Vehicle lane changing control method, device and equipment, automobile and storage medium

Abstract

The embodiment of the invention provides a vehicle lane changing control method, device and equipment, an automobile and a storage medium, and relates to the technical field of intelligent driving. The method comprises the following steps: acquiring a first space income and a second space income of a vehicle within a preset time period; the first space revenue is the revenue obtained by simulating that the vehicle runs according to a target lane changing planning track, and the target lane changing planning track is a track which is determined based on a preset dynamic planning algorithm and consumes the minimum total cost in lane changing longitudinal planning tracks at which the vehicle can change to a target position of a target lane; the second space revenue is the revenue obtained by simulating the self-vehicle to run along the target cruise planning track; determining lane changing income according to the first space income and the second space income; and controlling the own vehicle to change the lane according to the lane changing income. The method is used for achieving the effects of improving the accuracy of the lane changing decision and improving the passing efficiency of the vehicle in complex scenes such as medium and low speeds.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a vehicle lane change control method, device, equipment, automobile and storage medium. Background Art

[0002] In autonomous driving and assisted driving systems, vehicle lane changing is an important function. The ultimate goal of lane change control technology is to ensure that vehicles can change lanes safely and efficiently in complex and changing traffic environments.

[0003] In the prior art, common lane change decisions usually rely on simple rules or algorithms based on fixed parameters, which are only applicable to relatively simple road scenarios such as highways, but cannot be applied to complex and changeable urban traffic roads.

[0004] Since traffic flow in urban scenarios is highly irregular and vehicles travel at low speeds, with frequent starts and stops, especially during peak hours when traffic volume is extremely high and the distance between vehicles is small, it is difficult to quickly decide on a correct and safe lane change plan based on existing solutions. Summary of the invention

[0005] The vehicle lane change control method, device, equipment, automobile and storage medium provided in the embodiments of the present application are used to achieve the effects of improving the intelligence and adaptability of lane change decisions and optimizing the vehicle's lane change path in different traffic environments.

[0006] In a first aspect, an embodiment of the present application provides a vehicle lane change control method, the method comprising:

[0007] Obtaining a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, wherein the target lane change planning trajectory is a trajectory with the minimum total cost among the lane change longitudinal planning trajectories in which the vehicle can change lanes to a target position of the target lane, determined based on a preset dynamic programming algorithm; the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, wherein the target cruise planning trajectory is a trajectory with the minimum total cost among the cruise longitudinal planning trajectories in which the vehicle can cruise to a desired position in the current lane, determined based on a preset dynamic programming algorithm;

[0008] determining a lane change benefit according to the first spatial benefit and the second spatial benefit;

[0009] The vehicle is controlled to change lanes according to the lane change benefit.

[0010] In a possible implementation manner, obtaining the first spatial benefit and the second spatial benefit of the vehicle within a preset time period includes:

[0011] Acquiring data required for lane change decision; wherein the data required for lane change decision at least includes lane perception information, vehicle positioning information and map navigation information;

[0012] Determine a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period according to the data required for the lane change decision and the preset dynamic planning algorithm;

[0013] A first spatial benefit and a second spatial benefit are determined according to the target lane change planning trajectory and the target cruise planning trajectory.

[0014] In a possible implementation, determining a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period according to the lane change decision data and the preset dynamic programming algorithm includes:

[0015] Determining obstacles in each lane according to the data required for the lane change decision, and determining a long-term predicted trajectory of the obstacles;

[0016] Determining the target position and the expected position according to the distribution of obstacles in each lane;

[0017] Based on the vehicle positioning information and the long-term predicted trajectory of the obstacle, a plurality of lane-changing longitudinal planning trajectories for the vehicle to change lanes to the target position and a plurality of cruising longitudinal planning trajectories for the vehicle to cruise in the current lane to the desired position are generated through the preset dynamic programming algorithm, and a total cost of each of the lane-changing longitudinal planning trajectories and a total cost of each of the cruising longitudinal planning trajectories are calculated;

[0018] Determine a trajectory with the minimum total cost among a plurality of lane-changing longitudinal planning trajectories through which the vehicle can change lanes to the target position, as the target lane-changing planning trajectory;

[0019] Determine the trajectory with the minimum total cost among multiple cruise longitudinal planning trajectories that the vehicle can cruise to the desired position in the current lane, as the target cruise planning trajectory.

[0020] In a possible implementation manner, the calculating the total cost of each lane change longitudinal planning trajectory and the total cost of each cruise longitudinal planning trajectory includes:

[0021] Calculating a total cost of the lane-changing longitudinal planning trajectory according to the lane-changing parameters of the lane-changing longitudinal planning trajectory and a preset objective function relationship;

[0022] The total cost of the longitudinal cruise planning trajectory is calculated based on the cruise parameters of the longitudinal cruise planning trajectory and a preset objective function relationship.

[0023] In a possible implementation manner, determining an obstacle in each lane according to the data required for the lane change decision, and determining a long-term predicted trajectory of the obstacle includes:

[0024] Analyzing and processing lane perception information in the data required for the lane change decision to determine obstacles in each lane and short-term predicted trajectories of the obstacles;

[0025] The long-term predicted trajectory of the obstacle is determined according to the map navigation information in the data required for the lane change decision and the short-term predicted trajectory of the obstacle in each lane.

[0026] In a possible implementation manner, determining the first spatial benefit and the second spatial benefit according to the target lane change planning trajectory and the target cruise planning trajectory includes:

[0027] Simulate the vehicle traveling along the target lane change planning trajectory, and determine the longitudinal displacement of the vehicle when the vehicle travels along the target lane change planning trajectory to the target position, which is the first spatial benefit;

[0028] The vehicle is simulated to travel along the target cruise planning trajectory, and the longitudinal displacement when the vehicle travels to the expected position along the target cruise planning trajectory is determined as the second spatial benefit.

[0029] In a possible implementation manner, determining the lane change benefit according to the first spatial benefit and the second spatial benefit includes:

[0030] A difference between the first spatial gain and the second spatial gain is determined, and the difference is determined as a lane change gain.

[0031] In a possible implementation manner, controlling the vehicle to change lanes according to the lane change benefit includes:

[0032] Get the lane change trigger threshold;

[0033] If the lane change benefit is greater than or equal to the lane change trigger threshold, then the lane change decision information is generated and executed; wherein the lane change decision information is used to instruct the vehicle to change lanes according to the target lane change planning trajectory.

[0034] In a possible implementation manner, obtaining the lane change triggering threshold includes:

[0035] Get the real-time distance between the vehicle and the target lane-changing point;

[0036] Determining the lane changing task of the vehicle according to the real-time distance and the first preset corresponding relationship; wherein the first preset corresponding relationship is the corresponding relationship between the real-time distance and the lane changing task;

[0037] A lane change triggering threshold is determined according to the lane change task and a second preset corresponding relationship; wherein the second preset corresponding relationship is a corresponding relationship between the lane change task and the lane change triggering threshold.

[0038] In a possible implementation manner, the executing lane change decision information includes:

[0039] Control the vehicle to turn on the lane change indicator;

[0040] After the lighting time of the lane change turn signal lamp reaches a preset time length, if it is determined that the vehicle meets the preset safe lane change requirements, the vehicle is controlled to change lanes according to the target lane change planning trajectory.

[0041] In a possible implementation manner, after controlling the vehicle to turn on the lane change turn signal indicator, and before the lighting time of the lane change turn signal indicator reaches a preset time, the method further includes:

[0042] The steps of obtaining the first spatial gain and the second spatial gain of the vehicle within a preset time period are repeatedly performed, and whether to change the lane change decision is determined according to the repeatedly obtained lane change gains.

[0043] In a second aspect, an embodiment of the present application provides a vehicle lane change control device, the device comprising:

[0044] A processing unit, used to obtain a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, wherein the target lane change planning trajectory is a trajectory with the minimum total cost in a lane change longitudinal planning trajectory in which the vehicle can change lanes to a target position of a target lane, determined based on a preset dynamic programming algorithm; and the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, wherein the target cruise planning trajectory is a trajectory with the minimum total cost in a cruise longitudinal planning trajectory in which the vehicle can cruise to a desired position in a current lane, determined based on a preset dynamic programming algorithm;

[0045] a determining unit, configured to determine a lane change benefit according to the first spatial benefit and the second spatial benefit;

[0046] A control unit is used to control the vehicle to change lanes according to the lane change benefit.

