An event-triggered preview decision method for path following of an autonomous vehicle

Abstract

The application relates to an event-triggered preview decision method for path following of an automatic driving vehicle, comprising the following steps: S1, obtaining a to-be-followed expected speed scheme of the automatic driving vehicle and selecting a preview target; S2, updating a to-be-followed pose list according to a preview path point of the preview target; S3, inserting a road point in the to-be-followed pose list into a following road point list and deleting the same, and simultaneously calculating a first-last mileage difference of the following road point list, and stopping the insertion when the shortest walking distance is exceeded; S4, performing preview based on the current following road point list, and if preset accuracy is not met, triggering re-preview planning and inserting a preview result into a turning radius-mileage list; S5, repeating S3-S4 until the to-be-followed pose list is empty, and outputting the turning radius-mileage list; and S6, calculating an expected lateral acceleration based on current driving information and the turning radius-mileage list and performing following control. The application can guarantee the dynamic accuracy of the automatic driving vehicle following.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving cars, in particular to an event-triggered preview decision method for path following of an automatic driving car. BACKGROUND

[0002] With the development of science and technology, automatic driving cars have become one of the fastest growing and most concerned technology growth points in the current automobile industry. Path following is one of the important functions required by automatic driving cars. The current automatic driving system working process is mostly to first decide an expected trajectory according to the traffic environment, and then control the car to follow the trajectory, so following the predetermined ideal trajectory or path is an important part of car motion control. The current driving assistance system or automatic driving system generally has a high control frequency and fast changes in the motion control problem, which is not consistent with human driving habits, resulting in a decrease in the comfort and trust of the driver and passengers, and the automatic driving is "respectful but far away" and "buy but not use", which objectively inhibits the development and popularization of automatic driving technology. Therefore, in order to solve the problem of frequent adjustment of control actions in the process of following the predetermined trajectory or path of the existing automatic driving car, which leads to poor vehicle motion stability and poor driving comfort, the present application provides an event-triggered preview decision method for path following of an automatic driving car. SUMMARY

[0003] The purpose of the present application is to provide an event-triggered preview decision method for path following of an automatic driving car, which establishes an event-triggered planning method to establish an event-triggered mechanism with following deviation and execution mileage, and adjusts the driving operation when the following error exceeds the allowable deviation range; according to the preview result, the expected lateral acceleration is determined and the car steering system is controlled through the standard control strategy to ensure the dynamic accuracy of following.

[0004] To achieve the above purpose, the present application provides the following scheme:

[0005] An event-triggered preview decision method for path following of an automatic driving car, comprising:

[0006] S1, obtaining a to-be-followed expected speed scheme of an automatic driving car, and selecting a preview target according to the to-be-followed expected speed scheme;

[0007] S2, updating a to-be-followed pose list according to a preview path point of the preview target;

[0008] S3, inserting a road point in the to-be-followed pose list into a following road point list and deleting it at the same time, and calculating a first-last mileage difference of the following road point list, when the first-last mileage difference exceeds a preset minimum walking distance, stopping insertion;

[0009] S4, performing pre-look based on the current following waypoint list, if the pre-look result does not meet the preset accuracy, triggering re-planning of pre-look and inserting the pre-look result into the turning radius-mileage list, and returning to S3; if the pre-look result meets the preset accuracy, directly returning to S3;

[0010] S5, repeating S3-S4 until the to-be-followed pose list is empty, and outputting the turning radius-mileage list;

[0011] S6, based on the current driving information of the autonomous vehicle and the turning radius-mileage list, calculating an expected lateral acceleration and sending the expected lateral acceleration to the autonomous vehicle for following control.

[0012] Optionally, in S1, the to-be-followed expected speed scheme of the autonomous vehicle is obtained, and the pre-look target is selected according to the to-be-followed expected speed scheme, which includes:

[0013] Obtaining following path information and a current vehicle state of the autonomous vehicle;

[0014] Converting the current vehicle state into a same coordinate system as the following path to obtain a mileage range of the pre-look target.

