CN116674548A

CN116674548A - Steering collision avoidance path determining method and device

Info

Publication number: CN116674548A
Application number: CN202310524321.0A
Authority: CN
Inventors: 徐闯; 田广丰; 成昊; 刘勇; 屠科
Original assignee: Suzhou Changxing Zhijia Automobile Technology Co ltd
Current assignee: Suzhou Changxing Zhijia Automobile Technology Co ltd
Priority date: 2023-05-10
Filing date: 2023-05-10
Publication date: 2023-09-01
Anticipated expiration: 2043-05-10
Also published as: CN116674548B

Abstract

The embodiment of the invention provides a method and a device for determining a steering collision avoidance path. The method comprises the following steps: according to the position of the effective target and the maximum acceleration of the vehicle, calculating the steering track of the vehicle in the steering collision avoidance time period of the vehicle aiming at each effective target; predicting a target motion track of each effective target in a steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-steering track has collision risk or not according to the self-steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-steering track; and screening the steering collision avoidance path of the self-vehicle from the first candidate track list according to the collision risk assessment result. The method and the device for planning the path are reasonable and reliable, optimize the control logic of automatic emergency steering, and improve the performance of products for assisting driving.

Description

Steering collision avoidance path determining method and device

Technical Field

The invention relates to the technical field of auxiliary driving, in particular to a method and a device for determining a steering collision avoidance path.

Background

In intelligent driving and assisted driving technologies, driving safety has been a concern. At present, most passenger vehicles are mainly braked under emergency working conditions through an automatic emergency brake (Autonomous Emergency Braking, AEB) system, so that most dangerous accidents are avoided, but a part of emergency working conditions cannot be avoided by the current AEB system, and more preparation time is given to a driver compared with braking of emergency steering (Emergency Steering, ES), so that the ES system is generated.

Compared with the AEB system, the avoidance action of the ES system is more complex, and the evaluation of surrounding environments such as obstacles is more difficult. If the planning and screening algorithm of the steering collision avoidance path of the self-vehicle is improperly used, the vehicle is easy to be in dangerous conditions, so that the planning of the steering collision avoidance path, the collision risk assessment with other obstacles, the screening of the collision avoidance path and the like are of great importance.

At present, the calculation of the steering collision avoidance track mainly comprises two types: in the control method for the reference emergency lane keeping, when AES is activated, a steering wheel angle with a fixed value is applied to a front main target in a direction away from the target, and after a certain time is maintained, the steering wheel angle is applied in the opposite direction to enable the vehicle to return; another control method referring to automatic emergency braking is to use a sectional control method for a main target in front, and constant lateral acceleration is used in each section to control steering and return of the vehicle.

The current collision risk assessment method is also simpler: according to the surrounding environment information of the vehicle obtained by a camera, a radar and other sensors, firstly judging whether the adjacent lanes at two sides have targets, and if the adjacent lanes at the left and right only have other targets at one side, carrying out emergency steering on the adjacent lanes without targets; if other objects exist in the left lane and the right lane, respectively calculating the values of the lateral safety distances of left and right steering, and if the safety distances are larger than a set threshold value, avoiding danger after lane change, and performing lane change steering on the lane; if the safety distance conditions on the two sides are not met, steering is not performed.

However, the existing steering avoidance trajectory planning is mainly modified on the basis of the original function control algorithm, the algorithm strategy is too simple, and the accessibility of steering avoidance cannot be ensured due to the discontinuous acceleration; the algorithm lacks the prediction of the motion state of the main target and the evaluation or evaluation algorithm of the surrounding environment is too simple, so that collision avoidance can be realized under a certain scene, but the steering collision avoidance safety cannot be ensured in principle.

Disclosure of Invention

Aiming at the defects in the prior art, the embodiment of the invention provides a steering collision avoidance path determining method and device.

In a first aspect, an embodiment of the present invention provides a method for determining a steering collision avoidance path, including:

calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition;

predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target;

traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks;

and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

The method as above, optionally, further comprising:

predicting lane line tracks in the steering collision avoidance time period according to the lane line attribute information;

traversing each lane line track, evaluating whether each self-vehicle steering track in the first candidate track list has a risk of crossing a lane line, and determining a second candidate track list meeting the risk evaluation of crossing the lane line from the first candidate track list;

Correspondingly, the screening the steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result includes:

and screening a steering collision avoidance path of the own vehicle from the second candidate track list according to the collision risk assessment result.

According to the method, optionally, according to the position of the effective target and the maximum acceleration of the own vehicle, calculating the steering track of the own vehicle in the steering collision avoidance time period of the own vehicle for each effective target, including:

aiming at each effective target, calculating the transverse displacement of the vehicle required to move at the steering collision avoidance critical point according to the transverse position of the effective target;

calculating a transverse path track of the steering collision avoidance of the vehicle according to the transverse displacement and the maximum transverse acceleration of the vehicle;

determining a longitudinal path track of the vehicle steering collision avoidance according to the current longitudinal speed of the vehicle;

and determining the steering track of the vehicle according to the transverse path track and the longitudinal path track.

The method, optionally, the calculating the lateral displacement of the vehicle required to move at the critical point of steering collision avoidance according to the lateral position of the effective target includes:

calculating the lateral displacement of the vehicle required to move at the steering collision avoidance critical point according to the formula (1):

Y_end=posny+0.5·objwidth+0.5·egowwidth+widthmargin formula (1)

Wherein Y_END is the transverse displacement of the required movement of the bicycle; posnY is the lateral displacement of the longitudinal axis center line of the vehicle and the effective target; objWidth is the target width of the effective target; egoWidth is the width of the own vehicle; widthMargin is a preset width margin.

According to the above method, optionally, the calculating the lateral path track of the steering collision avoidance of the vehicle according to the lateral displacement and the maximum lateral acceleration of the vehicle comprises the following steps:

determining the vehicle maximum lateral acceleration according to formula (2):

ay_max=min (ay_limit, b1·g, b2·μ·g) formula (2)

Wherein ay_max is the maximum lateral acceleration of the vehicle; ay_limit is the upper limit value of the lateral acceleration of the vehicle; g is gravity acceleration; mu is the friction coefficient of the current ground, b1 is a first coefficient, and b2 is a second coefficient;

determining the transverse path trajectory according to equation (3):

PosnY_Ego＝a0+a1·t+a2·t ² +a3·t ³ +…+aN·t ^N ，t∈[0,T]formula (3)

Wherein PosnY_Ego is the lateral position of the own vehicle; a0-aN are coefficients of the transverse N-time curve track of the vehicle; t is a steering collision avoidance time period from the beginning of steering to the end of steering of the vehicle, and T is a steering time point;

calculating the coefficient of the vehicle transverse N times curve track corresponding to the maximum transverse acceleration of the vehicle according to the formula (3);

Substituting the calculated coefficient of the transverse N-time curve track of the vehicle into the formula (3) to determine the transverse path track of the steering collision avoidance of the vehicle.