[0047] In a third aspect, an embodiment of the present application provides a vehicle lane change control device, the vehicle lane change control device comprising: a memory, a processor;

[0048] The memory stores computer-executable instructions;

[0049] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0050] In a fourth aspect, an embodiment of the present application provides a car, comprising the vehicle lane change control device as described in the third aspect.

[0051] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0052] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0053] In the vehicle lane change control method, device, equipment, automobile and storage medium provided in the embodiments of the present application, the method includes: obtaining a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, and the target lane change planning trajectory is a trajectory with the minimum total cost in the lane change longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can change lanes to the target position of the target lane; the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, and the target cruise planning trajectory is a trajectory with the minimum total cost in the cruise longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can cruise to the desired position in the current lane; determining the lane change benefit based on the first spatial benefit and the second spatial benefit; and controlling the vehicle to change lanes based on the lane change benefit. The embodiment of the present application selects the trajectory with the smallest total cost through a dynamic programming algorithm and spatial benefit evaluation, thereby significantly optimizing the accuracy of path selection and lane change decisions. The vehicle can reach the destination faster and more efficiently. While improving the accuracy of lane change decisions, it also reduces traffic congestion and improves road capacity. It can quickly initiate lane change decisions and change lanes in complex traffic environments, effectively improving the vehicle's traffic efficiency in complex and low-speed scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0055] Figure 1 A flow chart of a vehicle lane change control method provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of the distribution of obstacles provided in an embodiment of the present application;

[0057] Figure 3 A flowchart of another vehicle lane change control method provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of a lane change scenario provided in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of another lane change scenario provided in an embodiment of the present application;

[0060] Figure 6 A schematic diagram of the structure of a vehicle lane change control device provided in an embodiment of the present application;

[0061] Figure 7 A schematic diagram of the structure of a vehicle lane change control device provided in an embodiment of the present application.

[0062] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0063] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0064] Highways have a relatively simple, straight linear layout, with a relatively large and fixed number of lanes, generally 2-4 or even more lanes, and a wide road width, providing vehicles with a relatively spacious driving space. Vehicles on highways usually travel at speeds of 60-120 km / h, and the distance between vehicles is relatively large. The traffic flow is relatively orderly, showing the characteristics of high speed and stability. On sections of highways, vehicles can maintain a relatively stable high-speed driving state, and the need to change lanes on highways is mainly for overtaking or adjusting to a more suitable lane. Based on this, in actual scenarios, the calculation accuracy requirements for lane change benefits in highway scenarios are relatively low, and it is only necessary to control the vehicle to complete lane changes as required.

[0065] In stark contrast to highways, urban roads present a complex grid layout, which usually includes numerous intersections, T-junctions, and street blocks of various shapes and sizes. The road width is relatively narrow, and the number of lanes is limited. The road's passability often changes due to factors such as roadside parking, bus stops, and construction areas. The traffic flow on urban roads is highly irregular, and the vehicle speed is also low, generally 0-60 kilometers per hour, and there are frequent starts and stops. Especially during peak hours, the traffic flow is extremely large, the distance between vehicles is small, and different types of vehicles (such as cars, buses, taxis, motorcycles, bicycles, etc.) are seriously mixed. The need to change lanes in urban road scenarios is mainly to adjust to a more suitable lane in order to have a better traffic plan.

[0066] Due to the difference in the environment between highways and urban roads, vehicles face different difficulties and risks when making lane change decisions. Existing lane change decision technologies usually rely on simple rules or algorithms based on fixed parameters, which often fail to take into account these two completely different scenarios. Especially in complex low-speed scenarios in cities and towns, due to the high complexity and variability of the traffic environment, not only does it increase the difficulty of lane change control, but it also requires accurate identification of lane change benefits and accurate control of lane change timing to improve vehicle traffic efficiency and driving safety.

[0067] In order to solve the above technical problems, the embodiment of the present application provides a vehicle lane change control method. The solution of the present application generates a lane change longitudinal planning trajectory for the vehicle to change lanes to the target position of the target lane, and a cruising longitudinal planning trajectory for the vehicle to cruise to the desired position in the current lane through a dynamic programming algorithm, while considering the benefits that can be obtained from lane change and cruising, and then controlling the lane change based on the lane change benefits determined by the two. Since the lane change and cruising conditions are comprehensively considered, the lane change decision determined based on this is more accurate, which can improve the accuracy and safety of lane change execution.

[0068] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0069] It should be noted that the execution subject of the vehicle lane change control method provided in the embodiment of the present application may be a vehicle lane change control device, and the vehicle lane change control device may be deployed in the intelligent driving system of the vehicle, and the intelligent driving system is located on the processor or control device of the vehicle, and the embodiment of the present application does not limit it. The embodiment of the present application is described in detail by taking the execution subject as a vehicle lane change control device as an example.

[0070] Figure 1 A flow chart of a vehicle lane change control method provided in an embodiment of the present application. Figure 1 As shown, the vehicle lane change control method provided by the embodiment of the present application may include:

[0071] S101. Obtain a first spatial benefit and a second spatial benefit of the vehicle within a preset time period.

[0072] Among them, the first spatial benefit is the benefit obtained by simulating the vehicle driving along the target lane change planning trajectory. The target lane change planning trajectory is the trajectory with the minimum total cost among the lane change longitudinal planning trajectories determined based on the preset dynamic programming algorithm, in which the vehicle can change lanes to the target position of the target lane; the second spatial benefit is the benefit obtained by simulating the vehicle driving along the target cruise planning trajectory. The target cruise planning trajectory is the trajectory with the minimum total cost among the cruise longitudinal planning trajectories determined based on the preset dynamic programming algorithm, in which the vehicle can cruise to the desired position in the current lane.

[0073] Exemplarily, the preset time period is the time period required to complete the lane change. The embodiment of the present application does not limit the specific value of the preset time period. For example, it can be set to 10s or 15s.

[0074] The first spatial benefit is the benefit obtained by simulating the vehicle driving along the target lane change planning trajectory. Optionally, the first spatial benefit can be represented by the longitudinal displacement of the vehicle from the current position of the current lane to the target position of the target lane, etc., which is not limited in the embodiment of the present application. Among them, the target lane change planning trajectory is determined based on a preset dynamic programming algorithm, and is the trajectory with the minimum total cost among the lane change longitudinal planning trajectories in which the vehicle can change lanes from the current lane to the target position of the target lane within a preset time period.

[0075] The second spatial benefit is the benefit obtained by simulating the vehicle driving along the target cruise planning trajectory. Optionally, the second spatial benefit can be represented by the longitudinal displacement of the vehicle from the current position of the current lane to the desired position, etc., which is not limited in the embodiment of the present application. Among them, the target cruise planning trajectory refers to the trajectory with the minimum total cost among the various cruise longitudinal planning trajectories determined based on the preset dynamic programming algorithm, in which the vehicle can cruise to the desired position in the current lane within a preset time period.

[0076] Among them, the preset dynamic programming algorithm is an algorithm for optimizing problems, which can find the optimal solution by decomposing the problem into smaller sub-problems in a multi-stage decision-making process. In the embodiment of the present application, by presetting the dynamic programming algorithm, multiple trajectories can be generated for the vehicle to change lanes from the current lane to the target position of the target lane. The lane change parameters of each trajectory, such as speed, acceleration, trajectory, etc., are different, so the cost consumed is also different. In order to achieve a better lane change effect, the embodiment of the present application selects the trajectory with the least cost as the target lane change planning trajectory. Similarly, by presetting the dynamic programming algorithm, multiple trajectories can also be generated for the vehicle to cruise to the desired position in the current lane. Since the lane change parameters of each trajectory, such as speed, acceleration, etc., are different, the cost consumed is also different. In order to achieve a better cruising effect, the embodiment of the present application selects the trajectory with the least cost as the target cruise planning trajectory.

[0077] It should be noted that the total cost refers to the cost that the vehicle needs to pay during the driving process, which may be related to the driving speed, acceleration, distance, time, energy consumption, safety, comfort, etc., and is not limited in the embodiments of the present application.

[0078] Exemplarily, the embodiment of the present application does not limit how to obtain the first spatial benefit and the second spatial benefit of the vehicle within a preset time period. For example, the first spatial benefit and the second spatial benefit can be obtained by other devices based on the data required for the lane change decision and combined with a preset dynamic programming algorithm, and then sent to the vehicle lane change control device of the embodiment of the present application; or, the vehicle lane change control device of the embodiment of the present application can first select the target lane change planning trajectory and the target cruise planning trajectory based on the data required for the lane change decision and combined with a preset dynamic programming algorithm, and then simulate the vehicle driving along the target lane change planning trajectory and the target cruise planning trajectory respectively, and then calculate the corresponding spatial benefit in combination with the benefit algorithm; etc., and can be obtained in a variety of ways.

