A vehicle lane changing method, system, vehicle and storage medium

Abstract

The application relates to the technical field of vehicle control, and discloses a vehicle lane-changing method, a vehicle lane-changing system, a vehicle and a storage medium, the method comprising the following steps: acquiring vehicle information of a lane-changing vehicle, all lane information of a current driving road and a target detection result, the target detection result comprising obstacle targets on each lane; performing regional division on each lane based on the target detection result, so as to obtain a plurality of feasible regions; determining a lane-changing safety distance based on the vehicle information and the lane information; determining adjacent feasible regions and corresponding lane-changing weights based on all feasible regions, the lane-changing safety distance and the lane information; screening a lane-changing path of the lane-changing vehicle based on the vehicle information, the adjacent feasible regions and the corresponding lane-changing weights; determining a lane-changing path of the lane-changing vehicle based on the lane-changing path and the lane information; and controlling the lane-changing vehicle to drive along the lane-changing path. According to the application, the pose requirement of vehicle lane-changing can be considered, the rationality of lane-changing decision is improved, and the safety of vehicle lane-changing is ensured.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, specifically to a vehicle lane-changing method, system, vehicle, and storage medium. Background Technology

[0002] When a vehicle is driving autonomously on a closed road, it plans its route through the cloud and then follows the route provided by the cloud. Typically, the cloud receives all obstacle and map information and then determines whether the vehicle should change lanes to avoid potential congestion based on its current driving status.

[0003] However, in complex driving scenarios involving lane changes, such as when there is continuous traffic in the target lane and multiple lanes and obstacles need to be navigated around, existing lane-changing schemes only consider the vehicle's driving requirements and ignore the vehicle's position and posture requirements. This makes it impossible to make lane-changing decisions completely accurate, and lane-changing poses certain safety risks. Summary of the Invention

[0004] In view of this, the present invention provides a vehicle lane changing method, system, vehicle and storage medium to solve the problem that existing vehicle lane changing methods ignore vehicle position requirements, have unreasonable lane changing decisions, and are difficult to ensure vehicle lane changing safety.

[0005] In a first aspect, the present invention provides a vehicle lane-changing method, the method comprising:

[0006] Acquire vehicle information of vehicles changing lanes, information of all lanes on the current driving road, and target detection results, including obstacle targets in each lane;

[0007] Based on the target detection results, each lane is divided into regions to obtain multiple feasible regions;

[0008] Determine the safe lane-changing distance based on vehicle and lane information;

[0009] Based on all feasible areas, lane change safety distances, and lane information, adjacent feasible areas and their corresponding lane change weights are determined.

[0010] Based on vehicle information, adjacent feasible areas and their corresponding lane change weights, the reversible lane paths for lane-changing vehicles are selected.

[0011] The lane-changing path of the vehicle is determined based on the variable lane path and lane information.

[0012] Control vehicles changing lanes to travel along the lane-changing path.

[0013] The vehicle lane-changing method of the present invention comprehensively considers the vehicle's own position adjustment requirements, road structure, and other obstacles on the lane to perform multi-lane and multi-obstacle lane changes, which greatly improves the rationality of lane-changing decisions and ensures the safety of vehicle lane changes in complex driving scenarios.

[0014] In one optional implementation, vehicle information includes the vehicle's current position, vehicle steering mode, vehicle current attitude, vehicle target attitude, vehicle steering angle, and vehicle curvature; lane information includes the number of lanes, lane lines, and lane type; based on the vehicle information and lane information, determining the lane-changing safety distance includes:

[0015] Based on the vehicle's current steering angle, vehicle curvature, and target vehicle attitude, determine the vehicle's pose adjustment distance;

[0016] Based on the current position and steering mode of the vehicle changing lanes, determine the distance from the current position of the vehicle to the corresponding lane line.

[0017] The lane change distance is determined based on the spacing, the vehicle's current attitude, the vehicle's steering angle, the vehicle's curvature, and the vehicle's pose adjustment distance.

[0018] The safe lane-changing distance is obtained by adding the vehicle's lane-changing distance and the vehicle's position adjustment distance.

[0019] The lane change safety distance of the present invention takes into account the vehicle's position adjustment requirements and determines the lane change safety distance by using the vehicle's current vehicle information and lane information, which can improve the rationality of lane change decisions and ensure the safety of vehicle lane changes to a certain extent.

[0020] In one optional implementation, based on all feasible areas, lane change safety distances, and lane information, adjacent feasible areas and their corresponding lane change weights are determined, including:

[0021] Select two feasible regions that share a lane line from all feasible regions to form a region group set;

[0022] Get the length of the shared lane line between the two feasible regions corresponding to each group in the region group set, and denot it as the region adjacency length.

[0023] Determine if the adjacent length of the area is greater than the lane change safety distance;

[0024] If the adjacency length of a region is not greater than the lane change safety distance, then the two feasible regions corresponding to the current group are determined to be non-adjacent, and lane change weights are assigned to the two non-adjacent feasible regions, which are denoted as the first lane change weight.

[0025] If the adjacency length of a region is greater than the lane change safety distance, then the two feasible regions corresponding to the current group are determined to be adjacent. The lane type and adjacency length of the lanes to which the two adjacent feasible regions belong are obtained. Based on the lane type and the adjacency length of the region, a lane change weight is assigned to the two adjacent feasible regions, which is recorded as the second lane change weight. The second lane change weight is greater than the first lane change weight.

[0026] This invention determines whether two feasible areas are adjacent based on the relationship between the area adjacency length and the lane change safety distance. It also sets the path weight of adjacent feasible areas by lane type and area adjacency length, which can quickly and accurately obtain candidate areas that lane-changing vehicles can reach, thus helping to improve the rationality of vehicle lane-changing decisions.

