Lane-changing control method and device for vehicle

Abstract

This application relates to the field of automation and computer technology, and particularly to a lane-changing control method and device for a vehicle. The method includes: detecting the actual working condition of the vehicle; when the detected actual working condition is a low-speed lane-changing condition, collecting obstacle information around the vehicle and determining whether the obstacle ahead meets the preset lane-changing condition; if the preset lane-changing condition is met, regarding the obstacle as an obstacle to be concerned in the lane-changing scenario to detect whether the vehicle meets the preset free lane-changing condition, and when the free lane-changing condition is met, obtaining a lane-changing planning path from a preset fitting curve based on the current position and the target lane-changing position of the vehicle, and performing corresponding lane-changing actions according to the lane-changing planning path. The embodiments of this application can perform secondary scenario decision analysis, obtain a lane-changing planning path by using a preset fitting curve, and thus perform corresponding lane-changing actions, making the lane-changing planning closer to human habits, ensuring the safety and reliability of autonomous driving, and improving the comfort of users' driving and riding.

Description

Technical Field

[0001] This application relates to the field of automation and computer technology, and particularly to a lane-changing control method and device for a vehicle. Background Art

[0002] In related technologies, a lane-changing decision can be made based on the movement information of the host vehicle, obstacle information, and map information, and then a decision-making plan of generating a path by fitting a cubic polynomial curve and selecting an optimal path is adopted to achieve the rapidity, smoothness, and safety of lane-changing.

[0003] However, in related technologies, there will be deviations in the selection of target obstacles in actual lane-changing scenarios, resulting in too rough decision-making judgments on obstacles and the host vehicle, and insufficient smoothness of trajectory fitting, reducing the safety and reliability of driverless driving and unable to meet the driving needs of users. Summary of the Invention

[0004] This application provides a lane-changing control method and device for a vehicle to solve the technical problems in related technologies that there will be deviations in the selection of target obstacles in actual lane-changing scenarios, resulting in too rough decision-making judgments on obstacles and the host vehicle, and insufficient smoothness of trajectory fitting, reducing the safety and reliability of driverless driving and unable to meet the driving needs of users.

[0005] The first aspect embodiment of this application provides a lane-changing control method for a vehicle, including the following steps: detecting the actual working condition of the vehicle; when it is detected that the actual working condition is a low-speed lane-changing condition, collecting obstacle information around the vehicle and determining whether a front obstacle meets a preset lane-changing condition; if the preset lane-changing condition is met, regarding it as an obstacle of concern in the lane-changing scenario to detect whether the vehicle meets the preset free lane-changing condition, and when the free lane-changing condition is met, obtaining a lane-changing planned path from a preset fitting curve based on the current position and target lane-changing position of the vehicle, and performing corresponding lane-changing actions according to the lane-changing planned path.

[0006] According to the above technical means, the embodiment of this application can perform secondary scenario decision analysis, and when the free lane-changing condition is met, obtain a lane-changing planned path from a preset fitting curve based on the current position and target lane-changing position of the vehicle, so as to perform corresponding lane-changing actions, a lane-changing plan closer to human habits, ensuring the safety and reliability of autonomous driving and improving the comfort of users' driving.

[0007] Optionally, in an embodiment of the present application, the preset free lane change condition includes: whether the first distance from the obstacle concerned in the lane change scenario to the main path meets the first preset distance condition; whether the lateral distance from the obstacle concerned in the lane change scenario to the trajectory is within a preset range; when the second distance between the projection point of the obstacle on the trajectory and the projection point of the vehicle on the trajectory meets the second preset condition, the second distance is greater than a preset threshold.

[0008] According to the above technical means, the embodiments of the present application can focus on the distance from the obstacle to the main path based on the lane change scenario, thereby reducing the occurrence of traffic safety accidents and ensuring the safety and reliability of autonomous driving.

[0009] Optionally, in an embodiment of the present application, detecting the actual working condition of the vehicle includes: obtaining the positioning information and the global planning path information of the vehicle; determining whether the vehicle meets the preset activation lane change path planning condition according to the positioning information and the global planning path information; if the preset activation lane change path planning condition is met, controlling the vehicle to enter the low-speed lane change working condition.

[0010] According to the above technical means, the embodiments of the present application can determine whether the vehicle meets the lane change condition according to the positioning information and the global planning path information of the vehicle, thereby improving the reliability of the vehicle's driverless operation, reducing the occurrence of traffic accidents.

[0011] Optionally, in an embodiment of the present application, determining whether the front obstacle meets the preset lane change condition includes: determining whether the front obstacle meets the preset condition; if the preset condition is met, calculating the actual distance between the front obstacle and the vehicle; when the actual distance is less than or equal to the preset safety distance, calculating the dissatisfaction accumulation degree of the front obstacle to determine the obstacle concerned in the lane change scenario.

[0012] According to the above technical means, the embodiments of the present application can determine whether the lane change condition is met according to the front obstacle to ensure the safety of the vehicle lane change, improve the driving experience of users, and meet the use requirements of users.

