Predicted trajectory optimization method and device for surrounding vehicles, vehicle and storage medium

Abstract

The embodiment of the invention discloses a predicted trajectory optimization method and device for surrounding vehicles, a vehicle and a storage medium, and relates to the technical field of vehicle control, and the method comprises the steps: obtaining an initial predicted trajectory of the surrounding vehicles of a current vehicle, and determining a starting point lane corresponding to a trajectory starting point of the initial predicted trajectory and a terminal point lane corresponding to a trajectory terminal point; determining an optimized lane of the terminal lane according to the position of the starting lane and the position of the terminal lane, and performing direction optimization on the initial prediction trajectory according to the starting lane and the optimized lane to obtain an intermediate prediction trajectory; determining a preceding vehicle of the surrounding vehicles according to the intermediate prediction trajectory; determining interaction track points of the surrounding vehicles and the front vehicle based on the intermediate prediction track, and moving the interaction track points to obtain optimized track points of the interaction track points; and speed optimization is carried out on the intermediate prediction trajectory based on the optimized trajectory points to obtain the target prediction trajectory of the surrounding vehicles, so that the reasonability and accuracy of the prediction trajectory are improved, and the driving safety of the autonomous vehicle is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle control technology, and in particular, to a method, device, vehicle and storage medium for optimizing the predicted trajectories of surrounding vehicles. Background Art

[0002] When making decisions and planning for the vehicle itself, an autonomous vehicle needs to predict the movement trajectories of surrounding vehicles to ensure the safe driving of the autonomous vehicle.

[0003] At present, neural network models are used to predict the movement trajectories of surrounding vehicles in the future. However, the prediction results based on the neural network model rely on the training results of the neural network model based on the data set, which may not give sufficient consideration to the lane lines, surrounding vehicles and the rationality of vehicle driving. As a result, the prediction results may lead to unreasonable driving scenarios, such as changing the driving trajectory of three lanes and colliding with surrounding vehicles, which in turn leads to low prediction accuracy of the movement trajectory of surrounding vehicles and reduces the driving safety of autonomous driving vehicles. Summary of the invention

[0004] The embodiments of the present application provide a method, device, vehicle and storage medium for optimizing the predicted trajectory of surrounding vehicles, implement an optimization method for the predicted trajectory, improve the prediction accuracy of the motion trajectory of surrounding vehicles, and solve the problem of low prediction accuracy of the predicted trajectory determined based on the neural network model in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a method for optimizing predicted trajectories of surrounding vehicles, the method comprising:

[0006] Obtaining the initial predicted trajectory of the vehicles around the current vehicle, and determining a starting lane corresponding to the starting point of the initial predicted trajectory and an ending lane corresponding to the ending point of the trajectory;

[0007] The optimized lane of the terminal lane is determined according to the position of the starting lane and the position of the terminal lane, and the direction of the initial predicted trajectory is optimized according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory;

[0008] Determine the leading vehicle of the surrounding vehicles based on the intermediate predicted trajectory;

[0009] Determine the interaction trajectory points between the surrounding vehicles and the front vehicle based on the intermediate predicted trajectory, and move the interaction trajectory points to obtain the optimized trajectory points of the interaction trajectory points;

[0010] The speed of the intermediate predicted trajectory is optimized based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles.

[0011] In a second aspect, an embodiment of the present application provides a device for optimizing predicted trajectories of surrounding vehicles, the device comprising:

[0012] A lane determination module is used to obtain an initial predicted trajectory of vehicles around the current vehicle, and determine a starting lane corresponding to a trajectory starting point of the initial predicted trajectory and an ending lane corresponding to an ending point of the trajectory;

[0013] A direction optimization module is used to determine the optimized lane of the end lane according to the position of the starting lane and the position of the end lane, and to optimize the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory;

[0014] A leading vehicle determination module, used to determine the leading vehicle of the surrounding vehicles based on the intermediate predicted trajectory;

[0015] A trajectory point optimization module is used to determine the interaction trajectory points between the surrounding vehicles and the front vehicle based on the intermediate predicted trajectory, and to move the interaction trajectory points to obtain the optimized trajectory points of the interaction trajectory points;

[0016] The speed optimization module is used to optimize the speed of the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles.

[0017] In a third aspect, an embodiment of the present application provides a vehicle, the vehicle comprising:

[0018] at least one processor; and a memory communicatively coupled to the at least one processor;

[0019] Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the method for optimizing the predicted trajectories of surrounding vehicles of any embodiment of the present application.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for optimizing the predicted trajectories of surrounding vehicles as in any embodiment of the present application.

[0021] In the embodiment of the present application, the initial predicted trajectory of the surrounding vehicles of the current vehicle can be obtained, and the starting lane corresponding to the starting point of the initial predicted trajectory and the terminal lane corresponding to the end point of the trajectory can be determined. Secondly, the optimized lane of the terminal lane is determined according to the position of the starting lane and the position of the terminal lane, and the direction of the initial predicted trajectory is optimized according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory. Then, the front vehicle of the surrounding vehicles is determined according to the intermediate predicted trajectory, and then the interaction trajectory points of the surrounding vehicles and the front vehicle are determined based on the intermediate predicted trajectory, and the interaction trajectory points are moved to obtain the optimized trajectory points of the interaction trajectory points. After that, the speed of the intermediate predicted trajectory is optimized based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles, thereby realizing the predicted trajectory optimization function of the surrounding vehicles; the optimized lane is determined by the starting lane and the terminal lane of the initial predicted trajectory, and the direction is optimized based on the optimized lane, so that the intermediate predicted trajectory is more in line with actual traffic rules and driving habits, and there will be no dangers such as changing two or more lanes at one time. The problem that the prediction results in the prior art do not take into account the rationality of lane lines and vehicle driving, which may lead to unreasonable driving scenarios, is effectively avoided, thereby improving the rationality and accuracy of the target prediction trajectory; by introducing the leading vehicle of the surrounding vehicles, moving interactive trajectory points to obtain optimized trajectory points, and optimizing the speed based on the optimized trajectory points, the target prediction trajectory is closer to the actual driving scenario, and there will be no dangerous situations such as collisions between the surrounding vehicles and the leading vehicle, which effectively avoids the problem that the prediction results in the prior art do not take into account the environmental vehicles (i.e., the leading vehicles of the surrounding vehicles) and may lead to unreasonable driving scenarios, thereby improving the rationality and accuracy of the target prediction trajectory; by performing multi-level optimization on the initial prediction trajectory, the current vehicle can better cope with various uncertainties and changing factors, and can plan obstacle avoidance paths in advance, optimize driving speed and routes, make the autonomous driving system more reliable and stable, thereby improving the driving safety of autonomous driving vehicles, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 It is a flowchart of a method for optimizing the predicted trajectories of surrounding vehicles provided in an embodiment of the present application;

[0024] Figure 2 is another flowchart of the method for optimizing the predicted trajectories of surrounding vehicles provided in an embodiment of the present application;

[0025] Figure 3 is an example diagram of a lane network provided in an embodiment of the present application;

[0026] Figure 4 is an example diagram of the initial prediction trajectory of direction optimization provided by an embodiment of the present application;

[0027] Figure 5 is another example diagram of the direction optimization initial prediction trajectory provided by an embodiment of the present application;

[0028] Figure 6 It is another flowchart of the method for optimizing the predicted trajectory of surrounding vehicles provided in an embodiment of the present application;

[0029] Figure 7 is an example diagram of a speed optimization intermediate prediction trajectory provided by an embodiment of the present application;

[0030] Figure 8 It is a structural schematic diagram of a device for optimizing predicted trajectories of surrounding vehicles provided in an embodiment of the present application;

[0031] Fig. 9 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0033] It should be noted that the terms "first", "second", "target", and "original" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including", "having", and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0034] Figure 1It is a flow chart of the method for optimizing the predicted trajectories of surrounding vehicles provided in an embodiment of the present application. This embodiment can be applied to scenarios where the predicted trajectories of surrounding vehicles of the current vehicle need to be optimized. The method for optimizing the predicted trajectories of surrounding vehicles provided in this embodiment can be executed by the device for optimizing the predicted trajectories of surrounding vehicles provided in an embodiment of the present application, and the device can be implemented by software and / or hardware. In a specific embodiment, the device for optimizing the predicted trajectories of surrounding vehicles can be integrated into a vehicle. For example, the vehicle can be an autonomous driving vehicle, and the vehicle can include a vehicle controller. The execution subject of this method can be the vehicle controller of the vehicle (i.e., the vehicle controller of the current vehicle), see Figure 1 The method for optimizing the predicted trajectories of surrounding vehicles in this embodiment includes but is not limited to the following steps:

[0035] S110, obtaining an initial predicted trajectory of vehicles surrounding the current vehicle, and determining a starting lane corresponding to a trajectory starting point of the initial predicted trajectory and an ending lane corresponding to an ending point of the trajectory.