[0027] In one optional implementation, based on vehicle information, adjacent feasible areas and their corresponding lane-change weights, the reversible paths for lane-changing vehicles are selected, including:

[0028] Determine the feasible area corresponding to the current position of the lane-changing vehicle, and record it as the starting area;

[0029] Based on the starting region and the preset ending region, other feasible regions adjacent to the current feasible region are selected, and reachable paths are constructed.

[0030] The lane change weights corresponding to each feasible region in the reachable path are summed to obtain the sum of the lane change weights of the reachable path.

[0031] Select the path with the smallest lane change weight as the lane change path for the vehicle.

[0032] This invention filters lane-change paths based on vehicle information of lane-changing vehicles, adjacent feasible areas and their corresponding lane-change weights, which can ensure the accuracy of lane-change paths and improve vehicle lane-change safety to a certain extent.

[0033] In one optional implementation, determining the lane-changing path of a lane-changing vehicle based on the variable lane path and lane information includes:

[0034] Determine the straight path corresponding to the current feasible area in the reversible lane path and the crab path corresponding to traveling from the current feasible area to the next feasible area; wherein, the straight path is determined based on the current position of the lane-changing vehicle and the crab starting point, the crab starting point is the position point that is farther away along the vehicle's travel direction between the current position of the vehicle and the starting point of the next feasible area in the reversible lane path, and the crab path is determined based on the position of the crab starting point and the next feasible area traveled by the lane-changing vehicle;

[0035] The straight-through paths and crab-walking paths of all feasible areas in the lane-changing path are summed to obtain the lane-changing path of the lane-changing vehicle.

[0036] This invention splices together the straight-through paths and crab-walking paths corresponding to all feasible areas in the lane-changing path to obtain the corresponding lane-changing path as a reference path for lane-changing vehicles, enabling them to travel along the reference path and ensuring lane-changing safety.

[0037] In one alternative implementation, controlling the lane-changing vehicle to travel along the lane-changing path includes:

[0038] The lane-changing path is fitted based on the current vehicle information of the lane-changing vehicle to obtain the corresponding driving path.

[0039] Control the vehicles changing lanes to travel along the driving path and execute the lane change.

[0040] This invention maximizes the path fitting of the lane change path, enabling vehicles to travel along the reference path accordingly, thus greatly improving the rationality of lane change decisions.

[0041] In one optional implementation, the obstacle targets include other vehicles and obstacles; based on the target detection results, each lane is divided into regions to obtain multiple feasible regions, including:

[0042] Other vehicles or obstacles are considered inaccessible areas;

[0043] Adjust the infeasible areas according to the preset distance;

[0044] Based on the adjusted infeasible areas, multiple lanes are divided into multiple feasible areas.

[0045] This invention divides and optimizes the feasible area based on other vehicles or obstacles, and has the advantage of reasonable and accurate division.

[0046] Secondly, the present invention provides a vehicle lane-changing system, the system comprising:

[0047] The acquisition module is used to acquire vehicle information of vehicles changing lanes, information of all lanes on the current driving road, and target detection results. The target detection results include obstacle targets in each lane.

[0048] The partitioning module is used to divide each lane into regions based on the target detection results, thereby obtaining multiple feasible regions;

[0049] The first determining module is used to determine the safe distance for lane changing based on vehicle information and lane information;

[0050] The second determination module is used to determine adjacent feasible areas and their corresponding lane change weights based on all feasible areas, lane change safety distances, and lane information.

[0051] The filtering module is used to filter the reversible paths of vehicles that change lanes based on vehicle information, adjacent feasible areas and their corresponding lane change weights.

[0052] The third determination module is used to determine the lane-changing path of the lane-changing vehicle based on the variable lane path and lane information;

[0053] The control module is used to control the vehicles changing lanes to travel along the lane-changing path.

[0054] The vehicle lane-changing system of the present invention can comprehensively consider the vehicle's own position adjustment requirements, road structure and other obstacles in the lane, which greatly improves the rationality of lane-changing decisions and ensures the safety of vehicle lane changing in complex driving scenarios.

[0055] Thirdly, the present invention provides a vehicle, the vehicle including a controller, the controller including a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform a vehicle lane-changing method according to the first aspect or any corresponding embodiment described above.

[0056] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform a vehicle lane-changing method according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0057] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0058] Figure 1 This is a schematic flowchart of a vehicle lane-changing method according to an embodiment of the present invention;

[0059] Figure 2 This is a schematic flowchart of another vehicle lane-changing method according to an embodiment of the present invention;

[0060] Figure 3 This is a schematic diagram of a driving scenario according to an embodiment of the present invention;

[0061] Figure 4 This is a schematic diagram of the region adjacency table according to an embodiment of the present invention;

[0062] Figure 5 This is a schematic diagram of an undirected graph according to an embodiment of the present invention;

[0063] Figure 6 This is a flowchart illustrating another vehicle lane-changing method according to an embodiment of the present invention;

[0064] Figure 7 This is a schematic diagram of the lane change path results according to an embodiment of the present invention;

[0065] Figure 8 This is a structural block diagram of a vehicle lane-changing system according to an embodiment of the present invention;

[0066] Figure 9 This is a schematic diagram of the structure of the vehicle controller according to an embodiment of the present invention. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] This invention provides an embodiment of a vehicle lane-changing method. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0069] This embodiment provides a vehicle lane-changing method. Figure 1 This is a flowchart illustrating a vehicle lane-changing method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the process includes the following steps:

[0070] Step S101: Obtain vehicle information of the lane-changing vehicle, all lane information of the current driving road, and target detection results. The target detection results include obstacle targets in each lane.

[0071] The vehicle information, lane information, and target detection results in this embodiment were all obtained by those skilled in the art using common data acquisition methods. For example, in a closed road scenario, there are V2X devices on both sides of the road. These V2X devices continuously report detected obstacle information, which is then processed in the cloud and converted into obstacle information associated with the lane. It should be noted that V2X (Vehicle to X) is a key technology in intelligent transportation systems, enabling communication between vehicles, between vehicles and base stations, and between base stations. This allows for the acquisition of real-time traffic conditions, road information, pedestrian information, and other traffic information, thereby improving driving safety, reducing congestion, increasing traffic efficiency, and providing in-vehicle entertainment information.