[0013] Optionally, in an embodiment of the present application, the preset condition includes whether the lateral distance from the target vehicle to the trajectory is within a preset range, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles.

[0014] According to the above technical means, the embodiments of the present application can determine whether the preset condition is met based on the projection points on the vehicle trajectory, thereby improving the feasibility of driverless driving, ensuring the smoothness and stability of autonomous driving, and further enhancing the comfort of users' driving.

[0015] Optionally, in an embodiment of the present application, the method of the embodiment of the present application further includes: after performing the lane change action, determining whether the actual distance from the vehicle to the main path is less than or equal to a preset distance; if the actual distance is less than or equal to the preset distance, screening at least one target obstacle that meets the preset return lane condition; generating a return path to the main path from the preset fitting curve according to the at least one target obstacle and the target lane change position screened out, and performing a corresponding return action according to the return path to return to the main path.

[0016] According to the above technical means, the embodiment of the present application can generate a return path to the main path from the preset fitting curve according to the at least one target obstacle and the target lane change position screened out, and perform a corresponding return action according to the return path to return to the main path, which is a lane change plan closer to human habits, reduces the occurrence of traffic safety accidents, and further ensures the safety and reliability of autonomous driving.

[0017] An embodiment of the second aspect of the present application provides a lane change control device for a vehicle, including: a detection module, configured to detect the actual working condition of the vehicle; a judgment module, configured to collect obstacle information around the vehicle and judge whether a front obstacle meets a preset lane change condition when detecting that the actual working condition is a low-speed lane change condition; a control module, configured to, if the preset lane change condition is met, regard the obstacle as an obstacle concerned in the lane change scenario to detect whether the vehicle meets the preset free lane change condition, and when the free lane change condition is met, obtain a lane change planned path from the preset fitting curve based on the current position and the target lane change position of the vehicle, and perform a corresponding lane change action according to the lane change planned path.

[0018] Optionally, in an embodiment of the present application, the preset free lane change condition includes: whether the first distance from the obstacle concerned in the lane change scenario to the main path meets a first preset distance condition, whether the lateral distance from the obstacle concerned in the lane change scenario to the trajectory is within a preset interval, and while the second distance between the projection point of the obstacle concerned in the lane change scenario on the trajectory and the projection point of the vehicle on the trajectory meets a second preset condition, the second distance is greater than a preset threshold.

[0019] Optionally, in an embodiment of the present application, the detection module includes: an acquisition unit, configured to acquire the positioning information and the global planned path information of the vehicle; a determination unit, configured to determine whether the vehicle meets a preset activation lane change path planning condition according to the positioning information and the global planned path information; a control unit, configured to, if the preset activation lane change path planning condition is met, control the vehicle to enter the low-speed lane change condition.

[0020] Optionally, in an embodiment of the present application, the determination module includes: a determination unit configured to determine whether the obstacle ahead meets a preset condition; a first calculation unit configured to calculate the actual distance between the obstacle ahead and the vehicle if the preset condition is met; and a second calculation unit configured to calculate the dissatisfaction accumulation degree of the obstacle ahead to determine the obstacle of concern in the lane change scenario when the actual distance is less than or equal to a preset safety distance.

[0021] Optionally, in an embodiment of the present application, the preset condition includes whether the lateral distance from the target vehicle to the trajectory is within a preset interval, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles.

[0022] Optionally, in an embodiment of the present application, the device of the embodiment of the present application further includes: a determination module configured to determine whether the actual distance from the vehicle to the main path is less than or equal to a preset distance after the lane change action is executed; a screening module configured to screen at least one target obstacle that meets the preset return lane condition if the actual distance is less than or equal to the preset distance; and a control module configured to generate a return path to the main path from a preset fitting curve according to the at least one target obstacle and the target lane change position screened out, and perform a corresponding return action according to the return path to return to the main path.

[0023] An embodiment of the third aspect of the present application provides a vehicle, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the lane change control method of the vehicle as described in the above embodiment.

[0024] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the lane change control method of the vehicle as described above.

[0025] Advantages of the present application:

[0026] (1) The embodiment of the present application can determine whether the vehicle meets the lane change condition according to the positioning information of the vehicle and the global planning path information, thereby improving the reliability of the vehicle's driverless driving and reducing the occurrence of traffic accidents.

[0027] (2) The embodiment of the present application can determine whether the preset condition is met based on the projection point on the vehicle trajectory, thereby improving the feasibility of driverless driving, ensuring the smoothness and stability of autonomous driving, and further improving the comfort of the user's ride.

[0028] (3) The embodiments of the present application can perform secondary scenario decision analysis. When the conditions for free lane change are met, a lane change planning path is obtained from a preset fitting curve based on the current position of the vehicle and the target lane change position, thereby performing corresponding lane change actions. The lane change planning is closer to human habits, ensuring the safety and reliability of autonomous driving and improving the comfort of users' driving and riding.