[0079] Optionally, in a possible embodiment, obtaining the first spatial benefit and the second spatial benefit of the vehicle within a preset time period may include:

[0080] S1. Acquire data required for lane change decision; wherein the data required for lane change decision at least includes lane perception information, vehicle positioning information, and map navigation information;

[0081] S2. Determine a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period based on the data required for lane change decision and a preset dynamic planning algorithm;

[0082] S3. Determine a first spatial benefit and a second spatial benefit according to a target lane change planning trajectory and a target cruise planning trajectory.

[0083] Exemplarily, in an embodiment of the present application, determining the first spatial gain and the second spatial gain of the vehicle within a preset time period is to determine the lane change gain, thereby performing vehicle lane change control. To this end, when obtaining the first spatial gain and the second spatial gain, the data required for the lane change decision can be obtained first, and then the target lane change planning trajectory and the target cruise planning trajectory of the vehicle can be determined based on the data required for the lane change decision and the preset dynamic planning algorithm, and then the first spatial gain and the second spatial gain can be determined.

[0084] Among them, the data required for lane change decision refers to the data involved in determining the lane change strategy. In an embodiment of the present application, the data required for lane change decision includes at least lane perception information, vehicle positioning information, and map navigation information.

[0085] Lane perception information mainly includes environment-related information and lane-related information around the vehicle on the road on which the vehicle is traveling. Environment-related information includes but is not limited to obstacle information around the vehicle, such as vehicles, pedestrians, cones, non-motor vehicles, etc. Obstacles around the vehicle have basic information such as position, driving speed, acceleration, and driving direction relative to the vehicle; lane-related information includes but is not limited to the number and width of lanes, and the position and type of lane lines (such as solid lines, dotted lines, etc.). Optionally, lane perception information can be obtained through a perception module deployed on the vehicle, which can be a vehicle-mounted sensor such as a camera, radar, etc., which is not limited in the embodiments of the present application.

[0086] The vehicle positioning information can be obtained through a positioning module deployed on the vehicle. The positioning module can be implemented based on the Global Positioning System (GPS) or other positioning technologies. The embodiments of the present application are not limited thereto. The positioning module can be used to obtain the precise position, speed, direction and other information of the vehicle, thereby managing the vehicle travel data.

[0087] Map navigation information can be obtained through a map module deployed on the vehicle. The map module may include pre-stored high-precision maps. The road shape, lane information, traffic light information, intersection information, real-time road conditions and navigation path information of the road where the vehicle is currently located can be obtained from the high-precision map according to the vehicle's driving mission (such as the driving route from the vehicle to the destination, etc.)

[0088] Due to the numerous buildings and green vegetation around urban roads, there are various traffic facilities (such as traffic lights, street light poles, billboards, etc.) blocking the roads. In addition, due to the limitations of the perception module's visual range, the perception field of the vehicle is greatly limited, and there are a large number of blind spots, especially when turning at intersections, entering and exiting parking lots, and passing through narrow streets. Therefore, in order to improve the accuracy of lane change benefits, the embodiment of the present application also incorporates the vehicle's positioning information and map navigation information into the lane change benefit calculation, thereby improving the accuracy of lane change decisions in urban scenarios.

[0089] Exemplarily, after obtaining the data required for lane change decision, the target lane change planning trajectory and the target cruise planning trajectory of the vehicle within a preset time period can be determined based on the data required for lane change decision and the preset dynamic programming algorithm. For example, a model using a preset dynamic programming algorithm is pre-built and trained, the input is the data required for lane change decision, and the output is the target lane change planning trajectory and the target cruise planning trajectory of the vehicle within a preset time period, which is not limited in the embodiments of the present application.

[0090] Optionally, in a possible embodiment, step S2, determining a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period according to the data required for the lane change decision and a preset dynamic planning algorithm, may include:

[0091] S21. Determine obstacles in each lane according to the data required for lane change decision, and determine the long-term predicted trajectory of the obstacles;

[0092] S22, determining the target position and the expected position according to the distribution of obstacles in each lane;

[0093] S23, based on the vehicle positioning information and the long-term predicted trajectory of the obstacle, a preset dynamic programming algorithm is used to generate multiple lane change longitudinal planning trajectories for the vehicle to change lanes to the target position, and multiple cruising longitudinal planning trajectories for the vehicle to cruise to the desired position in the current lane, and the total cost of each lane change longitudinal planning trajectory and the total cost of each cruising longitudinal planning trajectory are calculated;

[0094] S24, determining a trajectory with the smallest total cost among multiple lane-changing longitudinal planning trajectories in which the vehicle can change lanes to the target position, as the target lane-changing planning trajectory;

[0095] S25. Determine a trajectory with the smallest total cost among multiple longitudinal cruise planning trajectories that enable the vehicle to cruise to a desired position in the current lane, as the target cruise planning trajectory.

[0096] For example, there may be multiple obstacles around the vehicle. When the location and driving trajectory of each obstacle are different, the target location that the vehicle can change lanes to and the expected location that it can cruise to will be different, and accordingly, the determined planning trajectory will also be different. Therefore, it is necessary to first determine the obstacles in each lane based on the data required for lane change decision, and determine the long-term predicted trajectory of each obstacle, and then determine the planning trajectory.

[0097] Optionally, in a possible embodiment, step S21, determining obstacles in each lane according to data required for lane change decision, and determining a long-term predicted trajectory of the obstacles, may include:

[0098] S211, analyzing and processing lane perception information in the data required for lane change decision, and determining obstacles in each lane and short-term predicted trajectories of the obstacles;

[0099] S212: Determine the long-term predicted trajectory of the obstacle based on the map navigation information in the data required for the lane change decision and the short-term predicted trajectory of the obstacle in each lane.

[0100] For example, according to the position of each obstacle in the lane perception information, the obstacles in each lane can be calculated, and according to the basic information such as the position, driving speed, acceleration, and driving direction of each obstacle, the short-term predicted trajectory of each obstacle can be determined. It should be noted that the initial data form of the lane perception information obtained by vehicle-mounted sensors such as cameras and radars may be images or point cloud data. The initial data can be processed by existing data processing methods to determine the obstacles and basic information contained therein, and then the lane attribution calculation can be performed for each obstacle. The embodiments of the present application do not limit this and will not be elaborated here.

[0101] For example, when calculating lane attribution, a Frenet coordinate system can be established, and all obstacles can be projected based on the driving reference line, and then the lanes can be divided according to the coordinate values ​​of the obstacles in the coordinate system. It should be noted that the Frenet coordinate system is a coordinate system used to describe curved motion, with the starting position of the vehicle as the origin, and the coordinate axes are perpendicular to each other, divided into the S-axis direction and the L-axis direction, and the coordinates are expressed as (S, L). The Frenet coordinate system can project the trajectory of the vehicle at a certain moment onto the reference line, and decompose it into two dimensions of motion, longitudinal and lateral. S represents the longitudinal displacement based on the reference line, and L represents the lateral displacement that deviates from the reference line.

[0102] In the embodiment of the present application, all obstacles in the area of ​​interest of the lane of the vehicle can be set as a set obstacle{}, and the virtual stop line of each lane is calculated by combining the obstacle attribution information, the traffic facility information and dynamic information obtained from the navigation map, and the order of obstacles and the interference of obstacles in front and behind the same lane are calculated from large to small according to the longitudinal displacement S projected by the driving reference line. The sorted obstacle set can be recorded as obstacle{obs1, obs2, obs3, obs4...}. Optionally, the obstacles in front of and behind the vehicle in each lane can be counted separately, that is, the obstacles in front of the current position of the vehicle in each lane are counted as one obstacle set, and the obstacles behind the current position of the vehicle are counted as another obstacle set.

[0103] For example, Figure 2 A schematic diagram of the distribution of obstacles provided in the embodiment of the present application. Figure 2 As shown, in the left lane of the ego car ego, the obstacles obs1 and obs2 in front of the ego car can be grouped into one obstacle set; in the current lane of the ego car ego, the obstacle obs3 in front of the ego car can be grouped into another obstacle set.

[0104] It should be noted that the short-term predicted trajectory of the obstacle is based on a kinematic model or a short-term prediction model, etc., and the trajectory of the obstacle in a short period of time is predicted to obtain the trajectory. Among them, the time range of the short-term prediction is generally within 3s, which can be set according to actual needs, and the embodiment of the present application is not limited. The basic information such as the position, driving speed, acceleration, driving direction of each obstacle can be input into the kinematic model or the short-term prediction model for prediction, so as to obtain the short-term predicted trajectory of each obstacle.