[0072] Step S102: Based on the target detection results, the lanes are divided into regions to obtain multiple feasible regions.

[0073] In this embodiment, the feasible area is the area where the lane-changing vehicle can travel in the changed lane. The lane is divided by the obstacles existing in the current lane to obtain multiple lane-changing areas, which helps to determine the optimal lane-changing path and greatly improves the rationality of the lane-changing decision.

[0074] Step S103: Determine the safe lane-changing distance based on vehicle information and lane information.

[0075] In this embodiment, the lane-changing safety distance is determined by comprehensively considering the vehicle's own position adjustment requirements, road structure, and other obstacles in the lane, which helps to improve the accuracy and rationality of vehicle lane-changing decisions.

[0076] Step S104: Based on all feasible areas, lane change safety distance, and lane information, determine adjacent feasible areas and their corresponding lane change weights.

[0077] In this embodiment, all feasible areas are filtered for adjacent areas based on lane change safety distance and lane information. This can obtain the areas that the vehicle can reach after multiple lane changes, providing sufficient data for determining the optimal lane change path and enhancing the rationality and accuracy of lane change decisions to a certain extent.

[0078] Step S105: Based on vehicle information, adjacent feasible areas and their corresponding lane change weights, filter the lane change paths for lane change vehicles.

[0079] In this embodiment, the lane change path is a reference path for lane change obtained by comprehensively considering the relevant information of the target vehicle, lane information, and lane obstacle information under a given driving scenario, with the minimum cost to the vehicle.

[0080] Step S106: Determine the lane-changing path of the lane-changing vehicle based on the variable lane path and lane information.

[0081] In this embodiment, by obtaining the reference change lane path and the current status information of the lane-changing vehicle, the actual lane-changing driving path of the vehicle is determined, which can provide reasonable guidance for the lane-changing vehicle and improve the safety of the lane-changing vehicle.

[0082] Step S107: Control the lane-changing vehicle to travel along the lane-changing path.

[0083] In this embodiment, after obtaining the corresponding lane change decision, the lane-changing vehicle performs corresponding fitting driving based on the received lane change path to achieve safe lane change.

[0084] The vehicle lane-changing method of this invention comprehensively considers the vehicle's own position adjustment requirements, road structure, and other obstacles in the lane. It can meet the vehicle's operational position requirements, support multi-lane and multi-obstacle lane changes, help improve the accuracy of lane-changing decisions, and ensure the safety of vehicle lane-changing driving.

[0085] This embodiment provides a vehicle lane-changing method. Figure 2 This is a flowchart illustrating another vehicle lane-changing method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0086] Step S201: Obtain vehicle information of the lane-changing vehicle, all lane information of the current driving road, and target detection results. The target detection results include obstacle targets in each lane. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0087] Step S202: Based on the target detection results, each lane is divided into regions to obtain multiple feasible regions. For details, please refer to [link to relevant documentation]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0088] Step S203: Determine the safe lane-changing distance based on vehicle information and lane information.

[0089] In this embodiment, vehicle information includes the vehicle's current position, vehicle steering mode, vehicle current attitude, vehicle target attitude, vehicle steering angle, and vehicle curvature; lane information includes the number of lanes, lane lines, and lane type. It should be noted that the vehicle's current position is an equivalent vehicle position reference point, determined based on the actual installation location of the vehicle position acquisition device or the vehicle type. For example, a flatbed truck uses its center point as the vehicle position reference point; for an onboard GPS system, if the GPS is installed at the front of the vehicle, the corresponding vehicle position reference point is the location of the front of the vehicle. This is only an example and is not intended to be limiting.

[0090] Specifically, step S203 includes:

[0091] Step S2031: Determine the vehicle pose adjustment distance based on the vehicle steering angle, vehicle curvature, and vehicle target attitude corresponding to the current driving of the lane-changing vehicle.

[0092] In this embodiment, the distance required for the vehicle body to adjust to a specified position is called the vehicle position adjustment distance L. adjust It is a value evaluated based on vehicle attributes, and is related to vehicle attributes and vehicle posture requirements, i.e., vehicle posture adjustment distance L. adjust =f(p vehicle ), where p vehicle These are vehicle-related attributes, including parameters such as the vehicle's current attitude, steering mode, steering angle, and curvature. It should be noted that different vehicle types have different corresponding vehicle pose adjustment distances, L. adjust Different. For example, the distance L required for the flatbed truck to adjust its body to a specified position. adjust The value of 1 is for illustrative purposes only and is not intended to be limiting. It can be adjusted adaptively according to actual needs.

[0093] Step S2032: Based on the current position of the vehicle and the vehicle's steering mode, determine the distance between the current position of the vehicle and the corresponding lane line.

[0094] In this embodiment, the vehicle's current location is obtained via onboard GPS; the vehicle's steering mode includes left turn and right turn, determined by the driving trajectory of the lane-changing vehicle.

[0095] Step S2033: Determine the vehicle lane change distance based on the spacing, the vehicle's current attitude, the vehicle's steering angle, the vehicle's curvature, and the vehicle's pose adjustment distance.

[0096] It should be noted that the lane change distance of a vehicle is obtained based on empirical formulas corresponding to different vehicle types.

[0097] In this embodiment, the lane-changing vehicle is a flatbed truck, and its corresponding empirical formula is:

[0098] L change =L intervel / Math.sin(angle)+2×angle / maxCurvature+1

[0099] Among them, L change For vehicle lane change distance, L intervelThe distance to the lane line is given by angle (the vehicle's steering angle when changing lanes, which must be less than the maximum steering angle the vehicle can support), maxCurvature is the maximum curvature of the vehicle, and 1 is the vehicle pose adjustment distance L of the flatbed truck. adjust .

