Vehicle lane changing track generation method and device, vehicle and storage medium
By obtaining and using the speed, lane width, and obstacles when the autonomous vehicle has changed the track, determine the end point and horizontal position of the target changes, and generate a safer and comfortable trajectory. Low safety issues.
Patent Information
- Application Number
- CN202411704606.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-26
- Publication Date
- 2025-01-28
Smart Images
Figure CN119370124A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of lane change of autonomous driving vehicles, and in particular to a method, device, vehicle and storage medium for generating a lane change trajectory of a vehicle. Background Art
[0002] When the vehicle is automatically controlled to change lanes, the QP (Quadratic Programming) optimization target can be used to generate the corresponding lane change trajectory, thereby controlling the vehicle to automatically change lanes.
[0003] The QP optimization targets include the lateral distance from the center line of the lane, the lateral distance from the dynamically planned guidance path, the lateral speed, the lateral acceleration, the lateral acceleration change rate, the difference between the lateral distance of the planned end position and the expected lateral distance, the difference between the lateral speed of the planned end position and the expected lateral speed, and the difference between the lateral acceleration of the planned end position and the expected lateral acceleration. The lane change trajectory generated by the existing method is different from human driving behavior habits, and the lane change may be too slow or unnecessarily too close to the vehicle in front, affecting the customer's driving experience and safety. Summary of the invention
[0004] The main purpose of the present application is to provide a method, device, vehicle and storage medium for generating a lane change trajectory for a vehicle, aiming to solve the current technical problem of low safety when changing lanes.
[0005] To achieve the above objectives, the present application proposes a vehicle lane change trajectory generation method, the vehicle lane change trajectory generation method comprising:
[0006] When the vehicle changes lanes automatically, obtain the current lane change speed, lane width and obstacle information;
[0007] Determining a target lane change end point according to the current lane change vehicle speed and the lane width;
[0008] determining a lateral position of a target according to the obstacle information;
[0009] A lane change trajectory is generated using the target lane change end point and the target lateral position.
[0010] In one embodiment, the step of determining the target lane change end point according to the current lane change vehicle speed and the lane width includes:
[0011] According to the current lane-changing vehicle speed and the lane width, a target lane-changing time corresponding to the current lane-changing vehicle speed and the lane width is searched from a preset mapping table;
[0012] A target lane change end point is determined based on the target lane change time and the current lane change vehicle speed.
[0013] In one embodiment, the step of determining the target lane change end point based on the target lane change time and the current lane change vehicle speed includes:
[0014] Get the statistical time of the vehicle's automatic lane change;
[0015] Calculating a lane change end time according to the target lane change time and the statistical time;
[0016] The target lane change end point is calculated by the current lane change vehicle speed and the lane change end time.
[0017] In one embodiment, the step of determining the lateral position of the target according to the obstacle information comprises:
[0018] Obtaining an obstacle position according to the obstacle information;
[0019] determining at least one reference lateral position from the obstacle position;
[0020] A target lateral position is determined based on the obstacle position and the reference lateral position.
[0021] In one embodiment, the step of determining at least one reference lateral position by means of the obstacle position comprises:
[0022] Get vehicle width information and lane boundary line of the current lane;
[0023] Determining whether there is a preset obstacle on the lane boundary line based on the lane boundary line and the obstacle position;
[0024] When the preset obstacle exists on the lane boundary line, at least one reference lateral position is calculated according to the obstacle position and the vehicle width information.
[0025] In one embodiment, the step of determining the target lateral position according to the obstacle position and the reference lateral position comprises:
[0026] When the obstacle position is located at both sides of the lane boundary line, determining a first position relationship between the reference lateral position and the lane centerline and a second position relationship between the reference lateral positions;
[0027] A target lateral position is determined according to the reference lateral position, the first position relationship and / or the second position relationship.
