the vehicle, or if the lane line information indicates that a lane line has been identified and the obstacle is located within the current driving lane of the vehicle, then the current operating condition of the vehicle is determined to be the following operating condition. If the steering wheel angle of the vehicle is greater than the first preset angle, and the obstacle is located within the future driving trajectory of the vehicle, then the current working condition of the vehicle is determined to be the turning working condition. If the steering wheel angle of the vehicle is less than the second preset angle, and the absolute value of the heading angle of the obstacle and the heading angle of the vehicle is a preset value, then the current working condition of the vehicle is determined to be the crossing working condition, wherein the second preset angle is less than the first preset angle.

4. The vehicle emergency braking method according to claim 1, characterized in that, The determination of target obstacles around the vehicle based on the current operating conditions includes: Based on the current operating conditions, determine the corresponding obstacle screening conditions and obstacle suppression strategies; The target obstacles around the vehicle are determined based on the obstacle screening conditions and the obstacle suppression strategy.

5. A vehicle emergency braking device, characterized in that, include: The acquisition module is used to acquire environmental information around the vehicle and vehicle status information, wherein the vehicle status information includes at least one of vehicle position, current driving trajectory, steering wheel angle, heading angle, future driving trajectory, speed, and acceleration; The identification module is used to identify lane line information, at least one obstacle, and corresponding status information in the environmental information. The determination module is used to determine the current operating condition of the vehicle based on at least one of the vehicle status information, the lane line information, and the status information of at least one obstacle, and to determine the target obstacles around the vehicle based on the current operating condition, wherein the status information of the obstacle includes at least one of position, speed, heading angle, and acceleration; The control module is configured to calculate the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle, and control the vehicle to perform emergency braking based on the collision time; the calculation of the collision time between the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle includes: calculating the moment of overlap of the longitudinal positions of the vehicle and the target obstacle based on the state information of the target obstacle and the state information of the vehicle; calculating the lateral position of the target obstacle at the moment of overlap based on the state information of the target obstacle and the circular arc model; and calculating the lateral position of the target obstacle based on the state information of the vehicle and the circular arc model. The lateral position of the vehicle at the moment of overlap; taking the moment of overlap as the initial point, a first target time range is set, and within the first target time range, a first collision moment that meets a preset condition is gradually filtered with a first target step size, wherein the preset condition is that the longitudinal position of the vehicle overlaps with the longitudinal position of the target obstacle, and the lateral position of the vehicle overlaps with the lateral position of the target obstacle; taking the first collision moment as the center, a second target time range is set, and within the second target time range, a second collision moment that meets the preset condition is gradually filtered with a second target step size, and the second collision moment is taken as the collision time between the vehicle and the target obstacle.

6. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle emergency braking method as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, The computer program or instructions are executed by a processor to implement the vehicle emergency braking method as described in any one of claims 1-4.

8. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the vehicle emergency braking method as described in any one of claims 1-4.

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