[0036] The current vehicle is the vehicle that is performing the autonomous driving task. The vehicle can plan its own driving path according to the motion trajectory of the surrounding vehicles and control its own driving. The surrounding vehicles are other vehicles near the current vehicle, which may affect the driving of the current vehicle.

[0037] The initial predicted trajectory is based on the surrounding vehicle data collected by the current vehicle's sensors (such as cameras, lidar, and millimeter-wave radar, etc.), and is a preliminary prediction of the possible driving paths of surrounding vehicles in the future using a neural network model. The neural network model is used to predict the vehicle's driving trajectory.

[0038] Optionally, the initial predicted trajectory may include multiple trajectory points and status data of each trajectory point; the status data of the trajectory point may include the position corresponding to the trajectory point, the distance corresponding to the trajectory point, the time corresponding to the trajectory point, the speed corresponding to the trajectory point, the steering angle corresponding to the trajectory point and the driving direction corresponding to the trajectory point; the distance corresponding to the trajectory point is the distance between the trajectory point and the starting point of the trajectory; the time corresponding to the trajectory point is the time required for the surrounding vehicles to travel from the starting point of the trajectory to the trajectory point; the speed corresponding to the trajectory point is the speed of the surrounding vehicles when they travel to the trajectory point; the steering angle corresponding to the trajectory point is the angle between the center line of the surrounding vehicles and the lane line when the surrounding vehicles travel to the trajectory point; the driving direction corresponding to the trajectory point is the driving direction of the surrounding vehicles at the trajectory point, such as north, south, east or west.

[0039] The starting point of the trajectory is the starting position of the initial predicted trajectory, that is, the position of the surrounding vehicles at the current moment; the starting point of the trajectory is determined in real time based on the sensors of the current vehicle. The starting lane is the lane where the starting point of the trajectory is located.

[0040] The end point of the trajectory is the end position of the initial predicted trajectory, that is, the position where the surrounding vehicles are expected to arrive at the end of the prediction period. The end lane is the lane where the trajectory ends.

[0041] Specifically, when it is necessary to optimize the predicted trajectory of the surrounding vehicles of the current vehicle, the initial predicted trajectory of the surrounding vehicles of the current vehicle can be obtained, that is, the current vehicle's sensors (such as cameras, laser radars, and millimeter-wave radars, etc.) can be used to collect the state data of the surrounding vehicles in real time, such as the state data such as the position, speed, and acceleration of the surrounding vehicles, as well as environmental information such as road structures and traffic signs, and then based on the collected data, the pre-trained neural network model is used to predict the future driving trajectory of the surrounding vehicles, and the predicted trajectory of the surrounding vehicles is obtained, and the predicted trajectory is determined as the initial predicted trajectory. Among them, the neural network model can be a recurrent neural network (RNN) and a long short-term memory network (LSTM).

[0042] Afterwards, the starting point and end point of the trajectory can be extracted from the initial predicted trajectory. Then, based on the position of the starting point of the trajectory and the high-precision map information, the lane corresponding to the starting point of the trajectory can be determined using the lane line detection algorithm to obtain the starting lane. Based on the position of the end point of the trajectory and the high-precision map information, the lane corresponding to the end point of the trajectory can be determined using the lane line detection algorithm to obtain the end point lane.

[0043] S120, determining an optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane, and optimizing the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory.

[0044] Among them, the optimized lane is the best terminal lane selected according to traffic rules (such as lane change rules), which can provide better driving conditions and lower potential risks.

[0045] The intermediate predicted trajectory is the trajectory obtained after the direction optimization of the initial predicted trajectory, which can provide a smooth driving path that meets traffic rules between the starting lane and the optimized lane. Optionally, the intermediate predicted trajectory may include multiple trajectory points and the status data of each trajectory point; the status data of the trajectory point may include the position corresponding to the trajectory point, the distance corresponding to the trajectory point, the time corresponding to the trajectory point, the speed corresponding to the trajectory point, the steering angle corresponding to the trajectory point, and the driving direction corresponding to the trajectory point; and the direction optimization does not change the time corresponding to the trajectory point and the speed corresponding to the trajectory point.

[0046] Specifically, after obtaining the starting lane and the terminal lane, the optimized lane of the terminal lane can be determined according to the position of the starting lane and the position of the terminal lane. For example, based on the position of the starting lane and the position of the terminal lane, the attribute information of the starting lane and the attribute information of the terminal lane, such as lane width, lane markings, traffic flow, and road curvature, can be collected using the sensors of the current vehicle. Then, based on the collected attribute information, the traffic conditions and traffic rules restrictions of the terminal lane (such as no lane change areas, one-way areas, and continuous lane change rules and restrictions) are determined. Then, based on the traffic conditions and traffic rules restrictions of the terminal lane, an optimal lane is selected for the terminal lane as the optimized lane. At this time, the optimized lane can minimize conflicts with other vehicles and improve driving safety and efficiency.

[0047] Afterwards, the direction of the initial predicted trajectory can be optimized according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory. For example, based on the positional relationship between the starting lane and the optimized lane, the steering angle that needs to be adjusted for each trajectory point in the initial predicted trajectory can be calculated. Then, on the basis of ensuring that the predicted trajectory is safe and meets traffic regulations, the direction of each trajectory point in the initial predicted trajectory is adjusted to generate an intermediate predicted trajectory. At this time, the intermediate predicted trajectory can smoothly connect the starting lane and the optimized lane, and the time and speed corresponding to each trajectory point in the intermediate predicted trajectory have not changed, and are still the same as the time and speed of the corresponding trajectory point in the initial predicted trajectory.

[0048] S130, determining the preceding vehicle of the surrounding vehicles according to the intermediate predicted trajectory.

[0049] The preceding vehicle is the vehicle located on the left and right sides and in front of the surrounding vehicles. For example, when the surrounding vehicles are in the left lane change state, the vehicles located on the left and left front side of the surrounding vehicles are determined as the preceding vehicle; when the surrounding vehicles are in the right lane change state, the vehicles located on the right and right front side of the surrounding vehicles are determined as the preceding vehicle; when the surrounding vehicles are in the lane keeping state (i.e., the lane not changing state), the vehicle located directly in front of the surrounding vehicles is determined as the preceding vehicle.

[0050] Specifically, after obtaining the intermediate predicted trajectory, the leading vehicle of the surrounding vehicles can be determined according to the intermediate predicted trajectory, that is, the lateral intentions of the surrounding vehicles, such as changing left lanes, changing right lanes and keeping lanes, can be determined according to the intermediate predicted trajectory, and then the leading vehicle of the surrounding vehicles can be determined according to the lateral intentions.

[0051] Specifically, when the starting lane and the lane corresponding to the end point in the intermediate predicted trajectory are the same lane, it can be determined that the lateral intention of the surrounding vehicles is to maintain the lane, and the vehicle directly in front of the surrounding vehicles is determined as the leading vehicle; when the lane corresponding to the end point in the intermediate predicted trajectory is on the left side of the starting lane, it can be determined that the lateral intention of the surrounding vehicles is to change lanes left, and the vehicles on the left and left front of the surrounding vehicles are determined as the leading vehicle; when the lane corresponding to the end point in the intermediate predicted trajectory is on the right side of the starting lane, it can be determined that the lateral intention of the surrounding vehicles is to change lanes right, and the vehicles on the right and right front of the surrounding vehicles are determined as the leading vehicle.

[0052] S140: Determine interaction trajectory points between surrounding vehicles and the front vehicle based on the intermediate predicted trajectory, and move the interaction trajectory points to obtain optimized trajectory points of the interaction trajectory points.

[0053] The interactive trajectory point is a trajectory point where the surrounding vehicles and the preceding vehicle may interact among the multiple trajectory points included in the intermediate predicted trajectory.

[0054] The optimized trajectory points are more reasonable and safer predicted position points obtained by fine-tuning or moving the interactive trajectory points. They take into account factors such as traffic rules, road conditions, vehicle dynamics characteristics and safety, and aim to reduce the risk of collision between vehicles.

[0055] Specifically, after determining the leading vehicle of the surrounding vehicles, the interaction trajectory points between the surrounding vehicles and the leading vehicle can be determined based on the intermediate predicted trajectory. That is, the sensors of the current vehicle can be used to obtain surrounding environment information, such as driving data such as the position and speed of the leading vehicle, and then based on the surrounding environment information and the intermediate predicted trajectory, the trajectory points where the surrounding vehicles and the leading vehicle may interact can be identified from the multiple trajectory points included in the intermediate predicted trajectory, and the trajectory points can be determined as interaction trajectory points.

