Method, device and electronic equipment for determining low-speed emergency braking

Abstract

This invention provides a method, apparatus, and electronic device for determining low-speed emergency braking. It calculates the collision-sensitive width corresponding to each discrete trajectory based on trajectory confidence, which tightens the collision-sensitive width of discrete trajectories with low confidence, thus focusing more on the central region. The surrounding area of ​​the vehicle is divided, and target areas where collisions may occur are determined from these divisions, reducing subsequent computational load. Obstacle position coefficients are set for target obstacles within the target division areas. The target collision coefficient for each target obstacle is calculated based on the collision-sensitive width corresponding to each discrete trajectory. Furthermore, the risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on its obstacle position coefficient and corresponding target collision coefficient. The existence of collision risk is determined based on the risk coefficient, making the final determined emergency braking timing more accurate.

Description

Technical Field

[0001] This invention relates to the technical field of driver assistance, and in particular to a method, apparatus, and electronic device for determining low-speed emergency braking. Background Technology

[0002] Low-speed emergency braking (MEB) is a sub-function within the Level 2 driver assistance system. This function typically activates at speeds below 12 km / h. In scenarios such as parking, turning, and navigating confined spaces, it identifies obstacles around the vehicle and intervenes with braking when a collision risk is detected, thus preventing a collision and ensuring the safety of the driver and vehicle.

[0003] Since MEB is an active safety feature, it is activated when the driver is manually driving. Compared to AEB (Automatic Emergency Braking) at higher speeds, at low speeds, there will be frequent acceleration and deceleration, as well as rapid steering wheel turning.

[0004] The traditional approach is to predict the vehicle's trajectory based on its current state, combine this with the location of obstacles detected by sensors, and use vehicle kinematics formulas to calculate the collision time. When the collision time is less than a threshold, the vehicle is triggered to apply emergency braking.

[0005] Because it's difficult to understand the driver's intentions in low-speed scenarios, it's challenging to predict the vehicle's movement trend during acceleration, deceleration, or rapid steering wheel turns. Furthermore, the accuracy of obstacle perception (angle, outer dimensions, etc.) decreases during rapid turns. These two factors lead to numerous instances of "false braking" or "missed braking."

[0006] In summary, improving the accuracy of low-speed emergency braking has become an urgent technical problem to be solved. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide a method, apparatus and electronic device for determining low-speed emergency braking, so as to alleviate the technical problem of poor accuracy of existing low-speed emergency braking.

[0008] In a first aspect, embodiments of the present invention provide a method for determining low-speed emergency braking, comprising:

[0009] Based on the vehicle's current state information, the discrete trajectory of the vehicle at each discrete time point within a future preset time period and the trajectory confidence level corresponding to each discrete trajectory are calculated. Based on the trajectory confidence level and the width of the vehicle, the collision-sensitive width corresponding to each discrete trajectory is calculated. The time interval between adjacent discrete time points is the same.

[0010] The area surrounding the current position of the vehicle is divided, and a target area where a collision may occur is determined within the divided area based on the vehicle's direction of travel.

[0011] Based on the distance between the target obstacle and the vehicle in the target division area, an obstacle position coefficient is set for each target obstacle to obtain the obstacle position coefficient for each target obstacle;

[0012] The collision coefficient between each target obstacle and each discrete trajectory is calculated based on the collision-sensitive width corresponding to each discrete trajectory, and the target collision coefficient corresponding to each target obstacle is determined based on the collision coefficient between each target obstacle and each discrete trajectory.

[0013] The risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on the obstacle position coefficient of each target obstacle and its corresponding target collision coefficient, wherein the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient;

[0014] Based on the risk coefficient of each target obstacle relative to the target discrete trajectory, determine whether each target obstacle has a collision risk with the target discrete trajectory;

[0015] If there is a risk of collision, the timing of emergency braking is determined based on the vehicle's performance and the discrete trajectory of the target with the risk of collision.

[0016] Furthermore, based on the vehicle's current state information, the discrete trajectories of the vehicle at each discrete time point within a preset future time period and the trajectory confidence level corresponding to each discrete trajectories are calculated, including:

[0017] The formula HeadAng is used to calculate the angle of the vehicle's front. [i] =HeadAng [i-1] +YawRate*T calculates the vehicle's head angle at discrete time points within a preset future time period, where HeadAng... [i] HeadAng represents the vehicle's head angle at the i-th discrete time point within a preset future time period. [i-1] This represents the vehicle's head angle at the (i-1)th discrete time point within a preset future time period, where YawRate represents the angular velocity in the current state information, and T represents the time interval. When i is 1, HeadAng... [i-1] This indicates the current vehicle front angle in the current status information;

[0018] The formula X is calculated based on the vehicle's X coordinate. [i] =X [i-1] +V [i] *cos(HeadAng[i] )*T calculates the x-coordinate of the vehicle at each discrete time point within a preset future time period, where X [i] X represents the X coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the x-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] X represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, X... [i-1] This indicates the current X-coordinate of the vehicle in the current status information;

[0019] The formula Y is calculated based on the vehicle's Y coordinate. [i] =Y [-1] +V [i] *sin(HeadAng [i] )*T calculates the Y-coordinate of the vehicle at each discrete time point within a preset future time period, where Y [i] Y represents the Y-coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the Y-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] Y represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, Y... [i-1] This indicates the current Y-coordinate of the vehicle in the current status information;

[0020] The vehicle's front angle, X-coordinate, and Y-coordinate at each discrete time point within a future preset time period are used as the discrete trajectories of the vehicle at each discrete time point within the future preset time period.

[0021] Confidence is calculated based on the trajectory confidence formula. [i] =A1*(Distance) Pred -Distance [i] ) / Distance Pred +A2*(Lgt AccMax -Lgt Acc ) / Lgt AccMax +A3*(Steer SpdMax -Steer Spd) / Steer SpdMax

[0022] Calculate the trajectory confidence score corresponding to each of the discrete trajectories, where Confidence [i] Distance represents the trajectory confidence of the discrete trajectory at the i-th discrete time point. Pred Distance represents the total length of the discrete trajectory corresponding to the current state information. [i] Lgt represents the length of the discrete trajectory at the i-th discrete time point. AccMax Lgt represents the maximum value of longitudinal acceleration. Acc This represents the longitudinal acceleration in the current state information, Steer SpdMax This indicates the maximum turning speed of the steering wheel, Steer Spd The steering wheel rotation speed is represented in the current state information, and A1, A2, and A3 represent preset weighting coefficients.