[0028] In one embodiment, the step of generating a lane change trajectory using the target lane change end point and the target lateral position includes:
[0029] Taking the target lane change end point and the target lateral position as update optimization targets;
[0030] The preset objective function is updated by the updating optimization objective to obtain an optimized objective function;
[0031] Get boundary constraints;
[0032] A target vector is solved by using the boundary constraint and the optimization objective function, and a lane change trajectory is generated according to the target vector.
[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle lane change trajectory generation device, the vehicle lane change trajectory generation device comprising:
[0034] An acquisition module is used to obtain the current lane-changing speed, lane width and obstacle information when the vehicle automatically changes lanes;
[0035] A determination module, configured to determine a target lane change end point according to the current lane change vehicle speed and the lane width;
[0036] The determination module is further used to determine the lateral position of the target according to the obstacle information;
[0037] A generation module is used to generate a lane change trajectory according to the target lane change end point and the target lateral position.
[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle lane change trajectory generation method as described above.
[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the vehicle lane change trajectory generation method described above are implemented.
[0040] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the vehicle lane change trajectory generation method as described above.
[0041] One or more technical solutions proposed in this application obtain the current lane change speed, lane width and obstacle information when the vehicle changes lanes automatically; determine the target lane change end point according to the current lane change speed and the lane width; determine the target lateral position according to the obstacle information; and generate a lane change trajectory through the target lane change end point and the target lateral position. Compared with the existing lane change trajectory that does not consider the problem of changing lanes too slowly or getting close to the vehicle in front during the lane change process, this application comprehensively considers the lane change speed of the vehicle during the lane change process and generates the target lateral position according to the obstacle information, thereby increasing the optimization target of the lane change end point and the optimization target of the distance between the vehicle and the obstacle, planning the optimal lane change path for the vehicle, and improving the safety during the automatic lane change process. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.
[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.
[0044] Figure 1 A flowchart diagram of the first embodiment of the method for generating a lane change trajectory of a vehicle provided in the present application;
[0045] Figure 2 A flow chart of the second embodiment of the method for generating a lane change trajectory of a vehicle provided in the present application;
[0046] Figure 3 A flowchart diagram of a third embodiment of the method for generating a lane change trajectory of a vehicle provided in the present application;
[0047] Figure 4 This is a schematic diagram of the module structure of a vehicle lane change trajectory generating device according to an embodiment of the present application;
[0048] Figure 5 A schematic diagram of the vehicle structure of the hardware operating environment involved in the vehicle lane change trajectory generation method in the embodiment of the present application.
[0049] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION
[0050] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.
[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.
[0052] The main solution of the embodiment of the present application is: when the vehicle changes lanes automatically, obtain the current lane change speed, lane width and obstacle information; determine the target lane change end point according to the current lane change speed and the lane width; determine the target lateral position according to the obstacle information; generate a lane change trajectory through the target lane change end point and the target lateral position.
[0053] Since the lane change trajectory optimized by the existing technology through QP quadratic planning is different from human driving behavior habits, the lane change may be too slow or too close to the vehicle in front unnecessarily, affecting the customer's driving experience and safety.
[0054] The present application provides a solution, which adds an optimization target of the lateral distance from obstacles on both sides to the QP quadratic programming optimization target, and adds an optimization target of the lateral distance from the lane centerline after the anthropomorphic lane change end point, so as to plan the optimal driving path of the vehicle.
[0055] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a controller in a vehicle, etc. The following takes the controller in a vehicle as an example to illustrate this embodiment and the following embodiments.
[0056] Based on this, the embodiment of the present application provides a method for generating a vehicle lane change trajectory, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for generating a lane change trajectory for a vehicle of the present application.
[0057] In this embodiment, the vehicle lane change trajectory generation method includes steps S10 to S40:
[0058] Step S10: When the vehicle automatically changes lanes, obtain the current lane change speed, lane width and obstacle information.
