Automatic driving automobile track planning method and system guided by reference to front automobile track

Abstract

The invention discloses an automatic driving automobile track planning method and system guided by referring to a front automobile track, and relates to the technical field of automatic driving, and the method comprises the steps: constructing a front automobile path; according to different transverse and longitudinal control targets, planning schemes are executed in a classified mode. According to the automatic driving automobile track planning method based on front automobile track guidance, on the basis of construction of the front automobile path, the historical path of the front automobile is considered, a future path of the front automobile is also considered, so that the planning distance is prolonged, the purpose of performing motion planning in advance is achieved, consistency with motion of the pilot automobile can be guaranteed, and the driving efficiency is improved. Moreover, the situation that the formation vehicle motion planning effect is not good or even fails when the vehicle distance is short can be prevented, and the capability of vehicle formation to adapt to the environment is improved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a method and system for autonomous driving vehicle trajectory planning guided by reference to the trajectory of a preceding vehicle. Background Art

[0002] Most current vehicle formations use a pilot vehicle driven by a driver, while the rest of the vehicles are autonomous. The path planning of vehicle formations can be based on a global path or on the historical trajectory of the preceding vehicle. The former not only needs to provide a global path, but also the driving environment is constantly changing, so there may be a large deviation between the global path and the actual situation. In addition, the motion consistency between the formation vehicles and the pilot vehicle is poor when avoiding obstacles. The latter does not require a global path, but only needs to construct the historical path of the preceding vehicle. However, it is also possible that the distance between the vehicle and the preceding vehicle is short, resulting in a short planning distance and poor motion planning effect.

[0003] Although the current vehicle formation motion planning method can ensure normal driving in many scenarios, it will cause large consumption of computing resources and bring unnecessary complexity in simple scenarios. Usually, different planning algorithms can be used to improve planning efficiency for scenarios of different complexity. Therefore, appropriate planning methods should be used for scenarios of different complexity. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: it can improve the motion consistency of platoon vehicles, especially in obstacle avoidance scenarios, while solving the problem of short planning distance and poor motion planning effect caused by relying solely on the historical path of the preceding vehicle, thereby improving the ability of vehicle platoons to adapt to environmental changes.

[0006] It improves the flexibility of vehicle formation motion planning in different scenarios, and can switch different planning methods according to the complexity of the scene, solving the problem of high computing resource consumption and complex algorithms in current vehicle formation motion planning in simple scenarios.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for planning a trajectory of an autonomous driving vehicle guided by the trajectory of a preceding vehicle, comprising:

[0008] Construct the path of the preceding vehicle;

[0009] According to different horizontal and vertical control objectives, the planning schemes are implemented in different categories.

[0010] As a preferred solution of the method for trajectory planning of an autonomous driving vehicle guided by the reference trajectory of a preceding vehicle described in the present invention, wherein: the construction of the preceding vehicle path includes initializing the preceding vehicle path, initializing a straight line from the platoon vehicle to the preceding vehicle, and discretizing the straight line into a number of points, assuming that the distance between the points is 1 meter, and the point sequence capacity is n;

[0011] When the vehicle formation is driving normally, the distance to the front point of the front vehicle's path will be calculated based on the current positioning information of the front vehicle. If it is greater than 1 meter, the current point will be added to the front vehicle's path, otherwise it will not be added; if the sequence of the front vehicle's path points is greater than the capacity n, the last point will be removed when adding a new point;

[0012] Based on the positioning information of the preceding vehicle and the constant acceleration model, a section of the preceding vehicle's future path is predicted and spliced ​​onto the path to complete the construction of the preceding vehicle's path.

[0013] As a preferred solution of the automatic driving vehicle trajectory planning method guided by reference to the trajectory of the preceding vehicle described in the present invention, the planning scheme classification includes a first scheme, a second scheme and a third scheme.

[0014] As a preferred solution of the method for trajectory planning of an autonomous driving vehicle guided by a reference to the trajectory of a preceding vehicle described in the present invention, the first solution includes obtaining a lateral control point by pre-aiming forward a certain distance from the position of the vehicle according to the construction result of the preceding vehicle path in the lateral direction;

[0015] In the longitudinal direction, the expected acceleration is obtained by considering the ideal vehicle distance, the actual vehicle distance, and the difference between the speeds of the preceding vehicle and the vehicle itself.