[0056] Afterwards, the interaction trajectory point can be moved to obtain the optimized trajectory point of the interaction trajectory point, that is, the position corresponding to the interaction trajectory point can be obtained from the intermediate predicted trajectory, and then the movement strategy of the interaction trajectory point can be determined, and the position corresponding to the interaction trajectory point can be moved based on the movement strategy. For example, the position corresponding to the interaction trajectory point can be moved a random distance toward the end of the trajectory to avoid collision between the surrounding vehicles and the front vehicle at the interaction trajectory point. The random distance can be randomly set according to the actual situation on the basis of ensuring that the surrounding vehicles do not collide with the front vehicle.

[0057] S150: Optimize the speed of the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles.

[0058] The target predicted trajectory is the final predicted trajectory obtained by optimizing the speed of each trajectory point in the intermediate predicted trajectory based on the optimized interactive trajectory points. Optionally, the target predicted trajectory may include multiple trajectory points and the status data of each trajectory point; the status data of the trajectory point may include the position corresponding to the trajectory point, the distance corresponding to the trajectory point, the time corresponding to the trajectory point, the speed corresponding to the trajectory point, the steering angle corresponding to the trajectory point, and the driving direction corresponding to the trajectory point; the speed optimization does not change the time corresponding to the trajectory point and the driving direction corresponding to the trajectory point.

[0059] Specifically, after obtaining the optimized trajectory points, the speed of the intermediate predicted trajectory can be optimized based on the optimized trajectory points. For example, the position of each trajectory point can be moved based on the moving distance (i.e., the distance between the interactive trajectory point and the optimized trajectory point), such as moving the position corresponding to each trajectory point by the moving distance in the direction of the trajectory end point to obtain the target distance corresponding to each trajectory point (i.e., the distance between the trajectory point and the trajectory starting point). At this time, there is no need to move the position corresponding to the trajectory starting point, and then calculate the ratio between the target distance corresponding to each trajectory point and the time corresponding to each trajectory point to obtain the target speed of the surrounding vehicles at each trajectory point. Then, the target speed corresponding to each trajectory point is smoothed to ensure that the speed change is within a reasonable range and to avoid the impact of sudden acceleration or deceleration on passenger comfort and safety. Then, the smoothed target speed is combined with the target distance corresponding to each trajectory point to reconstruct the target predicted trajectory of the surrounding vehicles. At this time, both the interaction between vehicles and the smoothness and safety of driving are considered. After that, the generated target predicted trajectory can be verified to ensure that it meets the requirements of traffic rules, road conditions, and vehicle dynamics characteristics.

[0060] Optionally, after obtaining the target predicted trajectory, the vehicle controller of the current vehicle can determine the control strategy of the current vehicle (i.e., the control operations of the current vehicle in the future) based on the target predicted trajectory, such as adjusting the vehicle speed and changing lanes and other control operations, so as to make decisions and plans for the vehicle, so that the current vehicle can plan obstacle avoidance paths in advance, optimize driving speed and route, and effectively respond to emergencies and reduce traffic accidents, thereby ensuring the safety and efficiency of the current vehicle during driving, thereby improving the driving safety of autonomous driving vehicles.

[0061] The technical solution of the embodiment of the present application determines the optimized lane by the starting lane and the end lane of the initial predicted trajectory, and optimizes the direction based on the optimized lane, so that the intermediate predicted trajectory is more in line with the actual traffic rules and driving habits, and there will be no dangerous situations such as changing two or more lanes at one time, which effectively avoids the problem that the prediction results in the prior art do not consider the rationality of lane lines and vehicle driving enough and may appear unreasonable driving scenes, thereby improving the rationality and accuracy of the target predicted trajectory; by introducing the leading vehicle of the surrounding vehicles and the mobile interactive trajectory points to obtain the optimized trajectory points and optimizing the speed based on the optimized trajectory points, the target predicted trajectory is closer to the actual driving scene, and there will be no dangerous situations such as collision between the surrounding vehicles and the leading vehicle, which effectively avoids the problem that the prediction results in the prior art do not consider the environmental vehicles (i.e., the leading vehicles of the surrounding vehicles) enough and may appear unreasonable driving scenes, thereby improving the rationality and accuracy of the target predicted trajectory; by performing multi-level optimization on the initial predicted trajectory, the current vehicle can better cope with various uncertainties and changing factors, and can plan obstacle avoidance paths in advance, optimize the driving speed and route, make the automatic driving system more reliable and stable, thereby improving the driving safety of the automatic driving vehicle, thereby improving the user experience.

[0062] The following further describes a method for optimizing the predicted trajectory of surrounding vehicles provided by an embodiment of the present application. Figure 2 is another flow chart of the method for optimizing the predicted trajectory of surrounding vehicles provided in the embodiment of the present application. The embodiment of the present application is a specific refinement of "determining the optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane, and optimizing the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain the intermediate predicted trajectory". Figure 2 The method of this embodiment includes but is not limited to the following steps:

[0063] S201. Determine a lane change situation according to a position of a starting lane and a position of an end lane.

[0064] Among them, the lane change situation refers to the situation where the vehicle needs to change from the current lane to another lane due to factors such as road conditions, traffic regulations or driving needs during driving; the lane change situation can include single lane change, continuous lane change and no lane change.

[0065] Specifically, the positional relationship between the starting lane and the ending lane may be determined according to the position of the starting lane and the position of the ending lane, and the lane change situation may be determined according to the positional relationship.

[0066] Specifically, if the starting lane and the ending lane are the same lane, it indicates that the surrounding vehicles are in the lane keeping state, and the lane change situation can be determined as no lane change; if the starting lane and the ending lane are not the same lane, and the ending lane is adjacent to the starting lane, it indicates that the surrounding vehicles are in a single lane change state, and the lane change situation can be determined as a single lane change; if the starting lane and the ending lane are not the same lane, and the ending lane is not adjacent to the starting lane, it indicates that the surrounding vehicles are in a continuous lane change state, and the lane change situation can be determined as a continuous lane change.

[0067] For example, Figure 3 The figure shows an example of a lane network provided by an embodiment of the present application. Figure 3 The position of the surrounding vehicles in is the starting point of the initial predicted trajectory. At this time, the starting lane corresponding to the starting point of the trajectory is lane 2; if the trajectory end point of the initial predicted trajectory is lane 4, it indicates that the end lane is lane 4, and the lane change situation is continuous lane change; if the trajectory end point of the initial predicted trajectory is lane 3, it indicates that the end lane is lane 3, and the lane change situation is single lane change; if the trajectory end point of the initial predicted trajectory is lane 2, it indicates that the end lane is lane 2, and the lane change situation is no lane change.

[0068] S202: Determine whether the lane change condition is no lane change.

[0069] Specifically, after obtaining the lane change situation, it can be determined whether the lane change situation is no lane change. If the lane change situation is no lane change, it indicates that the initial predicted trajectory meets the lane change rules, and S203 can be executed at this time; if the lane change situation is not no lane change, S207 can be executed to continue to determine whether the initial predicted trajectory meets the lane change rules.

[0070] S203: When the lane change condition is no lane change, determine a middle point lane corresponding to the middle point of the initial predicted trajectory.

[0071] The middle point lane is the lane where the middle point of the initial predicted trajectory is located; the middle point of the trajectory does not include the trajectory starting point and the trajectory end point.

[0072] Specifically, when the lane change situation is no lane change, it indicates that the surrounding vehicles are in the lane keeping state. At this time, the middle point lane corresponding to the middle point of the initial predicted trajectory can be determined, that is, each middle point of the trajectory in the initial predicted trajectory can be traversed, and based on the position of each middle point of the trajectory and the high-precision map information, the lane line detection algorithm can be used to determine the middle point lane corresponding to each middle point of the trajectory.

[0073] S204: Determine whether the middle lane and the starting lane are the same lane.

[0074] Specifically, after determining the intermediate point lane corresponding to each intermediate point of the trajectory, it can be determined whether the intermediate point lane and the starting lane are the same lane. If each intermediate point lane is the same lane as the starting lane, S206 can be executed; if there is an intermediate point lane that is not the same lane as the starting lane, S205 can be executed.

[0075] S205: When the middle lane and the starting lane are not the same lane, optimize the direction of the initial predicted trajectory according to the starting lane and the end lane to obtain an intermediate predicted trajectory.

[0076] The lanes corresponding to the trajectory points in the intermediate predicted trajectory are the same as the starting lane.

[0077] Specifically, when there is a middle point lane that is not the same lane as the starting lane, the direction of the initial predicted trajectory can be optimized according to the starting lane and the end lane to obtain the intermediate predicted trajectory, that is, the steering angle that needs to be adjusted for each middle point of the trajectory in the initial predicted trajectory can be calculated based on the starting lane and the end lane, and then the direction of each middle point of the trajectory in the initial predicted trajectory is adjusted on the basis of ensuring the safety of the predicted trajectory and satisfying the restrictions of traffic regulations to generate the intermediate predicted trajectory, and the lanes corresponding to each trajectory point in the intermediate predicted trajectory are the same as the starting lane. At this time, the intermediate predicted trajectory can smoothly connect the starting lane and the end lane, and the time and speed corresponding to each middle point of the trajectory in the intermediate predicted trajectory have not changed, and are still the same as the time and speed of the corresponding middle point of the trajectory in the initial predicted trajectory.