[0023] Calculate the collision-sensitive width corresponding to each discrete trajectory based on the confidence level of each trajectory and the width of the vehicle, including:

[0024] The collision-sensitive width is calculated using the formula: Collision-sensitive width = Vehicle width × Trajectory confidence level. This formula calculates the collision-sensitive width corresponding to each discrete trajectory.

[0025] Furthermore, the area surrounding the current location of the vehicle is divided, including:

[0026] The area surrounding the vehicle is divided into six zones based on the horizontal lines of the front bumper, the rear axle, and the rear bumper.

[0027] Based on the distance between the target obstacle and the vehicle within the target area, an obstacle position coefficient is set for each target obstacle, including:

[0028] If the distance between the first target obstacle and the vehicle is not greater than a first preset distance, then the obstacle position coefficient of the first target obstacle is set to 1;

[0029] If the distance between the second target obstacle and the vehicle is greater than the first preset distance and less than the second preset distance, then the obstacle position coefficient of the second target obstacle is set according to a preset decreasing rule. The preset decreasing rule is that when the distance is between the first preset distance and the second preset distance, the obstacle position coefficient is linearly decreased from 1 to 0 from near to far.

[0030] If the distance between the third target obstacle and the vehicle is greater than the second preset distance, then the obstacle position coefficient of the third target obstacle is set to 0.

[0031] Furthermore, based on the collision-sensitive width corresponding to each of the discrete trajectories, the collision coefficient between each target obstacle and each of the discrete trajectories is calculated, and the target collision coefficient corresponding to each target obstacle is determined according to the collision coefficient between each target obstacle and each of the discrete trajectories, including:

[0032] The collision coefficient between each target obstacle and each discrete trajectory is calculated using the collision coefficient calculation formula Collision_Coe = CE / AE, where Collision_Coe represents the collision coefficient between a target obstacle and a discrete trajectory, CE represents the overlap width between the target obstacle and the discrete trajectory, and AE represents half of the collision-sensitive width corresponding to the discrete trajectory.

[0033] The maximum collision coefficient among the collision coefficients of each target obstacle and each discrete trajectory is taken as the target collision coefficient corresponding to each target obstacle.

[0034] Furthermore, based on the obstacle position coefficient of each of the target obstacles and its corresponding target collision coefficient, a risk coefficient relative to the discrete trajectory of the target is calculated, including:

[0035] The risk coefficient is calculated using the formula: Risk coefficient = Obstacle position coefficient × Target collision coefficient. This formula calculates the risk coefficient of each target obstacle relative to the discrete trajectory of the target.

[0036] Furthermore, determining whether each of the target obstacles poses a collision risk with the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory includes:

[0037] If the risk coefficient is greater than the preset risk threshold, then it is determined that the corresponding target obstacle poses a collision risk to the target discrete trajectory.

[0038] Furthermore, the vehicle's performance includes: the time required for the vehicle to complete braking; determining the emergency braking timing based on the vehicle's performance and the discrete trajectory of the target with collision risk, including:

[0039] The time when a vehicle will collide in the future is determined based on the discrete trajectory of the target with collision risk.

[0040] The timing of emergency braking is determined based on the time required for the vehicle to complete braking and the time when the vehicle will collide in the future.

[0041] Secondly, embodiments of the present invention also provide a device for determining low-speed emergency braking, comprising:

[0042] The first calculation unit is used to calculate the discrete trajectory of the vehicle at each discrete time point within a future preset time period and the trajectory confidence level corresponding to each discrete trajectory based on the current state information of the vehicle, and to calculate the collision sensitive width corresponding to each discrete trajectory based on the trajectory confidence level and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same.

[0043] The division and determination unit is used to divide the area surrounding the current position of the vehicle, and determine the target division area in the divided area where a collision may occur based on the driving direction of the vehicle.

[0044] The setting unit is used to set an obstacle position coefficient for each of the target obstacles according to the distance between the target obstacle and the vehicle in the target division area, so as to obtain the obstacle position coefficient of each target obstacle;

[0045] The calculation and determination unit is used to calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision sensitive width corresponding to each discrete trajectory, and to determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory.

[0046] The second calculation unit is used to calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient of each target obstacle and its corresponding target collision coefficient, wherein the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient;

[0047] The first determining unit is used to determine whether there is a collision risk between each of the target obstacles and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory.

[0048] The second determining unit is used to determine the timing of emergency braking based on the performance of the vehicle and the discrete trajectory of the target with collision risk if there is a collision risk.

[0049] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0050] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing machine-executable instructions, which, when invoked and executed by a processor, cause the processor to perform the method described in any of the first aspects above.

[0051] In this embodiment of the invention, a method for determining low-speed emergency braking is provided, comprising: calculating discrete trajectories of the vehicle at discrete time points within a future preset time period and the trajectory confidence level corresponding to each discrete trajectory based on the vehicle's current state information; calculating the collision-sensitive width corresponding to each discrete trajectory based on the trajectory confidence level and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same; dividing the area surrounding the vehicle's current position, and determining a target area in the divided area where a collision may occur based on the vehicle's driving direction; setting an obstacle position coefficient for each target obstacle based on the distance between the target obstacle and the vehicle in the target area, thereby obtaining the obstacle position coefficient for each target obstacle. Position coefficient; calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision-sensitive width corresponding to each discrete trajectory, and determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory; calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient and its corresponding target collision coefficient, where the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient; determine whether there is a collision risk between each target obstacle and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory; if there is a collision risk, determine the emergency braking timing based on the vehicle performance and the target discrete trajectory with collision risk. As described above, the low-speed emergency braking determination method of the present invention uses trajectory confidence to characterize the reliability of each discrete trajectory, and calculates the collision-sensitive width corresponding to each discrete trajectory based on the trajectory confidence. This tightens the collision-sensitive width of discrete trajectories with low trajectory confidence, thereby focusing more on the central area, improving accuracy, and avoiding "false braking." In addition, the area surrounding the vehicle's current position is divided into regions, and target regions where collisions may occur are determined from the divided regions. The calculation of obstacles in the divided regions that have no impact on vehicle movement is discarded, reducing the subsequent calculation workload. An obstacle position coefficient is also set for the target obstacles in the target divided regions to characterize the detection accuracy of the sensor. Finally, the target collision coefficient corresponding to each target obstacle is calculated based on the collision-sensitive width corresponding to each discrete trajectory. The risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on the obstacle position coefficient and its corresponding target collision coefficient. The existence of collision risk is determined based on the risk coefficient. The above collision risk determination process is more in line with natural laws, making the final determined emergency braking timing more accurate and alleviating the technical problem of poor accuracy in existing low-speed emergency braking. Attached Figure Description

[0052] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0053] Figure 1 A flowchart illustrating a method for determining low-speed emergency braking according to an embodiment of the present invention;

[0054] Figure 2 A schematic diagram illustrating the calculation of the collision-sensitive width corresponding to each discrete trajectory, provided in an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of the six partitioned regions provided in an embodiment of the present invention;

[0056] Figure 4 This is a schematic diagram illustrating the setting of obstacle position coefficients according to an embodiment of the present invention;

[0057] Figure 5 A schematic diagram illustrating the calculation of the collision coefficient provided in an embodiment of the present invention;

[0058] Figure 6 A schematic diagram of a low-speed emergency braking determination device provided in an embodiment of the present invention;

[0059] Figure 7 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0060] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] Traditional low-speed emergency braking is inaccurate.