[0016] As a preferred solution of the method for trajectory planning of an autonomous driving vehicle guided by a reference to the trajectory of a preceding vehicle described in the present invention, the second solution includes that in the lateral direction, the platoon vehicles use the construction result of the preceding vehicle's path as a reference path to perform lateral obstacle avoidance;

[0017] Maintain distance and follow speed in the longitudinal direction.

[0018] As a preferred solution of the method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle described in the present invention, the third solution includes executing the second solution in the lateral direction to obtain the planned path of the vehicle;

[0019] In the vertical direction, dynamic programming obtains a rough solution, opens up the solution space, and then performs secondary programming to obtain the speed planning curve.

[0020] As a preferred solution of the automatic driving vehicle trajectory planning method guided by the reference to the preceding vehicle trajectory of the present invention, wherein: the platoon vehicles determine the scene to which they belong based on the surrounding environment information, and if the platoon vehicles determine that there are no obstacles around, the first solution is adopted;

[0021] If a static obstacle is found on the way, the planning scheme switches to the second scheme;

[0022] If a dynamic obstacle is found along the way, the planning scheme switches to the third scheme.

[0023] Another object of the present invention is to provide an autonomous driving vehicle trajectory planning system guided by the trajectory of the preceding vehicle, which can improve the motion consistency of platoon vehicles and the flexibility of motion planning of vehicle platoons in different scenarios by constructing an autonomous driving vehicle trajectory planning system guided by the trajectory of the preceding vehicle.

[0024] To solve the above technical problems, the present invention provides the following technical solutions: an autonomous driving vehicle trajectory planning system guided by the trajectory of a preceding vehicle, comprising: a planning module and a control module; the planning module is used to construct the path of the preceding vehicle; the control module is used to classify and execute planning schemes according to different lateral and longitudinal control targets.

[0025] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the automatic driving vehicle trajectory planning method guided by referring to the trajectory of a preceding vehicle as described above are implemented.

[0026] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the automatic driving vehicle trajectory planning method guided by the trajectory of the preceding vehicle as described above.

[0027] Beneficial effects of the present invention: The method for trajectory planning of an autonomous driving vehicle guided by the reference trajectory of a preceding vehicle provided by the present invention is based on the construction of the path of the preceding vehicle, and not only considers the historical path of the preceding vehicle, but also considers a section of the path of the preceding vehicle in the future, thereby extending the planned distance and achieving the purpose of advance motion planning. It can not only ensure consistency with the movement of the lead vehicle, but also prevent the situation where the motion planning of the platoon vehicles is poor or even fails when the distance between vehicles is short, thereby improving the ability of the vehicle formation to adapt to the environment.

[0028] According to the perceived surrounding environment information, driving scenarios are divided into three types: no obstacles, static obstacles, and dynamic obstacles. According to these three scenarios, three planning schemes with different levels of complexity are designed. In most (simple) scenarios, the platoon vehicles only need to follow the front vehicle, using a simpler planning method. In a few (complex) scenarios, motion planning is performed to achieve the purpose of obstacle avoidance, which improves the flexibility and planning efficiency of vehicle platoon motion planning in different scenarios.

[0029] Scheme 1 can achieve efficient driving of the vehicle formation by directly following the movement of the vehicle in front; Schemes 1 and 2 both maintain the distance and follow the speed in the longitudinal direction, thus achieving the safety and energy-saving characteristics of the vehicle formation; Schemes 2 and 3 plan in the lateral direction, while ensuring the safety of the vehicle formation, improving the quality of the obstacle avoidance trajectory of the leading vehicle and enhancing comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0031] Figure 1 An overall flow chart of a method for autonomous driving vehicle trajectory planning guided by reference to the trajectory of a preceding vehicle provided in accordance with an embodiment of the present invention.