[0078] For example, Figure 4 The figure shows an example of an initial prediction trajectory of direction optimization provided by an embodiment of the present application. Figure 4 The orange curve in a is the initial predicted trajectory. The starting lane corresponding to the starting point of the initial predicted trajectory is lane 2, and the end lane corresponding to the end point of the trajectory is lane 2. At this time, the lane change of the initial predicted trajectory is no lane change, and the direction of the initial predicted trajectory is optimized based on the starting lane and the end lane. The intermediate predicted trajectory is Figure 4 The orange straight line in b, that is, the lane corresponding to each trajectory point in the middle predicted trajectory is lane 2.

[0079] S206: When the middle point lane and the starting point lane are the same lane, determine the initial predicted trajectory as the middle predicted trajectory.

[0080] Specifically, when each intermediate point lane is the same lane as the starting point lane, it indicates that there is no need to optimize the direction of the initial predicted trajectory. In this case, the initial predicted trajectory can be directly determined as the intermediate predicted trajectory.

[0081] S207: When the lane change condition is not no lane change, determine whether the lane change condition is a continuous lane change.

[0082] Specifically, when the lane change situation is not no lane change, it can be determined whether the lane change situation is a continuous lane change. If the lane change situation is a continuous lane change, it indicates that the initial predicted trajectory does not satisfy the lane change rules (that is, two or more lanes cannot be changed at one time), and S208 can be executed at this time; if the lane change situation is a single lane change, it indicates that the lane change situation is not a continuous lane change, that is, the initial predicted trajectory satisfies the lane change rules, and S211 can be executed at this time.

[0083] S208: When the lane change situation is a continuous lane change, determine the lane change direction according to the position of the starting lane and the position of the end lane.

[0084] The lane changing direction is the direction selected by surrounding vehicles when changing lanes; the lane changing direction may include left lane changing and right lane changing.

[0085] Specifically, when the lane change situation is a continuous lane change, the lane change direction can be determined according to the position of the starting lane and the position of the end lane, that is, if the end lane is on the left side of the starting lane, the lane change direction can be determined as a left lane change; if the end lane is on the right side of the starting lane, the lane change direction can be determined as a right lane change.

[0086] For example, Figure 3 As shown, the starting lane corresponding to the starting point of the trajectory is lane 2; if the end lane is lane 4, the lane change direction is left.

[0087] S209: Determine an adjacent lane of the starting lane based on the lane change direction, and determine the adjacent lane as an optimized lane.

[0088] The adjacent lane is the lane adjacent to the starting lane in the lane changing direction.

[0089] Specifically, after determining the lane change direction, the adjacent lane of the starting lane in the lane change direction may be determined as the optimized lane. Figure 3 As shown, if the starting lane corresponding to the starting point of the trajectory is lane 2, and the ending lane corresponding to the end point of the trajectory is lane 4, then the lane change direction is left lane change. At this time, lane 3 can be determined as the adjacent lane of lane 2 on the left lane change, and lane 3 can be determined as the optimized lane.

[0090] S210: Optimize the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory.

[0091] Among them, the lane corresponding to the end point in the intermediate predicted trajectory is the optimized lane.

[0092] Specifically, after obtaining the optimized lane, the direction of the initial predicted trajectory can be optimized according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory. For example, based on the positional relationship between the starting lane and the optimized lane, the steering angle that needs to be adjusted for each trajectory point in the initial predicted trajectory can be calculated. Then, on the basis of ensuring the safety of the predicted trajectory and satisfying traffic regulations, the direction of each trajectory point in the initial predicted trajectory is adjusted to generate an intermediate predicted trajectory, and the lane corresponding to the end point in the intermediate predicted trajectory is the optimized lane. At this time, the intermediate predicted trajectory can smoothly connect the starting lane and the optimized lane, and the time and speed corresponding to each trajectory point in the intermediate predicted trajectory have not changed, and are still the same as the time and speed of the corresponding trajectory point in the initial predicted trajectory.

[0093] For example, Figure 5 FIG. 1 is another example diagram of the initial prediction trajectory of the direction optimization provided by the embodiment of the present application. Figure 5 The orange curve in c is the initial predicted trajectory, that is, the starting lane corresponding to the starting point of the initial predicted trajectory is lane 2, and the end lane corresponding to the end point of the trajectory is lane 4. At this time, the lane change situation of the initial predicted trajectory is continuous lane change, the lane change direction is left lane change, and the optimized lane determined based on the lane change direction is lane 3. The initial predicted trajectory is optimized based on the starting lane and the optimized lane, and the intermediate predicted trajectory is obtained as follows: Figure 5 The orange curve in d, that is, the starting lane corresponding to the starting point of the intermediate predicted trajectory is lane 2, and the lane corresponding to the end point is lane 3 (that is, the lane corresponding to the end point in the intermediate predicted trajectory is the optimized lane).

[0094] S211. When the lane change situation is a single lane change, determine the initial predicted trajectory as the intermediate predicted trajectory.

[0095] Specifically, when the lane change situation is a single lane change, it indicates that the initial predicted trajectory meets the lane change rule, and there is no need to optimize the direction of the initial predicted trajectory. At this time, the initial predicted trajectory can be directly determined as the intermediate predicted trajectory.

[0096] It should be noted that there is no obvious order in the execution of S203 to S206 and S207 to S211, and the execution order can be determined according to actual conditions, and this embodiment does not make specific restrictions on this; there is no obvious order in the execution of S205 and S206, and the execution order can be determined according to actual conditions, and this embodiment does not make specific restrictions on this; there is no obvious order in the execution of S208 to S210 and S211, and the execution order can be determined according to actual conditions, and this embodiment does not make specific restrictions on this.

[0097] The technical solution of the embodiment of the present application can determine the lane change situation, i.e., single lane change, continuous lane change and no lane change, according to the position of the starting lane and the position of the end lane, and when the lane change situation is no lane change, determine the middle point lane corresponding to the middle point of the trajectory of the initial predicted trajectory, and then, when the middle point lane is not the same lane as the starting lane, optimize the direction of the initial predicted trajectory according to the starting lane and the end lane to obtain the intermediate predicted trajectory. At this time, the lanes corresponding to each trajectory point in the intermediate predicted trajectory are the same as the starting lane, which can maintain the stable driving of the vehicle in the current lane, avoid unnecessary lane changes, and thus reduce the safety hazards caused by lane changes, effectively improve the rationality of the intermediate predicted trajectory when there is no lane change, thereby improving the accuracy of determining the intermediate predicted trajectory. , which provides data support for the subsequent determination of the target predicted trajectory; when the lane change situation is a continuous lane change, the lane change direction is determined according to the position of the starting lane and the position of the end lane, and then the adjacent lane of the starting lane is determined based on the lane change direction, and the adjacent lane is determined as the optimized lane, and then the direction of the initial predicted trajectory is optimized according to the starting lane and the optimized lane to obtain the intermediate predicted trajectory. By determining the lane change direction and the optimized lane, the rationality of the intermediate predicted trajectory in the lane change situation can be improved, and the occurrence of continuous lane changes can be effectively avoided, thereby improving the determination accuracy of the intermediate predicted trajectory, providing data support for the subsequent determination of the target predicted trajectory, and providing a strong guarantee for the driving safety and traffic efficiency of the autonomous driving vehicle, thereby improving the driving safety of the autonomous driving vehicle.

[0098] The following further describes a method for optimizing the predicted trajectory of surrounding vehicles provided by an embodiment of the present application. Figure 6 It is another flowchart of the method for optimizing the predicted trajectories of surrounding vehicles provided in the embodiment of the present application. The embodiment of the present application is a specific refinement of "determining the interaction trajectory points between the surrounding vehicles and the preceding vehicle based on the intermediate predicted trajectory, and moving the interaction trajectory points to obtain the optimized trajectory points of the interaction trajectory points; optimizing the speed of the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles", as well as a detailed explanation of determining the longitudinal intentions of the surrounding vehicles after optimizing the speed of the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles. See Figure 6 The method of this embodiment includes but is not limited to the following steps:

[0099] S601. Determine interaction trajectory points between surrounding vehicles and the preceding vehicle based on the intermediate predicted trajectory.

[0100] S602: Obtain a first speed of surrounding vehicles at the interaction trajectory point, and obtain a second speed of the leading vehicle at the interaction trajectory point.

[0101] The first speed is the speed of the surrounding vehicles when they travel to the interactive trajectory point, and the second speed is the speed of the front vehicle when it travels to the interactive trajectory point.

[0102] Specifically, after obtaining the interaction trajectory point, the speed corresponding to the interaction trajectory point can be obtained from the intermediate predicted trajectory, and the speed can be determined as the first speed. Then, the speed of the front vehicle at the interaction trajectory point can be obtained using the sensors of the current vehicle (such as cameras, lidars, and millimeter-wave radars, etc.), and the speed can be determined as the second speed.