The method optionally includes determining a longitudinal path track of the vehicle steering collision avoidance according to the current longitudinal speed of the vehicle, including:

determining the longitudinal path trajectory according to equation (4):

PosnX_Ego=VelX_Ego.t formula (4)

Where PosnX_Ego is the longitudinal position of the own vehicle and VelX_Ego is the current longitudinal speed of the own vehicle.

As described above, optionally, the predicting, according to the motion state information of the effective targets, the target motion trajectory of each effective target in the steering collision avoidance period includes:

if the effective target is judged to meet the uniform acceleration linear motion, determining the relative acceleration of the effective target according to the target acceleration and the vehicle acceleration of the effective target;

determining the relative speed of the effective target according to the target speed of the effective target and the vehicle speed of the vehicle;

and determining a target motion track of the effective target in the steering collision avoidance time period according to the relative acceleration, the relative vehicle speed, the initial position of the effective target and the target course angle of the effective target.

As described above, optionally, the determining the target motion trajectory of the effective target in the steering collision avoidance period according to the relative acceleration, the relative vehicle speed, the initial position of the effective target, and the target heading angle of the effective target includes:

determining the longitudinal position of the effective target within the steering collision avoidance period according to equation (5):

PosnX_Obj＝

PosnX0_Obj+(VelX_Revel·t+0.5·AccelX_Relvel·t ² )·cos(Heading)，t∈[0,T]formula (5)

Wherein PosnX_obj is the longitudinal position of the effective target, posnX0_obj is the initial longitudinal position of the effective target, accelX_Relvel is the relative longitudinal acceleration of the effective target, velX_Relvel is the relative longitudinal speed of the effective target, head is the target navigation angle of the effective target, T is the steering collision avoidance time period from the beginning of steering to the end of steering, and T is the steering time point;

determining a lateral position of the effective target within the steering collision avoidance period according to equation (6):

PosnY_Obj＝PosnY0_Obj+(VelY_Revel·t+0.5·AccelY_Relvel·t ² )·sin(Heading)，t∈[0,T]formula (6)

Wherein PosnY_obj is the lateral position of the effective target, posnY0_obj is the initial lateral position of the effective target, accelY_Relvel is the relative lateral acceleration of the effective target, and VelY_Relvel is the relative lateral vehicle speed of the effective target.

if the effective target is judged to meet the circular motion, determining an arc track of the effective target according to the relative vehicle speed and the relative acceleration of the effective target;

determining longitudinal components and transverse components of the circular motion track of the effective target in the longitudinal direction and the transverse direction respectively according to the circular arc track;

and calculating a target motion track of the effective target in the steering collision avoidance time period according to the longitudinal component, the transverse component and the target navigation angle of the effective target.

As described above, optionally, the calculating the target motion trajectory of the effective target in the steering collision avoidance period according to the longitudinal component, the lateral component, and the target navigation angle of the effective target includes:

determining the longitudinal position of the effective target within the steering collision avoidance period according to equation (7):

PosnX_obj=PosnX0_obj+Xrot_cos (head) -Yrot_sin (head) equation (7)

Wherein PosnX_obj is the longitudinal position of the effective target, posnX0_obj is the initial longitudinal position of the effective target, xrot is the longitudinal component, yrot is the transverse component, and rising is the target navigation angle of the effective target;

Determining the lateral position of the effective target within the steering collision avoidance period according to equation (8):

PosnY_obj=PosnY0_obj+Xrot_sin (Heading) +Yrot_cos (Heading) equation (8)

Wherein PosnY_Obj is the lateral position of the effective target, and PosnY0_Obj is the initial lateral position of the effective target.

As described above, optionally, the traversing each of the effective targets, and evaluating whether each of the steering tracks of the vehicle has a collision risk according to the steering track of the vehicle and the target motion track, includes:

calculating a distance collision time TTR and a distance travel time TTP for each effective target;

determining the actual collision time TTC of the own vehicle according to the distance collision time TTR and the distance driving time TTP;

calculating a steering track of the vehicle and a target motion track corresponding to the actual collision time TTC;

and traversing all the effective targets according to each self-steering track, and judging whether collision risks exist between the self-steering track and other effective targets according to the calculated self-steering track and the target motion track.

According to the above method, optionally, the screening the steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result includes:

And taking the steering track of the self-vehicle with the minimum transverse displacement in the first candidate track list as a steering collision avoidance path of the self-vehicle.

As described above, optionally, predicting a lane line track in the steering collision avoidance period according to lane line attribute information includes:

determining lane line trajectories according to equation (9):

Posnyline=PosnY_Ego-PosnX_Ego. FirstCoeff+ConstCoeff equation (9)

Wherein, posnYLine is the predicted lane line transverse position, posnY_Ego is the vehicle transverse position, posnX_Ego is the vehicle longitudinal position, constCoeff is the constant term coefficient of the lane line equation, and FirstCoeff is the first term coefficient of the lane line equation.

Optionally, the method further includes traversing each lane line track, and evaluating whether each steering track of the first candidate track list has a risk of crossing a lane line, including:

calculating actual collision time TTLC of the own vehicle according to each lane line track;

calculating a self-vehicle steering track and a lane line track corresponding to the actual conflict time TTLC for each self-vehicle steering track in the first candidate track list;

and traversing all lane lines aiming at each self-vehicle steering track in the first candidate track list, and judging whether the self-vehicle steering track collides with the lane lines according to the calculated self-vehicle steering track and the lane line track.

In a second aspect, an embodiment of the present invention provides a steering collision avoidance path determining apparatus, including:

the calculation module is used for calculating the steering track of the own vehicle in the steering collision avoidance time period of the own vehicle for each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting the preset condition;

the prediction module is used for predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target;

the evaluation module is used for traversing each effective target, evaluating whether each self-steering track has collision risk or not according to the self-steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-steering tracks;

and the screening module is used for screening the steering collision avoidance path of the self-vehicle from the first candidate track list according to the collision risk assessment result.