[0015] Optionally, in S4, the pre-look includes:

[0016] Constructing a double-arc multi-segment trajectory calculation model, solving the double-arc multi-segment trajectory calculation model based on a trajectory shape free variable θ, and obtaining a double-arc multi-segment trajectory, wherein the trajectory shape free variable θ is determined by a target function.

[0017] Optionally, the double-arc multi-segment trajectory calculation model is:

[0018]

[0019] J=A+R1(N1-V);

[0020] C A =A+R1N1;

[0021] C B =J+R2V;

[0022] Wherein, A is a starting position, θ A is a starting direction, B is an ending point, θ B is an ending direction, α is an angle of AB pointing to θ A , β is an angle of AB pointing to θ B , θ is an angle of a first arc, N1 is a normal vector of point A, V is a normal vector of point J, R1 is a radius of the first arc, R2 is a radius of a second arc, C A , CB The center of the two arcs.

[0023] Optionally, the target function is:

[0024]

[0025] L1≥L min ;

[0026] L2≥L min ;

[0027] Wherein, w d is the weight of lateral deviation, d is the preview deviation, w R is the curvature weight, κ min is the minimum curvature, κ max is the maximum curvature, L1 is the length of the first arc, L2 is the length of the second arc, and L min is the minimum distance.

[0028] Optionally, in the S4, triggering the re-planning of the preview is determined by a preset trigger mechanism, the trigger mechanism is constructed according to a following deviation and an execution mileage, and the trigger mechanism is:

[0029]

[0030] Wherein, s e is the current mileage of the host vehicle, d e is the path following deviation, d max is the maximum allowable path following deviation, s max is the maximum execution mileage, and e is the trigger result.

[0031] Optionally, in the S4, after triggering the re-planning of the preview and inserting the preview result into the turning radius-mileage list, the other road points in the current following road point list except the last two road points are deleted, a new following road point list is obtained, and the S3 is returned.

[0032] Optionally, in the S6, the calculation of the expected lateral acceleration includes:

[0033]

[0034] Wherein, a y is the lateral acceleration, V is the current vehicle speed, and R n is the turning radius.

[0035] The beneficial effects of the present application are:

[0036] The application can trigger the driving preview function based on the event that whether the predefined following error exceeds the predetermined range, reduce the operation adjustment times as much as possible under the premise of ensuring the following accuracy, and improve the vehicle motion stability and driving comfort. The double circular arc is used as the motion primitive for previewing, so as to ensure the simultaneous achievement of the target position and direction. The multi-section previewing method based on the motion primitive is established, so that the preview error can be directly used as the preview section basis in the previewing process, and the following accuracy when the following target does not match the motion primitive is positively ensured. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings described in the following only constitute some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0038] Figure 1 The flow chart of the event-triggered preview decision method for the path following of the automatic driving vehicle according to the embodiment of the present application;

[0039] Figure 2 The preview target selection coordinate system according to the embodiment of the present application;

[0040] Figure 3 The flow chart of the event-triggered planning method according to the embodiment of the present application;

[0041] Figure 4 The same-side double circular arc example according to the embodiment of the present application;

[0042] Figure 5 The opposite-side double circular arc example according to the embodiment of the present application;

[0043] Figure 6 The double circular arc symbol definition diagram according to the embodiment of the present application;

[0044] Figure 7 The multi-section following decision flow chart based on the motion primitive according to the embodiment of the present application. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0046] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0047] The embodiment provides an event-triggered preview decision method for path following of an autonomous vehicle, as shown in the figure, comprising the following steps of: Figure 1

[0048] S1, obtaining a to-be-followed expected speed scheme of the autonomous vehicle, and selecting a preview target according to the to-be-followed expected speed scheme;

[0049] S2, updating a to-be-followed pose list according to a preview path point of the preview target;

[0050] S3, inserting a road point in the to-be-followed pose list into a following road point list and deleting the road point at the same time, and calculating a first-last mileage difference of the following road point list, and stopping the insertion when the first-last mileage difference exceeds a preset minimum walking distance;

[0051] S4, performing preview based on a current following road point list, if a preview result does not satisfy a preset accuracy, triggering re-preview planning and inserting the preview result into a turning radius-mileage list, and returning to S3; if the preview result satisfies the preset accuracy, directly returning to S3;

[0052] S5, repeating S3-S4 until the to-be-followed pose list is empty, and outputting the turning radius-mileage list;

[0053] S6, calculating an expected lateral acceleration based on current driving information and the turning radius-mileage list of the autonomous vehicle, and sending the expected lateral acceleration to the autonomous vehicle for following control.