[0103] S603: Determine whether the first speed is greater than the second speed.

[0104] Specifically, after obtaining the first speed and the second speed, it can be determined whether the first speed is greater than the second speed; if the first speed is greater than the second speed, it indicates that there is a collision risk between the surrounding vehicles and the front vehicle, and S604 can be executed at this time; if the first speed is not greater than the second speed, it indicates that there is no collision risk between the surrounding vehicles and the front vehicle, and S609 can be executed at this time.

[0105] S604: When the first speed is greater than the second speed, the interactive trajectory point is moved toward the trajectory starting point by a preset distance to obtain an optimized trajectory point.

[0106] Among them, the preset distance is a pre-set value used to characterize the moving distance of the interaction trajectory point. The user can adjust and set the preset distance according to actual usage requirements, and the embodiment of the present application does not make specific limitations on this.

[0107] For example, Figure 7 The figure shows an example of a speed optimization intermediate prediction trajectory provided by an embodiment of the present application. Figure 7 The orange curve in e is the intermediate predicted trajectory, and the interaction trajectory point between the surrounding vehicles and the front vehicle is determined as s_pre based on the intermediate predicted trajectory; when the first speed of the surrounding vehicles at the interaction trajectory point is 60km / h, the second speed of the front vehicle at the interaction trajectory point is 55km / h, and the preset distance is 2m, the first speed is greater than the second speed, that is, there is a collision risk between the surrounding vehicles and the front vehicle. At this time, the interaction trajectory point can be moved 2m toward the trajectory starting point to obtain the optimized trajectory point, that is Figure 7 of f in s_new.

[0108] S605: Determine a trajectory shrinkage ratio according to the interactive trajectory points and the optimized trajectory points.

[0109] The trajectory shrinkage ratio is a parameter that describes the relationship between the intermediate prediction trajectory and the target prediction trajectory, and reflects the degree to which the intermediate prediction trajectory needs to be shrunk.

[0110] Specifically, after obtaining the optimized trajectory point, the position and distance corresponding to the interactive trajectory point can be extracted from the intermediate predicted trajectory, and then the position corresponding to the optimized trajectory point can be determined according to the preset distance and the position corresponding to the interactive trajectory point. Then, according to the position corresponding to the optimized trajectory point and the position corresponding to the trajectory starting point, the target distance between the optimized trajectory point and the trajectory starting point can be determined, and then the ratio between the target distance and the distance corresponding to the interactive trajectory point is calculated to obtain the trajectory shrinkage ratio.

[0111] Optionally, speed optimization is performed on each trajectory point in the intermediate predicted trajectory based on the trajectory contraction ratio to obtain a target predicted trajectory of surrounding vehicles, and each trajectory point does not include the trajectory starting point, that is, the speed optimization is not performed on the trajectory starting point in the intermediate predicted trajectory. In the embodiment of the present application, speed optimization of the intermediate predicted trajectory based on the trajectory contraction ratio can effectively avoid collisions between surrounding vehicles and the preceding vehicle, thereby improving the accuracy and rationality of the target predicted trajectory, thereby improving the driving safety of the current vehicle.

[0112] S606: proportionally shrink the distance corresponding to each trajectory point based on the trajectory shrinkage ratio to obtain a corrected distance corresponding to each trajectory point.

[0113] The corrected distance is the new distance between the trajectory point and the trajectory starting point after the trajectory point in the intermediate predicted trajectory is proportionally shrunk.

[0114] Specifically, after obtaining the trajectory shrinkage ratio, any trajectory point can be selected from the multiple trajectory points of the intermediate predicted trajectory as the current trajectory point, and then the product between the distance corresponding to the current trajectory point and the trajectory shrinkage ratio is calculated, and the product is determined as the corrected distance corresponding to the current trajectory point; then, other trajectory points can be selected as the current trajectory point, and the above process is repeated to obtain the corrected distance corresponding to each trajectory point. It should be noted that the trajectory point selected from the multiple trajectory points of the intermediate predicted trajectory does not include the trajectory starting point.

[0115] S607, optimizing the speed corresponding to each trajectory point respectively to obtain the corrected speed corresponding to each trajectory point.

[0116] The corrected speed is the new speed corresponding to the trajectory point after the speed of the trajectory point in the intermediate prediction trajectory is optimized.

[0117] Specifically, the speed corresponding to each trajectory point is optimized respectively to obtain the corrected speed corresponding to each trajectory point, including Sa1-Sa3:

[0118] Sa1. For each trajectory point, determine whether the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point.

[0119] Specifically, for each trajectory point in the intermediate predicted trajectory, any trajectory point can be selected from the trajectory points except the trajectory starting point as the current trajectory point, and it is determined whether the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point. If the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point, it indicates that the current trajectory point is the trajectory point before the surrounding vehicles enter the interactive area, and Sa2 can be executed at this time; if the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, it indicates that the current trajectory point is the trajectory point after the surrounding vehicles enter the interactive area, and Sa3 can be executed at this time.

[0120] Sa2. When the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point, the correction speed corresponding to the current trajectory point is determined according to the correction distance corresponding to each trajectory point.

[0121] Specifically, in one implementation, when the distance corresponding to the current trajectory point is smaller than the distance corresponding to the interaction trajectory point, a deceleration prediction can be made for surrounding vehicles before the interaction occurs, that is, the time corresponding to the current trajectory point can be obtained from the intermediate predicted trajectory, and then the corrected speed corresponding to the current trajectory point is determined based on the corrected distance corresponding to the current trajectory point and the time corresponding to the current trajectory point, that is, the ratio between the corrected distance corresponding to the current trajectory point and the time corresponding to the current trajectory point is calculated, and the ratio is determined as the corrected speed corresponding to the current trajectory point. At this time, the corrected distance corresponding to the current trajectory point is smaller than the distance corresponding to the current trajectory point, and therefore the corrected speed corresponding to the current trajectory point is smaller than the speed corresponding to the current trajectory point.

[0122] Specifically, in another implementation, the correction speed corresponding to the current trajectory point is determined according to the correction distance corresponding to each trajectory point, including Sb1-Sb3:

[0123] Sb1. Select a trajectory point corresponding to a first preset distance from the current trajectory point to the trajectory starting point to obtain a first trajectory point.

[0124] Among them, the first preset distance is a pre-set value used to determine the distance that needs to be reached when searching from the current trajectory point to the trajectory starting point. The user can adjust and set it according to actual usage, and the embodiment of the present application does not make specific limitations on this.

[0125] The first track point is a track point reached after moving a first preset distance from the position corresponding to the current track point toward the track starting point.

[0126] Specifically, starting from the position corresponding to the current trajectory point, the trajectory points can be traversed toward the trajectory starting point. For each traversed trajectory point, the distance between it and the current trajectory point is calculated. When the first trajectory point whose distance is greater than or equal to the first preset distance is found, the search is stopped and the trajectory point is determined as the first trajectory point.

[0127] Sb2. Select a trajectory point corresponding to a second preset distance from the current trajectory point to the trajectory end point to obtain a second trajectory point.

[0128] The second preset distance is a value preset to determine the distance to be reached when searching from the current track point to the track end point. The user can adjust and set it according to actual usage, and the embodiment of the present application does not specifically limit this. It should be noted that the first preset distance and the second preset distance can be equal or unequal.

[0129] The second trajectory point is a trajectory point reached after moving a second preset distance from the position corresponding to the current trajectory point toward the trajectory end point.

[0130] Specifically, starting from the position corresponding to the current trajectory point, the trajectory points can be traversed toward the trajectory end point. For each traversed trajectory point, the distance between it and the current trajectory point is calculated. When the first trajectory point whose distance is greater than or equal to the second preset distance is found, the search is stopped and the trajectory point is determined as the second trajectory point.

[0131] Sb3. Determine a correction speed corresponding to the current trajectory point according to the correction distance corresponding to the first trajectory point, the time corresponding to the first trajectory point, the correction distance corresponding to the second trajectory point, and the time corresponding to the second trajectory point.

[0132] The time corresponding to the first trajectory point is the time required for the surrounding vehicles to travel from the starting point of the trajectory to the first trajectory point, that is, the time corresponding to the first trajectory point in the intermediate predicted trajectory. The time corresponding to the second trajectory point is the time required for the surrounding vehicles to travel from the starting point of the trajectory to the second trajectory point, that is, the time corresponding to the second trajectory point in the intermediate predicted trajectory.

[0133] Specifically, after obtaining the first trajectory point and the second trajectory point, the corrected distance corresponding to the first trajectory point, the time corresponding to the first trajectory point, the corrected distance corresponding to the second trajectory point, and the time corresponding to the second trajectory point can be obtained, and then the difference between the corrected distance corresponding to the second trajectory point and the corrected distance corresponding to the first trajectory point (recorded as the distance difference) is calculated, and the difference between the time corresponding to the second trajectory point and the time corresponding to the first trajectory point (recorded as the time difference) is calculated, and then the ratio between the distance difference and the time difference is calculated, and the ratio is determined as the corrected speed corresponding to the current trajectory point.