[0105] Furthermore, the behavior of obstacles is analyzed based on the map navigation information and the short-term predicted trajectory of obstacles in each lane, and the driving intention of the obstacles is taken into consideration to determine the long-term predicted trajectory of each obstacle. It can be understood that the long-term predicted trajectory is combined with the intention prediction technology, which can predict the trajectory of obstacles over a longer period of time. Among them, the time range of the long-term prediction is generally more than 8s, which can be set according to actual needs. The embodiment of the present application is not limited. For example, it can be set to the time required for the vehicle to change lanes, such as 10s or 15s. The collected map navigation information and the calculated short-term predicted trajectory of obstacles in each lane can be input into a pre-trained long-term prediction model for prediction, thereby obtaining the long-term predicted trajectory of each obstacle.

[0106] It can be understood that long-term predicted trajectories can provide more comprehensive path planning information. Through long-term predicted trajectories, more and better lane change plans can be generated, thereby improving traffic efficiency and driving safety.

[0107] For example, after determining the obstacles in each lane, the target position and expected position of each lane can be determined according to the distribution of obstacles in each lane. The determination of the target position and expected position should take into account safety, traffic rules (such as no lane change areas), navigation path, and driving efficiency. Figure 2 Taking the left lane change as an example, we can first preliminarily screen out the target space on the left lane. The target space is the position where the ego vehicle can change lanes in theory. According to the left lane affiliation, we can obtain three lane change target spaces A1, A2, and A3, which can be recorded as A1{-1, obs1}, A2{obs1, obs2}, and A3{obs2, -2} from the front to the back of the ego vehicle, respectively. Among them, -1 means that there is no obstacle in front to restrict lane change, and -2 means that there is no obstacle in the back to restrict lane change. Similarly, the ego vehicle cruises in the current lane and can determine the expected position B.

[0108] Furthermore, by combining the positioning information of the vehicle and the long-term predicted trajectory of each obstacle, a preset dynamic programming algorithm can be used to generate multiple lane change longitudinal planning trajectories that the vehicle can change lanes to the target space, and determine the longitudinal pursuit capability of the vehicle, and then determine whether the vehicle can successfully change lanes to the target space within the preset time period based on the generated lane change longitudinal planning trajectory. If the determination fails, the next target space is calculated. When the space is successfully selected, the target position can be determined, and then the target lane change planning trajectory can be selected through the total cost of each lane change longitudinal planning trajectory. Similarly, by combining the positioning information of the vehicle and the long-term predicted trajectory of each obstacle, a preset dynamic programming algorithm can also be used to generate multiple cruise longitudinal planning trajectories that the vehicle can cruise to the desired position, and the target cruise planning trajectory can also be selected through the total cost of each cruise longitudinal planning trajectory.

[0109] Optionally, in a possible embodiment, calculating the total cost of each lane change longitudinal planning trajectory and the total cost of each cruise longitudinal planning trajectory in step S23 may include:

[0110] S231, calculating the total cost of the lane change longitudinal planning trajectory according to the lane change parameters of the lane change longitudinal planning trajectory and a preset objective function relationship;

[0111] S232. Calculate the total cost of the longitudinal cruise planning trajectory according to the cruise parameters of the longitudinal cruise planning trajectory and a preset objective function relationship.

[0112] Exemplarily, each lane change longitudinal planning trajectory has its corresponding lane change parameters, and each cruise longitudinal planning trajectory also has its corresponding cruise parameters. When the lane change parameters and the cruise parameters are different, the total costs corresponding to the lane change longitudinal planning trajectories and the cruise longitudinal planning trajectories will also be different.

[0113] First, we can define the main state variables involved in the vehicle's driving process, including:

[0114] Longitudinal position: It can be expressed by the distance of the vehicle in the direction of travel relative to a fixed reference point (such as the current position of the vehicle), and the unit can be meters (m). This variable describes the longitudinal position information of the vehicle on the road and is the basis for determining the vehicle's travel path.

[0115] Speed: refers to the vehicle's driving speed, which can be expressed in meters per second (m / s). It reflects the speed of the vehicle's movement, and its change directly affects the vehicle's driving time and energy consumption.

[0116] Acceleration: The rate of change of vehicle speed, expressed in meters per second squared (m / s 2 ), which is closely related to the vehicle's dynamic performance and driving comfort.

[0117] Furthermore, based on the principles of vehicle dynamics, a state transfer equation can be established to describe how the vehicle state changes over time or travel distance. Taking the movement of the vehicle in the longitudinal direction as an example, the state transfer equation involved is as follows:

[0118] About location updates: Among them, x t is the current position, v t is the current speed, a t is the current acceleration, is the time interval.

[0119] About speed update:

[0120] It can be understood that during the state transfer process, the vehicle dynamics constraints, namely the acceleration a t The physical limitations of the vehicle must be met, min ≤a t ≤a max , where a min and a max are the minimum and maximum acceleration of the vehicle, respectively. At the same time, the constraints of the front and rear vehicles when changing lanes to the target space should also be considered. If the position of the front vehicle is x front , the speed is v front , then the safe distance d between the vehicle and the vehicle ahead s Certain conditions should be met. For example, a simple safety distance model can be used as Among them, d0 is the preset minimum safe distance, and T is the preset minimum reaction time. Similarly, the safe distance between the vehicle and the vehicle behind should also meet certain conditions, which will not be elaborated here. During the state transfer process, any vehicle needs to ensure that the vehicle does not violate the safe distance constraint to ensure driving safety.

[0121] Optionally, in order to reduce the amount of calculation, in the embodiment of the present application, when the lane change longitudinal planning trajectory and the cruise longitudinal planning trajectory are generated by the preset dynamic programming algorithm, a sampling method of front dense and rear comb can be adopted. For example, if the preset time period is 10s, when the lane change longitudinal planning trajectory is generated by the preset dynamic programming algorithm, the corresponding lane change parameters can be configured for the 1st, 2nd, 3rd, 5th, 7th, and 10th seconds in sequence, and the embodiment of the present application does not limit this.

[0122] It can be understood that in the trajectory generation method based on the preset dynamic programming algorithm in the embodiment of the present application, since the problem is decomposed into smaller sub-problems at each sampling point to find the optimal solution, the cost of state transition at each sampling point does not need to be repeatedly calculated, which greatly reduces the amount of data processing and improves data processing efficiency. In addition, in the process of decomposing the problem into smaller sub-problems at each sampling point to find the optimal solution, the planned trajectory that obviously does not meet the preset requirements (such as failing to meet the preset safety distance requirements, failing to meet the speed limit requirements, failing to meet the acceleration limit requirements, etc.) can also be eliminated by pruning to reduce the amount of calculation and improve data processing efficiency. The embodiment of the present application does not limit this and will not be repeated here.

[0123] Combining the main state variables involved in the driving process of the above-mentioned vehicle, it can be seen that the lane change parameters and cruising parameters mainly involve the vehicle's speed, acceleration, longitudinal position, etc. According to these parameters and the preset objective function relationship, the corresponding total cost can be calculated.

[0124] For example, the preset objective function relationship may be the following formula (1):

[0125] Total cost = obstacle distance cost + speed cost + acceleration cost + target longitudinal position cost (1)

[0126] Among them, regarding the obstacle distance related cost: we can first calculate the distance difference between the longitudinal position s of the vehicle and the longitudinal position s of the front and rear obstacles at each sampling point, and then calculate the difference between each distance difference and the expected safety distance, and square each difference respectively, and then sum each square, and finally multiply the sum result by the distance weight W_s to get the obstacle distance related cost cost.

[0127] Regarding the speed-related cost cost: you can first calculate the difference between the speed of the vehicle at each sampling point and the speed of the previous sampling point, then square each difference, then sum the squares, and finally multiply the sum by the speed weight W_v to get the speed-related cost cost.

[0128] Regarding the acceleration-related cost cost: you can first calculate the square of the vehicle's acceleration at each sampling point, then find the sum of the squares, and then multiply the sum result by the acceleration weight W_a to get the acceleration-related cost cost.

[0129] Regarding the cost related to the target longitudinal position: first calculate the difference between the end point (that is, the corresponding target position or expected position) and the position s of each sampling point, and calculate the sum of the differences, and then multiply the sum by the position weight W_target to obtain the cost related to the target longitudinal position.