The apparatus as above, optionally, the prediction module is further configured to:

accordingly, the evaluation module is specifically configured to:

correspondingly, the screening module is specifically configured to:

The above apparatus, optionally, the computing module is specifically configured to:

The above device, optionally, the calculating module is configured to calculate, according to the lateral position of the effective target, a lateral displacement of the vehicle required to move at the critical point of steering collision avoidance, specifically configured to:

y_end=posny+0.5·objwidth+0.5·egowwidth+widthmargin formula (1)

According to the above device, optionally, the calculating module is configured to calculate, according to the lateral displacement and the maximum lateral acceleration of the vehicle, a lateral path trajectory of the vehicle steering collision avoidance, specifically configured to:

determining the vehicle maximum lateral acceleration according to formula (2):

ay_max=min (ay_limit, b1·g, b2·μ·g) formula (2)

determining the transverse path trajectory according to equation (3):

PosnY_Ego＝a0+a1·t+a2·t ² +a3·t ³ +…+aN·t ^N ，t∈[0,T]formula (3)

According to the device, optionally, the calculation module is used for determining the longitudinal path track of the steering collision avoidance of the vehicle according to the current longitudinal speed of the vehicle, and is specifically used for:

determining the longitudinal path trajectory according to equation (4):

PosnX_Ego=VelX_Ego.t formula (4)

The above apparatus, optionally, the prediction module is specifically configured to:

In the above device, optionally, the prediction module is configured to determine, according to the relative acceleration, the relative vehicle speed, an initial position of the effective target, and a target heading angle of the effective target, a target motion trajectory of the effective target in the steering collision avoidance time period, where the prediction module is specifically configured to:

PosnX_Obj＝PosnX0_Obj+(VelX_Revel·t+0.5·AccelX_Relvel·t ² )·cos(Heading)，t∈[0,T]formula (5)

The above device, optionally, the prediction module is configured to calculate, according to the longitudinal component, the lateral component, and the target navigation angle of the effective target, a target motion trajectory of the effective target in the steering collision avoidance period, where the prediction module is specifically configured to:

PosnX_obj=PosnX0_obj+Xrot_cos (head) -Yrot_sin (head) equation (7)

PosnY_obj=PosnY0_obj+Xrot_sin (Heading) +Yrot_cos (Heading) equation (8)

The above apparatus, optionally, the evaluation module is specifically configured to:

The above apparatus, optionally, the screening module is specifically configured to:

In the above device, optionally, the prediction module is configured to predict, according to lane line attribute information, a lane line trajectory in the steering collision avoidance time period, specifically configured to:

Determining lane line trajectories according to equation (9):

Posnyline=PosnY_Ego-PosnX_Ego. FirstCoeff+ConstCoeff equation (9)

In the above apparatus, optionally, the evaluation module is configured to traverse each lane line track, evaluate whether each vehicle steering track in the first candidate track list has a risk of crossing a lane line, and specifically is configured to:

In a third aspect, an embodiment of the present invention provides an electronic device, including:

The device comprises a memory and a processor, wherein the processor and the memory are communicated with each other through a bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions capable of performing the method of: calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition; predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks; and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

In a fourth aspect, embodiments of the present invention provide a storage medium having stored thereon a computer program which, when executed by a processor, performs a method of: calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition; predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks; and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

According to the method for determining the steering collision avoidance path, provided by the embodiment of the invention, all the steering paths of the self-vehicle for steering collision avoidance are calculated, risk assessment is carried out on the steering paths of the self-vehicle based on the predicted target motion path, whether collision with other obstacles occurs in the steering collision avoidance process of the self-vehicle is judged, and finally, the steering path of the self-vehicle which is easiest to realize is selected by arbitration under the condition of ensuring safety, so that collision with the obstacles does not occur during steering collision avoidance of the self-vehicle is ensured, the safety of a driver is ensured, the predicted steering path of the self-vehicle ensures the continuity of vehicle control, the impact of sudden acceleration change is eliminated, the planned path is more reasonable and reliable, the control logic of automatic emergency steering is optimized, and the product performance of auxiliary driving is improved.

Drawings

FIG. 1 is a flow chart of steps of an embodiment of a method for determining a steering collision avoidance path of the present invention;

FIG. 2 is a schematic diagram of a lateral movement displacement of a steering collision avoidance of a vehicle in an embodiment of a method for determining a steering collision avoidance path of the present invention;

FIG. 3 is a schematic diagram of candidate steering collision avoidance path selection in an embodiment of a method for determining a steering collision avoidance path according to the present invention;

FIG. 4 is a schematic diagram of an effective target circular motion path in an embodiment of a method for determining a steering collision avoidance path according to the present invention;

FIG. 5 is a schematic diagram of a predicted lane line lateral position in an embodiment of a method for determining a steering collision avoidance path according to the present invention;

fig. 6 is a block diagram showing the construction of an embodiment of a steering collision avoidance path determination device of the present invention.

Fig. 7 is a block diagram of an embodiment of an electronic device of the present invention.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.

Referring to fig. 1, a step flowchart of an embodiment of a method for determining a steering collision avoidance path according to the present invention may specifically include the following steps:

step S110, calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle for each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition;

specifically, an effective target needs to be determined first, wherein the effective target refers to a target that needs to be avoided when the own vehicle performs emergency steering, and the own vehicle refers to a vehicle currently performing emergency collision avoidance operation. The effective targets may be screened by setting preset conditions, which may include:

(1) The target longitudinal position is larger than a longitudinal threshold, namely PosnX_obj > PosnXThreshold, wherein PosnX_obj is the target longitudinal position, posnXThreshold is a preset longitudinal threshold, and the target longitudinal position is larger than the threshold, so that enough space is ensured for steering collision avoidance;

(2) The transverse distance of the target distance from the vehicle is smaller than a transverse threshold, namely |PosnY_obj-PosnY_Ego| < PosnYThreshold, wherein PosnY_obj is the target transverse position, posnY_Ego is the vehicle transverse position, posnYThreshold is a preset transverse threshold, and when the transverse distance of the target distance from the vehicle is smaller than the threshold, emergency collision avoidance is needed;

(3) The target ID is valid, i.e., the target ID is not equal to 0;

(4) The target life cycle is larger than a life cycle threshold, namely, age_obj > Age threshold, wherein age_obj is the target life cycle, and Age threshold is a preset life cycle threshold;

(5) The target Confidence is greater than a Confidence threshold, i.e., confidence_obj > ConfThreshold, where confidence_obj is the target Confidence and ConfThreshold is a preset Confidence threshold;

the target ID, the target life cycle and the target confidence are all inherent attributes of the target, and the own vehicle can be acquired through the perception front end. The target satisfying the above condition is taken as an effective target of the own vehicle.

After the effective targets are determined, calculating the steering track of the vehicle in the steering collision avoidance time period of the vehicle aiming at the effective targets according to the determined position Posn_obj of each effective target and the maximum acceleration a_max of the vehicle:

firstly, for each effective target, calculating the lateral displacement of the vehicle required to move at the steering collision avoidance critical point according to the lateral position of the effective target, referring to fig. 2, a schematic diagram of the lateral displacement of the vehicle steering collision avoidance path determination method according to the embodiment of the invention is shown, the position shown by the dotted line in the figure is the position of the vehicle to be moved, only a schematic diagram of the right-turn avoidance displacement of the vehicle is shown in fig. 2, in practical application, the vehicle can select the left-turn avoidance effective target, and specific steering needs to be adaptively adjusted according to different scenes.