[0134] In the embodiment of the present application, the correction speed is determined based on the information of the first trajectory point and the second trajectory point, so that the smoothness of the correction speed can be maintained, the discomfort caused by the sudden change of speed can be avoided, and the rationality of the target predicted trajectory can be improved; and the accuracy of determining the correction speed is improved, which provides data support for the subsequent determination of the target predicted trajectory, thereby improving the accuracy of the target predicted trajectory.

[0135] Sa3. When the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, the correction speed corresponding to the current trajectory point is determined according to the second speed of the preceding vehicle at the interactive trajectory point.

[0136] Specifically, when the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, it indicates that the current trajectory point is the trajectory point after the surrounding vehicles enter the interactive area, and the deceleration of the surrounding vehicles has been predicted before entering the interactive area. Therefore, the surrounding vehicles have maintained a safe distance with the leading vehicle when arriving at the interactive trajectory point, and there is no need to continue to decelerate. Therefore, the second speed of the leading vehicle at the interactive trajectory point can be directly determined as the corrected speed corresponding to the current trajectory point.

[0137] Afterwards, other trajectory points can be selected from the trajectory points except the trajectory starting point as the current trajectory point, and Sa1-Sa3 can be repeatedly executed to obtain the corrected speed corresponding to each trajectory point.

[0138] Exemplarily, the intermediate predicted trajectory is {trajectory starting point, intermediate point 1, intermediate point 2, intermediate point 3, trajectory end point}, the distance corresponding to each trajectory point in the intermediate predicted trajectory is {0, 2, 4, 6, 8}, the unit of distance is meter (m), the corrected distance corresponding to each trajectory point in the intermediate predicted trajectory is {0, 1, 2, 3, 4}, the time corresponding to each trajectory point in the intermediate predicted trajectory is {0, 0.1, 0.2, 0.3, 0.4}, and the unit of time is second (s). If the interactive trajectory point is intermediate point 3, and the second speed of the front vehicle at the interactive trajectory point is 20m / s, then the distance corresponding to intermediate point 1 (i.e. 2m) and the distance corresponding to intermediate point 2 (i.e. 4m) are less than the distance corresponding to the interactive trajectory point (i.e. 6m), and the distance corresponding to intermediate point 3 (i.e. 6m) and the distance corresponding to the trajectory end point (i.e. 8m) are not less than the distance corresponding to the interactive trajectory point (i.e. 6m).

[0139] When the first preset distance is 2m and the second preset distance is 2m, the process of determining the corrected speed corresponding to the intermediate point 1 can be: the first trajectory point can be determined as the starting point of the trajectory, the second trajectory point can be determined as the intermediate point 2, and then the distance difference can be determined to be 4m (i.e. 4-0), and the time difference can be determined to be 0.2s (i.e. 0.2-0), and then the corrected speed corresponding to the intermediate point 1 can be determined to be 20m / s; the process of determining the corrected speed corresponding to the intermediate point 2 can be: the first trajectory point can be determined as the intermediate point 1, the second trajectory point can be determined as the intermediate point 3, and then the distance difference can be determined to be 4m (i.e. 6-2), and the time difference can be determined to be 0.2s (i.e. 0.3-0.1), and then the corrected speed corresponding to the intermediate point 2 can be determined to be 20m / s; the corrected speed corresponding to the intermediate point 3 is the second speed of the preceding vehicle at the interactive trajectory point, i.e. 20m / s; the corrected speed corresponding to the end point of the trajectory is the second speed of the preceding vehicle at the interactive trajectory point, i.e. 20m / s.

[0140] In an embodiment of the present application, when the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point, the correction speed is determined according to the correction distance, so that the speed corresponding to the trajectory point before entering the interactive area can be appropriately reduced, and a safe distance between the surrounding vehicles and the vehicle in front can be maintained, thereby effectively avoiding the occurrence of a collision; when the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, the correction speed is determined according to the second speed, so that the speed corresponding to the trajectory point after entering the interactive area can be closer to the speed of the actual traffic flow; by reasonably adjusting the correction speed under different distance conditions, the accuracy of determining the correction speed is improved, thereby improving the rationality and accuracy of the target prediction trajectory.

[0141] S608: Determine the target predicted trajectory according to the corrected distance corresponding to each trajectory point and the corrected speed corresponding to each trajectory point.

[0142] Specifically, after obtaining the corrected speed corresponding to each trajectory point, the corrected distance corresponding to each trajectory point and the corrected speed corresponding to each trajectory point can be combined with the time and driving direction corresponding to each trajectory point in the intermediate predicted trajectory to reconstruct the target predicted trajectory of the surrounding vehicles. After that, S610 can be executed.

[0143] For example, Figure 7 As shown, Figure 7 The orange curve in f is the target prediction trajectory obtained after speed optimization of the intermediate prediction trajectory. When the surrounding vehicles travel according to the target prediction trajectory, there is no interaction trajectory point between the surrounding vehicles and the front vehicle.

[0144] S609: When the first speed is not greater than the second speed, determine the intermediate predicted trajectory as the target predicted trajectory.

[0145] Specifically, when the first speed is not greater than the second speed, it indicates that there is no collision risk between the surrounding vehicles and the preceding vehicle, and there is no need to optimize the speed of the intermediate predicted trajectory. In this case, the intermediate predicted trajectory can be directly determined as the target predicted trajectory. Then, S610 can be executed.

[0146] S610: Obtain the starting speed of the surrounding vehicles at the starting point of the trajectory, and determine the target distance and target time of the target trajectory point in the target predicted trajectory.

[0147] The starting speed is the speed of the surrounding vehicles at the current moment, that is, the speed of the surrounding vehicles at the starting point of the trajectory.

[0148] The target trajectory point is a trajectory point randomly selected from multiple trajectory points of the target predicted trajectory, and the target trajectory point is not the trajectory starting point of the target predicted trajectory; the target distance is the corrected distance corresponding to the target trajectory point, that is, the distance between the target trajectory point and the trajectory starting point; the target time is the time required for the surrounding vehicles to travel from the trajectory starting point to the target trajectory point, that is, the time corresponding to the target trajectory point in the target predicted trajectory.

[0149] Specifically, after obtaining the target predicted trajectory, the current speed of the surrounding vehicles can be collected in real time using the sensors of the current vehicle (such as cameras, lidars, and millimeter-wave radars, etc.) to obtain the starting speed of the surrounding vehicles at the starting point of the trajectory; then, a trajectory point other than the starting point of the trajectory can be randomly selected from multiple trajectory points of the target predicted trajectory as the target trajectory point, and then the distance corresponding to the target trajectory point (i.e., the corrected distance) and the time corresponding to the target trajectory point are obtained from the target predicted trajectory, and the distance corresponding to the target trajectory point is determined as the target distance, and the time corresponding to the target trajectory point is determined as the target time.

[0150] S611, calculating the distance that the surrounding vehicles travel from the starting point of the trajectory at the starting point speed for the target time to obtain a predetermined distance.

[0151] The predetermined distance is the distance that the surrounding vehicles travel at a constant speed at the starting speed within the target time.

[0152] Specifically, after obtaining the starting speed, the target distance, and the target time, the product of the starting speed and the target time may be calculated, and the product may be determined as the predetermined distance.

[0153] S612: Determine the longitudinal intention of surrounding vehicles according to the target distance and the predetermined distance.

[0154] The longitudinal intention is the driving intention of the surrounding vehicles in the longitudinal direction (ie, the driving direction).

[0155] Specifically, after obtaining the predetermined distance, the size relationship between the target distance and the predetermined distance can be determined, and the longitudinal intention of the surrounding vehicles can be determined based on the size relationship, that is, when the target distance is greater than the sum of the predetermined distance and the set threshold, the longitudinal intention of the surrounding vehicles is determined to be acceleration; when the target distance is less than the sum of the predetermined distance and the set threshold, the longitudinal intention of the surrounding vehicles is determined to be deceleration; when the target distance is equal to the sum of the predetermined distance and the set threshold, the longitudinal intention of the surrounding vehicles is determined to be uniform speed. Wherein, the set threshold is a pre-set value used to characterize the safety distance or buffer distance, which can provide additional considerations when judging the longitudinal intention of the surrounding vehicles. The user can adjust and set it according to the actual use situation, and the embodiment of the present application does not specifically limit this. In the embodiment of the present application, the set threshold provides a fault-tolerant mechanism, which can still make relatively accurate judgments in the face of slight changes in vehicle speed, measurement errors or changes in road conditions, thereby ensuring the accuracy and reliability of the longitudinal intention; by adjusting the size of the set threshold, the sensitivity and robustness of the judgment can be balanced to adapt to different application scenarios and needs.