[0062] Based on this, in the low-speed emergency braking determination method of the present invention, the reliability of each discrete trajectory is characterized by trajectory confidence, and the collision-sensitive width corresponding to each discrete trajectory is calculated based on the trajectory confidence. This allows the collision-sensitive width of discrete trajectories with low trajectory confidence to be tightened, thereby focusing more on the central area, improving accuracy, and avoiding "false braking". In addition, the area surrounding the current position of the vehicle is divided into regions, and target regions that may collide are determined from the divided regions. The calculation of obstacles in the divided regions that have no impact on the vehicle's movement is discarded, reducing the subsequent calculation workload. An obstacle position coefficient is also set for the target obstacles in the target divided regions to characterize the detection accuracy of the sensor. Finally, the target collision coefficient corresponding to each target obstacle is calculated based on the collision-sensitive width corresponding to each discrete trajectory, and the risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on the obstacle position coefficient and its corresponding target collision coefficient. The existence of collision risk is determined based on the risk coefficient. The above collision risk determination process is more in line with natural laws, making the final determined emergency braking timing more accurate.

[0063] To facilitate understanding of this embodiment, a method for determining low-speed emergency braking disclosed in this embodiment of the invention will first be described in detail.

[0064] Example 1:

[0065] According to an embodiment of the present invention, an embodiment of a method for determining low-speed emergency braking is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0066] Figure 1 This is a flowchart of a method for determining low-speed emergency braking according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0067] Step S102: Calculate the discrete trajectory of the vehicle at each discrete time point within a future preset time period and the trajectory confidence of each discrete trajectory based on the current state information of the vehicle, and calculate the collision sensitive width corresponding to each discrete trajectory based on the trajectory confidence and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same.

[0068] In this embodiment of the invention, the aforementioned future preset time period can be within the next 5 seconds, and the time interval between the aforementioned adjacent discrete time points can be 100ms. That is, there is a discrete trajectory every 100ms within the next 5 seconds, so that 50 discrete trajectories can be obtained in the end. This embodiment of the invention does not limit the specific value of the above parameters.

[0069] The aforementioned trajectory confidence is used to characterize the credibility of the corresponding discrete trajectory. After obtaining the trajectory confidence, the collision sensitivity width corresponding to each discrete trajectory can be calculated based on the trajectory confidence. This tightens the collision sensitivity width of discrete trajectories with low trajectory confidence, thereby focusing more on the central region, improving accuracy, and avoiding "false braking". The process will be described in detail below and will not be repeated here.

[0070] Step S104: Divide the area around the vehicle's current position, and determine the target area where a collision may occur within the divided area according to the vehicle's driving direction.

[0071] Step S106: Set obstacle position coefficients for each target obstacle based on the distance between the target obstacle and the vehicle in the target area, and obtain the obstacle position coefficients for each target obstacle;

[0072] Specifically, the aforementioned target obstacles can be detected by sensors (such as ultrasonic sensors or surround-view cameras). Essentially, the detected obstacle information includes the obstacle's size and angle. Since sensor detection accuracy is limited, the closer the obstacle is to the vehicle, the more accurate the detection. Therefore, obstacle position coefficients are set for each target obstacle based on its distance from the vehicle. These obstacle position coefficients characterize the detection accuracy of the corresponding sensor, improving the accuracy of subsequent collision detection.

[0073] Step S108: Calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision sensitive width corresponding to each discrete trajectory, and determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory.

[0074] Step S110: Calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient of each target obstacle and its corresponding target collision coefficient, wherein the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient;

[0075] Specifically, the risk coefficient not only considers the target collision coefficient, but also the obstacle position coefficient of the target obstacle, which means that the detection accuracy of the sensor is also taken into account, further improving the accuracy of the calculated risk coefficient.

[0076] Step S112: Determine whether there is a collision risk between each target obstacle and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory;

[0077] Specifically, compared to the determination process of binary systems, this process is more in line with natural laws, and the collision risk determined is more accurate and reliable.

[0078] Step S114: If there is a collision risk, determine the timing of emergency braking based on the vehicle's performance and the discrete trajectory of the target with the collision risk.

[0079] In this embodiment of the invention, a method for determining low-speed emergency braking is provided, comprising: calculating discrete trajectories of the vehicle at discrete time points within a future preset time period and the trajectory confidence level corresponding to each discrete trajectory based on the vehicle's current state information; calculating the collision-sensitive width corresponding to each discrete trajectory based on the trajectory confidence level and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same; dividing the area surrounding the vehicle's current position, and determining a target area in the divided area where a collision may occur based on the vehicle's driving direction; setting an obstacle position coefficient for each target obstacle based on the distance between the target obstacle and the vehicle in the target area, thereby obtaining the obstacle position coefficient for each target obstacle. Position coefficient; calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision-sensitive width corresponding to each discrete trajectory, and determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory; calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient and its corresponding target collision coefficient, where the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient; determine whether there is a collision risk between each target obstacle and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory; if there is a collision risk, determine the emergency braking timing based on the vehicle performance and the target discrete trajectory with collision risk. As described above, the low-speed emergency braking determination method of the present invention uses trajectory confidence to characterize the reliability of each discrete trajectory, and calculates the collision-sensitive width corresponding to each discrete trajectory based on the trajectory confidence. This tightens the collision-sensitive width of discrete trajectories with low trajectory confidence, thereby focusing more on the central area, improving accuracy, and avoiding "false braking." In addition, the area surrounding the vehicle's current position is divided into regions, and target regions where collisions may occur are determined from the divided regions. The calculation of obstacles in the divided regions that have no impact on vehicle movement is discarded, reducing the subsequent calculation workload. An obstacle position coefficient is also set for the target obstacles in the target divided regions to characterize the detection accuracy of the sensor. Finally, the target collision coefficient corresponding to each target obstacle is calculated based on the collision-sensitive width corresponding to each discrete trajectory. The risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on the obstacle position coefficient and its corresponding target collision coefficient. The existence of collision risk is determined based on the risk coefficient. The above collision risk determination process is more in line with natural laws, making the final determined emergency braking timing more accurate and alleviating the technical problem of poor accuracy in existing low-speed emergency braking.