Referring to fig. 2, the lateral displacement of the vehicle at the critical point of steering collision avoidance can be calculated according to formula (1):

y_end=posny+0.5·objwidth+0.5·egowwidth+widthmargin formula (1)

Wherein Y_END is the lateral displacement of the required movement of the own vehicle (represented by EGO in FIG. 2), namely the displacement of the effective target of the own vehicle just avoiding collision; posnY is the lateral displacement of the longitudinal axis centerline of the vehicle and the active target (represented in FIG. 2 using OBJ); objWidth is the target width of the effective target; egoWidth is the width of the own vehicle; widthMargin is a preset width margin, wherein the preset width margin can be obtained through a vehicle speed table look-up.

And secondly, calculating a transverse path track of the steering collision avoidance of the vehicle according to the transverse displacement and the maximum transverse acceleration of the vehicle.

Specifically, the own vehicle maximum lateral acceleration is determined according to formula (2):

ay_max=min (ay_limit, b1·g, b2·μ·g) formula (2)

Wherein ay_max is the maximum lateral acceleration of the vehicle; ay_limit is the upper limit value of the lateral acceleration of the vehicle; g is gravity acceleration; mu is the friction coefficient of the current ground, b1 is a first coefficient, and b2 is a second coefficient; in practical applications, since the tires in the two-degree-of-freedom vehicle dynamics model are kept in a linear relationship within a certain slip angle range, the lateral acceleration should be less than 0.4g, so b1 may be set to 0.4, the maximum lateral acceleration limited by the ground friction is typically 0.67 μg, and b2 may be set to 0.67.

In order to ensure the continuity of the self-vehicle acceleration at the steering starting point and the steering ending point and eliminate the defect of impact, the method is characterized in that the longitudinal direction keeps the current speed to run at a constant speed, the transverse direction is steered by a track of an N-time curve, and in particular, the transverse path track is determined according to a formula (3):

PosnY_Ego＝a0+a1·t+a2·t ² +a3·t ³ +…+aN·t ^N ，t∈[0,T]formula (3)

Then, calculating the coefficient of the vehicle transverse N times curve track corresponding to the maximum transverse acceleration of the vehicle according to the formula (3);

specifically, the formula (3) is differentiated to obtain the lateral speed vely_ego of the own vehicle:

VelY_Ego＝a1+2·a2·t+3·a3·t ² +…+N·aN·t ^N-1 formula (10)

Differentiating the formula (10) to obtain the lateral acceleration AccelY_Ego of the vehicle:

AccelY_Ego＝2·a2+6·a3·t+…+N·(N-1)·aN·t ^N-2 formula (11)

At the initial time (t=0), posny_ygo (0) =0, vely_ygo (0) =0, accely_ygo (0) =0;

at the termination time (t=t), posny_ygo (T) =y_end, vely_ygo (T) =0, accely_ygo (T) =0;

substituting the transverse position, the transverse speed and the transverse acceleration of the vehicle at the initial time and the final time into a formula (3), a formula (10) and a formula (11), and obtaining the coefficient of the N-time curve track;

and finally substituting the calculated coefficient of the transverse N-time curve track of the vehicle into the formula (3) to determine the transverse path track of the vehicle steering collision avoidance.

In practical application, when the current speed is kept constant in the longitudinal direction and the vehicle runs at a constant speed, the vehicle is turned transversely by a track of a curve of five times, so that the continuity of the vehicle acceleration at the turning starting point and the turning ending point can be maintained, and the defect of impact is eliminated.

When n=5, substituting the above formula yields:

a0＝a1＝a2＝0；

a3＝10·Y_END/T ³ ；

a4＝-15·Y_END/T ⁴ ；

a5＝6·Y_END/T ⁵ ；

substituting the calculated a0 to a1 into the formula (3) yields:

in addition, it is also possible to obtain the differential acceleration AccelYEgo's expression, find the relation of the maximum lateral acceleration, lateral displacement and steering collision avoidance time period of the present steering as So the steering collision avoidance time period is +.>

Meanwhile, a longitudinal path track of the vehicle steering collision avoidance can be determined according to the current longitudinal speed of the vehicle, specifically, the vehicle is set to longitudinally keep the current speed and travel at a constant speed, and the longitudinal path track is determined according to a formula (4):

PosnX_Ego=VelX_Ego.t formula (4)

Wherein PosnX_Ego is the longitudinal position of the own vehicle, and VelX_Ego is the current longitudinal speed of the own vehicle.

After the transverse path track and the longitudinal path track of each effective target of the self-vehicle in the steering collision avoidance time period are calculated, the self-vehicle steering track of each effective target of the self-vehicle can be determined, and the self-vehicle steering tracks are used as candidate steering collision avoidance tracks of the emergency collision avoidance. Referring to fig. 3, a schematic diagram of candidate steering collision avoidance track selection in an embodiment of the present invention is shown, in fig. 3, taking collision avoidance on the left and right sides of an effective target as an example, and vehicle steering tracks on the left and right sides are calculated for the effective targets OBJ1, OBJ2 and OBJ3 respectively: the components are OBJ1_LeftSide, OJ1_ RightSide, OBJ2_LeftSide, OJ2_ RightSide, OBJ _LeftSide and OJ3_RightSide. In practical application, the left side collision avoidance, the right side collision avoidance or both sides of the collision avoidance are not considered, and the selection needs to be performed according to the practical situation, and the method is described in detail later.

Step S120, predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective targets;

specifically, firstly, judging the motion state of an effective target, and predicting the target motion trail of the effective target in a steering collision avoidance time period based on the motion state of the effective target:

(1) If the effective target vehicle speed is smaller than or equal to the speed threshold, namely VelX_Obj is smaller than or equal to V_Limit1, wherein the target vehicle speed of the VelX_Obj effective target is the speed threshold, and V_Limit1 is determined that the effective target is a stationary target.

The target position of the stationary target in the steering collision avoidance time period keeps the current position:

PosnX_Obj＝PosnX0_Obj；

PosnY_Obj＝PosnY0_Obj；

wherein PosnX_obj is the longitudinal position of the effective target, posnY_obj is the transverse position of the effective target, posnX0_obj is the initial longitudinal position of the effective target at the beginning of steering, and PosnY0_obj is the initial transverse position of the effective target at the beginning of steering.