[0059] It should be noted that the vehicle in this embodiment is an autonomous driving vehicle, and the main application scenarios include NOA (Navigate on Autopilot), ALC (Automatic Lane Change) or automatic lane changing scenarios such as unmanned driving.
[0060] When the user has a lane change requirement or the conditions for lane change exist, an automatic lane change instruction is generated to control the vehicle to change lanes automatically.
[0061] The current lane-changing speed is the speed at which the vehicle is traveling when it changes lanes automatically. The current lane-changing speed can be measured by a speed sensor. The lane width is the width of the lane that the vehicle needs to change lanes, which can be detected by a distance sensor. The obstacle information may include obstacle information around the vehicle, which may specifically include information such as the location of the obstacle, the type of obstacle, and the size of the obstacle.
[0062] Step S20: determining a target lane change end point according to the current lane change vehicle speed and the lane width.
[0063] It should be noted that the target lane change end point is the position where the vehicle's automatic lane change ends, specifically the longitudinal position corresponding to the end of the vehicle's lane change.
[0064] In a specific implementation, the position where the vehicle ends the lane change can be calculated using the current lane change speed and lane width. The calculation can be obtained based on the speed, distance, and time-related relationship.
[0065] Step S30: determining the lateral position of the target according to the obstacle information.
[0066] In a specific implementation, the target lateral position is the position of the vehicle on the lane being changed. When the obstacle position is different, the target lateral position corresponding to the vehicle is different. Therefore, the specific obstacle position can be determined according to the obstacle information, thereby determining the target lateral position.
[0067] Step S40: Generate a lane change trajectory using the target lane change end point and the target lateral position.
[0068] It should be noted that this embodiment adds a new optimization target in the lane change process. After obtaining the target lane change end point, the lateral distance between each point after the lane change end point and the lane centerline is used as a new optimization target. At the same time, the lateral distance from the obstacles on both sides of the current lane is obtained according to the target lateral position as a new optimization target, and the optimized lane change trajectory can be generated through the new optimization target.
[0069] In a feasible implementation, step S40 may include steps S41 to S44:
[0070] Step S41: taking the target lane change end point and the target lateral position as update optimization targets.
[0071] It should be noted that after obtaining the target lane change end point, the corresponding optimization point number can be set, and the corresponding optimization point number is recorded as i_LCend. The target lateral position is recorded as Ltarget. The target lane change end point and the target lateral position are used as the updated optimization target.
[0072] Step S42: updating the preset objective function by updating the optimization target to obtain the optimized objective function.
[0073] The preset objective function is the QP objective function, and the update optimization objective can be added to the QP objective function to obtain the optimized objective function.
[0074] As shown in the following formula 1, formula 1 is the expression of the preset objective function:
[0075]
[0076] In the above formula 1, cost is the target cost function of the entire optimization problem, l i , i = 0, ..., n-1 represents the target vector. For example, this is the lateral position of the vehicle at each time point, l ref , i = 0, ..., n-1 represents the reference trajectory or expected value, x end is the terminal state, that is, the value of the state variable at the last time step n-1. end , dd xend , ddd xend Respectively represent the speed, acceleration and third-order derivative (i.e. the rate of change of acceleration) of the vehicle state, which are the state variables at the last step. x ,ω ref ,ω_ xend ,ω_ dxend ,ω_ ddxend ,ω_ dddxend are weight coefficients, which determine the importance of the corresponding items in the total cost function. A larger weight means that the item is given a higher priority in the optimization process.
[0077] The optimization objective function obtained by adding the updated optimization objective to the preset objective function is expressed as follows:
[0078]
[0079] As shown in the above formula, the updated optimization objectives of the target lane change end point i_LCend and the target lateral position Ltarget are added.
[0080] Step S43: Obtain boundary constraints.