[0100] Step S2034: Add the vehicle lane change distance and the vehicle position adjustment distance to obtain the safe lane change distance.

[0101] In this embodiment, the lane change safety distance is the sum of the vehicle lane change distance and the vehicle position adjustment distance, i.e., the lane change safety distance L. safe =L change +L adjust .

[0102] Step S204: Based on all feasible areas, lane change safety distance, and lane information, determine adjacent feasible areas and their corresponding lane change weights.

[0103] Specifically, step S204 includes:

[0104] Step S2041: Filter out all feasible regions that have two feasible regions corresponding to the shared lane lines to form a region group set.

[0105] In this embodiment, Figure 3 This is a schematic diagram of a driving scenario according to an embodiment of the present invention. It should be noted that the diagram contains six feasible regions, with region IDs 1-6, where the lane-changing vehicle is located in region 1. (See also...) Figure 3 If area 1 and area 3 share a lane line, then area 1 and area 3 will be grouped together as a set of data.

[0106] Step S2042: Obtain the length of the shared lane line between the two feasible regions corresponding to each group in the region group set, and denot it as the region adjacency length.

[0107] In this embodiment, the region adjacency length L adjoin This refers to the length of a lane line shared by two areas. (See also...) Figure 3 Regions 1 and 3 share a set of data on lane lines. The corresponding adjacent lengths of these regions are marked in the figure using a box diagram, which is only for illustrative purposes.

[0108] Step S2043: Determine whether the adjacent length of the region is greater than the lane change safety distance.

[0109] In this embodiment, the relationship between the area adjacency length and the lane change safety distance is used to determine whether a set of data (area 1 and area 3) with shared lane lines are truly adjacent, that is, whether the two feasible areas are adjacent.

[0110] Step S2044: If the adjacency length of the region is not greater than the lane change safety distance, then it is determined that the two feasible regions corresponding to the current group are not adjacent, and lane change weights are assigned to the two non-adjacent feasible regions, which are recorded as the first lane change weight.

[0111] In this embodiment, the specific value of the first lane change weight is not limited and can be adjusted adaptively according to actual needs. For example, a first lane change weight of 0 indicates that the lane change weights of two feasible regions are 0 and that the two feasible regions are not adjacent.

[0112] Step S2045: If the area adjacency length is greater than the lane change safety distance, then determine that the two feasible areas corresponding to the current group are adjacent, obtain the lane type and area adjacency length of the lanes to which the two adjacent feasible areas belong, and assign lane change weights to the two adjacent feasible areas based on the lane type and area adjacency length, which are recorded as the second lane change weight. The second lane change weight is greater than the first lane change weight.

[0113] In this embodiment, the specific value of the second lane change weight is not limited and can be adjusted adaptively according to actual needs. For example, the second lane change weight is a non-zero value. It should be noted that a non-zero value indicates that two feasible regions are adjacent. Specific values ​​such as 1 or 2 represent the lane change weights of the two feasible regions, and different lane change weights represent the corresponding costs that vehicles need to pay for changing lanes.

[0114] In this embodiment, refer to Figure 3 When the adjacency length of an area is greater than the lane change safety distance, the areas are adjacent. It should be noted that an area is adjacent to itself, and area 1 is adjacent to itself.

[0115] In one specific embodiment, the obtained adjacent feasible regions and their corresponding lane change weights are displayed using a region adjacency table. See also... Figure 4 The rows and columns in the table represent the number of feasible regions in the current driving scenario, with the specific numbers indicating the adjacency relationship between two regions and their corresponding lane-change weights. Figure 4 It can be seen that area 1 and area 3 are adjacent, which means that vehicles can safely change lanes from area 1 to area 3.

[0116] It should be noted that in this embodiment, the attributes of two adjacent areas and their respective lanes are obtained, and the lane change weight is evaluated based on the lane attributes (for example, the adjacent lane is an overtaking lane or a temporarily controlled lane).

[0117] Specifically, the lane attribute evaluation lane change weight, i.e., the lane change weight W, satisfies the following relationship:

[0118] W = f(L) adjoin )+f(P lane )

[0119] Where, f(L) adjoin ) = 1 / L adjoin Adjacency distance L adjoin The longer the length, the lower the cost; f(P) lane The mapping function is denoted as , for example, an adjacent lane is an overtaking lane and its mapping is 1; a regular lane is mapped to 2; and a temporarily controlled lane is mapped to ∞. The lower the cost, the higher the priority when changing lanes. Specifically, in this embodiment, the weight of lane changes can be adjusted by manually setting lane attributes.

[0120] Step S205: Based on vehicle information, adjacent feasible areas and their corresponding lane change weights, filter the lane change paths for lane change vehicles.

[0121] Specifically, step S205 includes:

[0122] Step S2051: Determine the feasible area corresponding to the current position of the lane-changing vehicle, and record it as the starting area.

[0123] In this embodiment, refer to Figure 3 The vehicle changing lanes is in area 1, meaning the starting area is area 1.

[0124] Step S2052: Based on the starting area and the preset ending area, filter other feasible areas adjacent to the current feasible area and construct a reachable path.

[0125] In this embodiment, the preset endpoint area is a specific area determined before the lane-changing vehicle changes lanes, and it is set according to the driver's needs. (See also...) Figure 3 The preset endpoint area can be set to area 6 or area 3, which is only an example.

[0126] Step S2053: The lane change weights corresponding to each feasible region in the reachable path are accumulated to obtain the sum of the lane change weights of the reachable path.

[0127] In this embodiment, the reachable path is the minimum cost lane-changing path obtained based on the driving scenario of the current lane-changing vehicle, and it is determined according to the lane-changing weight of the provided reachable path.

[0128] Step S2054: Select the path with the smallest lane change weight as the lane change path for the lane-changing vehicle.

[0129] In one specific embodiment, a reachable path calculation method is provided to obtain the corresponding variable-tour path, the process including:

[0130] Step A1: Convert the adjacency table into an undirected graph.