(2) If the effective target speed is greater than the speed threshold and the target movement track Curvature is small, determining that the effective target movement state is uniform acceleration linear movement, namely VelX_obj > V_Limit1, and |Curvaturel is less than or equal to Cur_Limit1, wherein Curvatures are target movement track Curvature and Cur_Limit1 is Curvature threshold. The effective target motion state is determined to be uniformly accelerated linear motion.

For an effective target of uniform acceleration linear motion, firstly determining the relative acceleration of the effective target according to the target acceleration and the vehicle acceleration of the effective target;

specifically, the relative longitudinal acceleration of the effective target is calculated according to formula (12):

Accelx_Relvel = Accelx_obj-Accelx_Ego equation (12)

Wherein Accelx_Relvel is relative longitudinal acceleration, accelx_obj is target longitudinal acceleration of the effective target, accelx_Ego is vehicle longitudinal acceleration;

calculating the relative lateral acceleration of the effective target according to equation (13):

AccelY_Relvel=AccelY_obj_AccelY_Ego equation (13)

Where AccelY_Relvel is the relative lateral acceleration, accelY_obj is the target lateral acceleration of the effective target, and AccelY_Ego is the vehicle lateral acceleration.

Then, determining the relative speed of the effective target according to the target speed of the effective target and the vehicle speed of the vehicle;

specifically, the relative longitudinal vehicle speed of the effective target is calculated according to equation (14):

Velx_Relvel = Velx_obj-Velx_Ego equation (14)

Wherein VelX_Relvel is the relative longitudinal speed, velX_obj is the longitudinal speed of the effective target, and VelX_Ego is the longitudinal speed of the own vehicle;

calculating the relative lateral vehicle speed of the effective target according to equation (15):

Vely_relvel=vely_obj-vely_ygo equation (15)

Where VelY_Relvel is the relative lateral vehicle speed, velY_obj is the lateral vehicle speed of the effective target, and VelY_Ego is the lateral vehicle speed of the own vehicle.

And finally, determining a target motion track of the effective target in the steering collision avoidance time period according to the relative acceleration, the relative vehicle speed, the initial position of the effective target and the target course angle of the effective target.

Specifically, the longitudinal position of the effective target within the steering collision avoidance period is determined according to formula (5):

PosnY_Obj＝

PosnY0_Obj+(VelY_Revel·t+0.5·AccelY_Relvel·t ² )·sin(Heading)，t∈[0,T]formula (6)

(3) If the effective target speed is greater than the speed threshold and the target movement track Curvature exceeds the Curvature threshold, determining that the effective target movement state is circular movement, namely VelX_obj > V_Limit1, and |CurvatureI > Cur_Limit1, wherein Curvatures are the target movement track Curvature, cur_Limit1 is the Curvature threshold, and determining that the effective target movement state is circular movement.

Referring to fig. 4, a schematic diagram of an effective target circular motion track in an embodiment of a method for determining a steering collision avoidance path according to the present invention is shown, rotation is a central angle of circular motion, R is a turning radius of the effective target circular motion track, and rising is a navigation angle of a target, where the effective target moves from point a to point B.

For an effective target in circular motion, firstly determining an arc track of the effective target according to the relative vehicle speed and the relative acceleration of the effective target;

specifically, the circular arc trajectory of the effective target is determined according to equation (16):

DisofArc＝Vel_Relvel·t+0.5·Accel_Relvel·t ² formula (16)

Wherein Disofarc is the circular arc track of the effective target, vel_Relvel is the relative speed of the effective target, accel_Relvel is the relative acceleration of the effective target.

And then, determining longitudinal components in the longitudinal direction and transverse components in the transverse direction of the circular motion track of the effective target according to the circular arc track.

Specifically, the turning radius of the effective target is calculated according to formula (17):

R=1/Curv equation (17)

Wherein R is the turning radius of the effective target, and Curv is the curvature of the effective target;

calculating the angle by which the effective target turns according to equation (18):

angle of arc=Disofarc/R formula (18)

Wherein, angleofArc is the angle through which the effective target circular motion turns.

Calculating the longitudinal component of the circular motion trail of the effective target in the longitudinal direction according to the formula (19):

xrot=r. sin (AngleofArc) formula (19)

Wherein Xrot is a longitudinal component of the circular motion trajectory of the effective target in the longitudinal direction.

Calculating the transverse component of the circular motion trail of the effective target in the transverse direction according to the formula (20):

Yrot=R-R cos (AngleofArc) formula (20)

Wherein Yrot is a transverse component of the circular motion trail of the effective target in the transverse direction.

And finally, calculating a target motion track of the effective target in the steering collision avoidance time period according to the longitudinal component, the transverse component and the target navigation angle of the effective target.

Specifically, the longitudinal position of the effective target within the steering collision avoidance period is determined according to formula (7):

PosnX_obj=PosnX0_obj+Xrot_cos (head) -Yrot_sin (head) equation (7)

PosnY_obj=PosnY0_obj+Xrot_sin (Heading) +Yrot_cos (Heading) equation (8)

And repeating the steps, and carrying out track prediction on all the effective targets to obtain a curve of the change of the transverse and longitudinal positions of the effective targets along with time.

Step S130, traversing each effective target, evaluating whether collision risk exists in each self-steering track according to the self-steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-steering tracks;

specifically, all the effective targets are traversed to evaluate collision risk one by one, and the steering track of the vehicle without collision risk is put into a candidate track list CandidateList and is recorded as a first candidate track list.

First, for each of the effective targets, a distance collision Time (TTR) and a distance Travel Time (TTP) are calculated:

specifically, for each effective target, TTR is calculated according to formula (21):

PosnX_Obj-LengthAxle2rear＝VelX_Relvel·TTR+0.5·AccelX_Relvel·TTR ² formula (21)

Wherein PosnX_obj is the longitudinal position of the active target; lengthAxle2rear is the distance from the front of the vehicle to the rear axle of the vehicle, velX_Relvel is the relative longitudinal vehicle speed of the effective target, accelX_Relvel is the relative longitudinal acceleration.

Calculating TTP according to formula (22):

PosnX_Obj-LengthAxle2rear+LengtEgo+LengtObj＝VelX_Relvel·TTP+0.5·AccelX_Relvel·TTP ² formula (22)

Where PosnX_Obj is the longitudinal position of the active target; lengthAxle2rear is the distance from the front of the vehicle to the rear axle of the vehicle; lengthEgo is the length of the own vehicle; lengthObj is the length of the effective target, velX_Relvel is the relative longitudinal vehicle speed of the effective target, accelX_Relvel is the relative longitudinal acceleration.

Then, the actual collision time (Time To Collision, TTC) of the own vehicle is determined from the distance collision time TTR and the distance travel time TTP:

specifically, TTC is calculated according to formula (23):

ttc=min (TTR, TTP) formula (23)

And then, calculating the steering track of the vehicle and the target movement track corresponding to the actual collision time TTC.