[0081] In a specific implementation, during the process of generating the lane change trajectory, a boundary constraint algorithm module may also be set, so as to generate a boundary constraint matrix and upper and lower boundaries through the boundary constraint algorithm module, thereby serving as boundary constraints. The boundary constraints may include lateral position size constraints, lateral velocity size constraints, lateral acceleration size constraints, lateral position continuity constraints, lateral velocity continuity constraints, lateral position initial state constraints, lateral velocity initial state constraints, lateral acceleration initial state constraints, etc. As shown in the following formula 3, the following formula 3 is a boundary constraint expression:
[0082] x_lower≤A·x≤x_upper (Formula 3)
[0083] In the above formula 3, A is the boundary constraint matrix, x_lower is the lower boundary, and x_upper is the upper boundary.
[0084] Step S44: solving a target vector through the boundary constraint and the optimization objective function, and generating a lane change trajectory according to the target vector.
[0085] In a specific implementation, the target vector is an optimized target vector, as shown in the following formula 4, which is an expression of the target vector:
[0086] x=[l0,l1,...l n-2 ,l n-1 ,l'0,l'1,...,l' n-2 ,l' n-1 ,l"0,l"1,...,l" n-2 ,l" n-1 ] T (Formula 4)
[0087] In a specific implementation, the optimization objective function in the above formula 2 can be expanded and rewritten into the basic form of quadratic programming. By expanding the QP optimization objective function, merging the quadratic term, the linear term, and omitting the constant term, the rewritten formula obtained is as follows:
[0088]
[0089] By rewriting the above formula 5 into the basic matrix form of quadratic programming, it is expressed as follows:
[0090]
[0091] In equation 6, P is a symmetric positive semidefinite matrix, and q is a vector that determines the first-order term of the objective function.
[0092] The QP solver is called to solve the above equations 3 and 6, thereby solving the optimal x vector, that is, obtaining the optimal lateral position of each point along the lane reference line in the front path. Therefore, the lane change trajectory of the vehicle is generated according to the optimal lateral position planning of each point, and the optimal driving path for automatic lane change is obtained.
[0093] This embodiment provides a method for generating a lane change trajectory for a vehicle. When the vehicle changes lanes automatically, the current lane change speed, lane width, and obstacle information are obtained; a target lane change end point is determined based on the current lane change speed and the lane width; a target lateral position is determined based on the obstacle information; and a lane change trajectory is generated using the target lane change end point and the target lateral position. Compared to existing lane change trajectories that do not consider the problem of changing lanes too slowly or getting close to the vehicle ahead during lane change, this application comprehensively considers the lane change speed of the vehicle during lane change and generates a target lateral position based on obstacle information, thereby increasing the optimization target of the lane change end point and the optimization target of the distance from the obstacle, planning the optimal lane change path for the vehicle, and improving safety during automatic lane change.
[0094] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S20 includes steps S201 to S202:
[0095] Step S201: querying a preset mapping table for a target lane-changing time corresponding to the current lane-changing speed and the lane width according to the current lane-changing speed and the lane width.
[0096] It should be noted that the preset mapping table is a correspondence table between vehicle speed, lane width and lane change time. The preset mapping table can be obtained by collecting the lane change time in obstacle-free conditions at various vehicle speeds and lane widths during daily self-driving by users, and making a data table that can be used to look up the lane change time by vehicle speed and lane width.
[0097] Therefore, the lane change time corresponding to the current lane change speed and lane width can be queried from a preset mapping table according to the current lane change speed and lane width as the target lane change time. For example, the target lane change time is 5s, 6s, etc.
[0098] Step S202: Determine a target lane change end point based on the target lane change time and the current lane change vehicle speed.
[0099] In a specific implementation, after obtaining the target lane change time, the lane change end time can be calculated using information such as the target lane change time and the current lane change vehicle speed, so that the corresponding target lane change end point can be determined based on the lane change end time.
[0100] In a feasible implementation, step S202 may include steps A11 to A13:
[0101] Step A11: Obtain the statistical time of the vehicle's automatic lane change.