[0032] Figure 2 Overall structure diagram of an automatic driving vehicle trajectory planning system guided by reference to the preceding vehicle trajectory provided by one embodiment of the present invention

[0033] Figure 3 A global path avoidance static obstacle map based on a method for trajectory planning of an autonomous driving vehicle guided by a reference trajectory of a preceding vehicle provided in one embodiment of the present invention.

[0034] Figure 4 A method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle is provided in accordance with an embodiment of the present invention, which is based on a static obstacle map of the preceding vehicle's path avoidance.

[0035] Figure 5 A dynamic obstacle avoidance map for deceleration in a method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0037] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0038] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a method for trajectory planning of an autonomous driving vehicle guided by a trajectory of a preceding vehicle, comprising:

[0039] 1. Build the path of the previous vehicle:

[0040] The path of the preceding vehicle is the reference path for the platoon vehicles to perform motion planning. In a scenario without obstacles, the path of the preceding vehicle is the path that the platoon vehicles need to follow; in a scenario with obstacles, path planning needs to be performed based on the path of the preceding vehicle.

[0041] The specific steps are described as follows:

[0042] (1) Initialize the path of the leading vehicle. Initialize a straight line from the platoon vehicle to the leading vehicle and discretize the straight line into several points. Assume that the distance between points is 1 meter and the point sequence capacity is n.

[0043] (2) When the vehicle formation is driving normally, the distance to the front point of the front vehicle's path will be calculated based on the current positioning information of the front vehicle. If it is greater than 1 meter, the current point will be added to the front vehicle's path, otherwise it will not be added. If the sequence of points in the front vehicle's path is greater than the capacity n, the last point will be removed when adding a new point to ensure that the capacity remains unchanged.

[0044] (3) Based on the positioning information of the preceding vehicle and the constant acceleration model, a section of the preceding vehicle's future path is predicted and connected to the paths of steps (1) and (2), thus completing the construction of the preceding vehicle's path.

[0045] 2. According to different horizontal and vertical control objectives, the planning schemes are divided into three types:

[0046] (1) Solution 1: The platoon vehicles follow the preceding vehicle in lateral and longitudinal motion based on the preceding vehicle’s motion information.

[0047] The specific steps are described as follows:

[0048] (1-1) Laterally, according to the path obtained in step 1, the lateral control point (xr, yr, thetar, kappar) is obtained by previewing a certain distance forward from the vehicle position;

[0049] (1-2) In the longitudinal direction, the vehicle distance should be kept as ideal as possible, and the speed should follow the vehicle in front: the expected acceleration is obtained by considering the difference between the ideal vehicle distance and the actual vehicle distance and the speed of the vehicle in front and the vehicle itself, and then input into the control module.

[0050] (2) Solution 2: The platoon vehicles use the path obtained in step 1 as a reference path to perform lateral obstacle avoidance, i.e., path planning: first dynamically plan a rough solution, then open up a solution space based on this rough solution, and finally obtain an optimal path through secondary planning. In the longitudinal direction, the vehicles maintain the distance and follow the speed;

[0051] The specific steps are described as follows:

[0052] Dynamic Programming:

[0053] (2-1) The road boundary is used as the boundary of dynamic programming, the matching point of the ego-vehicle coordinates on the reference path is used as the origin, and the reference path is used as the Frenet coordinate axis to establish the Frenet coordinate system;

[0054] (2-2) Starting from the planning starting point, it is evenly discretized into several points in the s and l directions;

[0055] (2-3) Design the cost function, mainly considering three aspects: smoothing cost, obstacle distance cost, and reference line cost. The calculation formula is as follows:

[0056] cost_function = w1∑f′(s i ) 2 +w2∑f″(s i ) 2 +w3∑f″′(s i ) 2 +∑g[(s i -s) 2 +(l i -l) 2 ]+∑l i

[0057] (2-4) Find the optimal path based on the cost function.

[0058] Quadratic Programming:

[0059] (2-5) Treat the path of dynamic programming as a rough solution, open up a solution space, and search for the optimal path in the solution space, that is, find l = f(s) that satisfies: the second-order derivative of f(s) is continuous, l = f(s) is in the solution space, and l = f(s) is as smooth as possible.