[0080] The above provides a brief overview of the method for determining low-speed emergency braking according to the present invention. The specific details involved are described in detail below.

[0081] In an optional embodiment of the present invention, the discrete trajectory of the vehicle at each discrete time point within a preset future time period and the trajectory confidence level corresponding to each discrete trajectory are calculated based on the vehicle's current state information, specifically including the following steps:

[0082] (1) Calculation formula based on the head angle of the vehicle [i] =HeadAng [i-1] +YawRate*T calculates the vehicle's head angle at discrete time points within a preset future time period, where HeadAng... [i] HeadAng represents the vehicle's head angle at the i-th discrete time point within a preset future time period. [i-1] This represents the vehicle's head angle at the (i-1)th discrete time point within a preset future time period, where YawRate represents the angular velocity in the current state information, and T represents the time interval. When i is 1, HeadAng... [i-1] This indicates the current vehicle heading angle in the current status information;

[0083] Specifically, the time interval is 100ms as described in step S102 above.

[0084] (2) Calculate X based on the vehicle's X coordinate. [i] =X [i-1] +V [i] *cos(HeadAng [i] )*T calculates the x-coordinate of the vehicle at each discrete time point within a preset future time period, where X [i] X represents the X coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the X-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] X represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, X... [i-1] This indicates the current x-coordinate of the vehicle in the current status information;

[0085] Specifically, V [i] =V [i-1] +Lgt Acc *T, where V [i] V represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i-1] Lgt represents the velocity of the vehicle at the (i-1)th discrete time point within a preset future time period. Acc V represents the longitudinal acceleration in the current state information, T represents the time interval, and when i is 1, V[i-1] This indicates the current speed of the vehicle in the current status information.

[0086] (3) Calculate the formula Y based on the vehicle's Y coordinate. [i] =Y [i-1] +V [i] *sin(HeadAng [i] )*T calculates the Y-coordinate of the vehicle at each discrete time point within a preset future time period, where Y [i] Y represents the Y-coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the Y-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] Y represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, Y... [i-1] This indicates the current Y-coordinate of the vehicle in the current status information;

[0087] Specifically, V [i] =V [i-1] +Lgt Acc *T, where V [i] V represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i-1] Lgt represents the speed of the vehicle at the (i-1)th discrete time point within a preset future time period. Acc V represents the longitudinal acceleration in the current state information, T represents the time interval, and when i is 1, V [i-1] This indicates the current speed of the vehicle in the current status information.

[0088] (4) The vehicle's front angle, X coordinate, and Y coordinate at each discrete time point within a future preset time period are taken as the discrete trajectory of the vehicle at each discrete time point within a future preset time period.

[0089] (5) Calculate the confidence level based on the trajectory confidence formula. [i] =A1*(Distance) Pred -Distance [i] ) / Distance Pred +A2*(Lgt AccMax -Lgt Acc ) / Lgt AccMax +A3*(Steer SpdMax -Steer Spd ) / Steer SpdMax

[0090] Calculate the trajectory confidence score for each discrete trajectory, where Confidence [i] Distance represents the trajectory confidence of the discrete trajectory at the i-th discrete time point. Pred Distance represents the total length of the discrete trajectory corresponding to the current state information. [i] Lgt represents the length of the discrete trajectory at the i-th discrete time point. AccMax Lgt represents the maximum longitudinal acceleration. Acc This represents the longitudinal acceleration in the current state information, Steer. SpdMax This indicates the maximum turning speed of the steering wheel, Steer Spd This indicates the steering wheel rotation speed in the current status information, and A1, A2, and A3 represent preset weighting coefficients.

[0091] Specifically, trajectory confidence has three weighted dimensions. The first dimension is related to distance; the farther the predicted driving distance, the lower the trajectory confidence. The second dimension is related to longitudinal acceleration; the greater the absolute value of the vehicle's longitudinal acceleration, the lower the trajectory confidence. The third dimension is related to steering wheel rotation speed; the greater the absolute value of the steering wheel rotation speed, the lower the trajectory confidence. Based on these three dimensions, a trajectory confidence calculation formula was designed. That is, the farther the discrete trajectory, the greater the acceleration / deceleration, and the higher the steering wheel rotation speed, the lower the trajectory confidence. In other words, the farther the distance, the greater the acceleration / deceleration, and the faster the steering wheel rotation speed, the lower the reliability of the predicted discrete trajectory. These three dimensions are associated with three weight coefficients, A1, A2, and A3, ensuring that the output trajectory confidence ranges between [0, 1].

[0092] In an optional embodiment of the present invention, the collision-sensitive width corresponding to each discrete trajectory is calculated based on the confidence level of each trajectory and the width of the vehicle, specifically including the following steps:

[0093] The collision-sensitive width is calculated using the formula: Collision-sensitive width = Vehicle width × Trajectory confidence level. This formula calculates the collision-sensitive width corresponding to each discrete trajectory.

[0094] Specifically, such as Figure 2 As shown, the arrows indicate the vehicle's direction of travel, the leftmost rectangle represents the vehicle's current trajectory, and the subsequent rectangles represent the predicted / calculated discrete trajectories (only three are shown). The width of each rectangle represents the collision-sensitive width corresponding to that discrete trajectory. It can be seen that as the predicted discrete trajectories become increasingly inaccurate, the collision-sensitive width becomes increasingly narrow (i.e., the collision-sensitive width of discrete trajectories with low confidence narrows), focusing more on the central region.

[0095] In an optional embodiment of the present invention, the area surrounding the current location of the vehicle is divided, specifically including the following steps:

[0096] The area surrounding the vehicle is divided into six zones based on the horizontal lines of the front bumper, rear axle, and rear bumper.

[0097] Specifically, such as Figure 3 As shown, FL represents the left front axle, FR represents the right front axle, RL represents the left rear axle, and RR represents the right rear axle, with six division regions shown.