[0131] In this embodiment, based on the region where the current lane-changing vehicle is located (region 1), the next node of the graph, region 3, is determined by the adjacent regions (with values ​​greater than 0) of region 1 in the adjacency table. The undirected graph is obtained by traversing the table sequentially. Figure 5 This is a schematic diagram of an undirected graph according to an embodiment of the present invention.

[0132] Step A2: Determine the starting area, ending area, and maximum number of lane changes.

[0133] In this embodiment, the starting area is 1, the ending area is 6, and the maximum number of lane changes is 4.

[0134] It should be noted that the maximum number of lane changes is manually set, based on the driver's restrictions on automatic lane changing. Specifically, the more lane changes, the greater the probability of a successful lane change, but the more complex the lane change route may be. For example, a lane change cannot be achieved if the number of lane changes is 2, while a lane change route exists if the number of lane changes is greater than 5. This is only used as an example.

[0135] Step A3: Select the starting area as the current area.

[0136] Step A4: Decrease the maximum number of lane changes by 1. If the maximum number of lane changes is 0, exit the loop.

[0137] In this embodiment, the current region is region 1; the maximum number of lane changes is reduced to 3, and the following steps continue.

[0138] Step A5: Starting from the current region, find all reachable regions in the untraversed regions of the current region.

[0139] In this embodiment, the current area is area 1; the maximum number of lane changes is reduced to 3; and the reachable area is area 3.

[0140] Step A6: Record the status of reachable regions, including reachable region ID, current total path weight, traversed regions, and untraversed regions.

[0141] In this embodiment, the current path weight, traversed regions, and untraversed regions of reachable region 3 are recorded, and the corresponding records are updated.

[0142] Step A7: Compare the weight of the reachable region with the weight from the starting point to the current region, and retain the path with the smallest weight.

[0143] Step A8: Set the reachable area as the new current area, and repeat steps A3, A4, A5, and A6.

[0144] Step A9: After the termination condition is met, check the reachable paths in the destination area.

[0145] Step A10: If a reachable path exists, continue calculating the lane change path.

[0146] The results of the above process are shown in Table 1.

[0147] Table 1

[0148] Steps / Areas 2 3 4 5 6 1 ∞ 2，[1，3]，[2，4，5，6] ∞ ∞ ∞ 2 ∞ 2，[1，3]，[2，4，5，6] ∞ 4，[1，3，5]，[2，4，6] ∞ 3 ∞ 2，[1，3]，[2，4，5，6] 6，[1，3，5，4]，[2，6] 4，[1，3，5]，[2，4，6] ∞ 4 8[1，3，5，4，2]，[6] 2，[1，3]，[2，4，5，6] 6，[1，3，5，4]，[2，6] 4，[1，3，5]，[2，4，6] 8[1，3，5，4，6]，[2]

[0149] It should be noted that the rows in the table represent the calculation steps, and the columns represent other feasible regions. The starting region 1 is not listed. The values ​​in the table represent the cost of reaching that point from the starting region, [regions already visited], and [regions not yet visited].

[0150] Specifically, as shown in Table 1, in step 1: the initial starting point is region 1, and region 2 is unreachable, so the corresponding item in the table is ∞; region 3 is reachable, with a cost of 2, and the [regions already visited] are [1, 3], and the [regions not visited] are [2, 4, 5, 6]; region 4, region 5, and region 6 are unreachable, and the corresponding items in the table are all ∞.

[0151] Step 2: The initial starting point is region 3. Region 2 is unreachable; the path to region 3 remains unchanged; region 4 is unreachable; region 5 is reachable at a cost of 2. Therefore, the cost from region 1 to region 5 is 4. Thus, the table shows the following affected content: 4, [1,3,5], [2,4,6].

[0152] All other items in the table are obtained according to the steps described above.

[0153] If there is a reachable path [1,3,5,4,6] in step 4, then the subsequent lane change path calculation will be performed.

[0154] The embodiments of the present invention filter lane-changing paths based on vehicle information of lane-changing vehicles, adjacent feasible areas and their corresponding lane-changing weights, which can ensure the accuracy of lane-changing paths and improve the safety of lane-changing vehicles to a certain extent.

[0155] Step S206: Determine the lane-changing path of the vehicle based on the variable lane path and lane information. For details, please refer to [link to relevant documentation]. Figure 1 Step S106 of the illustrated embodiment will not be described again here.

[0156] Step S207: Control the vehicle changing lanes to travel along the lane-changing path. For details, please refer to [link / reference]. Figure 1 Step S106 of the illustrated embodiment will not be described again here.

[0157] This embodiment provides a vehicle lane-changing method. Figure 6 This is a flowchart illustrating another vehicle lane-changing method according to an embodiment of the present invention, such as... Figure 6As shown, the process includes the following steps:

[0158] Step S601: Obtain vehicle information of the lane-changing vehicle, all lane information of the current driving road, and target detection results. The target detection results include obstacle targets in each lane. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0159] Step S602: Based on the target detection results, the lanes are divided into regions to obtain multiple feasible regions.

[0160] In this embodiment, obstacle targets include other vehicles and obstacles.

[0161] Specifically, step S602 includes:

[0162] Step S6021: Other vehicles or obstacles are designated as inaccessible areas.

[0163] It should be noted that obstacles include pedestrians, roadblocks, etc., and are only used as examples and are not intended to be limiting.

[0164] Step S6022: Adjust the infeasible area according to the preset distance.

[0165] In this embodiment, the specific value of the preset distance is not limited and is set according to actual application requirements. For example, the infeasible area can be expanded according to different vehicle models and vehicle position reference points. The preset distance is half the length of the vehicle body in front of or behind the obstacle or other vehicles as the expansion range of the infeasible area. This is only an example for illustration.

[0166] Step S6023: Divide the multiple lanes into regions based on the adjusted infeasible regions to obtain multiple feasible regions.