[0029] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0031] Figure 1 is a flowchart of a lane change control method for a vehicle according to an embodiment of the present application;

[0032] Figure 2 is a schematic diagram of a lane change decision scenario for a specific embodiment of the present application;

[0033] Figure 3 is a schematic diagram of a post-lane change decision scenario for a specific embodiment of the present application;

[0034] Figure 4 is a schematic structural diagram of a lane change control device for a vehicle according to an embodiment of the present application;

[0035] Figure 5 is a schematic structural diagram of a vehicle according to an embodiment of the present application.

[0036] Among them, 10 is the lane change control device of the vehicle; 100 is the detection module, 200 is the judgment module, and 300 is the control module; 501 is the memory, 502 is the processor, and 503 is the communication interface. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0038] The lane change control method and device for a vehicle according to an embodiment of the present application will be described below with reference to the accompanying drawings. In view of the problem in the related art mentioned in the above background art that the selection of target obstacles in the actual lane change scenario will deviate, resulting in a too rough decision-making judgment on the obstacles and the vehicle itself, insufficient smoothness of trajectory fitting, reducing the safety and reliability of driverless driving, and unable to meet the driving needs of users, the present application provides a lane change control method for a vehicle. In this method, when it is detected that the actual working condition is a low-speed lane change working condition, the obstacle information around the vehicle is collected, and it is judged whether the front obstacle meets the preset lane change condition. When the preset lane change condition is met, it is used as the obstacle of concern in the lane change scenario to detect whether the vehicle meets the preset free lane change condition. When the free lane change condition is met, a lane change planning path is obtained from a preset fitting curve based on the current position of the vehicle and the target lane change position, and then the corresponding lane change action is executed, thereby ensuring the safety and reliability of autonomous driving and improving the comfort of the user's driving. Thus, the technical problem in the related art that the selection of target obstacles in the actual lane change scenario will deviate, resulting in a too rough decision-making judgment on the obstacles and the vehicle itself, insufficient smoothness of trajectory fitting, reducing the safety and reliability of driverless driving, and unable to meet the driving needs of users is solved.

[0039] Specifically, Figure 1 is a schematic flow chart of a lane change control method for a vehicle provided by an embodiment of the present application.

[0040] As Figure 1 shown, the lane change control method for the vehicle includes the following steps:

[0041] In step S101, the actual working condition of the vehicle is detected.

[0042] It can be understood that the actual working condition of the vehicle in the following steps can be detected in the embodiment of the present application, such as the vehicle speed, etc., so as to judge whether the vehicle needs to change lanes, ensure that the vehicle can change lanes quickly, smoothly and safely through driverless driving, and further improve the active safety of the vehicle and reduce the occurrence of road traffic accidents.

[0043] Among them, in an embodiment of the present application, detecting the actual working condition of the vehicle includes: obtaining the positioning information and the global planning path information of the vehicle; judging whether the vehicle meets the preset activation lane change path planning condition according to the positioning information and the global planning path information; if the preset activation lane change path planning condition is met, controlling the vehicle to enter the low-speed lane change working condition.

[0044] During the actual execution process, the embodiments of the present application can obtain the positioning information and global planning path information of the vehicle. For example, according to the positioning information of the vehicle, the global planning path information of the current lane where the vehicle is located can be read through a high-precision global map. The road information can include lane lines, speed limits, and the number of roads, etc. Thus, the input positioning information and global path planning information are loaded, and according to the matching situation between the positioning information and the global planning path information and the function state machine scheduling, it is determined whether the current scenario meets the preset activation lane-changing path planning condition. If the preset activation lane-changing path planning condition is met, the vehicle is controlled to enter the low-speed lane-changing working condition, thereby improving the intelligent level of the vehicle and enhancing the safety and reliability of driverless driving.

[0045] In step S102, when it is detected that the actual working condition is the low-speed lane-changing working condition, the obstacle information around the vehicle is collected, and it is determined whether the obstacle in front meets the preset lane-changing condition.

[0046] It can be understood that the embodiments of the present application can collect the obstacle information around the vehicle when it is detected that the actual working condition is the low-speed lane-changing working condition. For example, the obstacle information around the vehicle is collected through vehicle body sensors, and it is determined whether the obstacle in front meets the lane-changing condition, making the lane-changing planning of driverless driving closer to the human habit, improving the feasibility and reliability of driverless driving, and enhancing the comfort of users when driving.

[0047] It should be noted that the preset lane-changing condition is set by those skilled in the art according to the actual situation and is not specifically limited herein.

[0048] Among them, in an embodiment of the present application, determining whether the obstacle in front meets the preset lane-changing condition includes: determining whether the obstacle in front meets the preset condition; if the preset condition is met, calculating the actual distance between the obstacle in front and the vehicle; when the actual distance is less than or equal to the preset safety distance, calculating the dissatisfaction accumulation degree of the obstacle in front to determine the obstacle concerned in the lane-changing scenario.