[0098] After dividing the vehicle into six regions, the target regions where collisions may occur are further determined within these regions based on the vehicle's direction of travel (assuming the vehicle is a front-wheel steering vehicle), as shown in the table below:

[0099] driving direction Target area division Forward + Straight Area 1 Previous + Left Turn Area 1 + Area 2 + Area 5 Forward + Right Turn Area 1 + Area 6 + Area 3 Back up + go straight Area 4 Back up + turn left Area 4 + Area 3 + Area 6 Back + Right Area 4 + Area 5 + Area 2

[0100] In an optional embodiment of the present invention, an obstacle position coefficient is set for each target obstacle based on the distance between the target obstacle and the vehicle in the target division area, specifically including the following steps:

[0101] (1) If the distance between the first target obstacle and the vehicle is not greater than the first preset distance, then the obstacle position coefficient of the first target obstacle is set to 1;

[0102] (2) If the distance between the second target obstacle and the vehicle is greater than the first preset distance and less than the second preset distance, the obstacle position coefficient of the second target obstacle is set according to the preset decreasing rule. The preset decreasing rule is that when the distance is between the first preset distance and the second preset distance, the obstacle position coefficient is linearly decreased from 1 to 0 from near to far.

[0103] (3) If the distance between the third target obstacle and the vehicle is greater than the second preset distance, the obstacle position coefficient of the third target obstacle is set to 0.

[0104] Specifically, based on the detection characteristics (effective detection range) of the sensors (ultrasonic + surround-view camera), the position coefficient of obstacles within a straight-line distance d1 around the vehicle within the effective range is assigned a value of 1; the position coefficient of obstacles with a straight-line distance between d1 and d2 decreases linearly from 1 to 0 from near to far; the position coefficient of obstacles with a straight-line distance greater than d2 from the vehicle is set to 0. For example... Figure 4 As shown.

[0105] In an optional embodiment of the present invention, the collision coefficient between each target obstacle and each discrete trajectory is calculated based on the collision-sensitive width corresponding to each discrete trajectory, and the target collision coefficient corresponding to each target obstacle is determined according to the collision coefficient between each target obstacle and each discrete trajectory, specifically including the following steps:

[0106] (1) Calculate the collision coefficient between each target obstacle and each discrete trajectory according to the collision coefficient calculation formula Collision_Coe=CE / AE, where Collision_Coe represents the collision coefficient between a target obstacle and a discrete trajectory, CE represents the overlap width between the target obstacle and the discrete trajectory, and AE represents half of the collision sensitive width corresponding to the discrete trajectory.

[0107] Specifically, as illustrated in the example above, the algorithm executes once, resulting in 50 discrete trajectories. If the number of identified target obstacles is 10, then the collision coefficient between each target obstacle and each of the 50 discrete trajectories can be calculated. Thus, for each target obstacle, 50 collision coefficients are obtained, each representing the collision coefficient between the target obstacle and its corresponding discrete trajectory. Figure 5 The diagram illustrates the calculation of the collision coefficient between a target obstacle and a discrete trajectory. The smaller rectangle represents the target obstacle, and the larger rectangle represents the discrete trajectory. Based on the size and angle of the target obstacle, the size of the discrete trajectory (width being the collision-sensitive width and length being the vehicle length), and the vehicle's frontal angle, the overlap width between the target obstacle and the discrete trajectory can be calculated. Then, the collision coefficient between the target obstacle and the discrete trajectory can be calculated using the aforementioned formula.

[0108] (2) Take the maximum collision coefficient among the collision coefficients of each target obstacle and each discrete trajectory as the target collision coefficient corresponding to each target obstacle.

[0109] Specifically, as shown above, for each target obstacle, 50 collision coefficients were obtained, and the largest collision coefficient among them was taken as the target collision coefficient for each target obstacle.

[0110] In an optional embodiment of the present invention, the risk coefficient of each target obstacle relative to the discrete trajectory of the target is calculated based on the obstacle position coefficient of each target obstacle and its corresponding target collision coefficient, specifically including the following steps:

[0111] The risk coefficient is calculated using the formula: Risk coefficient = Obstacle position coefficient × Target collision coefficient. This formula calculates the risk coefficient of each target obstacle relative to the discrete trajectory of the target.

[0112] Specifically, the risk coefficient considers not only the target collision coefficient but also the obstacle position coefficient of the target obstacle. The larger the obstacle position coefficient, the higher the accuracy of the detected target obstacle, and the higher the corresponding risk coefficient should be. Therefore, performing the above product calculation can improve the accuracy of the risk coefficient.

[0113] In an optional embodiment of the present invention, determining whether each target obstacle poses a collision risk with the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory specifically includes the following steps:

[0114] If the risk coefficient is greater than the preset risk threshold, then the corresponding target obstacle is determined to pose a collision risk to the target discrete trajectory.

[0115] In an optional embodiment of the present invention, the vehicle performance includes: the time required for the vehicle to complete braking; and determining the emergency braking timing based on the vehicle performance and the discrete trajectory of the target with collision risk, specifically including the following steps:

[0116] (1) Determine the time when the vehicle will collide in the future based on the discrete trajectory of the target with collision risk;

[0117] Specifically, as in the example above, if the discrete trajectory of the target with collision risk is the discrete trajectory at the 4th discrete time point, then it can be known that the time when the vehicle will collide in the future is 400ms, because there is a discrete trajectory for every 100ms, and the time when the vehicle will collide in the future corresponding to the discrete trajectory at the 4th discrete time point is 400ms.

[0118] (2) Determine the timing of emergency braking based on the time required for the vehicle to complete braking and the time when the vehicle will collide in the future.

[0119] The method for determining low-speed emergency braking in this invention includes the following improvements:

[0120] (1) Adding acceleration and deceleration and steering wheel speed to the trajectory confidence can dynamically lock the effective trajectory, improve accuracy, and avoid "false braking";

[0121] (2) Introduce obstacle position coefficient. 1) Divide the obstacle into regions and discard obstacles that have no effect on the vehicle's movement to reduce the amount of calculation; 2) The farther away the obstacle is, the smaller the obstacle position coefficient is, which can be used to characterize the detection accuracy of the sensor (the farther away, the less accurate);

[0122] (3) Traditional obstacle selection is a binary system. This invention describes obstacle selection as a probability model and expresses collision risk in numerical form (i.e., risk coefficient), which is more in line with the laws of nature.

[0123] Example 2:

[0124] This invention also provides a device for determining low-speed emergency braking. This device is mainly used to execute the method for determining low-speed emergency braking provided in Embodiment 1 of this invention. The following is a detailed description of the device for determining low-speed emergency braking provided in this invention.

[0125] Figure 6 This is a schematic diagram of a low-speed emergency braking determination device according to an embodiment of the present invention, as shown below. Figure 6 As shown, the device mainly includes: a first calculation unit 10, a division and determination unit 20, a setting unit 30, a calculation and determination unit 40, a second calculation unit 50, a first determination unit 60, and a second determination unit 70, wherein:

[0126] The first calculation unit is used to calculate the discrete trajectory of the vehicle at each discrete time point within a future preset time period and the trajectory confidence level corresponding to each discrete trajectory based on the current state information of the vehicle, and to calculate the collision sensitive width corresponding to each discrete trajectory based on the trajectory confidence level and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same.