[0102] It should be noted that the statistical time for the vehicle's automatic lane change is the elapsed time from the start of the vehicle's automatic lane change to the current time, which can be calculated based on the time when the vehicle starts to change lanes automatically and the current time. For example, if the time when the vehicle starts to change lanes automatically is 9:00:10 and the current time is 9:00:13, the statistical time for the vehicle's automatic lane change is 3s.
[0103] Step A12: Calculate the lane change end time according to the target lane change time and the statistical time.
[0104] In a specific implementation, the lane change end time can be calculated in real time based on the target lane change time and the statistical time. For example, if the target lane change time is 5 seconds and the statistical time is 3 seconds, the lane change end time is 2 seconds after the current time, that is, 9:00:15.
[0105] Step A13: Calculate a target lane change end point by using the current lane change vehicle speed and the lane change end time.
[0106] In a specific implementation, the longitudinal position corresponding to the lane change end time can be obtained from the speed planning data as the target lane change end point. Therefore, the corresponding longitudinal position can be determined by the current lane change speed and the lane change end time, thereby obtaining the target lane change end point.
[0107] After obtaining the target lane change end point, the lateral distance between each point after the target lane change end point and the lane centerline can be optimized, so as to continuously adjust the lane change path, so that the target lane change end point is continuously close to the lane centerline, improving the safety and comfort of lane change.
[0108] This embodiment queries a target lane changing time corresponding to the current lane changing speed and the lane width from a preset mapping table according to the current lane changing speed and the lane width; determines a target lane changing end point based on the target lane changing time and the current lane changing speed, and determines the target lane changing time by the current lane changing speed and the lane width. The lane changing strategy can be adjusted according to different lane changing speeds and different lane widths, and is applicable to a variety of road environments. By accurately calculating the target lane changing time and the lane changing end point, the trajectory during lane changing can be optimized, thereby improving the lane changing effect and safety.
[0109] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , step S30 includes steps S301 to S303:
[0110] Step S301: Obtain the obstacle position according to the obstacle information.
[0111] It should be noted that the obstacle information includes the obstacle position around the vehicle. The obstacle position may be located near the left boundary of the lane boundary line, near the right boundary of the lane boundary line, or near both the left and right boundaries of the lane boundary line.
[0112] Step S302: Determine at least one reference lateral position based on the obstacle position.
[0113] In a specific implementation, the reference lateral position is a position calculated according to the position of the obstacle. When the position of the obstacle is different, the corresponding reference lateral position is different.
[0114] For example, if the obstacle is located near the left boundary of the lane boundary line, the reference lateral position can be calculated based on the obstacle position. If the obstacle is located near the left and right boundaries of the lane boundary line, the reference position can be calculated based on the obstacle positions on both sides.
[0115] In a feasible implementation, step S302 may include steps B11 to B13:
[0116] Step B11: Obtain vehicle width information and lane boundary line of the current lane.
[0117] It should be understood that the vehicle width information can be queried in advance, for example, the vehicle width information is 1.6m, 1.8m, etc. The lane boundary lines of the current lane include a lane left boundary line and a lane right boundary line.
[0118] Step B12: Determine whether there is a preset obstacle on the lane boundary line based on the lane boundary line and the obstacle position.
[0119] In a specific implementation, the relationship between the left lane limit and the right lane boundary line and the obstacle position in the lane boundary line can be detected to determine whether there is a preset obstacle on the lane boundary line. The preset obstacle is a close-range obstacle. For example, a distance threshold can be set. For example, if the distance between the obstacle and the boundary line is less than 50 cm, the obstacle is determined to be a preset obstacle.
[0120] Step B13: When the preset obstacle exists on the lane boundary line, at least one reference lateral position is calculated according to the obstacle position and the vehicle width information.
[0121] It should be noted that when there is a preset obstacle on the lane boundary line, the reference lateral position can be calculated based on the obstacle position and vehicle width information.