[0049] As a possible implementation manner, as Figure 2 shown, when the vehicle meets the activation lane-changing path planning condition, the obstacle information is processed and judged as follows:

[0050] Step S1: Determine whether the obstacle A in front meets the preset condition.

[0051] Step S2: If the preset condition is met, determine whether the distance between the obstacle A in front and the vehicle is less than or equal to the minimum safe distance MSPA, and MSPA is in a decreasing state, that is:

[0052] MSP A =(V S -V A )*tc + 1 / 2a S *t c .^2 + Ssafe + S Long

[0053] Wherein, Vs is the vehicle speed of this vehicle, V A is the vehicle speed of the obstacle vehicle A ahead, tc is the unit time, as is the acceleration of this vehicle, Ssafe is the safety distance in the X direction, S Long is the threshold reserved longitudinally when changing lanes freely along the vehicle driving direction is activated.

[0054] Wherein, Ssafe is the safety distance in the X direction and can be 5m.

[0055] Step S3: When the actual distance is less than or equal to the preset safety distance, then judge the dissatisfaction accumulation degree of the obstacle A ahead, that is:

[0056] D(K) = D(K - 1) + T * (Udes - Us) / Udes

[0057] Wherein, Udes is the desired speed, taking 30 km / h, Us is the current vehicle speed of the host vehicle, T is the sampling time interval, taking 0.1 s, D(K) >= Dthreshold, wherein, Dthreshold is the preset minimum threshold of dissatisfaction accumulation.

[0058] Through the condition judgment of the above steps, it is thus determined as the obstacle concerned in the lane change scenario, thereby ensuring the safety of driverless driving and effectively meeting the driving and riding needs of users.

[0059] Optionally, in an embodiment of the present application, the preset conditions include whether the lateral distance from the target vehicle to the trajectory is within a preset interval, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles.

[0060] In some embodiments, the preset conditions include whether the lateral distance from the target vehicle to the trajectory is within a preset interval. For example, -1 / 2 * Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2 * Zy1, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles. For example, the projection point of the target vehicle on the trajectory offset - the projection point of this vehicle on the trajectory offset = Aoffset > 0, and the absolute value is the smallest min(Lx3) among all obstacles, thereby improving the feasibility of low-speed lane change of driverless driving, enhancing the safety of the vehicle, and reducing the occurrence of traffic accidents.

[0061] In step S103, if the preset lane-changing condition is satisfied, the obstacles are regarded as the lane-changing scenario to detect whether the vehicle meets the preset free lane-changing condition. When the free lane-changing condition is satisfied, a lane-changing planned path is obtained from the preset fitting curve based on the current position of the vehicle and the target lane-changing position, and the corresponding lane-changing action is executed according to the lane-changing planned path.

[0062] In some embodiments, when it is detected that the vehicle in the embodiment of the present application meets the lane-changing condition in the above steps, the obstacles are regarded as the lane-changing scenario to detect whether the vehicle meets the free lane-changing condition in the following steps. When the free lane-changing condition is satisfied, a lane-changing planned path can be obtained by performing multiple curve fittings based on the current position of the vehicle and the target lane-changing position. For example, a lane-changing planned path can be obtained from a fifth-degree fitting curve, effectively improving the smoothness of the trajectory fitting and enhancing the accuracy of the decision-making judgment between the obstacles and the vehicle itself, so as to execute the corresponding lane-changing action, thereby ensuring the safety and reliability of autonomous driving and enhancing the comfort of the user's driving and riding.

[0063] It should be noted that the preset fitting curve can be, but is not limited to, a fifth-degree fitting curve. In the embodiments of the present application, for the convenience of description, the following steps will take obtaining the lane-changing planned path from a fifth-degree fitting curve as an example for elaboration.

[0064] Optionally, in an embodiment of the present application, the preset free lane-changing condition includes: whether the first distance from the obstacle concerned in the lane-changing scenario to the main path meets the first preset distance condition, whether the lateral distance from the obstacle concerned in the lane-changing scenario to the trajectory is within a preset interval, and while the second distance between the projection point of the obstacle concerned in the lane-changing scenario on the trajectory and the projection point of the vehicle on the trajectory meets the second preset condition, the second distance is greater than a preset threshold.

[0065] In the actual execution process, as Figure 2 shown, when the vehicle meets the lane-changing condition, the obstacles are regarded as the lane-changing scenario to detect whether the vehicle meets the free lane-changing condition. Here, taking a left lane change as an example to detect whether the free lane-changing condition is met.

[0066] Screening condition 1:

[0067] 1). The distance from the target vehicle to the main path is negative.

[0068] 2). 1 / 2*Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2*Zy1 + Ly2.

[0069] 3). The offset of the projection point of the target vehicle on the trajectory - the offset of the projection point of the vehicle itself on the trajectory = Boffset >= 0, and it is the minimum min(Lx1) among all obstacles.