[0127] The division and determination unit is used to divide the area surrounding the vehicle's current position and determine the target division area where a collision may occur within the divided area according to the vehicle's driving direction.

[0128] The setting unit is used to set the obstacle position coefficient for each target obstacle according to the distance between the target obstacle and the vehicle in the target division area, so as to obtain the obstacle position coefficient of each target obstacle;

[0129] The calculation and determination unit is used to calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision sensitive width corresponding to each discrete trajectory, and to determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory.

[0130] The second calculation unit is used to calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient of each target obstacle and its corresponding target collision coefficient, wherein the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient;

[0131] The first determining unit is used to determine whether there is a collision risk between each target obstacle and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory.

[0132] The second determining unit is used to determine the timing of emergency braking based on the vehicle's performance and the discrete trajectory of the target with collision risk if there is a collision risk.

[0133] In this embodiment of the invention, a low-speed emergency braking determination device is provided, comprising: calculating discrete trajectories of the vehicle at discrete time points within a future preset time period and trajectory confidence levels corresponding to each discrete trajectory based on the vehicle's current state information; calculating collision-sensitive widths corresponding to each discrete trajectory based on the trajectory confidence levels and the vehicle's width, wherein the time interval between adjacent discrete time points is the same; dividing the area surrounding the vehicle's current position; determining potential collision target areas within the divided areas based on the vehicle's driving direction; and setting obstacle position coefficients for each target obstacle based on the distance between the target obstacle and the vehicle within the target area, thereby obtaining the obstacle position coefficients for each target obstacle. Position coefficient; calculate the collision coefficient between each target obstacle and each discrete trajectory based on the collision-sensitive width corresponding to each discrete trajectory, and determine the target collision coefficient corresponding to each target obstacle based on the collision coefficient between each target obstacle and each discrete trajectory; calculate the risk coefficient of each target obstacle relative to the target discrete trajectory based on the obstacle position coefficient and its corresponding target collision coefficient, where the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient; determine whether there is a collision risk between each target obstacle and the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory; if there is a collision risk, determine the emergency braking timing based on the vehicle performance and the target discrete trajectory with collision risk. As described above, the low-speed emergency braking determination device of the present invention uses trajectory confidence to characterize the reliability of each discrete trajectory, and calculates the collision-sensitive width corresponding to each discrete trajectory based on the trajectory confidence. This allows the collision-sensitive width of discrete trajectories with low trajectory confidence to be tightened, thereby focusing more on the central area, improving accuracy, and avoiding "false braking." In addition, the area surrounding the vehicle's current position is divided into regions, and target regions where collisions may occur are determined from the divided regions. The calculation of obstacles in the divided regions that have no impact on vehicle movement is discarded, reducing the subsequent calculation workload. An obstacle position coefficient is also set for the target obstacles in the target divided regions to characterize the detection accuracy of the sensor. Finally, the target collision coefficient corresponding to each target obstacle is calculated based on the collision-sensitive width corresponding to each discrete trajectory. The risk coefficient of each target obstacle relative to the target discrete trajectory is calculated based on the obstacle position coefficient and its corresponding target collision coefficient. The existence of collision risk is determined based on the risk coefficient. The above collision risk determination process is more in line with natural laws, making the final determined emergency braking timing more accurate and alleviating the technical problem of poor accuracy in existing low-speed emergency braking.

[0134] Optionally, the first calculation unit is also used to: calculate the formula HeadAng based on the vehicle's front angle. [i] =HeadAng [i-1]+YawRate*T calculates the vehicle's head angle at discrete time points within a preset future time period, where HeadAng... [i] HeadAng represents the vehicle's head angle at the i-th discrete time point within a preset future time period. [i-1] This represents the vehicle's head angle at the (i-1)th discrete time point within a preset future time period, where YawRate represents the angular velocity in the current state information, and T represents the time interval. When i is 1, HeadAng... [i-1] This indicates the current vehicle front angle in the current status information; the formula X is calculated based on the vehicle's X coordinate. [i] =X [i-1] +V [i] *cos(HeadAng [i]) *T calculates the x-coordinate of the vehicle at each discrete time point within a preset future time period, where X [i] X represents the X coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the x-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] X represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, X... [i-1] This represents the vehicle's current x-coordinate in the current status information; the formula Y is calculated based on the vehicle's Y-coordinate. [i] =Y [i-1] +V [i] *sin(HeadAng [i] )*T calculates the Y-coordinate of the vehicle at each discrete time point within a preset future time period, where Y [i] Y represents the Y-coordinate of the vehicle at the i-th discrete time point within a preset future time period. [i-1] V represents the Y-coordinate of the vehicle at the (i-1)th discrete time point within a preset future time period. [i] HeadAng represents the speed of the vehicle at the i-th discrete time point within a preset future time period. [i] Y represents the vehicle's front-end angle at the i-th discrete time point within a preset future time period, where T represents the time interval. When i is 1, Y... [i-1] This represents the vehicle's current Y-coordinate in the current state information; the vehicle's frontal angle, X-coordinate, and Y-coordinate at each discrete time point within a preset future time period are used as the vehicle's discrete trajectory at each discrete time point within the preset future time period; the confidence level is calculated using the trajectory confidence formula. [i]=A1*(Distance) Pred -Distance [i] ) / Distance Pred +A2*(Lgt AccMax -Lgt Acc ) / Lgt AccMax +A3*(Steer SpdMax -Steer Spd ) / Steer SpdMax

[0135] Calculate the trajectory confidence score for each discrete trajectory, where Confidence [i] Distance represents the trajectory confidence of the discrete trajectory at the i-th discrete time point. Pred Distance represents the total length of the discrete trajectory corresponding to the current state information. [i] Lgt represents the length of the discrete trajectory at the i-th discrete time point. AccMax Lgt represents the maximum longitudinal acceleration. Acc This represents the longitudinal acceleration in the current state information, Steer. SpdMax This indicates the maximum turning speed of the steering wheel, Steer Spd The steering wheel rotation speed is indicated in the current status information. A1, A2, and A3 represent preset weighting coefficients. The collision-sensitive width is calculated based on the following formula: Collision-sensitive width = Vehicle width × Trajectory confidence level. The collision-sensitive width corresponding to each discrete trajectory is calculated.