Specifically, the TTC calculated in the formula (23) is substituted into the formula (3) to obtain a lateral position predictposny_ego=posny_ego (t=ttc) at the moment of the TTC of the own vehicle, and the TTC calculated in the formula (23) is substituted into the formula (6) or the formula (8) according to the actual situation to obtain a lateral position predictposny_obj=posny_obj (t=ttc) at the moment of the TTC of the effective target.

And finally, traversing all the effective targets according to each self-steering track, and judging whether collision risks exist between the self-steering track and other effective targets according to the calculated self-steering track and the target motion track.

Specifically, for each steering track of the own vehicle, traversing all effective targets, and judging that collision risks exist for the two vehicles if the first effective target obj1 is on the left side of the own vehicle and the target obj1 is on the right side of the own vehicle or has overlapping TTC moment, wherein Conflic is true; i.e. judging posny_obj1>0 and predictposny_obj1-predictposny_ego <0.5 (widthego+widthobj 1), then determining that the first effective target has collision risk.

If the first effective target obj1 is on the right side of the own vehicle, but the TTC time effective target obj1 is on the left side of the own vehicle or is overlapped, judging that collision risks exist for the two vehicles, wherein Conflict is true; i.e., judging PosnY_Obj1>0 and predictPosnY_Obj1-predictPosnY_Ego > -0.5 (WidthEgo+WidthObj1); otherwise, the current steering track and the first effective target have no collision risk Conflic is false.

And repeating the steps aiming at the steering track of the vehicle, and carrying out risk assessment judgment one by one aiming at all effective targets.

If the first vehicle steering track has no collision risk for all the effective targets, the first vehicle steering track is added into a first candidate track list.

And step 140, screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

Specifically, traversing the first candidate track list, selecting one track with the smallest lateral movement displacement of the vehicle as the steering track which is easiest to realize, and controlling the vehicle to steer and avoid collision as the expected steering collision avoidance path track if the automatic emergency steering function is activated at the moment. If the first candidate trajectory list is empty, activation of the automatic emergency steering function is not allowed.

On the basis of the above embodiment, further, the method further includes:

In particular, in practical applications, there is a risk that the vehicle may cross the lane line during collision avoidance, and thus prediction of the lane line is also required.

Referring to fig. 5, a schematic diagram of a predicted lane line lateral position in an embodiment of a method for determining a steering collision avoidance path according to the present invention is shown.

First, a lane line trajectory is determined according to formula (9):

Posnyline=PosnY_Ego-PosnX_Ego. FirstCoeff+ConstCoeff equation (9)

All lane line tracks identified by cameras such as a left lane line, an adjacent lane left lane line, a right lane line, an adjacent lane right lane line … and the like can be predicted by the formula (9).

Then, calculating the actual collision time (Time To Line Collision, TTLC) of the own vehicle according to the formula (24) for each lane line track;

wherein ConstCoeff is a constant term coefficient of the lane line equation, and FirstCoeff is a first term coefficient of the lane line equation.

Then, calculating a self-vehicle steering track and a lane line track corresponding to the actual conflict time TTLC for each self-vehicle steering track in the first candidate track list;

specifically, for each self-vehicle steering track in the first candidate track list, traversing all lane lines, and judging whether the steering action collides with the lane lines or not according to the self-vehicle steering track and the predicted lane line track, and whether the risk of crossing the lane lines exists or not.

Substituting the TTLC of the lane Line into the formula (3) to obtain a lateral position predictposny_ego=posny_ego (t=ttlc) at the moment of the TTLC of the own vehicle, and substituting the TTLC of the lane Line into the formula (9) to obtain a lateral position predictposny_line=posyline (t=ttlc) at the moment of the TTLC of the lane Line.

Specifically, if the first lane line is on the left side of the own vehicle, but the first lane line is on the right side of the own vehicle or the own vehicle is on the lane line at the moment of TTLC, judging that the own vehicle has the risk of crossing the lane line, wherein Conflic is true; i.e. judging that PosnY_Line1>0 and predictPosnY_Line1-predictPosnY_Ego is less than or equal to 0.5.WidthEgo, determining that the risk of crossing the lane Line exists.

If the first lane line is on the right side of the own vehicle but the first lane line is on the left side of the own vehicle or on the lane line at the TTLC moment, judging that the own vehicle has the risk of crossing the lane line, wherein Conflict is true; i.e. judging that PosnY_Line1>0 and predictPosnY_Line1-predictPosnY_Ego is not less than-0.5.WidthEgo, determining that the risk of crossing the lane Line exists.

Otherwise, the current steering track of the vehicle does not have the risk of crossing the lane line, and Conflic is false. And repeating the steps for the steering action to perform risk assessment on all the lane lines one by one.

After the self-vehicle steering track is subjected to lane line risk assessment, if Conflic is true, the steering collision avoidance track has the risk of collision with other targets or crossing lane lines, and the steering track is unavailable; if Conflic is false, the steering track has no risk of collision or crossing lane lines, and the steering track is saved in a candidate track list and is recorded as a second candidate track list.

And finally, selecting the steering track of the self-vehicle with the smallest transverse displacement from the second candidate track list as a steering collision avoidance path of the self-vehicle.

In practical application, the target motion track and the lane line track of the effective targets can be synchronously predicted, all the effective targets are traversed according to each self-vehicle steering collision avoidance track, whether the steering collision avoidance track has collision risk with other effective targets or not is judged according to the predicted target track, and a first candidate track list which does not have collision risk with the effective targets is determined;

traversing all lane lines aiming at each self-vehicle steering collision avoidance track, judging whether the steering collision avoidance track collides with the lane lines according to the predicted lane line track, and determining a third candidate track list without the risk of crossing the lane lines if the steering collision avoidance track has the risk of crossing the lane lines;

And then selecting the steering track of the self-vehicle with the smallest lateral displacement from the intersection of the first candidate track list and the third candidate track list as a steering collision avoidance path of the self-vehicle.

According to the method for determining the steering collision avoidance path, provided by the embodiment of the invention, the steering collision avoidance path is calculated and screened in the automatic emergency steering function, the risk assessment is carried out on the steering collision avoidance path of the self-vehicle by predicting the movement path and the lane line path of the target, so that the self-vehicle is ensured not to collide with other static or dynamic obstacles when the self-vehicle steers to avoid collision with the main target, the safety of a driver is ensured, the control logic of automatic emergency steering is optimized, and the product performance of auxiliary driving is improved.

The method for determining the steering collision avoidance path provided by the embodiment of the invention is exemplified for a specific scene.