[0070] If the above conditions are met, continue to determine whether Boffset is greater than the threshold SLCLeftmin[max(SLCmin, K)]:

[0071] If VB >= VS, K = -(VB - VS).^2 / (2 * as) + LB + WS * Sin(theta), where as = 1 m / s^2;

[0072] If VB < VS, K = 3 * (VB - VS).^2 / (2 * as) + LB + WS * Sin(theta).

[0073] Among them, VB is the speed of obstacle vehicle B, VS is the speed of the host vehicle, K is the minimum threshold for calculating the offset of obstacle vehicle B, as is the acceleration of the host vehicle, LB is the length of obstacle vehicle B, WS is the width of the host vehicle, and Sin(theta) is the sine value of the included angle of the projection point.

[0074] Among them, SLCmin is the minimum distance of 15 m between the vehicle and the obstacle in front. If there is no lane width, then:

[0075] L = WLCs + Wveh / 2 + Dsafe

[0076] Among them, WLCs is the tangent distance from the outermost point on the left side of the vehicle to the path of the driver's seat, Dsafe is the safety distance, which can be calibrated to 1.75 meters.

[0077] Screening condition two:

[0078] 1). The distance from the target vehicle to the main path is negative.

[0079] 2). 1 / 2 * Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2 * Zy1 + Ly2.

[0080] 3). The offset of the projection point of the target vehicle on the trajectory - the offset of the projection point of the host vehicle on the trajectory = Coffset < 0, and the absolute value is the smallest among all obstacles, min(Lx2).

[0081] If the above conditions are met, continue to determine whether |Coffset| is greater than the threshold, that is:

[0082] SLCLeftminback[max(SLCmin, VC * ta - (VC + VS) * ta / 2 + LS + WC * Sin(theta)

[0083] Among them, ta = (VC - VS) / as.

[0084] Among them, Wveh / 2 is the half-width of the vehicle itself, VC is the speed of obstacle vehicle C, ta is the unit time, LS is the vehicle length of the vehicle itself, as is the acceleration of the vehicle itself, SLCLeftminback is the minimum distance between the vehicle and the obstacle in the left rear, WC is the width of obstacle vehicle C, and Sin(theta) is the sine value of the included angle of the projection point.

[0085] For example, when both the above screening condition 1 and screening condition 2 are satisfied, it is determined that the current scenario allows for free lane change. Then, based on the current position of the vehicle and the target lane change position, a lane change planning path is obtained from a fifth-degree fitting curve, and corresponding lane change actions are executed according to the lane change planning path.

[0086] For example, taking the left lane as an example, the lane change trajectory is planned as follows:

[0087] Step S11: The starting point of the lane change is the current position of the vehicle, and the ending point of the lane change is the center of the left lane (XLC1, YLC1).

[0088] Step S12: Lane change terminal conditions: The longitudinal offset is Long_offset_LC, and the lateral offset is Lat_offset_LC = -(1 / 2Zy1 + 1 / 2Ly2).

[0089] Step S13: Ensure that the planned trajectory is a fifth-degree fitting curve to improve the smoothness of the trajectory fitting and the accuracy of decision-making.

[0090] Step S14: The number of planned points N = max(Nacc, NPF).

[0091] Among them, Nacc is the number of preview points planned by the ACC function, and the algorithm calibration value is 100. NPF is the number of preview points planned by the path tracking function, and the algorithm calibration value is 100.

[0092] Step S15: When the distance along the center line of the left lane planned is greater than Long_offset_LC, the lateral offset distance remains Lat_offset_LC unchanged.

[0093] Step S16: Long_offset_LC = K * Vs * Sqrt[abs(lat_offset_LC)] / sqrt(as), where K is an adjustable coefficient, taking 2.7, as is the acceleration of the vehicle itself, taking 1 m / s2.

[0094] In summary, the embodiments of the present application can perform secondary scenario decision analysis, obtain a lane change planning path using a fifth-degree fitting curve, and then execute corresponding lane change actions, which is a lane change planning closer to human habits, reduces the occurrence of traffic safety accidents, and further ensures the safety and reliability of autonomous driving and improves the comfort of users' driving and riding.

[0095] It should be noted that the first preset distance condition, the second preset condition, and the preset interval are set by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0096] Furthermore, in an embodiment of the present application, the method of the embodiment of the present application further includes: after performing the lane change action, determining whether the actual distance from the vehicle to the main path is less than or equal to the preset distance; if the actual distance is less than or equal to the preset distance, screening at least one target obstacle that meets the preset return lane condition; generating a return path to the main path from the preset fitting curve according to the at least one target obstacle and the target lane change position, and performing corresponding return actions according to the return path to return to the main path.

[0097] For example, as Figure 3 shown, if it is necessary to return to the main path after performing the lane change action, the following judgment is required:

[0098] Step S21: Determine whether the distance from the host vehicle to the main path is less than or equal to 1 / 2Zy1 + 1 / 2Ly2 - Para_Lat, where Para_Lat = 0.3.

[0099] Step S22: If the condition of Step S21 is met, continue to screen the target obstacles.