[0136] Optionally, the division and determination unit is also used to: divide the area around the vehicle into six division zones based on the horizontal line of the front bumper, the horizontal line of the rear axle, and the horizontal line of the rear bumper.

[0137] The setting unit is further configured to: if the distance between the first target obstacle and the vehicle is not greater than the first preset distance, set the obstacle position coefficient of the first target obstacle to 1; if the distance between the second target obstacle and the vehicle is greater than the first preset distance and less than the second preset distance, set the obstacle position coefficient of the second target obstacle according to a preset decreasing rule, wherein the preset decreasing rule is that when the distance is between the first preset distance and the second preset distance, the obstacle position coefficient is linearly decreased from 1 to 0 from near to far; if the distance between the third target obstacle and the vehicle is greater than the second preset distance, set the obstacle position coefficient of the third target obstacle to 0.

[0138] Optionally, the calculation and determination unit is further configured to: calculate the collision coefficient between each target obstacle and each discrete trajectory according to the collision coefficient calculation formula Collision_Coe=CE / AE, where Collision_Coe represents the collision coefficient between a target obstacle and a discrete trajectory, CE represents the overlap width between the target obstacle and the discrete trajectory, and AE represents half of the collision-sensitive width corresponding to the discrete trajectory; and take the maximum collision coefficient among the collision coefficients between each target obstacle and each discrete trajectory as the target collision coefficient corresponding to each target obstacle.

[0139] Optionally, the second calculation unit is also used to: calculate the risk coefficient of each target obstacle relative to the discrete trajectory of the target based on the formula: Risk coefficient = Obstacle position coefficient × Target collision coefficient.

[0140] Optionally, the first determining unit is further configured to: if the risk coefficient is greater than a preset risk threshold, determine that the corresponding target obstacle poses a collision risk to the target discrete trajectory.

[0141] Optionally, the vehicle's performance includes: the time required for the vehicle to complete braking; the second determining unit is also used to: determine the time when the vehicle will collide in the future based on the discrete trajectory of the target with collision risk; and determine the timing of emergency braking based on the time required for the vehicle to complete braking and the time when the vehicle will collide in the future.

[0142] The device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0143] like Figure 7 As shown in the embodiment of this application, an electronic device 600 includes a processor 601, a memory 602, and a bus. The memory 602 stores machine-readable instructions executable by the processor 601. When the electronic device is running, the processor 601 communicates with the memory 602 via the bus, and the processor 601 executes the machine-readable instructions to perform the steps of the low-speed emergency braking determination method described above.

[0144] Specifically, the memory 602 and processor 601 mentioned above can be general-purpose memory and processor, without any specific limitations. When the processor 601 runs the computer program stored in the memory 602, it can execute the above-mentioned method for determining low-speed emergency braking.

[0145] The processor 601 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 601 or by instructions in software form. The processor 601 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 602, and processor 601 reads the information from memory 602 and, in conjunction with its hardware, completes the steps of the above method.

[0146] Corresponding to the above-described method for determining low-speed emergency braking, this application also provides a computer-readable storage medium storing machine-executable instructions. When these machine-executable instructions are invoked and executed by a processor, they cause the processor to perform the steps of the above-described method for determining low-speed emergency braking.

[0147] The low-speed emergency braking determination device provided in this application embodiment can be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this application embodiment are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0148] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0149] For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0150] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0151] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0152] If the aforementioned function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the low-speed emergency braking determination method described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0153] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0154] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method of determining a low-speed emergency braking, characterized in that, The method comprises the following steps: calculating discrete trajectories of the vehicle at discrete time points in a preset future time according to current state information of the vehicle, and calculating trajectory confidence degrees corresponding to the discrete trajectories according to the trajectory confidence degrees and a width of the vehicle, wherein a time interval between adjacent discrete time points is the same; dividing a surrounding area of a current position of the vehicle, and determining a target division area in which a collision is likely to occur in the division area according to a driving direction of the vehicle; setting an obstacle position coefficient of each target obstacle according to a distance between the target obstacle and the vehicle in the target division area, to obtain the obstacle position coefficient of each target obstacle; calculating a collision coefficient of each target obstacle and each discrete trajectory based on the collision sensitive width corresponding to each discrete trajectory, and determining a target collision coefficient corresponding to each target obstacle according to the collision coefficient of each target obstacle and each discrete trajectory; calculating a risk coefficient of each target obstacle relative to a target discrete trajectory according to the obstacle position coefficient of each target obstacle and the target collision coefficient corresponding to the target obstacle, wherein the target discrete trajectory is a discrete trajectory corresponding to the target collision coefficient; determining whether each target obstacle has a collision risk relative to the target discrete trajectory based on the risk coefficient of each target obstacle relative to the target discrete trajectory; if there is a collision risk, determining an emergency braking timing according to a performance of the vehicle and the target discrete trajectory with the collision risk; wherein the collision sensitive width corresponding to each discrete trajectory is calculated according to the trajectory confidence degree and the width of the vehicle, comprising: calculating the collision sensitive width corresponding to each discrete trajectory according to a collision sensitive width calculation formula: collision sensitive width = width of the vehicle × trajectory confidence degree; wherein the obstacle position coefficient of each target obstacle is set according to the distance between the target obstacle and the vehicle in the target division area, comprising: if a distance between a first target obstacle in the target obstacles and the vehicle is not greater than a first preset distance, setting the obstacle position coefficient of the first target obstacle as 1; if a distance between a second target obstacle in the target obstacles and the vehicle is greater than the first preset distance and less than a second preset distance, setting the obstacle position coefficient of the second target obstacle according to a preset decreasing rule, wherein the preset decreasing rule is that when the distance is between the first preset distance and the second preset distance, the obstacle position coefficient is linearly decreased from 1 to 0 from near to far; if a distance between a third target obstacle in the target obstacles and the vehicle is greater than the second preset distance, setting the obstacle position coefficient of the third target obstacle as 0.