In practice, the emergency steering ES system can be roughly divided into three subsystems:

(1) In-lane emergency steering (CES): an obstacle target exists in front of the lane, and the system turns in an emergency manner in the lane to avoid or slow down collision. (2) driver triggered emergency steering (DES): when there is a collision risk in front of the vehicle, the driver triggers steering but is not enough to avoid the collision, and the system emergently steers to intervene to avoid or slow down the collision. (3) automatic emergency diversion (AES): the running environments of the front, the side and the side back of the vehicle are monitored in real time, and the steering of the vehicle is automatically controlled when the collision danger possibly occurs so as to avoid or slow down the collision.

Aiming at a CES subsystem, when an emergency collision avoidance is carried out, firstly, calculating the whole steering collision avoidance time and a steering track of a quintic curve according to the transverse position of a front effective target and the maximum transverse acceleration of steering of a vehicle, traversing the left side and the right side of all the front effective targets, and obtaining all candidate tracks; predicting the motion trail of all targets according to the motion state information of the targets; predicting the track of all lane lines according to the attribute information of the lane lines; then, traversing all effective targets and lane lines, performing collision risk assessment one by one, and determining that two tracks do not have overlapping points in space according to a predicted target track and a planning track of a vehicle through a transverse position relation; according to the predicted lane line track and the planned track of the own vehicle, determining that the own vehicle cannot pass through the lane line in the steering collision avoidance process through the transverse position; and finally, selecting one track which is the easiest to realize from the vehicle to be the most steering collision avoidance path track through transverse movement displacement from a candidate track list meeting collision risk assessment.

Aiming at the DES subsystem, when the emergency collision avoidance is carried out, determining an emergency steering direction according to the steering of a driver, traversing all effective targets at the side of the emergency steering direction of the vehicle, firstly calculating the whole steering collision avoidance time and the steering track of a quintic curve according to the transverse position of the front effective target and the maximum transverse acceleration of the steering of the vehicle, and obtaining all candidate tracks; predicting the motion trail of all targets according to the motion state information of the targets; then traversing all the effective targets, carrying out collision risk assessment one by one, and determining that two tracks do not have coincident points in space through a transverse position relation according to the predicted target track and the planning track of the vehicle; and finally, selecting one track which is the easiest to realize from the vehicle to be the most steering collision avoidance path track through transverse movement displacement from a candidate track list meeting collision risk assessment.

Aiming at an AES subsystem, when an emergency collision avoidance is carried out, firstly, calculating the whole steering collision avoidance time and a steering track of a quintic curve according to the transverse position of a front effective target and the maximum transverse acceleration of steering of a vehicle, traversing the left side and the right side of all the front effective targets, and obtaining all candidate tracks; predicting the motion trail of all targets according to the motion state information of the targets; then, traversing all effective targets and lane lines, performing collision risk assessment one by one, and determining that two tracks do not have overlapping points in space according to a predicted target track and a planning track of a vehicle through a transverse position relation; and finally, selecting one track which is the easiest to realize from the vehicle to be the most steering collision avoidance path track through transverse movement displacement from a candidate track list meeting collision risk assessment.

In summary, for the CES subsystem, it is necessary to traverse the left and right sides of the effective target, determine collision avoidance paths on the left and right sides, and in risk assessment, it is necessary to consider whether the pre-effective target has a collision risk or not, and also whether the pre-effective target crosses the lane line or not; aiming at the DES subsystem, the collision avoidance paths on the left side and the right side of the effective target are not required to be determined, the collision avoidance paths on the emergency steering direction side of the driver steering of the effective target are only required to be determined, the risk assessment is carried out by considering whether the collision risk exists in the pre-effective target or not, and the assessment on whether the collision risk crosses the lane line or not is not required; aiming at the AES subsystem, the left side and the right side of the effective target are required to be traversed, collision avoidance paths of the left side and the right side are determined, and in risk assessment, whether collision risks exist in the pre-effective target or not is only required to be considered, and assessment on whether the effective target crosses a lane line or not is not required.

According to the method for determining the steering collision avoidance path, provided by the embodiment of the invention, the risk assessment is carried out on the steering collision avoidance path of the self-vehicle by predicting the movement track and the lane line track of the target, so that the collision with other static or dynamic obstacles is avoided when the self-vehicle steers to the collision avoidance main target, different assessment methods are provided for three sub-functions of an automatic emergency steering system, the steering of the CES sub-function is avoided across the lane, the safety of a driver is ensured, the control logic of the automatic emergency steering is optimized, and the product performance of auxiliary driving is improved.

It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the invention.

Referring to fig. 6, a block diagram of an embodiment of a steering collision avoidance path determining device according to the present invention may specifically include the following modules: a calculation module 610, a prediction module 620, an evaluation module 630, and a screening module 640, wherein:

The calculating module 610 is configured to calculate a steering trajectory of the own vehicle in a steering collision avoidance time period for each effective target according to a position of the effective target and a maximum acceleration of the own vehicle, where the effective target is a target that meets a preset condition; the prediction module 620 is configured to predict a target motion trajectory of each of the effective targets in the steering collision avoidance period according to the motion state information of the effective targets; the evaluation module 630 is configured to traverse each of the effective targets, evaluate whether each of the steering tracks of the vehicle has a collision risk according to the steering track of the vehicle and the target motion track, and determine a first candidate track list that satisfies the collision risk evaluation from the steering tracks of the vehicle; the screening module 640 is configured to screen a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

As in the above apparatus, optionally, the prediction module 620 is further configured to:

accordingly, the evaluation module 630 is specifically configured to:

Accordingly, the screening module 640 is specifically configured to:

As in the above apparatus, optionally, the computing module 610 is specifically configured to:

The above device, optionally, the calculating module 610 is configured to calculate, according to the lateral position of the effective target, a lateral displacement of the vehicle required to move at the critical point of collision avoidance, specifically:

y_end=posny+0.5·objwidth+0.5·egowwidth+widthmargin formula (1)

In the above apparatus, optionally, the calculating module 610 is configured to calculate, according to the lateral displacement and the maximum lateral acceleration of the vehicle, a lateral path trajectory of the steering collision avoidance of the vehicle, specifically:

determining the vehicle maximum lateral acceleration according to formula (2):

ay_max=min (ay_limit, b1·g, b2·μ·g) formula (2)

determining the transverse path trajectory according to equation (3):

PosnY_Ego＝a0+a1·t+a2·t ² +a3·t ³ +…+aN·t ^N ，t∈[0,T]formula (3)

In the above apparatus, optionally, the calculating module 610 is configured to, when determining the longitudinal path track of the steering collision avoidance of the vehicle according to the current longitudinal speed of the vehicle, specifically:

Determining the longitudinal path trajectory according to equation (4):

PosnX_Ego=VelX_Ego.t formula (4)