[0130] According to the lane change parameters of each lane change longitudinal planning trajectory and formula (1), the total cost of each lane change longitudinal planning trajectory can be calculated. In the embodiment of the present application, the trajectory with the minimum total cost can be selected as the target lane change planning trajectory. Similarly, according to the cruise parameters of each cruise longitudinal planning trajectory and formula (1), the total cost of each cruise longitudinal planning trajectory can also be calculated, so as to select the trajectory with the minimum total cost and determine it as the target cruise planning trajectory.

[0131] The above-mentioned preset objective function relationship can more accurately calculate the longitudinal pursuit capability of the vehicle, and comprehensively consider the influence of speed, acceleration, longitudinal displacement, etc. on the pursuit capability. The target lane change planning trajectory and target cruise planning trajectory determined based on this are more accurate, which improves the accuracy of subsequent lane change decisions.

[0132] Further, according to the target lane change planning trajectory and the target cruise planning trajectory, the first space benefit and the second space benefit can be determined. Optionally, in a possible embodiment, step S3, determining the first space benefit and the second space benefit according to the target lane change planning trajectory and the target cruise planning trajectory, may include:

[0133] S31, simulating the vehicle to travel along the target lane change planning trajectory, and determining the longitudinal displacement when the vehicle travels along the target lane change planning trajectory to the target position as the first spatial benefit;

[0134] S32, simulating the vehicle to travel along the target cruise planning trajectory, and determining the longitudinal displacement when the vehicle travels to the expected position along the target cruise planning trajectory, which is the second spatial benefit.

[0135] Exemplarily, computer simulation technology can be used to simulate the situation where the vehicle travels along the target lane change planning trajectory, and then the longitudinal displacement of the vehicle when it travels from the current position along the target lane change planning trajectory to the target position (the final position after the lane change is completed) can be calculated. The embodiment of the present application can determine the longitudinal displacement as the first spatial revenue, which can be recorded as Revenue_LC, to reflect the forward distance that the vehicle can achieve by traveling on the lane change trajectory within a preset time period.

[0136] Similarly, computer simulation technology can be used to simulate the situation where the vehicle travels along the target cruise planning trajectory, and then the longitudinal displacement of the vehicle when it travels from the current position along the target cruise planning trajectory to the expected position can be calculated. The embodiment of the present application can determine the longitudinal displacement as the second spatial revenue, which can be recorded as Revenue_LK, to reflect the forward distance that the vehicle can achieve within a preset time period without changing lanes.

[0137] By simulating the driving trajectory of the vehicle, the first spatial benefit and the second spatial benefit can be quickly and accurately obtained, so as to more accurately evaluate which driving strategy is more conducive to achieving the driving goal.

[0138] In summary, by obtaining the data required for lane change decision-making and combining it with the preset dynamic programming algorithm, it is possible to determine the target lane change planning trajectory and target cruise planning trajectory of the vehicle within a preset time period in a complex traffic environment, and to calculate more accurate first space benefits and second space benefits, so as to provide an accurate data basis for subsequent lane change decisions and improve driving efficiency and safety.

[0139] S102: Determine a lane change benefit according to the first spatial benefit and the second spatial benefit.

[0140] Exemplarily, the lane change benefit provides a quantitative indicator to help evaluate the potential benefits of lane change. In the embodiment of the present application, the lane change benefit is used to evaluate whether the lane change can bring additional benefits relative to not changing lanes, so as to determine whether to change lanes.

[0141] Optionally, in a possible embodiment, determining the lane change benefit according to the first spatial benefit and the second spatial benefit may include: determining a difference between the first spatial benefit and the second spatial benefit, and determining the difference as the lane change benefit.

[0142] For example, if the longitudinal displacement of the vehicle when it travels to the target position with the target lane change planning trajectory is determined as the first spatial revenue Revenue_LC, and the longitudinal displacement of the vehicle when it travels to the desired position with the target cruise planning trajectory is determined as the second spatial revenue Revenue_LK, then the difference between the first spatial revenue Revenue_LC and the second spatial revenue Revenue_LK can be calculated, and the difference reflects the additional longitudinal displacement that can be brought about by changing lanes relative to not changing lanes. In the embodiment of the present application, the difference can be determined as the lane change revenue. If the lane change revenue is positive, it means that changing lanes can make the vehicle move forward a longer distance; if it is negative, it means that changing lanes may not be as beneficial as keeping the current lane.

[0143] The lane change benefit is determined by calculating the difference between the first spatial benefit and the second spatial benefit. This intuitive method reduces the complex calculation process and makes the decision process simpler and more efficient.

[0144] S103: Control the vehicle to change lanes according to the lane change benefit.

[0145] For example, the lane change benefit can be used as a quantitative indicator to quickly decide whether to change lanes. Since dynamic planning fully considers the longitudinal execution capability of the vehicle, lane changes are often more decisive, and further avoids the problem of lane changes being initiated and then cancelled due to environmental changes caused by long lane change waiting time, greatly improving the traffic efficiency of vehicles in urban areas.

[0146] Optionally, in a possible embodiment, controlling the vehicle to change lanes according to the lane change benefit may include:

[0147] S01. Obtaining a lane change trigger threshold;

[0148] S02. If the lane change benefit is greater than or equal to the lane change trigger threshold, generate and execute lane change decision information; wherein the lane change decision information is used to instruct the ego vehicle to change lanes according to the target lane change planning trajectory.

[0149] Exemplarily, the lane change trigger threshold is a pre-set value used to determine whether the lane change benefit is high enough to trigger the lane change operation. The lane change trigger threshold can be set according to a variety of factors, such as traffic environment, vehicle performance, driving strategy, driving habits, and passenger preferences, etc., which are not limited in the embodiments of the present application. In actual scenarios, the lane change trigger threshold can be dynamic and will be adjusted according to real-time traffic conditions, weather conditions, or driving modes. For example, in high traffic or bad weather conditions, the threshold can be increased to reduce the frequency of lane changes, thereby improving safety.

[0150] Optionally, in a possible embodiment, step S01, obtaining a lane change triggering threshold, may include:

[0151] S011, obtaining the real-time distance between the vehicle and the target lane-changing point;

[0152] S012, determining a lane changing task of the vehicle according to the real-time distance and a first preset corresponding relationship; wherein the first preset corresponding relationship is a corresponding relationship between the real-time distance and the lane changing task;

[0153] S013. Determine a lane change triggering threshold according to the lane change task and a second preset corresponding relationship; wherein the second preset corresponding relationship is a corresponding relationship between the lane change task and the lane change triggering threshold.

[0154] It is understandable that in the process of executing lane change, there should be a corresponding target lane change point. Before reaching the target lane change point, the vehicle should complete the lane change preparation so that the lane change can be executed when it reaches the target lane change point. If the lane change preparation cannot be completed before reaching the target lane change point, it may not be possible to complete the lane change according to the predetermined lane change trajectory. Therefore, different lane change trigger thresholds can be set according to the actual distance between the vehicle and the target lane change point so as to accurately complete the lane change.

[0155] Specifically, during the driving process of the vehicle, the vehicle can use on-board sensors (such as GPS, lidar, cameras, etc.) to monitor the real-time distance between the vehicle and the target lane changing point, and then determine the lane changing task of the vehicle based on the real-time distance and the first preset correspondence, and determine the lane changing trigger threshold based on the lane changing task and the second preset correspondence.

[0156] Among them, the first preset correspondence is the correspondence between the real-time distance and the lane change task, which is a predefined rule or table for mapping different real-time distances to specific lane change tasks. The second preset correspondence is the correspondence between the lane change task and the lane change trigger threshold, which is also a predefined rule or table for mapping the lane change task to the specific lane change trigger threshold. In the embodiment of the present application, the first preset correspondence and the second preset correspondence can be set according to the user's driving habits.

[0157] For example, if the road tasks for the left and right lanes are recorded as lane_task_left and lane_task_right respectively, according to the road tendency principle in the user's driving habits, when the self-vehicle is a certain distance away from the latest lane change point, such as 200m, the user is more inclined to drive in the lane with only a single direction and in line with the navigation direction. For example, if the self-vehicle needs to go straight, and the self-vehicle lane in front is a straight lane, and the right lane is a straight lane + right turn lane, then the user will tend to drive in the self-vehicle lane. At this time, the right lane task lane_task_right+1 of the self-vehicle can be set. For another example, according to the principle of avoiding driving in lanes on both sides in the user's driving habits, when the self-vehicle is 200m away from the latest lane change point, the user will avoid driving in the leftmost / rightmost lane. For example, in a three-lane scenario, the self-vehicle is in the middle lane. At this time, the left lane task lane_task_left+1 and the right lane task lane_task_right+1 of the self-vehicle can be set. For another example, according to the principle of changing lanes in the direction of the navigation lane change task in the user's driving habits, when the distance to the latest lane change point is within 200m, the user will try to change lanes in the direction of the navigation lane change task. For example, if the navigation task points to turn right ahead and the vehicle is still in the straight lane, the right lane task lane_task_right-1 can be set for the vehicle.