[0167] In one specific embodiment, vehicles or obstacles are designated as infeasible areas, thus dividing each lane into multiple zones. These infeasible zones are expanded based on different vehicle types and vehicle position reference points. It should be noted that the lane-changing vehicle itself does not participate in zone segmentation. For example, a flatbed truck uses its center point as the vehicle position reference point, and extends half the length of the truck body forward and backward based on obstacles or other vehicles to create infeasible zones, thus dividing multiple lanes into multiple feasible zones. Specifically, by splicing the straight-through paths and zigzag paths corresponding to all feasible zones in the lane-changing path, a corresponding lane-changing path is obtained as a reference path for the lane-changing vehicle, enabling the vehicle to travel along the reference path and ensuring lane-changing safety.

[0168] Step S603: Determine the safe lane-changing distance based on vehicle and lane information. For details, please refer to [link to relevant documentation]. Figure 2Step S203 of the illustrated embodiment will not be described again here.

[0169] Step S604: Based on all feasible areas, lane change safety distances, and lane information, determine adjacent feasible areas and their corresponding lane change weights. For details, please refer to [link to relevant documentation]. Figure 2 Step S204 of the illustrated embodiment will not be described again here.

[0170] Step S605: Based on vehicle information, adjacent feasible areas, and their corresponding lane-change weights, filter the lane-change paths for vehicles changing lanes. For details, please refer to [link to relevant documentation]. Figure 2 Step S205 of the illustrated embodiment will not be described again here.

[0171] Step S606: Determine the lane-changing path of the lane-changing vehicle based on the variable lane path and lane information.

[0172] In this embodiment, after the reachable path is calculated, a change-path calculation is required for each path segment.

[0173] Specifically, step S606 includes:

[0174] Step S6061: Determine the straight path corresponding to the current feasible area in the variable lane path and the crab path corresponding to traveling from the current feasible area to the next feasible area; wherein, the straight path is determined based on the current position of the lane-changing vehicle and the crab starting point, the crab starting point is the position point that is farther away along the vehicle's travel direction from the current position of the vehicle and the starting position of the next feasible area in the variable lane path, and the crab path is determined based on the position of the crab starting point and the next feasible area traveled by the lane-changing vehicle.

[0175] It should be noted that the crab-walking path is related to the crab-walking mode supported by the vehicle. Crab-walking modes, also known as lateral movement modes, include: front-wheel steering, rear-wheel steering, and four-wheel steering. The crab-walking mode in this embodiment is determined based on a flatbed truck.

[0176] Step S6062: The straight-through paths and crab-walking paths of all feasible areas in the lane-changing path are accumulated to obtain the lane-changing path of the lane-changing vehicle.

[0177] In one specific embodiment, the lane change path calculation process for each path segment includes:

[0178] Step B1: Take the larger value between the current point and the starting point of the next area as the starting point for the vehicle's crab movement in the current area.

[0179] Step B2: Calculate the straight path from the current point to the starting point of the crab movement.

[0180] Step B3: Calculate the crab's path from the crab's final crawling point to the next area. Repeat steps B1, B2, and B3. After reaching the last area, calculate the execution path from the final crab crawling point to the lane change point. Concatenate all paths and return. The corresponding lane change path result is as follows: Figure 7 As shown.

[0181] Depend on Figure 7 As can be seen, the point that is farther away from the current point and the starting point of the next area in the mapping points of the current lane is used as the starting point of the crab movement and the end point of the straight movement. In one cycle, the detailed path from the current point to the end point of the straight movement and the crab movement route from the starting point to another lane can be calculated, and then the next cycle can begin.

[0182] Step S607: Control the lane-changing vehicle to travel along the lane-changing path.

[0183] Specifically, step S607 includes:

[0184] Step S6071: Fit the lane-changing path based on the current vehicle information of the lane-changing vehicle to obtain the corresponding driving path.

[0185] In this embodiment, the fitting method is not limited and is set based on actual needs.

[0186] Step S6072: Control the lane-changing vehicle to travel along the driving path and execute the lane change.

[0187] In this embodiment, the calculated final route is the reference lane-changing path of the vehicle reference point (the location where the GPS is installed on the vehicle). The vehicle-side then fits this reference route to determine the actual execution path, aiming for the smallest possible error between the actual path and the reference path. This path can be calculated by the lane-based autonomous driving algorithm. Specifically, by maximizing the path fitting of the lane-changing path, the vehicle can drive accordingly along the reference path, greatly improving the rationality of lane-changing decisions.

[0188] In summary, the vehicle lane-changing method of this invention comprehensively considers the vehicle's own position adjustment requirements, road structure, and other obstacles in the lane to perform multi-lane and multi-obstacle lane changes, greatly improving the rationality of lane-changing decisions and ensuring the safety of vehicle lane changes in complex driving scenarios.

[0189] This embodiment also provides a vehicle lane-changing system for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, a "module" is a combination of software and / or hardware that performs a predetermined function. Although the systems described in the following embodiments are preferably implemented in software, hardware implementations, or combinations of software and hardware, are also possible and contemplated.

[0190] This invention provides a vehicle lane-changing system, such as Figure 8 As shown, the system includes:

[0191] The acquisition module 801 is used to acquire vehicle information of vehicles changing lanes, all lane information of the current driving road, and target detection results. The target detection results include obstacle targets in each lane.

[0192] The partitioning module 802 is used to partition each lane into regions based on the target detection results, thereby obtaining multiple feasible regions.

[0193] The first determining module 803 is used to determine the safe distance for lane changing based on vehicle information and lane information.

[0194] The second determining module 804 is used to determine adjacent feasible areas and their corresponding lane change weights based on all feasible areas, lane change safety distances, and lane information.

[0195] The filtering module 805 is used to filter the lane change paths of lane-changing vehicles based on vehicle information, adjacent feasible areas and their corresponding lane change weights.

[0196] The third determining module 806 is used to determine the lane-changing path of the lane-changing vehicle based on the variable lane path and lane information.