[0060] (2-6) Continuity constraint: Assuming that the third-order derivative of the curve f(s) connecting li and li+1 is always (li+1i”-li”) / △s, then expand li+1 and li+1' by Taylor,

[0061]

[0062] Convert it into matrix form:

[0063]

[0064] Assuming there are n points to be optimized, then:

[0065]

[0066] Let it be A eq x=b eq .

[0067] (2-7) Solution space constraints: The four vertices of the vehicle should be within the solution space;

[0068] Calculate the l of the four vertices of the vehicle. It is known that the distance from the center of mass of the vehicle to the front and rear of the vehicle is d1 and d2, the width is w, and the heading angle is θ. Then the l of the four vertices of the vehicle is:

[0069]

[0070] Make some approximations: sinθ≈tanθ≈l', cosθ≈1 and constrain it in the solution space:

[0071]

[0072] Also assume that there are n points to be processed:

[0073]

[0074] Denoted as Ax≤b.

[0075] (2-8) Cost function design: reference line cost, smoothness cost, solution space center cost;

[0076]

[0077] (2-9) According to the above two constraints and cost function, the quadratic programming solver is used to solve li, li', li" and si, and then the optimal path under quadratic programming can be obtained;

[0078] (2-10) The planned path and the expected acceleration considering distance maintenance and speed following are transmitted to the control module.

[0079] (3) Scheme 3: The vehicles in the platoon use the path obtained in step 1 as a reference path for path planning in the horizontal direction and speed planning in the vertical direction.

[0080] The specific steps are described as follows:

[0081] (3-1) Horizontally: Repeat steps (2-1)-(2-9) in solution 2 to obtain the planned path of the vehicle;

[0082] (3-2) Vertically: Use the same method as (3-1) to first obtain a rough solution through dynamic programming, open up the solution space, and then perform secondary programming to obtain the speed planning curve.

[0083] a. Generate ST graph: Project the dynamic obstacle onto the Frenet coordinate system with the planned path of the ego-vehicle as the coordinate axis to obtain the coordinates of the dynamic obstacle (s0, l0); predict the obstacle to move at a uniform speed, calculate s and T when the obstacle cuts in and out, and then generate the ST graph;

[0084] b. Dynamic programming:

[0085] S and T are sampled at scattered points, and the cost function is used to find a rough solution for the speed planning;

[0086] Cost function = obstacle cost + acceleration cost + recommended speed cost + jerk cost

[0087]

[0088] c. Secondary programming:

[0089] Generate the solution space from the rough solution of the previous step and obtain the upper and lower boundaries of the solution space;

[0090] Considering the vehicle dynamics constraints, no reversing constraints, continuity constraints and cost functions, we can get the matrices of quadratic programming solution, and then solve si, si', si" and combine them with Ti to get the optimal speed curve under quadratic programming.

[0091] Dynamic constraints:

[0092] No reverse restraint allowed:s i+1 ≥s i ;

[0093] Continuity constraints:

[0094] Cost function: reference line cost, acceleration cost, jerk cost

[0095]

[0096] (3-3) Combine (3-1) and (3-2) and input them into the control module together.

[0097] 3. Specific implementation of the planning scheme

[0098] The platoon vehicles determine the scene they belong to based on the surrounding environment information. If the platoon vehicles determine that there are no obstacles around, planning scheme one is adopted at this time. The platoon vehicles drive completely according to the path of the vehicle in front in the lateral direction, and maintain the ideal distance and speed in the longitudinal direction. If a static obstacle is found on the way, the planning method will switch to scheme two at this time. It can achieve obstacle avoidance while ensuring the consistency of the platoon movement, and it can also improve the obstacle avoidance path of the leading vehicle, and maintain the ideal distance and speed in the longitudinal direction. If a dynamic obstacle is found on the way, the planning method will switch to scheme three, and a certain response will be made to the obstacle in both the lateral and longitudinal directions to avoid the dynamic obstacle.

[0099] Example 2, reference Figure 2 , which is an embodiment of the present invention, provides an automatic driving vehicle trajectory planning system guided by a preceding vehicle trajectory, comprising:

[0100] Planning module 100 and control module 200;

[0101] The planning module 100 is used to construct a path for the preceding vehicle;

[0102] The control module 200 is used to classify and execute planning schemes according to different horizontal and vertical control targets.