[0100] Step S22.1: First, determine the front obstacle A.

[0101] (1) Satisfy -1 / 2*Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2*Zy1.

[0102] (2) And the projection point of the target vehicle on the trajectory - the projection point of the host vehicle on the trajectory = Aoffset > 0, and the absolute value is the smallest among all obstacles min(Lx3).

[0103] (3) Finally, determine whether the distance between A and the host vehicle is greater than the threshold max[SLCmin(15m), (VS - VA)*tc + 1 / 2aS*tc.^2 + LA + WSSin(thata)].

[0104] Where, VA is the vehicle speed of obstacle A, WS is the vehicle width of the host vehicle, and sin(theta) is the sine value of the projection point included angle.

[0105] Step S22.2: Screen obstacle E.

[0106] (1) The lateral distance from the target vehicle to the main path is positive.

[0107] (2) 1 / 2*Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2*Zy1 + Ry2.

[0108] (3) The offset of the projection point of the target vehicle on the trajectory - the offset of the projection point of the host vehicle on the trajectory = Eoffset >= 0, and it is the minimum min(Lx5) among all obstacles.

[0109] (4) Finally, determine whether Eoffset is greater than the threshold SLCLeftmin[max(SLCmin, K)]:

[0110] If VE >= VS, K = -(VE - VS).^2 / 2as + LE + WSSin(theta), as = 1m / s2;

[0111] If VE < VS, K = 3(VE - VS).^2 / 2as + LE + WSSin(theta).

[0112] Among them, VE is the vehicle speed of obstacle vehicle E, VS is the vehicle speed of the host vehicle, and LE is the vehicle length of obstacle vehicle E.

[0113] Step S22.3: Screen obstacle F.

[0114] (1) The lateral distance from the target vehicle to the main path is positive.

[0115] (2) 1 / 2 * Zy1 < the lateral distance from the target vehicle to the trajectory < 1 / 2 * Zy1 + Ry2.

[0116] (3) The offset of the projection point of the target vehicle on the trajectory - the offset of the projection point of the host vehicle on the trajectory = Foffset < 0, and its absolute value is the minimum min(Lx6) among all obstacles.

[0117] (4) Finally, determine whether |Foffset| is greater than the threshold SLCLeftminback[max(SLCmin, VF * ta - (VF + VS) * ta / 2 + LS + WFSin(theta)]), where ta = (VF - VS) / aS.

[0118] Among them, VF is the vehicle speed of obstacle vehicle F, LS is the vehicle length of the host vehicle, WF is the vehicle width of obstacle vehicle F, and sin(theta) is the sine value of the included angle of the projection point.

[0119] If the conditions in Step S21 and Step S22 are met, then plan the trajectory to return to the main path, specifically as follows:

[0120] Step S31: The starting point of the lane change is the current position of the vehicle, and the ending point of the lane change is the point (XLC2, YLC2) on the center line of the right lane.

[0121] Step S32: The lane change terminal condition is Long_offset_LC, and the lateral offset is Lat_offset_LC = 0.

[0122] Step S33: Ensure that the planned trajectory is a fifth-degree fitting curve to improve the smoothness of trajectory fitting and the accuracy of decision-making.

[0123] Step S34: The number of planned points N = max(Nacc, NPF).

[0124] Step S35: When the distance along the center line of the left lane in the plan is greater than SLCmin + 5m, the lateral offset distance remains unchanged at 1 / 2Zy1 + 1 / 2Ry2.

[0125] Step S36: Long_offset_LC = K * Vs * Sqrt[abs(lat_offset_LC)] / sqrt(as), where K is an adjustable coefficient, taking 2.7, and as is the acceleration of the host vehicle, taking 1m / s2.

[0126] Among them, Sqrt() is for square root extraction, abs() is for taking the absolute value, and lat_offset_LC is the lateral offset of the lane change.

[0127] In summary, the embodiment of the present application can generate a return path to the main path from a fifth-degree fitting curve according to at least one selected target obstacle and the target lane change position, and perform corresponding return actions according to the return path to return to the main path, making the lane change plan closer to the human habit, reducing the occurrence of traffic safety accidents, and thus ensuring the safety and reliability of autonomous driving and improving the comfort of user driving.

[0128] According to the lane change control method of the vehicle proposed by the embodiment of the present application, when it is detected that the actual working condition is a low-speed lane change working condition, the obstacle information around the vehicle can be collected, and it can be judged whether the front obstacle meets the preset lane change conditions. When the preset lane change conditions are met, it is used as an obstacle of concern in the lane change scenario to detect whether the vehicle meets the preset free lane change conditions. When the free lane change conditions are met, a lane change planning path can be obtained from a preset fitting curve based on the current position and the target lane change position of the vehicle, so as to perform corresponding lane change actions, thereby ensuring the safety and reliability of autonomous driving and improving the comfort of user driving. Thus, the technical problem in the related art that the selection of target obstacles in the actual lane change scenario will deviate, resulting in a too rough decision-making judgment on the obstacle and the host vehicle, and insufficient smoothness of trajectory fitting, reducing the safety and reliability of driverless driving and unable to meet the driving needs of users is solved.