[0158] By searching the first preset corresponding relationship through the real-time distance between the vehicle and the target lane changing point, the left lane lane changing task and the right lane lane changing task of the vehicle can be determined, and then according to the left lane lane changing task and the right lane lane changing task of the vehicle, the final lane task lane_task can be determined. For example, the task with the smaller task value between the left lane lane changing task and the right lane lane changing task is determined as the final lane changing task lane_task, etc., and the embodiments of the present application are not limited thereto.

[0159] Further, according to the determined lane change task, the second preset corresponding relationship is searched to determine the lane change triggering threshold. Generally speaking, a lane change to a lane with a lane change task lane_task>0 requires a larger threshold, and a lane change to a lane with a lane change task lane_task<0 requires only a smaller threshold, which can be set according to actual needs and is not limited in the embodiment of the present application.

[0160] By obtaining the real-time distance and using the preset correspondence, the lane change trigger threshold can be dynamically adjusted. This method enables the vehicle to flexibly respond to different driving conditions and environmental changes, and improves the accuracy and adaptability of lane change decisions.

[0161] Exemplarily, after the lane change trigger threshold is obtained, the lane change benefit is compared with the lane change trigger threshold. If the lane change benefit is greater than or equal to the lane change trigger threshold, it means that the potential benefit of the lane change is large enough and it is worth performing the lane change operation, and the lane change decision information can be generated and executed; if the lane change benefit is less than the lane change trigger threshold, it means that the potential benefit of the lane change is not large enough and it is not worth performing the lane change.

[0162] By setting a lane change trigger threshold and making lane change decisions based on lane change benefits, the vehicle can make wise lane change choices in complex traffic environments. This approach ensures that lane change operations are not only based on potential efficiency benefits, but also take safety and environmental adaptability into consideration, making it more practical.

[0163] Optionally, in a possible embodiment, step S02, executing lane change decision information, may include:

[0164] S021, control the vehicle to turn on the lane change turn indicator;

[0165] S022. After the lighting time of the lane change turn signal indicator reaches a preset time length, if it is determined that the vehicle meets the preset safe lane change requirements, control the vehicle to change lanes according to the target lane change planning trajectory.

[0166] Exemplarily, the execution process of the lane change decision can be managed by a lane change state machine. It is understandable that according to traffic rules, the lane change turn signal indicator needs to be turned on before changing lanes to send a clear signal to other road users around (such as vehicles and pedestrians, etc.) that the vehicle is about to change lanes. In the embodiment of the present application, when executing the lane change decision information, it is also necessary to first control the lane change turn signal indicator of the vehicle to turn on. During the period when the light is on for a preset time (such as 3s or 5s, etc.), the surrounding environment of the vehicle is continuously monitored to confirm whether the preset safety lane change requirements are met. If it is determined that the vehicle meets the preset safety lane change requirements, the vehicle is controlled to change lanes according to the target lane change planning trajectory.

[0167] Among them, the embodiment of the present application does not limit how to determine whether the vehicle meets the preset safe lane change requirements. It can be understood that the lane change safety has been fully considered when planning the lane change trajectory. Here, it is judged again whether the vehicle meets the preset safe lane change requirements in order to re-evaluate the possible risks in the lane change process. If there is no risk, the lane change is performed normally, and the corresponding steering wheel angle, driving or braking torque, etc. are output according to the lane change parameters of the target lane change planning trajectory to control the vehicle trajectory; if there is a risk, the lane change is canceled and returned to the original lane, so as to further improve the safety of lane change.

[0168] By using turn indicators and waiting for a preset time, not only are the requirements of traffic regulations on the use of turn indicators strictly followed to ensure the legality and compliance of lane change operations, but also the transparency and predictability of lane change operations are ensured, reducing the risk of collision caused by sudden lane changes and improving the overall driving experience and road safety.

[0169] Optionally, in a possible embodiment, after controlling the vehicle to turn on the lane change turn signal indicator, before the lighting time of the lane change turn signal indicator reaches a preset time length, the step of obtaining the first spatial gain and the second spatial gain of the vehicle within a preset time period can be repeated, and based on the repeatedly obtained lane change gains, it is determined whether to change the lane change decision.

[0170] Exemplarily, through real-time updated sensor data and environmental information, the lane change benefit can be continuously recalculated to control the vehicle to dynamically evaluate the potential benefits of lane changing according to the latest traffic conditions and vehicle status within a preset time period. If the repeatedly calculated lane change benefit shows a significant change within the preset time period (for example, from positive to negative or the benefit is greatly reduced, etc.), the original lane change decision can be changed. The change decision may include delaying the lane change, selecting a different lane change trajectory, or canceling the lane change operation, etc., which is not limited in the embodiments of the present application.

[0171] By continuously monitoring and evaluating over a preset period of time, potential safety hazards (such as sudden obstacles or quickly approaching vehicles) can be identified in a timely manner, and the lane change plan can be adjusted accordingly, which can further improve lane change safety.

[0172] The vehicle lane change control method provided by the embodiment of the present application includes: obtaining a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, and the target lane change planning trajectory is a trajectory with the minimum total cost in the lane change longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can change lanes to a target position in a target lane; the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, and the target cruise planning trajectory is a trajectory with the minimum total cost in the cruise longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can cruise in the current lane to a desired position; determining the lane change benefit based on the first spatial benefit and the second spatial benefit; and controlling the vehicle to change lanes based on the lane change benefit. The embodiment of the present application selects the trajectory with the smallest total cost through a dynamic programming algorithm and spatial benefit evaluation, thereby significantly optimizing the accuracy of path selection and lane change decisions. The vehicle can reach the destination faster and more efficiently. While improving the accuracy of lane change decisions, it also reduces traffic congestion and improves road capacity. It can quickly initiate lane change decisions and change lanes in complex traffic environments, effectively improving the vehicle's traffic efficiency in complex and low-speed scenarios.

[0173] For example, Figure 3 A flowchart of another vehicle lane change control method provided in an embodiment of the present application.

[0174] like Figure 3 As shown, the vehicle lane change control method provided by the embodiment of the present application may include:

[0175] S301. Obtain data required for lane change decision.

[0176] Among them, the data required for lane change decision-making includes at least lane perception information, vehicle positioning information and map navigation information.

[0177] S302: Analyze and process lane perception information in the data required for lane change decision to determine obstacles in each lane and the short-term predicted trajectory of each obstacle.

[0178] S303: Determine the long-term predicted trajectory of each obstacle according to the map navigation information in the data required for lane change decision and the short-term predicted trajectory of the obstacles in each lane.

[0179] S304: Determine the target position and the expected position according to the distribution of obstacles in each lane.

[0180] S305. Based on the positioning information of the ego vehicle and the long-term predicted trajectory of the obstacle, a preset dynamic programming algorithm is used to generate multiple lane change longitudinal planning trajectories for the ego vehicle to change lanes to the target position, and multiple cruising longitudinal planning trajectories for the ego vehicle to cruise to the desired position in the current lane.

[0181] S306. Calculate the total cost of the lane change longitudinal planning trajectory based on the lane change parameters of the lane change longitudinal planning trajectory and a preset objective function relationship; and calculate the total cost of the cruise longitudinal planning trajectory based on the cruise parameters of the cruise longitudinal planning trajectory and a preset objective function relationship.

[0182] S307, determining the trajectory with the smallest total cost among multiple lane-changing longitudinal planning trajectories that the vehicle can change lanes to the target position, as the target lane-changing planning trajectory; and determining the trajectory with the smallest total cost among multiple cruising longitudinal planning trajectories that the vehicle can cruise to the desired position in the current lane, as the target cruising planning trajectory.

[0183] S308, simulating the vehicle to travel along the target lane change planning trajectory, and determining the longitudinal displacement when the vehicle travels to the target position along the target lane change planning trajectory, which is the first spatial benefit; and simulating the vehicle to travel along the target cruise planning trajectory, and determining the longitudinal displacement when the vehicle travels to the expected position along the target cruise planning trajectory, which is the second spatial benefit.