[0197] The control module 807 is used to control the vehicles changing lanes to travel along the lane-changing path.

[0198] In some optional implementations, the partitioning module 802 includes: a first partitioning submodule, a second partitioning submodule, and a third partitioning submodule; wherein, the first partitioning submodule is used to designate other driving vehicles or obstacles as infeasible areas; the second partitioning submodule is used to adjust the infeasible areas according to a preset distance; and the third partitioning submodule is used to partition multiple lanes based on the adjusted infeasible areas to obtain multiple feasible areas.

[0199] In some optional implementations, the first determining module 803 includes: a first determining submodule, a second determining submodule, a third determining submodule, and a fourth determining submodule; wherein, the first determining submodule is used to determine the vehicle pose adjustment distance based on the vehicle steering angle, vehicle curvature, and vehicle target posture corresponding to the current driving of the lane-changing vehicle; the second determining submodule is used to determine the distance from the current position of the vehicle to the corresponding lane line based on the current position and vehicle steering mode corresponding to the current driving of the lane-changing vehicle; the third determining submodule is used to determine the vehicle lane-changing distance based on the distance, the current vehicle posture, the vehicle steering angle, the vehicle curvature, and the vehicle pose adjustment distance; and the fourth determining submodule is used to add the vehicle lane-changing distance and the vehicle pose adjustment distance to obtain the safe lane-changing distance.

[0200] In some optional implementations, the second determining module 804 includes: a filtering submodule, an acquisition submodule, a judgment submodule, a first result submodule, and a second result submodule; wherein, the filtering submodule is used to filter all feasible regions that have two feasible regions corresponding to a shared lane line, forming a region group set; the acquisition submodule is used to acquire the length of the shared lane line between the two feasible regions corresponding to each group in the region group set, denoted as the region adjacency length; the judgment submodule is used to determine whether the region adjacency length is greater than the lane change safety distance; the first result submodule is used to determine that the two feasible regions corresponding to the current group are not adjacent if the region adjacency length is not greater than the lane change safety distance, and assign a lane change weight to the two non-adjacent feasible regions, denoted as the first lane change weight; the second result submodule is used to determine that the two feasible regions corresponding to the current group are adjacent if the region adjacency length is greater than the lane change safety distance, acquire the lane type and region adjacency length of the lanes to which the adjacent feasible regions belong, and assign a lane change weight to the two adjacent feasible regions based on the lane type and region adjacency length, denoted as the second lane change weight, the second lane change weight being greater than the first lane change weight.

[0201] In some optional implementations, the filtering module 805 includes: a first filtering submodule, a second filtering submodule, a third filtering submodule, and a fourth filtering submodule; wherein, the first filtering submodule is used to determine the feasible area corresponding to the current position of the lane-changing vehicle, denoted as the starting area; the second filtering submodule is used to filter other feasible areas adjacent to the current feasible area based on the starting area and a preset ending area, and construct an reachable path; the third filtering submodule is used to accumulate the lane-changing weights corresponding to each feasible area in the reachable path to obtain the sum of the lane-changing weights of the reachable path; the fourth filtering submodule is used to filter the reachable path with the smallest sum of lane-changing weights as the lane-changing path for the lane-changing vehicle.

[0202] In some optional implementations, the third determining module 806 includes a fifth determining submodule and a sixth determining submodule; wherein, the fifth determining submodule is used to determine the straight path corresponding to the current feasible area in the variable lane path and the crab path corresponding to traveling from the current feasible area to the next feasible area; wherein, the straight path is determined based on the current position of the lane-changing vehicle and the crab starting point, the crab starting point is the position point that is farther away along the vehicle's travel direction from the current position of the vehicle and the starting position of the next feasible area in the variable lane path, and the crab path is determined based on the position of the crab starting point and the next feasible area traveled by the lane-changing vehicle; the sixth determining submodule is used to accumulate the straight paths and crab paths of all feasible areas in the variable lane path to obtain the lane-changing path of the lane-changing vehicle.

[0203] In some optional implementations, the control module 807 includes a fitting submodule and a control submodule; wherein the fitting submodule is used to fit the lane-changing path based on the current vehicle information of the lane-changing vehicle to obtain the corresponding driving path; the control submodule is used to control the lane-changing vehicle to drive along the driving path and execute the lane change.

[0204] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0205] In this embodiment, the vehicle lane-changing system is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0206] The vehicle lane-changing system of this invention can take into account the positional requirements of the vehicle lane-changing, improve the rationality of lane-changing decisions, and ensure the safety of vehicle lane-changing.

[0207] This invention also provides a vehicle, which includes a controller; please refer to [link to relevant documentation]. Figure 9 , Figure 9 This is a schematic diagram of the structure of the controller provided in an optional embodiment of the present invention, as shown below. Figure 9 As shown, the controller includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the main controller, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple main controllers can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 9 Take a processor 10 as an example.

[0208] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0209] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0210] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the controller. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the controller via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0211] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0212] The controller also includes a communication interface 30 for the main control chip to communicate with other devices or communication networks.

[0213] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium after being downloaded via a network. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor main control chips, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0214] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A vehicle lane change method, characterized by, The method comprises: obtaining vehicle information of a lane-changing vehicle, all lane information of a current driving road, and target detection results, the target detection results comprising obstacle targets on each lane; regional division is performed on each lane based on the target detection results, to obtain a plurality of feasible regions; a lane-changing safety distance is determined based on the vehicle information and the lane information; adjacent feasible regions and corresponding lane-changing weights thereof are determined based on all feasible regions, the lane-changing safety distance, and the lane information; a lane-changing path of the lane-changing vehicle is screened based on the vehicle information, the adjacent feasible regions, and the corresponding lane-changing weights thereof; a lane-changing path of the lane-changing vehicle is determined based on the lane-changing path and the lane information; the lane-changing vehicle is controlled to drive along the lane-changing path; the vehicle information comprises a current vehicle position, a vehicle steering mode, a current vehicle posture, a target vehicle posture, a vehicle steering angle, and a vehicle curvature; the lane information comprises a number of lanes, lane lines, and lane types; the lane-changing safety distance is determined based on the vehicle information and the lane information, comprising: a vehicle pose adjustment distance is determined based on a current driving corresponding vehicle steering angle, vehicle curvature, and target vehicle posture of the lane-changing vehicle; a distance from the current vehicle position to a corresponding lane line is determined based on a current driving corresponding current vehicle position and vehicle steering mode of the lane-changing vehicle; a vehicle lane-changing distance is determined based on the distance, current vehicle posture, vehicle steering angle, vehicle curvature, and vehicle pose adjustment distance; the vehicle lane-changing distance and the vehicle pose adjustment distance are added to obtain the lane-changing safety distance.