[0129] Next, a lane change control device of a vehicle proposed according to an embodiment of the present application is described with reference to the accompanying drawings.

[0130] Figure 4 It is a block diagram of a lane change control device for a vehicle according to an embodiment of the present application.

[0131] As Figure 4 shown, the lane change control device 10 of the vehicle includes: a detection module 100, a judgment module 200, and a control module 300.

[0132] Specifically, the detection module 100 is configured to detect the actual working condition of the vehicle.

[0133] The judgment module 200 is configured to collect obstacle information around the vehicle and judge whether the front obstacle meets a preset lane change condition when the detected actual working condition is a low-speed lane change condition.

[0134] The control module 300 is configured to, if the preset lane change condition is met, regard the obstacle in the lane change scenario as the obstacle to be concerned to detect whether the vehicle meets the preset free lane change condition, and when the free lane change condition is met, obtain a lane change planning path from a preset fitting curve based on the current position of the vehicle and the target lane change position, and perform corresponding lane change actions according to the lane change planning path.

[0135] Optionally, in an embodiment of the present application, the preset free lane change condition includes: whether the first distance from the obstacle concerned in the lane change scenario to the main path meets the first preset distance condition, whether the lateral distance from the obstacle concerned in the lane change scenario to the trajectory is within a preset interval, and while the second distance between the projection point of the obstacle concerned in the lane change scenario on the trajectory and the projection point of the vehicle on the trajectory meets the second preset condition, the second distance is greater than a preset threshold.

[0136] Optionally, in an embodiment of the present application, the detection module 100 includes: an acquisition unit, a determination unit, and a control unit.

[0137] Among them, the acquisition unit is configured to acquire the positioning information and the global planning path information of the vehicle.

[0138] The determination unit is configured to determine whether the vehicle meets the preset active lane change path planning condition according to the positioning information and the global planning path information.

[0139] The control unit is configured to, if the preset active lane change path planning condition is met, control the vehicle to enter the low-speed lane change condition.

[0140] Optionally, in an embodiment of the present application, the judgment module 200 includes: a judgment unit, a first calculation unit, and a second calculation unit.

[0141] Among them, the judgment unit is configured to judge whether the front obstacle meets the preset condition.

[0142] The first calculation unit is configured to calculate the actual distance between the front obstacle and the vehicle if the preset condition is met.

[0143] A second calculation unit, configured to calculate the dissatisfaction accumulation degree of the obstacle ahead when the actual distance is less than or equal to the preset safety distance, so as to determine the obstacle concerned in the lane change scenario.

[0144] Optionally, in an embodiment of the present application, the preset conditions include whether the lateral distance from the target vehicle to the trajectory is within a preset interval, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles.

[0145] Optionally, in an embodiment of the present application, the device 10 in the embodiment of the present application further includes: a judgment module, a screening module, and a control module.

[0146] The judgment module is configured to judge whether the actual distance from the vehicle to the main path is less than or equal to the preset distance after the lane change action is executed.

[0147] The screening module is configured to screen at least one target obstacle that meets the preset return lane conditions if the actual distance is less than or equal to the preset distance.

[0148] The control module is configured to generate a return path to the main path from a preset fitting curve according to the at least one target obstacle and the target lane change position screened out, and execute a corresponding return action according to the return path to return to the main path.

[0149] It should be noted that the foregoing explanation of the embodiment of the lane change control method for a vehicle is also applicable to the lane change control device for a vehicle in this embodiment, and will not be elaborated here.

[0150] According to the lane change control device for a vehicle provided by the embodiment of the present application, when it is detected that the actual working condition is a low-speed lane change working condition, the obstacle information around the vehicle can be collected, and it can be judged whether the obstacle ahead meets the preset lane change conditions. When the preset lane change conditions are met, it is used as an obstacle concerned in the lane change scenario to detect whether the vehicle meets the preset free lane change conditions. When the free lane change conditions are met, a lane change planning path can be obtained from a preset fitting curve based on the current position and the target lane change position of the vehicle, so as to execute a corresponding lane change action, thereby ensuring the safety and reliability of autonomous driving and improving the comfort of user driving. Thus, the technical problem in the related art that the selection of the target obstacle in the actual lane change scenario will deviate, resulting in a too rough decision-making judgment on the obstacle and the vehicle, and the insufficient smoothness of the trajectory fitting, reducing the safety and reliability of driverless driving and unable to meet the driving needs of users is solved.

[0151] Figure 5 It is a schematic structural diagram of a vehicle provided by an embodiment of the present application. The vehicle may include:

[0152] A memory 501, a processor 502, and a computer program stored in the memory 501 and executable on the processor 502.

[0153] When the processor 502 executes the program, it implements the lane-changing control method for a vehicle provided in the above embodiments.