[0054] Specifically, the embodiment can trigger the driving preview function based on whether the predefined following error exceeds the predetermined range, reduce the number of operation adjustments as much as possible under the premise of ensuring the following accuracy, and improve the vehicle motion stability and driving comfort. The double-arc is taken as a motion primitive for preview, so that the target position and direction are achieved at the same time. A multi-section preview method based on the motion primitive is established, so that the preview error can be directly used as a preview section basis in the preview process, and the following accuracy when the following target does not match the motion primitive is positively ensured.

[0055] Further, in S1, the to-be-followed expected speed scheme of the autonomous vehicle is obtained, and the preview target is selected according to the to-be-followed expected speed scheme, which comprises the following steps of:

[0056] obtaining following path information and a current vehicle state of the autonomous vehicle;

[0057] ​Convert the current vehicle state into the same coordinate system as the following path, and obtain the range of the pre-aim target.

[0058] Specifically, the pre-aim target selection in the embodiment includes the following contents:

[0059] The path and speed that the driver wants to follow are various, in order to be able to express the target path and target speed uniformly, the expected path and expected speed are described in the form of discrete point sequence in the embodiment. i ,Y i ) represents the position coordinates of the following path, and θ i represents the direction of the following path. For the path following target, it can be represented in the form of (X i , Y i , θ i ) point sequence.

[0060] When driving, the expected target will advance along the expected driving path, therefore, it is assumed that the pre-aim target is always selected along the direction of the following path, and a pre-aim target selection method is proposed. As shown in Figure 2 , the frenet coordinate system is established with the following path as the s-axis. The current vehicle geodetic coordinates are (X e , Y e ), the vehicle speed is V, the pre-aim time interval is T P , and VT P is the pre-aim distance. First, the vehicle geodetic coordinates are converted into frenet coordinates (s e , d e ). The pre-aim target is the following target between [s e , s Tp ], wherein s Tp =s e +VT P . That is, the frenet distance is used as the pre-aim distance. Obviously, when the mileage difference is constant, the greater the expected following path curvature, the shorter the straight line distance of the driver to the pre-aim point, which is consistent with the characteristics that the greater the road curvature when driving, the smaller the field of view, and the shorter the forward distance.

[0061] Further, in the S4, the pre-aiming includes:

[0062] A double-arc multi-segment trajectory calculation model is constructed, and the double-arc multi-segment trajectory is obtained by solving the double-arc multi-segment trajectory calculation model based on a trajectory shape free variable θ, wherein the trajectory shape free variable θ is determined by a target function.

[0063] Double circular arc is a simplest G1 continuous curve which can connect the first and last positions. In order to ensure the position and direction are reached simultaneously, the double circular arc is used as the motion primitive of the horizontal motion in the embodiment, C A , C B are the centers of the two circular arcs, and J is the common tangent point of the two circular arcs. C A , C B may be on the same side as shown in Figure 4 , or on the opposite side as shown in Figure 5 .

[0064] The starting position is defined as A, and the direction is θ A , and the ending position is B, and the direction is θ B . α is the angle of θ A pointing to AB, β is the angle of AB pointing to θ B , θ is the angle of the first circular arc, N1 is the normal vector of A, V is the normal vector of J, R1 is the radius of the first circular arc, and R2 is the radius of the second circular arc. As shown in Figure 6 .

[0065] The double circular arc multi-segment trajectory calculation model is:

[0066]

[0067] J = A + R1(N1-V);

[0068] C A = A + R1N1;

[0069] C B = J + R2V;

[0070] Wherein, A is the starting position, θ A is the starting direction, B is the ending position, θ B is the ending direction, α is the angle of θ A pointing to AB, β is the angle of AB pointing to θ B , θ is the angle of the first circular arc, N1 is the normal vector of A, V is the normal vector of J, R1 is the radius of the first circular arc, and R2 is the radius of the second circular arc.