2. The vehicle lane-changing method according to claim 1, characterized by, the adjacent feasible regions and corresponding lane-changing weights thereof are determined based on all feasible regions, the lane-changing safety distance, and the lane information, comprising: two feasible regions corresponding to a common lane line in all feasible regions are screened to form a region group set; a common lane line length of each group of two feasible regions in the region group set is obtained, denoted as a region adjacency length; it is judged whether the region adjacency length is greater than the lane-changing safety distance; if the region adjacency length is not greater than the lane-changing safety distance, it is determined that the two feasible regions corresponding to the current group are not adjacent, and lane-changing weight values are assigned to the two non-adjacent feasible regions, denoted as a first lane-changing weight; if the region adjacency length is greater than the lane-changing safety distance, it is determined that the two feasible regions corresponding to the current group are adjacent, the lane types corresponding to the lanes to which the two adjacent feasible regions belong and the region adjacency length are obtained, and lane-changing weight values are assigned to the two adjacent feasible regions based on the lane types and the region adjacency length, denoted as a second lane-changing weight, the second lane-changing weight being greater than the first lane-changing weight.

3. The vehicle lane-changing method according to claim 1, characterized by, the lane-changing path of the lane-changing vehicle is screened based on the vehicle information, the adjacent feasible regions, and the corresponding lane-changing weights thereof, comprising: a feasible region corresponding to a current position of the lane-changing vehicle is determined, denoted as a starting region; other feasible regions adjacent to the current feasible region are screened based on the starting region and a preset ending region to construct an accessible path; The lane change weights corresponding to each feasible region in the reachable path are summed to obtain the sum of the lane change weights of the reachable path; The path with the smallest lane change weight is selected as the lane change path for the vehicle.

4. The vehicle lane-changing method according to claim 3, characterized by, Determining the lane-changing path of the vehicle based on the variable lane path and the lane information includes: Determine the straight path corresponding to the current feasible area in the variable lane path and the crab path corresponding to traveling from the current feasible area to the next feasible area; wherein, the straight path is determined based on the current position of the lane-changing vehicle and the crab starting point, the crab starting point is the position point that is farther away along the vehicle's travel direction between the current position of the vehicle and the starting position of the next feasible area in the variable lane path, and the crab path is determined based on the position of the crab starting point and the next feasible area traveled by the lane-changing vehicle; The straight-through paths and crab-walking paths of all feasible areas in the variable lane path are summed to obtain the lane-changing path of the lane-changing vehicle.

5. The vehicle lane-changing method according to any one of claims 1 to 4, characterized by, Controlling the lane-changing vehicle to travel along the lane-changing path includes: The lane-changing path is fitted based on the current vehicle information of the lane-changing vehicle to obtain the corresponding driving path. Control the vehicle to travel along the stated travel path and execute the lane change.

6. The vehicle lane-changing method according to claim 1, characterized by, The obstacle targets include other vehicles and obstacles; The process involves dividing each lane into regions based on the target detection results, resulting in multiple feasible regions, including: Other vehicles or obstacles are considered inaccessible areas; The infeasible area is adjusted according to a preset distance; Based on the adjusted infeasible areas, multiple lanes are divided into multiple feasible areas.

7. A vehicle lane change system for implementing the vehicle lane change method according to any one of claims 1 to 6, characterized in that The system includes: The acquisition module is used to acquire vehicle information of vehicles changing lanes, all lane information of the current driving road, and target detection results, wherein the target detection results include obstacle targets in each lane; The partitioning module is used to divide each lane into regions based on the target detection results, thereby obtaining multiple feasible regions; The first determining module is used to determine the safe distance for lane changing based on the vehicle information and the lane information; The second determining module is used to determine adjacent feasible areas and their corresponding lane change weights based on all feasible areas, the lane change safety distance, and the lane information. The filtering module is used to filter the reversible paths of the lane-changing vehicle based on the vehicle information, the adjacent feasible areas and their corresponding lane-changing weights. The third determining module is used to determine the lane-changing path of the lane-changing vehicle based on the variable lane path and the lane information; The control module is used to control the lane-changing vehicle to travel along the lane-changing path; The vehicle information includes the vehicle's current position, vehicle steering mode, vehicle current attitude, vehicle target attitude, vehicle steering angle, and vehicle curvature; the lane information includes the number of lanes, lane lines, and lane type; determining the lane change safety distance based on the vehicle information and the lane information includes: Based on the vehicle's current steering angle, vehicle curvature, and target vehicle attitude, determine the vehicle's pose adjustment distance; Based on the current position and steering mode of the lane-changing vehicle, the distance from the current position of the vehicle to the corresponding lane line is determined. The vehicle lane change distance is determined based on the distance, the vehicle's current posture, the vehicle's steering angle, the vehicle's curvature, and the vehicle's posture adjustment distance. The safe lane-changing distance is obtained by adding the vehicle's lane-changing distance and the vehicle's position adjustment distance together.

8. A vehicle characterized by comprising: The vehicle includes a controller, which includes a memory and a processor, the memory and the processor being communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the vehicle lane-changing method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the vehicle lane-changing method according to any one of claims 1 to 6.

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