[0184] S309: Determine the difference between the first spatial benefit and the second spatial benefit, and determine the difference as the lane change benefit.

[0185] S310: Obtain a lane change trigger threshold.

[0186] S311. Determine whether the lane change benefit is greater than or equal to the lane change trigger threshold.

[0187] If yes, execute step S312, if no, execute step S301.

[0188] S312. Control the vehicle to turn on the lane change turn indicator.

[0189] S313: After the lighting time of the lane change turn signal indicator reaches a preset time length, determine whether the vehicle meets the preset safe lane change requirements.

[0190] If yes, execute step S314, if no, execute step S315.

[0191] S314: Control the vehicle to change lanes according to the target lane change planning trajectory.

[0192] S315. Cancel lane change.

[0193] It should be noted that the specific implementation of the above steps in this embodiment can refer to the specific description of other embodiments, which will not be repeated here. In the process of vehicle lane change control, some or all of the above steps may be included, and the embodiment of this application is not limited.

[0194] Compared with the solution that makes decisions based only on visual maps and short-term obstacle prediction information, the vehicle lane change control method of the embodiment of the present application does not have the problems of initiating the wrong lane change or not changing the lane due to limited perception distance, unreasonable lane change due to missing obstacle intention information, frequent lane change initiation and cancellation due to inaccurate lane change feasibility determination and lane change benefit calculation. The embodiment of the present application generates the long-term prediction trajectory of the obstacle based on navigation map information, short-term prediction trajectory of the obstacle and other auxiliary information, fully considers the intention of the obstacle, and uses the dynamic programming algorithm to more accurately calculate the longitudinal pursuit capability of the vehicle and the lane change benefit that may be obtained after the vehicle initiates the lane change decision. The lane change decision based on this is often more decisive, avoiding the problem of cancellation after the lane change is initiated due to environmental changes caused by a long waiting time for the lane change, and greatly improving the traffic efficiency of vehicles in urban scenes.

[0195] For example, Figure 4 A schematic diagram of a lane change scenario provided in an embodiment of the present application. Figure 4 As shown, using the vehicle lane change control method provided by the embodiment of the present application, when it is determined based on the long-term predicted trajectory 20 of the obstacle that the obstacle ahead obs wants to cut into the ego lane, when the left lane is passable, the lane change process that the ego vehicle ego can execute can be calculated according to the preset dynamic programming algorithm, and the lane change longitudinal planning trajectory 10 shown in the figure is generated, simulating the process in which the ego vehicle ego just changes lanes to the left lane when the obstacle ahead obs cuts into the ego lane, thereby obtaining a larger lane change benefit, and finally initiating a lane change request to complete an efficient lane change.

[0196] For example, Figure 5 A schematic diagram of another lane change scenario provided in an embodiment of the present application. Figure 5As shown, the vehicle lane change control method provided by the embodiment of the present application can also handle the scene of arriving at a traffic light intersection. It can be understood that due to the limited field of view, the perception module of the vehicle cannot directly obtain the red light information in front. If only the obstacle obs1 in front of the lane is identified to slow down and stop, the lane change analysis is directly performed according to the speed information of the obstacle obs1 and the information that the left lane is passable, then the lane change result that the left lane change can greatly improve the traffic efficiency will be obtained. However, according to the vehicle lane change control method of the embodiment of the present application, the vehicle will also obtain map navigation information. According to the map navigation information, it can be known that a red light brake is required at a certain distance ahead, so changing lanes may not have enough benefits, and it is more reasonable not to change lanes. According to the vehicle lane change control method provided by the embodiment of the present application, unreasonable lane changes can be avoided, and the accuracy of lane change execution is improved.

[0197] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0198] Figure 6 This is a schematic diagram of the structure of a vehicle lane change control device provided in an embodiment of the present application. Figure 6 As shown, the vehicle lane change control device 60 provided in this embodiment includes a processing unit 601 , a determination unit 602 and a control unit 603 .

[0199] Wherein, the processing unit 601 is used to obtain the first spatial benefit and the second spatial benefit of the vehicle within a preset time period; wherein, the first spatial benefit is the benefit obtained by simulating the vehicle driving along the target lane change planning trajectory, and the target lane change planning trajectory is a trajectory with the minimum total cost in the lane change longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can change lanes to the target position of the target lane; the second spatial benefit is the benefit obtained by simulating the vehicle driving along the target cruise planning trajectory, and the target cruise planning trajectory is a trajectory with the minimum total cost in the cruise longitudinal planning trajectory determined based on a preset dynamic programming algorithm, in which the vehicle can cruise to the desired position in the current lane;

[0200] A determining unit 602, configured to determine a lane change benefit according to the first spatial benefit and the second spatial benefit;

[0201] The control unit 603 is used to control the vehicle to change lanes according to the lane change benefit.

[0202] The device provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be described in detail here.

[0203] Based on the above embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0204] Acquire data required for lane change decision; wherein the data required for lane change decision at least includes lane perception information, vehicle positioning information, and map navigation information;

[0205] Determine the target lane change planning trajectory and target cruise planning trajectory of the vehicle within a preset time period according to the data required for lane change decision and the preset dynamic planning algorithm;

[0206] According to the target lane change planning trajectory and the target cruise planning trajectory, a first spatial benefit and a second spatial benefit are determined.

[0207] Based on the above embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0208] Based on the data required for lane change decision, determine the obstacles in each lane and determine the long-term predicted trajectory of the obstacles;

[0209] Determine the target position and expected position based on the distribution of obstacles in each lane;

[0210] Based on the positioning information of the ego vehicle and the long-term predicted trajectory of the obstacle, a preset dynamic programming algorithm is used to generate multiple lane-changing longitudinal planning trajectories for the ego vehicle to change lanes to the target position, and multiple cruising longitudinal planning trajectories for the ego vehicle to cruise to the desired position in the current lane, and the total cost of each lane-changing longitudinal planning trajectory and the total cost of each cruising longitudinal planning trajectory are calculated;

[0211] Determine the trajectory with the minimum total cost among multiple lane-changing longitudinal planning trajectories that the vehicle can change lanes to the target position, and use it as the target lane-changing planning trajectory;

[0212] Determine the trajectory with the minimum total cost among multiple cruise longitudinal planning trajectories that allow the vehicle to cruise to the desired position in the current lane, and use it as the target cruise planning trajectory.

[0213] Based on the above embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0214] The total cost of the lane change longitudinal planning trajectory is calculated according to the lane change parameters of the lane change longitudinal planning trajectory and a preset objective function relationship;

[0215] According to the cruise parameters of the cruise longitudinal planning trajectory and the preset objective function relationship, the total cost of the cruise longitudinal planning trajectory is calculated.

[0216] Based on the above embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0217] Analyze and process lane perception information in the data required for lane change decision-making to determine obstacles in each lane and their short-term predicted trajectories;

[0218] The long-term predicted trajectory of the obstacle is determined based on the map navigation information in the data required for lane change decision and the short-term predicted trajectory of the obstacles in each lane.

[0219] Based on the above embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0220] Simulate the ego vehicle to drive along the target lane change planning trajectory, and determine the longitudinal displacement when the ego vehicle drives along the target lane change planning trajectory to the target position, which is the first spatial benefit;

[0221] The vehicle is simulated to travel along the target cruise planning trajectory, and the longitudinal displacement when the vehicle travels to the desired position along the target cruise planning trajectory is determined as the second space benefit.

[0222] Based on the above embodiment, in some possible examples, the determining unit 602 is specifically configured to:

[0223] A difference between the first spatial benefit and the second spatial benefit is determined, and the difference is determined as the lane change benefit.

[0224] Based on the above embodiment, in some possible examples, the control unit 603 is specifically configured to:

[0225] Get the lane change trigger threshold;

[0226] If the lane change benefit is greater than or equal to the lane change trigger threshold, the lane change decision information is generated and executed; wherein the lane change decision information is used to instruct the ego vehicle to change lanes according to the target lane change planning trajectory.

[0227] Based on the above embodiment, in some possible examples, the control unit 603 is specifically configured to:

[0228] Get the real-time distance between the vehicle and the target lane-changing point;

[0229] Determine the lane change task of the vehicle according to the real-time distance and the first preset corresponding relationship; wherein the first preset corresponding relationship is the corresponding relationship between the real-time distance and the lane change task;

[0230] A lane change triggering threshold is determined according to the lane change task and the second preset corresponding relationship; wherein the second preset corresponding relationship is the corresponding relationship between the lane change task and the lane change triggering threshold.