[0122] For example, if there is a close obstacle at the left boundary of the lane line, the calculated reference lateral position L1 is the position of the close obstacle at the left boundary shifted to the right by (half the vehicle width information + 1) m. For example, if the vehicle width is 1.6 m, the reference lateral position L1 is the position of the close obstacle at the left boundary shifted to the right by 1.9 m.
[0123] If there is a close obstacle on the right edge of the lane line, the reference lateral position L2 is calculated as the position of the close obstacle on the right edge shifted to the left by (half the vehicle width information + 1) m. For example, if the vehicle width is 1.6 m, the reference lateral position L2 is the position of the close obstacle on the right edge shifted to the left by 1.9 m.
[0124] Step S303: determining the target lateral position according to the obstacle position and the reference lateral position.
[0125] In a specific implementation, a target lateral position may be selected from reference lateral positions according to the obstacle position and the calculated reference lateral position, and the target lateral position is a position corresponding to an optimal lateral distance between the vehicle and an obstacle near a lane boundary.
[0126] In the specific implementation, if the obstacle position is only on the left side of the lane boundary line, the positional relationship between the reference lateral position L1 and the lane centerline can be determined. If the reference lateral position L1 is on the right side of the lane centerline, that is, L1 is less than 0, the target lateral position L1 can be set. target is L1.
[0127] If the obstacle is only on the right side of the lane boundary, the positional relationship between the reference lateral position L2 and the lane centerline can be determined. If the reference lateral position L2 is on the left side of the lane centerline, that is, L2 is greater than 0, the target lateral position L2 can be set. target is L2.
[0128] In a feasible implementation, if the obstacle is located on both sides of the lane boundary line, step S303 may include steps C11 to C12:
[0129] Step C11: When the obstacle position is located on both sides of the lane boundary line, determine a first position relationship between the reference lateral position and the lane centerline and a second position relationship between the reference lateral positions.
[0130] It should be noted that when there are close obstacles on both sides of the lane boundary line, the positional relationship between the reference lateral position and the lane centerline can be determined. In this case, the reference lateral positions are L1 and L2.
[0131] Step C11: determining a target lateral position according to the reference lateral position, the first position relationship and / or the second position relationship.
[0132] In a specific implementation, the target lateral position may be determined according to the first positional relationship between the reference lateral positions L1 and L2 and the lane centerline. For example, if the reference lateral position L1 is located on the left side of the lane centerline or coincides with the lane centerline and the reference lateral position L2 is located on the right side of the lane centerline or coincides with the lane centerline, then the target lateral position L target is 0, that is, the reference lateral position L1 is greater than or equal to 0, the reference lateral position L2 is less than or equal to 0, and the target lateral position L target When it is 0, the vehicle maintains the current position.
[0133] In a specific implementation, the target lateral position may also be determined according to a second relationship between the reference lateral positions. For example, if the reference lateral position L1 is less than or equal to L2, the target lateral position L2 is set. target is (L1+L2) / 2.
[0134] As another example, the target lateral position can also be determined according to the first position relationship and the second position relationship. If the second position relationship is that the reference lateral position L1 is greater than L2 and the first position relationship is that L2 is located to the left of the lane centerline or coincides with the lane centerline, then the target lateral position L is set. target If the second position relationship is that the reference lateral position L1 is greater than L2 and the first position relationship is that L1 is located to the right of the lane centerline or coincides with the lane centerline, then the target lateral position L is set target For L1.
[0135] This embodiment obtains the obstacle position according to the obstacle information; determines at least one reference lateral position according to the obstacle position; and determines the target lateral position according to the obstacle position and the reference lateral position. The specific position of the obstacle is calculated, and then one or more reference lateral positions are determined based on the position information. Finally, the target lateral position that the vehicle should take is calculated in combination with the obstacle position and the selected reference lateral position to ensure driving safety and efficiency.
[0136] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle lane change trajectory generation method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.