As in the above apparatus, optionally, the prediction module 620 is specifically configured to:

As mentioned above, optionally, the prediction module 620 is configured to determine, according to the relative acceleration, the relative vehicle speed, the initial position of the effective target, and the target heading angle of the effective target, a target motion trajectory of the effective target in the steering collision avoidance period, where the prediction module is specifically configured to:

As mentioned above, optionally, the prediction module 620 is configured to calculate, according to the longitudinal component, the lateral component, and the target navigation angle of the effective target, a target motion trajectory of the effective target in the steering collision avoidance period, where the target motion trajectory is specifically configured to:

PosnX_obj=PosnX0_obj+Xrot_cos (head) -Yrot_sin (head) equation (7)

PosnY_obj=PosnY0_obj+Xrot_sin (Heading) +Yrot_cos (Heading) equation (8)

As in the above apparatus, optionally, the evaluation module 630 is specifically configured to:

As in the above apparatus, optionally, the screening module 640 is specifically configured to:

As mentioned above, optionally, the prediction module 620 is configured to predict, according to lane line attribute information, a lane line trajectory during the steering collision avoidance period, specifically configured to:

determining lane line trajectories according to equation (9):

Posnyline=PosnY_Ego-PosnX_Ego. FirstCoeff+ConstCoeff equation (9)

As mentioned above, optionally, the evaluation module 630 is configured to traverse each lane-line track, and evaluate whether each steering track of the first candidate track list has a risk of crossing a lane line, which is specifically configured to:

For the device embodiment, since the device embodiment is substantially similar to the method embodiment, the description is relatively simple, and the relevant points only need to be referred to the part of the description of the method embodiment, which is not repeated herein.

Referring to fig. 7, a schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown, where, as shown in fig. 7, the device includes: a processor (processor) 710, a memory (memory) 720, and a bus 730;

wherein processor 710 and memory 720 communicate with each other via bus 730;

Processor 710 is configured to invoke program instructions in memory 720 to perform the methods provided by the method embodiments described above, including, for example: calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition; predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks; and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

Embodiments of the present invention disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the method embodiments described above, for example comprising: calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition; predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks; and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

Embodiments of the present invention disclose a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments, for example, including: calculating a steering track of the own vehicle in a steering collision avoidance time period of the own vehicle aiming at each effective target according to the position of the effective target and the maximum acceleration of the own vehicle, wherein the effective target is a target meeting a preset condition; predicting a target motion track of each effective target in the steering collision avoidance time period according to the motion state information of the effective target; traversing each effective target, evaluating whether each self-vehicle steering track has collision risk or not according to the self-vehicle steering track and the target movement track, and determining a first candidate track list meeting collision risk evaluation from the self-vehicle steering tracks; and screening a steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result.

In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.

It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.

Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.

The above description of a steering collision avoidance path determination and a steering collision avoidance path determination provided by the present invention applies specific examples to illustrate the principles and embodiments of the present invention, and the above description of the examples is only for helping to understand the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.

Claims

1. A steering collision avoidance path determination method, characterized by comprising:

2. The method as recited in claim 1, further comprising:

3. The method of claim 1, wherein the calculating the vehicle steering trajectory for each of the active targets for the steering collision avoidance period of the vehicle based on the location of the active target and the maximum acceleration of the vehicle comprises:

4. A method according to claim 3, wherein said calculating the lateral displacement of the vehicle required to move at the steering collision avoidance threshold based on the lateral position of the active target comprises:

y_end=posny+0.5·objwidth+0.5·egowwidth+widthmargin formula (1)

5. The method of claim 4, wherein calculating a lateral path trajectory for a steer-by-collision of the host vehicle based on the lateral displacement, a maximum lateral acceleration of the host vehicle, comprises:

determining the vehicle maximum lateral acceleration according to formula (2):

ay_max=min (ay_limit, b1·g, b2·μ·g) formula (2)

determining the transverse path trajectory according to equation (3):

PosnY_Ego＝a0+a1·t+a2·t ² +a3·t ³ +…+aN·t ^N ，t∈[0,T]

formula (3)

6. The method of claim 5, wherein determining a longitudinal path trajectory for collision avoidance for vehicle steering from a current longitudinal vehicle speed of the vehicle comprises:

determining the longitudinal path trajectory according to equation (4):

PosnX_Ego=VelX_Ego.t formula (4)

7. The method of claim 1, wherein predicting the target motion profile of each of the active targets over the steering collision avoidance period based on the motion state information of the active targets comprises:

8. The method of claim 7, wherein the determining the target motion profile of the effective target within the steering collision avoidance period based on the relative acceleration, the relative vehicle speed, the initial position of the effective target, and the target heading angle of the effective target comprises:

PosnX_Obj＝

PosnX0_Obj+(VelX_Revel·t+0.5·AccelX_Relvel·t ² )·cos(Heading)，

t epsilon [0, T ] formula (5)

PosnY_Obj＝

PosnY0_Obj+(VelY_Revel·t+0.5·AccelY_Relvel·t ² )·sin(Heading)，

t epsilon [0, T ] formula (6)

9. The method of claim 1, wherein predicting the target motion profile of each of the active targets over the steering collision avoidance period based on the motion state information of the active targets comprises:

10. The method of claim 9, wherein the calculating a target motion trajectory of the effective target over the steering collision avoidance period from the longitudinal component, the lateral component, and a target voyage angle of the effective target comprises:

PosnX_obj=PosnX0_obj+Xrot_cos (head) -Yrot_sin (head) equation (7)

PosnY_obj=PosnY0_obj+Xrot_sin (Heading) +Yrot_cos (Heading) equation (8)

11. The method of claim 1, wherein said traversing each said active target, evaluating whether each said vehicle steering trajectory is at risk of collision based on said vehicle steering trajectory and said target motion trajectory, comprises:

12. The method according to any one of claims 1-11, wherein the screening the steering collision avoidance path of the own vehicle from the first candidate track list according to the collision risk assessment result includes:

13. The method of claim 2, wherein predicting a lane-line trajectory within the steering-collision avoidance period based on lane-line attribute information comprises:

determining lane line trajectories according to equation (9):

PosnYLine＝PosnY_Ego-PosnX_Ego·FirstCoeff+ConstCoeff

formula (9)

14. The method of claim 13, wherein traversing each of the lane-line trajectories, evaluating whether each of the self-steering trajectories in the first candidate trajectory list is at risk of crossing a lane line, comprises:

15. A steering collision avoidance path determination device, characterized by comprising:

16. An electronic device, comprising:

the device comprises a memory and a processor, wherein the processor and the memory are communicated with each other through a bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1-14.

17. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method of any one of claims 1 to 14.