[0154] Furthermore, the vehicle further includes:

[0155] A communication interface 503 for communication between the memory 501 and the processor 502.

[0156] The memory 501 is used to store a computer program executable on the processor 502.

[0157] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0158] If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 can be interconnected via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 5 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0159] Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 can communicate with each other through an internal interface.

[0160] The processor 502 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0161] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the above-described lane-changing control method for a vehicle.

[0162] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0163] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0164] Any process or method description shown in a flowchart or described in other ways herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logic function or process. The scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0165] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection part (electronic device) having one or N wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0166] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N 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 in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0167] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the methods of the above-described embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0168] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, may exist physically alone for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0169] The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present application.

Claims

1. A lane change control method for a vehicle, characterized in that, Including the following steps: Detect the actual working condition of the vehicle; When it is detected that the actual working condition is a low-speed lane-changing condition, collect the obstacle information around the vehicle, and determine whether the obstacle in front satisfies the preset lane-changing condition. Among them, determining whether the obstacle in front satisfies the preset lane-changing condition includes: determining whether the obstacle in front satisfies the preset condition; if the preset condition is satisfied, calculate the actual distance between the obstacle in front and the vehicle; when the actual distance is less than or equal to the preset safety distance, calculate the dissatisfaction accumulation degree of the obstacle in front to determine the obstacle concerned in the lane-changing scenario; among them, the preset condition includes whether the lateral distance from the target vehicle to the trajectory is within the preset interval, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles; and If the preset lane-changing condition is satisfied, use it as the obstacle concerned in the lane-changing scenario to detect whether the vehicle satisfies the preset free lane-changing condition, and when the free lane-changing condition is satisfied, obtain the lane-changing planning path from the preset fitting curve based on the current position and the target lane-changing position of the vehicle, and perform the corresponding lane-changing action according to the lane-changing planning path. Among them, the preset free lane-changing condition includes: whether the first distance from the obstacle concerned in the lane-changing scenario to the main path satisfies the first preset distance condition; whether the lateral distance from the obstacle concerned in the lane-changing scenario to the trajectory is within the preset interval; when the second distance between the projection point of the obstacle concerned in the lane-changing scenario on the trajectory and the projection point of the vehicle on the trajectory satisfies the second preset condition, the second distance is greater than the preset threshold.

2. The method according to claim 1, wherein The detecting the actual working condition of the vehicle includes: Obtain the positioning information and the global planning path information of the vehicle; Determine whether the vehicle satisfies the preset activation lane-changing path planning condition according to the positioning information and the global planning path information; If the preset activation lane-changing path planning condition is satisfied, control the vehicle to enter the low-speed lane-changing condition.

3. The method according to claim 1, characterized in that, It also includes: After performing the lane-changing action, determine whether the actual distance from the vehicle to the main path is less than or equal to the preset distance; If the actual distance is less than or equal to the preset distance, screen at least one target obstacle that satisfies the preset return lane condition; Generate a return path to the main path from the preset fitting curve according to the at least one target obstacle and the target lane-changing position screened out, and perform the corresponding return action according to the return path to return to the main path.

4. A lane change control device for a vehicle, characterized in that, It includes: A detection module for detecting the actual working condition of the vehicle; A judgment module, configured to collect obstacle information around the vehicle and judge whether a front obstacle meets a preset lane-changing condition when it is detected that the actual working condition is a low-speed lane-changing condition. Wherein, judging whether the front obstacle meets the preset lane-changing condition includes: judging whether the front obstacle meets a preset condition; if the preset condition is met, calculating the actual distance between the front obstacle and the vehicle; when the actual distance is less than or equal to a preset safety distance, calculating the dissatisfaction accumulation degree of the front obstacle to determine an obstacle of concern in the lane-changing scenario; wherein, the preset condition includes whether the lateral distance from the target vehicle to the trajectory is within a preset interval, and the absolute value between the projection point of the target vehicle on the trajectory and the projection point of the vehicle on the trajectory is the smallest among all obstacles; and A control module, configured to, if the preset lane-changing condition is met, use the obstacle of concern in the lane-changing scenario to detect whether the vehicle meets the preset free lane-changing condition, and when the free lane-changing condition is met, obtain a lane-changing planning path from a preset fitting curve based on the current position and the target lane-changing position of the vehicle, and perform corresponding lane-changing actions according to the lane-changing planning path. Wherein, the preset free lane-changing condition includes: whether the first distance from the obstacle of concern in the lane-changing scenario to the main path meets a first preset distance condition; whether the lateral distance from the obstacle of concern in the lane-changing scenario to the trajectory is within a preset interval; while the second distance between the projection point of the obstacle of concern in the lane-changing scenario on the trajectory and the projection point of the vehicle on the trajectory meets a second preset condition, the second distance is greater than a preset threshold value.

5. A vehicle, characterized in that, including: A memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the lane-changing control method of the vehicle according to any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used to implement the lane-changing control method of the vehicle according to any one of claims 1-3.

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