[0231] Based on the above embodiment, in some possible examples, the control unit 603 is specifically configured to:

[0232] Control the vehicle to turn on the lane change indicator;

[0233] After the lighting time of the lane change turn signal indicator reaches the preset time length, if it is determined that the vehicle meets the preset safe lane change requirements, the vehicle is controlled to change lanes according to the target lane change planning trajectory.

[0234] Based on the above embodiment, in some possible examples, the control unit 603 is further specifically configured to:

[0235] After controlling the vehicle to turn on the lane change turn signal indicator, before the lighting time of the lane change turn signal indicator reaches the preset time length, the control processing unit 601 repeatedly executes the steps of obtaining the first spatial gain and the second spatial gain of the vehicle within the preset time period, and determines whether to change the lane change decision based on the repeatedly obtained lane change gains.

[0236] The device provided in this embodiment can be used to execute the method of the above embodiment. Its implementation principle and technical effect are similar and will not be described in detail here.

[0237] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. In addition, it can also be stored in the memory of the above device in the form of program code, and the functions of the above data processing modules can be called and executed by a processing element of the above device. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0238] Figure 7 A schematic diagram of the structure of a vehicle lane change control device provided in an embodiment of the present application. Figure 7 As shown, the vehicle lane change control device 70 provided in this embodiment includes: at least one processor 701 and a memory 702. Optionally, the device 70 also includes a communication component 703. The processor 701, the memory 702 and the communication component 703 are connected via a bus 704.

[0239] In a specific implementation process, at least one processor 701 executes the computer-executable instructions stored in the memory 702, so that at least one processor 701 executes the above method.

[0240] The specific implementation process of the processor 701 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0241] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0242] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0243] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0244] The present application also provides a car, which includes the vehicle lane change control device as described above.

[0245] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0246] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0247] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0248] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0249] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0250] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0251] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0252] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0253] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0254] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A vehicle lane change control method, characterized in that: The method comprises: Obtaining a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, wherein the target lane change planning trajectory is a trajectory with the minimum total cost among the lane change longitudinal planning trajectories in which the vehicle can change lanes to a target position of the target lane, determined based on a preset dynamic programming algorithm; the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, wherein the target cruise planning trajectory is a trajectory with the minimum total cost among the cruise longitudinal planning trajectories in which the vehicle can cruise to a desired position in the current lane, determined based on a preset dynamic programming algorithm; determining a lane change benefit according to the first spatial benefit and the second spatial benefit; The vehicle is controlled to change lanes according to the lane change benefit.

2. The method according to claim 1, characterized in that The obtaining of the first space benefit and the second space benefit of the vehicle within a preset time period includes: Acquiring data required for lane change decision; wherein the data required for lane change decision at least includes lane perception information, vehicle positioning information and map navigation information; Determine a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period according to the data required for the lane change decision and the preset dynamic planning algorithm; A first spatial benefit and a second spatial benefit are determined according to the target lane change planning trajectory and the target cruise planning trajectory.

3. The method according to claim 2, characterized in that The step of determining a target lane change planning trajectory and a target cruise planning trajectory of the vehicle within a preset time period according to the lane change decision data and the preset dynamic planning algorithm includes: Determining obstacles in each lane according to the data required for the lane change decision, and determining a long-term predicted trajectory of the obstacles; Determining the target position and the expected position according to the distribution of obstacles in each lane; Based on the vehicle positioning information and the long-term predicted trajectory of the obstacle, a plurality of lane-changing longitudinal planning trajectories for the vehicle to change lanes to the target position and a plurality of cruising longitudinal planning trajectories for the vehicle to cruise in the current lane to the desired position are generated through the preset dynamic programming algorithm, and a total cost of each of the lane-changing longitudinal planning trajectories and a total cost of each of the cruising longitudinal planning trajectories are calculated; Determine a trajectory with the minimum total cost among a plurality of lane-changing longitudinal planning trajectories through which the vehicle can change lanes to the target position, as the target lane-changing planning trajectory; Determine the trajectory with the minimum total cost among multiple cruise longitudinal planning trajectories that the vehicle can cruise to the desired position in the current lane, as the target cruise planning trajectory.

4. The method according to claim 3, characterized in that: The calculating the total cost of each lane change longitudinal planning trajectory and the total cost of each cruise longitudinal planning trajectory includes: Calculating a total cost of the lane-changing longitudinal planning trajectory according to the lane-changing parameters of the lane-changing longitudinal planning trajectory and a preset objective function relationship; The total cost of the longitudinal cruise planning trajectory is calculated based on the cruise parameters of the longitudinal cruise planning trajectory and a preset objective function relationship.

5. The method according to claim 3, characterized in that: The determining of obstacles in each lane according to the data required for the lane change decision and determining the long-term predicted trajectory of the obstacles includes: Analyzing and processing lane perception information in the data required for the lane change decision to determine obstacles in each lane and short-term predicted trajectories of the obstacles; The long-term predicted trajectory of the obstacle is determined according to the map navigation information in the data required for the lane change decision and the short-term predicted trajectory of the obstacle in each lane.

6. The method according to claim 2, characterized in that The determining the first spatial benefit and the second spatial benefit according to the target lane change planning trajectory and the target cruise planning trajectory includes: Simulate the vehicle traveling along the target lane change planning trajectory, and determine the longitudinal displacement of the vehicle when the vehicle travels along the target lane change planning trajectory to the target position, which is the first spatial benefit; The vehicle is simulated to travel along the target cruise planning trajectory, and the longitudinal displacement when the vehicle travels to the expected position along the target cruise planning trajectory is determined as the second spatial benefit.

7. The method according to any one of claims 1 to 6, characterized in that The determining the lane change benefit according to the first spatial benefit and the second spatial benefit includes: A difference between the first spatial gain and the second spatial gain is determined, and the difference is determined as a lane change gain.

8. The method according to any one of claims 1 to 6, characterized in that The controlling the vehicle to change lanes according to the lane change benefit includes: Get the lane change trigger threshold; If the lane change benefit is greater than or equal to the lane change trigger threshold, then the lane change decision information is generated and executed; wherein the lane change decision information is used to instruct the vehicle to change lanes according to the target lane change planning trajectory.

9. The method according to claim 8, characterized in that The obtaining of the lane change triggering threshold comprises: Get the real-time distance between the vehicle and the target lane-changing point; Determining the lane changing task of the vehicle according to the real-time distance and the first preset corresponding relationship; wherein the first preset corresponding relationship is the corresponding relationship between the real-time distance and the lane changing task; A lane change triggering threshold is determined according to the lane change task and a second preset corresponding relationship; wherein the second preset corresponding relationship is a corresponding relationship between the lane change task and the lane change triggering threshold.

10. The method according to claim 8, characterized in that The lane change decision execution information includes: Control the vehicle to turn on the lane change indicator; After the lighting time of the lane change turn signal lamp reaches a preset time length, if it is determined that the vehicle meets the preset safe lane change requirements, the vehicle is controlled to change lanes according to the target lane change planning trajectory.

11. The method according to claim 10, characterized in that After controlling the vehicle to turn on the lane change turn signal indicator, and before the lighting time of the lane change turn signal indicator reaches a preset time, the method further includes: The steps of obtaining the first spatial gain and the second spatial gain of the vehicle within a preset time period are repeatedly performed, and whether to change the lane change decision is determined according to the repeatedly obtained lane change gains.

12. A vehicle lane change control device, characterized in that: The device comprises: A processing unit, used to obtain a first spatial benefit and a second spatial benefit of the vehicle within a preset time period; wherein the first spatial benefit is a benefit obtained by simulating the vehicle driving along a target lane change planning trajectory, wherein the target lane change planning trajectory is a trajectory with the minimum total cost in a lane change longitudinal planning trajectory in which the vehicle can change lanes to a target position of a target lane, determined based on a preset dynamic programming algorithm; and the second spatial benefit is a benefit obtained by simulating the vehicle driving along a target cruise planning trajectory, wherein the target cruise planning trajectory is a trajectory with the minimum total cost in a cruise longitudinal planning trajectory in which the vehicle can cruise to a desired position in a current lane, determined based on a preset dynamic programming algorithm; a determining unit, configured to determine a lane change benefit according to the first spatial benefit and the second spatial benefit; A control unit is used to control the vehicle to change lanes according to the lane change benefit.

13. A vehicle lane change control device, characterized in that: The vehicle lane change control device includes: a memory, a processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 11.

14. A car, characterized in that: The automobile includes the vehicle lane change control device as claimed in claim 13.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 11 when executed by a processor.

16. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 11 when being executed by a processor.

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