[0137] This application also provides a vehicle lane change trajectory generation device, please refer to Figure 4 , the vehicle lane change trajectory generating device comprises:
[0138] The acquisition module 10 is used to obtain the current lane-changing speed, lane width and obstacle information when the vehicle automatically changes lanes.
[0139] The determination module 20 is used to determine a target lane change end point according to the current lane change vehicle speed and the lane width.
[0140] The determination module 20 is further configured to determine a lateral position of a target according to the obstacle information.
[0141] The generating module 30 is configured to generate a lane changing trajectory according to the target lane changing end point and the target lateral position.
[0142] The vehicle lane change trajectory generation device provided by the present application adopts the vehicle lane change trajectory generation method in the above embodiment, which can solve the current technical problem of low safety when changing lanes. Compared with the prior art, the beneficial effects of the vehicle lane change trajectory generation device provided by the present application are the same as the beneficial effects of the vehicle lane change trajectory generation method provided by the above embodiment, and other technical features in the vehicle lane change trajectory generation device are the same as the features disclosed in the above embodiment method, which will not be repeated here.
[0143] In one embodiment, the determination module 20 is further used to query a target lane change time corresponding to the current lane change speed and the lane width from a preset mapping table according to the current lane change speed and the lane width; and determine a target lane change end point based on the target lane change time and the current lane change speed.
[0144] In one embodiment, the determination module 20 is further used to obtain the statistical time of the vehicle's automatic lane change; calculate the lane change end time according to the target lane change time and the statistical time; and calculate the target lane change end point according to the current lane change speed and the lane change end time.
[0145] In one embodiment, the determination module 20 is further used to obtain an obstacle position according to the obstacle information; determine at least one reference lateral position through the obstacle position; and determine a target lateral position according to the obstacle position and the reference lateral position.
[0146] In one embodiment, the determination module 20 is further used to obtain vehicle width information and a lane boundary line of a current lane; determine whether there is a preset obstacle on the lane boundary line based on the lane boundary line and the obstacle position; when the preset obstacle exists on the lane boundary line, calculate at least one reference lateral position based on the obstacle position and the vehicle width information.
[0147] In one embodiment, the determination module 20 is also used to determine a first position relationship between the reference lateral position and the lane centerline and a second position relationship between reference lateral positions when the obstacle position is located on both sides of the lane boundary line; and determine the target lateral position based on the reference lateral position, the first position relationship and / or the second position relationship.
[0148] In one embodiment, the generation module 30 is further used to use the target lane change end point and the target lateral position as updated optimization targets; update the preset objective function through the updated optimization target to obtain the optimized objective function; obtain boundary constraints; solve the target vector through the boundary constraints and the optimized objective function, and generate a lane change trajectory according to the target vector.
[0149] The present application provides a vehicle, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle lane change trajectory generation method in the above-mentioned embodiment one.
[0150] Reference below Figure 5 , which shows a schematic diagram of a structure of a vehicle suitable for implementing the embodiment of the present application. The vehicle in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The vehicle shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.
[0151] like Figure 5As shown, the vehicle may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for vehicle operation are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the vehicle to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a vehicle with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.
[0152] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.
[0153] The vehicle provided by the present application adopts the vehicle lane change trajectory generation method in the above embodiment, which can solve the current technical problem of low safety when changing lanes. Compared with the prior art, the beneficial effects of the vehicle provided by the present application are the same as the beneficial effects of the vehicle lane change trajectory generation method provided by the above embodiment, and other technical features in the vehicle are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.
[0154] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.
[0155] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
[0156] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle lane change trajectory generation method in the above-mentioned embodiment.
[0157] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.
[0158] The computer-readable storage medium may be included in the vehicle, or may exist independently without being installed in the vehicle.