[0156] Optionally, after determining the longitudinal intention, the vehicle controller of the current vehicle can determine the control strategy of the current vehicle based on the longitudinal intention of the surrounding vehicles to make decisions and plans for the vehicle.

[0157] In the technical solution provided by the embodiment of the present application, the interaction trajectory point between the surrounding vehicles and the front vehicle can be determined based on the intermediate predicted trajectory, and then the first speed of the surrounding vehicles at the interaction trajectory point is obtained, and the second speed of the front vehicle at the interaction trajectory point is obtained. Then, when the first speed is greater than the second speed, the interaction trajectory point is moved by a preset distance in the direction of the trajectory starting point to obtain an optimized trajectory point, which can ensure that a sufficient safety distance is maintained between the surrounding vehicles and the front vehicle, effectively avoiding the collision between the surrounding vehicles and the front vehicle, and providing data support for the subsequent determination of the trajectory contraction ratio, thereby improving the rationality and accuracy of speed optimization; then, the trajectory contraction ratio can be determined according to the interaction trajectory point and the optimized trajectory point, and the distance corresponding to each trajectory point is proportionally contracted based on the trajectory contraction ratio to obtain the corrected distance corresponding to each trajectory point, and then the speed corresponding to each trajectory point is optimized to obtain the corrected speed corresponding to each trajectory point, and the target predicted trajectory is determined according to the corrected distance corresponding to each trajectory point and the corrected speed corresponding to each trajectory point. By optimizing the distance and speed corresponding to each trajectory point, the target predicted trajectory is closer to the actual driving situation, thereby improving the accuracy and rationality of the target predicted trajectory, thereby improving the driving safety of the autonomous driving vehicle.

[0158] Afterwards, the starting speed of the surrounding vehicles at the starting point of the trajectory is obtained, and the target distance and target time of the target trajectory point in the target predicted trajectory are determined. Then, the distance traveled by the surrounding vehicles from the starting point of the trajectory for the target time at the starting speed is calculated to obtain the predetermined distance, and the longitudinal intention of the surrounding vehicles is determined based on the target distance and the predetermined distance, thereby realizing the function of determining the longitudinal intention. Through the relationship between the target distance and the predetermined distance, the driving intention of the surrounding vehicles in the driving direction can be accurately judged, thereby improving the accuracy and efficiency of determining the longitudinal intention; and, the autonomous driving vehicle can adjust its own driving strategy according to the longitudinal intention, and make safe driving decisions such as avoidance and deceleration in advance, thereby reducing the risk of traffic accidents, thereby improving the driving safety of the autonomous driving vehicle.

[0159] Figure 8 is a schematic diagram of a structure of a device for optimizing the predicted trajectory of surrounding vehicles provided in an embodiment of the present application, with reference to Figure 8 , the prediction trajectory optimization device for surrounding vehicles may include:

[0160] A lane determination module 810 is used to obtain an initial predicted trajectory of vehicles around the current vehicle, and determine a starting lane corresponding to a trajectory starting point of the initial predicted trajectory and an ending lane corresponding to an ending point of the trajectory;

[0161] A direction optimization module 820 is used to determine an optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane, and to optimize the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory;

[0162] A preceding vehicle determination module 830, for determining a preceding vehicle of surrounding vehicles according to an intermediate predicted trajectory;

[0163] A trajectory point optimization module 840 is used to determine the interaction trajectory points between the surrounding vehicles and the preceding vehicle based on the intermediate predicted trajectory, and to move the interaction trajectory points to obtain optimized trajectory points of the interaction trajectory points;

[0164] The speed optimization module 850 is used to optimize the speed of the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles.

[0165] In one embodiment, the predicted trajectory optimization device for surrounding vehicles also includes a continuous lane change optimization module, which is specifically used to: determine the lane change situation according to the position of the starting lane and the position of the terminal lane before determining the optimized lane of the terminal lane according to the position of the starting lane and the position of the terminal lane; when the lane change situation is a continuous lane change, trigger the execution of determining the optimized lane of the terminal lane according to the position of the starting lane and the position of the terminal lane.

[0166] In one embodiment, the predicted trajectory optimization device for surrounding vehicles also includes a lane change optimization module, which is specifically used to: after determining the lane change situation according to the position of the starting lane and the position of the end lane, when the lane change situation is no lane change, determine the middle point lane corresponding to the middle point of the trajectory of the initial predicted trajectory; when the middle point lane and the starting lane are not the same lane, optimize the direction of the initial predicted trajectory according to the starting lane and the end lane to obtain an intermediate predicted trajectory; the lanes corresponding to each trajectory point in the intermediate predicted trajectory are the same as the starting lane.

[0167] In one embodiment, the direction optimization module 820 determines the optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane, including: determining the lane change direction according to the position of the starting lane and the position of the destination lane; determining the adjacent lane of the starting lane based on the lane change direction, and determining the adjacent lane as the optimized lane; correspondingly, the lane corresponding to the destination in the intermediate predicted trajectory is the optimized lane.

[0168] In one embodiment, the predicted trajectory optimization device for surrounding vehicles also includes a collision optimization module, which is specifically used to: before moving the interaction trajectory point to obtain the optimized trajectory point of the interaction trajectory point, obtain the first speed of the surrounding vehicles at the interaction trajectory point, and obtain the second speed of the front vehicle at the interaction trajectory point; when the first speed is greater than the second speed, trigger the execution of moving the interaction trajectory point to obtain the optimized trajectory point of the interaction trajectory point.

[0169] In one embodiment, the trajectory point optimization module 840 moves the interactive trajectory point to obtain the optimized trajectory point of the interactive trajectory point, including: moving the interactive trajectory point toward the trajectory starting point by a preset distance to obtain the optimized trajectory point.

[0170] In one embodiment, the speed optimization module 850 performs speed optimization on the intermediate predicted trajectory based on the optimized trajectory points to obtain the target predicted trajectory of the surrounding vehicles, including: determining the trajectory shrinkage ratio according to the interactive trajectory points and the optimized trajectory points; and performing speed optimization on each trajectory point in the intermediate predicted trajectory based on the trajectory shrinkage ratio to obtain the target predicted trajectory of the surrounding vehicles, wherein each trajectory point does not include the trajectory starting point.

[0171] In one embodiment, the speed optimization module 850 optimizes the speed of each trajectory point in the intermediate predicted trajectory based on the trajectory contraction ratio to obtain the target predicted trajectory of the surrounding vehicles, including: proportionally contracting the distance corresponding to each trajectory point based on the trajectory contraction ratio to obtain the corrected distance corresponding to each trajectory point, where the distance corresponding to each trajectory point is the distance between each trajectory point and the starting point of the trajectory; optimizing the speed corresponding to each trajectory point to obtain the corrected speed corresponding to each trajectory point; and determining the target predicted trajectory according to the corrected distance corresponding to each trajectory point and the corrected speed corresponding to each trajectory point.

[0172] In one embodiment, the speed optimization module 850 optimizes the speed corresponding to each trajectory point respectively to obtain the corrected speed corresponding to each trajectory point, including: for each trajectory point, when the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point, the corrected speed corresponding to the current trajectory point is determined according to the corrected distance corresponding to each trajectory point; when the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, the corrected speed corresponding to the current trajectory point is determined according to the second speed of the preceding vehicle at the interactive trajectory point.

[0173] In one embodiment, the speed optimization module 850 determines the corrected speed corresponding to the current trajectory point according to the corrected distance corresponding to each trajectory point, including: selecting a trajectory point corresponding to a first preset distance from the current trajectory point to the trajectory starting point to obtain a first trajectory point; selecting a trajectory point corresponding to a second preset distance from the current trajectory point to the trajectory end point to obtain a second trajectory point; determining the corrected speed corresponding to the current trajectory point according to the corrected distance corresponding to the first trajectory point, the time corresponding to the first trajectory point, the corrected distance corresponding to the second trajectory point, and the time corresponding to the second trajectory point, the time corresponding to the first trajectory point is the time required for surrounding vehicles to travel from the trajectory starting point to the first trajectory point, and the time corresponding to the second trajectory point is the time required for surrounding vehicles to travel from the trajectory starting point to the second trajectory point.

[0174] In one embodiment, the predicted trajectory optimization device for surrounding vehicles also includes an intention determination module, which is specifically used to: obtain the starting speed of the surrounding vehicles at the starting point of the trajectory, and determine the target distance and target time of the target trajectory point in the target predicted trajectory, the target distance is the corrected distance corresponding to the target trajectory point, and the target time is the time required for the surrounding vehicles to travel from the starting point of the trajectory to the target trajectory point; calculate the distance that the surrounding vehicles travel from the starting point of the trajectory at the starting speed for the target time to obtain the predetermined distance; determine the longitudinal intention of the surrounding vehicles based on the target distance and the predetermined distance.