[0071] When α and β are of the same sign, it is constructed as a C-type double circular arc as shown in Figure 4 , otherwise it is constructed as an S-type double circular arc as shown in Figure 5 . In the above formula, θ is a free variable, and for the same starting and ending positions, different θ will produce different double circular arc curves. When planning, θ is determined by optimizing the objective function expressed in the following formula.

[0072] The objective function is:

[0073]

[0074] L1≥L min ;

[0075] L2≥L min ;

[0076] Among them, w d is the weight of the lateral deviation, d is the preview deviation, w R is the curvature weight, κ min is the minimum curvature, κ max is the maximum curvature, L1 is the length of the first arc, L2 is the length of the second arc, L min is the minimum distance.

[0077] Human drivers do not make decisions on a time-by-time basis while driving, but rather make decisions intermittently and with tolerance. This leads us to propose an event-triggered planning method. First, the event trigger is calculated. When an event is triggered, the plan is re-normalized; otherwise, the previous plan is executed.

[0078] Furthermore, in S4, the triggering of the re-preview planning is determined by a preset trigger mechanism, which is constructed based on the following deviation and the executed mileage. Specifically, this embodiment establishes the following Figure 3 The event-triggered planning method shown mainly considers the path following deviation d e Design an event trigger mechanism, the trigger mechanism is:

[0079]

[0080] Among them, s e is the current mileage of the main vehicle, d e is the path following deviation, d max To allow the maximum path following deviation, s max The maximum execution mileage is triggered when and only when the path following deviation exceeds the design allowable deviation or exceeds the maximum execution mileage of the previous plan, re-planning is performed.

[0081] Furthermore, in S4, after triggering re-preview planning and inserting the preview result into the turning radius-mileage list, the other waypoints except the last two waypoints in the current follow-up waypoint list are deleted, a new follow-up waypoint list is obtained, and the process returns to S3.

[0082] Specifically, such as Figure 7 As shown, to address the issue of excessive tracking deviation when the tracking target and motion primitives do not match, this embodiment employs a multi-segment following decision method based on motion primitives. Given a preview target, the preview target is previewed using motion primitives, and segmentation points are determined based on the preview error. This process keeps the following error within a reasonable range.

[0083] For path following, first, the waypoints (X i ,Y i ,θ i ) is inserted into the list of follow-up waypoints. Since the car needs to travel a long enough distance to be able to maneuver, it is determined whether the difference between the first and last mileage of the follow-up waypoint exceeds the shortest distance required for the car to maneuver. If the distance is insufficient, continue to insert waypoints until the mileage difference exceeds the shortest distance required for maneuvering. When the distance is sufficient, preview is performed using the objective function. If the preview tracking accuracy is less than the allowable error, continue to insert more waypoints. Otherwise, the preview result of the previous step ([(R i1 , s i1 ), (R i2 , s i2 )] where R i1 , R i2 are the radii of the first and second arcs in the i-th double arc, s i1 , s i2 (R1, s1), ..., (R2, ..., (R3, ..., (R4, ..., (R5, ..., (R6, ..., (R7, ..., (R8, ..., (R9, ..., (R1, s1), ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R2, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R1, ..., (R2, ..., (R1, ..., (R1, ..., (R1, ..., (R n , s n )] is the decision result.

[0084] Furthermore, in the above S6, according to the current mileage s of the host vehicle, e Determine the turning radius R. When s n ≤s e ≤s n+1 The turning radius is R n , the expected lateral acceleration is determined based on the turning radius and the current vehicle speed V, and the expected lateral acceleration is calculated as:

[0085]

[0086] Among them, a y is the lateral acceleration, V is the current vehicle speed, R n is the turning radius. y The goal of vehicle steering is represented by transmitting it to the autonomous driving system, and the vehicle steering system (such as the power steering motor) is followed by standard automatic control methods (such as PID), so that the vehicle can achieve the motion goal of following a predetermined trajectory or path.