[0103] Embodiment 3, an embodiment of the present invention, is different from the first two embodiments in that:

[0104] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0105] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0106] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0107] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0108] Example 4, reference Figure 3-Figure 5 , which is an embodiment of the present invention, provides a trajectory planning method for an autonomous driving vehicle guided by the trajectory of a preceding vehicle. In order to verify the beneficial effects of the present invention, a scientific demonstration is carried out through simulation experiments.

[0109] like Figure 3 , Figure 4 As shown in Figure 1, on the same road, the trajectories of lateral avoidance of static obstacles are based on the global path and the path of the preceding vehicle. Comparing the two trajectories, the latter convoy has a better consistency in trajectory.

[0110] Figure 5 The speed curves for avoiding dynamic obstacles on the same road are based on the previous vehicle's historical path and the previous vehicle's path (history + prediction). By comparison, although both can avoid dynamic obstacles by slowing down, the latter adds a predicted path to make the planned distance longer in order to prevent the planned distance provided by the previous vehicle's historical path from being too short, and starts to slow down and avoid earlier than the former, which improves the safety of the convoy's obstacle avoidance.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle, characterized in that: include: Construct the path of the preceding vehicle; According to different horizontal and vertical control objectives, the planning schemes are implemented in different categories.

2. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 1, characterized in that: The construction of the preceding vehicle path includes initializing the preceding vehicle path, initializing a straight line from the platoon vehicle to the preceding vehicle, and discretizing the straight line into a number of points, assuming that the distance between the points is 1 meter, and the point sequence capacity is n; When the vehicle formation is driving normally, the distance to the front point of the front vehicle's path will be calculated based on the current positioning information of the front vehicle. If it is greater than 1 meter, the current point will be added to the front vehicle's path, otherwise it will not be added; if the sequence of the front vehicle's path points is greater than the capacity n, the last point will be removed when adding a new point; Based on the positioning information of the preceding vehicle and the constant acceleration model, a section of the preceding vehicle's future path is predicted and spliced ​​onto the path to complete the construction of the preceding vehicle's path.

3. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 2, characterized in that: The planning scheme classification includes the first scheme, the second scheme and the third scheme.

4. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 3, characterized in that: The first solution includes obtaining a lateral control point by previewing a certain distance forward from the position of the vehicle according to the construction result of the path of the preceding vehicle in the lateral direction; In the longitudinal direction, the expected acceleration is obtained by considering the ideal vehicle distance, the actual vehicle distance, and the difference between the speeds of the preceding vehicle and the vehicle itself.

5. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 4, characterized in that: The second solution includes that in the lateral direction, the platoon vehicles use the constructed result of the path of the preceding vehicle as a reference path to perform lateral obstacle avoidance; Maintain distance and follow speed in the longitudinal direction.

6. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 5, characterized in that: The third solution includes executing the second solution in the horizontal direction to obtain the planned path of the vehicle; In the vertical direction, dynamic programming obtains a rough solution, opens up the solution space, and then performs secondary programming to obtain the speed planning curve.

7. The method for trajectory planning of an autonomous driving vehicle guided by the trajectory of a preceding vehicle as claimed in claim 6, characterized in that: The platoon vehicle determines the scene it belongs to based on the surrounding environment information. If the platoon vehicle determines that there are no obstacles around, the first solution is adopted; If a static obstacle is found on the way, the planning scheme switches to the second scheme; If a dynamic obstacle is found along the way, the planning scheme switches to the third scheme.

8. A system using the automatic driving vehicle trajectory planning method guided by the reference preceding vehicle trajectory as claimed in any one of claims 1 to 7, characterized in that: include: A planning module (100) and a control module (200); The planning module (100) is used to construct a path for the preceding vehicle; The control module (200) is used to classify and execute planning schemes according to different horizontal and vertical control targets.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for trajectory planning of an autonomous driving vehicle guided by reference to the trajectory of a preceding vehicle as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for trajectory planning of an autonomous driving vehicle guided by reference to the trajectory of a preceding vehicle as described in any one of claims 1 to 7 are implemented.

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