2. The method of claim 1, wherein, calculating the discrete trajectories of the vehicle at the discrete time points in the preset future time according to the current state information of the vehicle, and calculating the trajectory confidence degrees corresponding to the discrete trajectories, comprises: According to the vehicle head angle calculation formula calculating a vehicle head angle of the vehicle at each discrete time point within a future predetermined time, denotes a vehicle head angle of the vehicle at an i-th discrete time point within the future predetermined time, denotes a vehicle head angle of the vehicle at an (i-1)-th discrete time point within the future predetermined time, denotes an angular velocity in the current state information, denotes the time interval, when i is 1, denotes a current vehicle head angle in the current state information; X-coordinate calculation formula according to the X-coordinate of the vehicle calculating the X-coordinate of the vehicle at each discrete time point in the future predetermined time, denotes the X-coordinate of the vehicle at the i-th discrete time point in the future predetermined time, denotes the X-coordinate of the vehicle at the (i-1)-th discrete time point in the future predetermined time, denotes the speed of the vehicle at the i-th discrete time point in the future predetermined time, denotes the vehicle head angle of the vehicle at the i-th discrete time point in the future predetermined time, denotes the time interval, when i is 1, denotes the current X-coordinate of the vehicle in the current state information; Y coordinate calculation formula according to the Y coordinate of the vehicle calculating the Y coordinate of the vehicle at each discrete time point in the future preset time, denotes the Y coordinate of the vehicle at the i-th discrete time point in the future preset time, denotes the Y coordinate of the vehicle at the (i-1)-th discrete time point in the future preset time, denotes the speed of the vehicle at the i-th discrete time point in the future preset time, denotes the vehicle head angle of the vehicle at the i-th discrete time point in the future preset time, denotes the time interval, when i is 1, denotes the current Y coordinate of the vehicle in the current state information; the vehicle head angle of each discrete time point of the vehicle within a preset future time, the X coordinate of each discrete time point of the vehicle within a preset future time, and the Y coordinate of each discrete time point of the vehicle within a preset future time are taken as discrete trajectories of each discrete time point of the vehicle within a preset future time; According to the trajectory confidence calculation formula Calculate the trajectory confidence corresponding to each of the discrete trajectories, wherein, denotes the trajectory confidence of the discrete trajectory at the i-th discrete time point, denotes the total length of the discrete trajectory corresponding to the current state information, denotes the length of the discrete trajectory at the i-th discrete time point, denotes the maximum value of the longitudinal acceleration, denotes the longitudinal acceleration in the current state information, denotes the maximum rotation speed of the steering wheel, denotes the rotation speed of the steering wheel in the current state information, , , denotes a preset weight coefficient.

3. The method of claim 1, wherein, the surrounding area of the current position of the vehicle is divided, including: the surrounding area of the vehicle is divided into six division areas according to the horizontal line of the front bumper, the horizontal line of the rear axle, and the horizontal line of the rear bumper of the vehicle.

4. The method of claim 1, wherein, a collision coefficient of each target obstacle and each discrete trajectory is calculated based on the collision-sensitive width corresponding to each discrete trajectory, and a target collision coefficient corresponding to each target obstacle is determined according to the collision coefficient of each target obstacle and each discrete trajectory, including: a collision coefficient of each target obstacle and each discrete trajectory is calculated according to a collision coefficient calculation formula Collision_Coe = CE / AE, wherein Collision_Coe represents the collision coefficient of one target obstacle and one discrete trajectory, CE represents the overlap width of the target obstacle and the discrete trajectory, and AE represents half of the collision-sensitive width corresponding to the discrete trajectory; the maximum collision coefficient in the collision coefficient of each target obstacle and each discrete trajectory is taken as the target collision coefficient corresponding to each target obstacle.

5. The method of claim 1, wherein, a risk coefficient of each target obstacle relative to a target discrete trajectory is calculated according to the obstacle position coefficient of each target obstacle and the target collision coefficient corresponding thereto, including: a risk coefficient of each target obstacle relative to a target discrete trajectory is calculated according to a risk coefficient calculation formula: risk coefficient = obstacle position coefficient × target collision coefficient.

6. The method of claim 1, wherein, whether each target obstacle has a collision risk relative to a target discrete trajectory is determined based on the risk coefficient of each target obstacle relative to a target discrete trajectory, including: if the risk coefficient is greater than a preset risk threshold, it is determined that the corresponding target obstacle has a collision risk relative to the target discrete trajectory.

7. The method of claim 1, wherein, the performance of the vehicle includes the time required for the vehicle to complete braking, and an emergency braking timing is determined according to the performance of the vehicle and the target discrete trajectory having a collision risk, including: the time when the vehicle will have a collision in the future is determined according to the target discrete trajectory having a collision risk; the emergency braking timing is determined according to the time required for the vehicle to complete braking and the time when the vehicle will have a collision in the future.

8. A device for determining a low-speed emergency braking, characterized in that including: a first calculation unit is configured to calculate discrete trajectories of each discrete time point of the vehicle within a preset future time and trajectory confidence degrees corresponding to each discrete trajectory according to current state information of the vehicle, and calculate collision-sensitive widths corresponding to each discrete trajectory according to each trajectory confidence degree and the width of the vehicle, wherein the time interval between adjacent discrete time points is the same; a division and determination unit is configured to divide the surrounding area of the current position of the vehicle, and determine a target division area in which a collision is likely to occur in the division area according to the driving direction of the vehicle. The setting unit is configured to set a barrier position coefficient of each target barrier according to a distance between the target barrier and the vehicle in the target division area, so as to obtain the barrier position coefficient of each target barrier; The calculating and determining unit is configured to calculate a collision coefficient of each target barrier and each discrete trajectory based on a collision-sensitive width corresponding to each discrete trajectory, and determine a target collision coefficient of each target barrier according to the collision coefficient of each target barrier and each discrete trajectory; The second calculating unit is configured to calculate a risk coefficient of each target barrier relative to a target discrete trajectory according to the barrier position coefficient of each target barrier and the target collision coefficient corresponding thereto, wherein the target discrete trajectory is the discrete trajectory corresponding to the target collision coefficient; The first determining unit is configured to determine whether each target barrier has a collision risk relative to the target discrete trajectory based on the risk coefficient of each target barrier relative to the target discrete trajectory; The second determining unit is configured to determine an emergency braking timing according to a performance of the vehicle and the target discrete trajectory having the collision risk if the collision risk exists. The first calculating unit is further configured to calculate the collision-sensitive width corresponding to each discrete trajectory according to a collision-sensitive width calculation formula: collision-sensitive width = width of the vehicle × trajectory confidence. The setting unit is further configured to set the barrier position coefficient of a first target barrier in the target barriers to 1 if a distance between the first target barrier and the vehicle is not greater than a first preset distance, set the barrier position coefficient of a second target barrier in the target barriers according to a preset decreasing rule if a distance between the second target barrier and the vehicle is greater than the first preset distance and less than a second preset distance, and set the barrier position coefficient of a third target barrier in the target barriers to 0 if a distance between the third target barrier and the vehicle is greater than the second preset distance, wherein the preset decreasing rule is to linearly decrease the barrier position coefficient from 1 to 0 from near to far when the distance is between the first preset distance and the second preset distance.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores machine executable instructions, and the machine executable instructions cause the processor to execute the method of any one of claims 1 to 7 when the machine executable instructions are invoked and executed by the processor.

Images