[0159] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the vehicle, the vehicle: obtains the current lane-changing speed, lane width and obstacle information when the vehicle automatically changes lanes; determines the target lane-changing end point according to the current lane-changing speed and the lane width; determines the target lateral position according to the obstacle information; and generates a lane-changing trajectory through the target lane-changing end point and the target lateral position.
[0160] Computer program code for performing the operations of the present application may be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0161] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0162] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.
[0163] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle lane change trajectory generation method, and can solve the current technical problem of low safety when changing lanes. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle lane change trajectory generation method provided by the above-mentioned embodiment, and will not be repeated here.
[0164] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned vehicle lane change trajectory generation method when executed by a processor.
[0165] The computer program product provided by the present application can solve the current technical problem of low safety when changing lanes. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the vehicle lane change trajectory generation method provided by the above embodiment, which will not be repeated here.
[0166] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.
Claims
1. A method for generating a vehicle lane change trajectory, characterized in that: The vehicle lane change trajectory generation method comprises: When the vehicle changes lanes automatically, obtain the current lane change speed, lane width and obstacle information; Determining a target lane change end point according to the current lane change vehicle speed and the lane width; determining a lateral position of a target according to the obstacle information; A lane change trajectory is generated using the target lane change end point and the target lateral position.
2. The method according to claim 1, characterized in that The step of determining the target lane change end point according to the current lane change vehicle speed and the lane width comprises: According to the current lane-changing vehicle speed and the lane width, a target lane-changing time corresponding to the current lane-changing vehicle speed and the lane width is searched from a preset mapping table; A target lane change end point is determined based on the target lane change time and the current lane change vehicle speed.
3. The method according to claim 2, characterized in that The step of determining the target lane change end point based on the target lane change time and the current lane change vehicle speed comprises: Get the statistical time of the vehicle's automatic lane change; Calculating a lane change end time according to the target lane change time and the statistical time; The target lane change end point is calculated by the current lane change vehicle speed and the lane change end time.
4. The method according to claim 1, characterized in that The step of determining the lateral position of the target according to the obstacle information comprises: Obtaining an obstacle position according to the obstacle information; determining at least one reference lateral position from the obstacle position; A target lateral position is determined based on the obstacle position and the reference lateral position.
5. The method according to claim 4, characterized in that The step of determining at least one reference lateral position by means of the obstacle position comprises: Get vehicle width information and lane boundary line of the current lane; Determining whether there is a preset obstacle on the lane boundary line based on the lane boundary line and the obstacle position; When the preset obstacle exists on the lane boundary line, at least one reference lateral position is calculated according to the obstacle position and the vehicle width information.
6. The method according to claim 4, characterized in that The step of determining the target lateral position according to the obstacle position and the reference lateral position comprises: When the obstacle position is located at both sides of the lane boundary line, determining a first position relationship between the reference lateral position and the lane centerline and a second position relationship between the reference lateral positions; A target lateral position is determined according to the reference lateral position, the first position relationship and / or the second position relationship.
7. The method according to any one of claims 1 to 6, characterized in that The step of generating a lane change trajectory by using the target lane change end point and the target lateral position comprises: Taking the target lane change end point and the target lateral position as update optimization targets; The preset objective function is updated by the updating optimization objective to obtain an optimized objective function; Get boundary constraints; A target vector is solved by using the boundary constraint and the optimization objective function, and a lane change trajectory is generated according to the target vector.
8. A vehicle lane change trajectory generation device, characterized in that: The device comprises: An acquisition module is used to obtain the current lane-changing speed, lane width and obstacle information when the vehicle automatically changes lanes; A determination module, configured to determine a target lane change end point according to the current lane change vehicle speed and the lane width; The determination module is further used to determine the lateral position of the target according to the obstacle information; A generation module is used to generate a lane change trajectory according to the target lane change end point and the target lateral position.
9. A vehicle, characterized in that: The vehicle comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle lane change trajectory generation method according to any one of claims 1 to 7.
10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle lane change trajectory generation method as described in any one of claims 1 to 7 are implemented.