[0087] The embodiment enables the autonomous vehicle to smoothly follow the expected path by establishing an event-triggered preview method; establishes a driving preview motion primitive model in a double-arc mode to ensure that the position and direction of the vehicle are achieved at the same time; and establishes a motion primitive multi-section preview method based on following error to improve the application range and following accuracy of the method.

[0088] The above-described embodiments are only descriptions of the preferred modes of the present application and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those skilled in the art shall fall within the protection scope determined by the claims of the present application.

Claims

1. An event-triggered preview decision method for path following of an autonomous vehicle, characterized in that: include: S1. Obtaining an expected speed plan of the autonomous vehicle to be followed, and selecting a preview target according to the expected speed plan; S2. Update the list of postures to be followed according to the preview path points of the preview target; S3, inserting the waypoints in the to-be-followed pose list into the following waypoint list and deleting them, and calculating the difference between the first and last mileages of the following waypoint list. When the difference between the first and last mileages exceeds a preset shortest walking distance, stopping the insertion; S4. Previewing is performed based on the current list of followed waypoints. If the preview result does not meet the preset accuracy, re-preview planning is triggered and the preview result is inserted into the turning radius-mileage list, and the process returns to S3. If the preview result meets the preset accuracy, the process directly returns to S3. S5. Repeat S3-S4 until the list of poses to be followed is empty, and output the turning radius-mileage list; S6. Calculate an expected lateral acceleration based on the current driving information of the autonomous vehicle and the turning radius-mileage list, and send the expected lateral acceleration to the autonomous vehicle for following control. In the step S4, performing preview includes: Constructing a double-arc multi-segment trajectory calculation model, solving the double-arc multi-segment trajectory calculation model based on a trajectory shape free variable θ to obtain a double-arc multi-segment trajectory, wherein the trajectory shape free variable θ is determined by an objective function; The double arc multi-segment trajectory calculation model is: J = A + R1 (N1 - V); C A =A+R1N1; C B =J+R2V; Among them, A is the starting position, θ A is the starting direction, B is the end point, θ B is the end direction, α is θ A The angle pointing to AB, β is the angle from AB to θ B The angle of the first arc, θ is the angle of the first arc, N1 is the normal vector of point A, V is the normal vector of point J, R1 is the radius of the first arc, R2 is the radius of the second arc, C A 、C B The centers of the two arcs.

2. The event-triggered preview decision method for path following of an autonomous vehicle according to claim 1, characterized in that: In S1, obtaining the expected speed plan of the autonomous driving vehicle to be followed, and selecting a preview target according to the expected speed plan to be followed includes: Obtaining following path information and a current vehicle state of the autonomous vehicle; The current vehicle state is converted to the same coordinate system as the following path to obtain the mileage range of the preview target.

3. The event-triggered preview decision method for path following of an autonomous vehicle according to claim 1, characterized in that: The objective function is: L1≥L min ; L2≥L min ; Among them, w d is the weight of the lateral deviation, d is the preview deviation, w R is the curvature weight, k min is the minimum curvature, k max is the maximum curvature, L1 is the length of the first arc, L2 is the length of the second arc, L min is the minimum distance.

4. The event-triggered preview decision method for path following of an autonomous vehicle according to claim 1, characterized in that: In S4, triggering the re-preview planning is determined by a preset trigger mechanism, which is constructed based on the following deviation and the executed mileage. The trigger mechanism is: Among them, s e is the current mileage of the main vehicle, d e is the path following deviation, d max To allow the maximum path following deviation, s max is the maximum execution mileage, and e is the trigger result.

5. The event-triggered preview decision method for path following of an autonomous vehicle according to claim 1, characterized in that: In the S4, after triggering the re-preview planning and inserting the preview result into the turning radius-mileage list, the other waypoints except the last two waypoints in the current follow-up waypoint list are deleted, a new follow-up waypoint list is obtained, and the process returns to the S3.

6. The event-triggered preview decision method for path following of an autonomous vehicle according to claim 1, characterized in that: In S6, calculating the expected lateral acceleration includes: Among them, a y is the lateral acceleration, V is the current vehicle speed, R n is the turning radius.

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