[0175] In one embodiment, the intention determination module determines the longitudinal intention of the surrounding vehicles based on the target distance and the predetermined distance, including: when the target distance is greater than the sum of the predetermined distance and a set threshold, determining that the longitudinal intention of the surrounding vehicles is acceleration; when the target distance is less than the sum of the predetermined distance and the set threshold, determining that the longitudinal intention of the surrounding vehicles is deceleration; when the target distance is equal to the sum of the predetermined distance and the set threshold, determining that the longitudinal intention of the surrounding vehicles is a constant speed.

[0176] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0177] The device for optimizing the predicted trajectories of surrounding vehicles provided in this embodiment can be applied to the method for optimizing the predicted trajectories of surrounding vehicles provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0178] Fig. 9 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. Fig. 9 A block diagram of an exemplary vehicle 11 suitable for implementing embodiments of the present application is shown. Fig. 9 The vehicle 11 shown is merely an example and should not bring any limitation to the function and scope of use of the present embodiment.

[0179] like Fig. 9 As shown, the vehicle 11 is embodied in the form of a general purpose computing electronic device. The components of the vehicle 11 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting various system components (including the system memory 28 and the processing unit 16).

[0180] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0181] The vehicle 11 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the vehicle 11, including volatile and non-volatile media, removable and non-removable media.

[0182] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The vehicle 11 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Fig. 9not shown, usually called a "hard drive"). Although Fig. 9 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical medium) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present application.

[0183] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0184] The vehicle 11 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the vehicle 11, and / or any device that enables the vehicle 11 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the vehicle 11 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20.

[0185] like Fig. 9 As shown, the network adapter 20 communicates with other modules of the vehicle 11 via the bus 18. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the vehicle 11, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0186] The processing unit 16 executes various functional applications and page displays by running the programs stored in the system memory 28, such as implementing a method for optimizing the predicted trajectories of surrounding vehicles provided in any embodiment of the present application.

[0187] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a method for optimizing the predicted trajectories of surrounding vehicles, for example, is implemented in any embodiment of the present application.

[0188] The computer storage medium of this embodiment can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0189] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0190] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0191] Computer program code for performing the operation of the present application can be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0192] It should be understood by those skilled in the art that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0193] In addition, the acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0194] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the inventive concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for optimizing the predicted trajectory of surrounding vehicles, characterized in that: The method comprises: Obtaining an initial predicted trajectory of vehicles around the current vehicle, and determining a starting lane corresponding to a trajectory starting point and an ending lane corresponding to an ending point of the initial predicted trajectory; Determining an optimized lane of the end lane according to the position of the starting lane and the position of the end lane, and optimizing the direction of the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory; Determining a preceding vehicle of the surrounding vehicles according to the intermediate predicted trajectory; Determining the interaction trajectory points between the surrounding vehicles and the front vehicle based on the intermediate predicted trajectory, and moving the interaction trajectory points to obtain optimized trajectory points of the interaction trajectory points; The intermediate predicted trajectory is speed optimized based on the optimized trajectory points to obtain a target predicted trajectory of the surrounding vehicles.

2. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 1, characterized in that: Before determining the optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane, the method further includes: Determining a lane change situation according to the position of the starting lane and the position of the end lane; When the lane change situation is a continuous lane change, the step of determining the optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane is triggered.

3. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 2, characterized in that: After determining the lane change situation according to the position of the starting lane and the position of the end lane, the method further includes: When the lane change condition is no lane change, determining a middle point lane corresponding to the middle point of the trajectory of the initial predicted trajectory; When the intermediate point lane is not the same lane as the starting lane, the initial predicted trajectory is direction-optimized according to the starting lane and the end lane to obtain the intermediate predicted trajectory; the lanes corresponding to the trajectory points in the intermediate predicted trajectory are the same as the starting lane.

4. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 2, characterized in that: The step of determining the optimized lane of the destination lane according to the position of the starting lane and the position of the destination lane comprises: Determining a lane change direction according to the position of the starting lane and the position of the end lane; Determine an adjacent lane of the starting lane based on the lane change direction, and determine the adjacent lane as the optimized lane; Correspondingly, the lane corresponding to the end point in the intermediate predicted trajectory is the optimized lane.

5. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 1, characterized in that: Before moving the interactive trajectory point to obtain the optimized trajectory point of the interactive trajectory point, the method further includes: Acquire a first speed of the surrounding vehicles at the interaction trajectory point, and acquire a second speed of the leading vehicle at the interaction trajectory point; When the first speed is greater than the second speed, the step of moving the interaction trajectory point to obtain an optimized trajectory point of the interaction trajectory point is triggered.

6. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 5, characterized in that: The moving the interaction trajectory point to obtain the optimized trajectory point of the interaction trajectory point includes: The interactive trajectory point is moved toward the trajectory starting point by a preset distance to obtain the optimized trajectory point.

7. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 5 or 6, characterized in that: The step of performing speed optimization on the intermediate predicted trajectory based on the optimized trajectory point to obtain the target predicted trajectory of the surrounding vehicles includes: Determining a trajectory contraction ratio according to the interactive trajectory points and the optimized trajectory points; Based on the trajectory contraction ratio, speed optimization is performed on each trajectory point in the intermediate predicted trajectory to obtain a target predicted trajectory of the surrounding vehicles, wherein each trajectory point does not include the trajectory starting point.

8. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 7, characterized in that: The step of optimizing the speed of each trajectory point in the intermediate predicted trajectory based on the trajectory contraction ratio to obtain the target predicted trajectory of the surrounding vehicles includes: Based on the trajectory contraction ratio, the distance corresponding to each trajectory point is contracted in equal proportion to obtain a corrected distance corresponding to each trajectory point, where the distance corresponding to each trajectory point is the distance between each trajectory point and the trajectory starting point; Optimizing the speed corresponding to each trajectory point respectively to obtain the corrected speed corresponding to each trajectory point; The target predicted trajectory is determined according to the corrected distance corresponding to each trajectory point and the corrected speed corresponding to each trajectory point.

9. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 8, characterized in that: The respectively optimizing the speed corresponding to each trajectory point to obtain the corrected speed corresponding to each trajectory point includes: For each of the trajectory points, when the distance corresponding to the current trajectory point is less than the distance corresponding to the interactive trajectory point, determining a correction speed corresponding to the current trajectory point according to the correction distance corresponding to each of the trajectory points; When the distance corresponding to the current trajectory point is not less than the distance corresponding to the interactive trajectory point, the corrected speed corresponding to the current trajectory point is determined according to the second speed of the preceding vehicle at the interactive trajectory point.

10. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 9, characterized in that: The determining the correction speed corresponding to the current trajectory point according to the correction distance corresponding to each trajectory point includes: Selecting a trajectory point corresponding to a first preset distance from the current trajectory point to the trajectory starting point to obtain a first trajectory point; Selecting a trajectory point corresponding to a second preset distance from the current trajectory point to the trajectory end point direction to obtain a second trajectory point; The corrected speed corresponding to the current trajectory point is determined according to the corrected distance corresponding to the first trajectory point, the time corresponding to the first trajectory point, the corrected distance corresponding to the second trajectory point, and the time corresponding to the second trajectory point, the time corresponding to the first trajectory point being the time required for the surrounding vehicles to travel from the starting point of the trajectory to the first trajectory point, and the time corresponding to the second trajectory point being the time required for the surrounding vehicles to travel from the starting point of the trajectory to the second trajectory point.

11. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 8, characterized in that: The method further comprises: Obtain the starting speed of the surrounding vehicles at the starting point of the trajectory, and determine the target distance and target time of the target trajectory point in the target predicted trajectory, wherein the target distance is the corrected distance corresponding to the target trajectory point, and the target time is the time required for the surrounding vehicles to travel from the starting point of the trajectory to the target trajectory point; Calculate the distance that the surrounding vehicles travel from the starting point of the trajectory at the starting point speed for the target time to obtain a predetermined distance; The longitudinal intention of the surrounding vehicles is determined based on the target distance and the predetermined distance.

12. The method for optimizing the predicted trajectory of surrounding vehicles according to claim 11, characterized in that: The determining the longitudinal intention of the surrounding vehicles according to the target distance and the predetermined distance comprises: When the target distance is greater than the sum of the predetermined distance and a set threshold, determining that the longitudinal intention of the surrounding vehicle is acceleration; When the target distance is less than the sum of the predetermined distance and a set threshold, determining that the longitudinal intention of the surrounding vehicle is to decelerate; When the target distance is equal to the sum of the predetermined distance and a set threshold, it is determined that the longitudinal intention of the surrounding vehicles is a uniform speed.

13. A device for optimizing the predicted trajectory of surrounding vehicles, characterized in that: The device comprises: A lane determination module is used to obtain an initial predicted trajectory of vehicles around the current vehicle, and determine a starting lane corresponding to a trajectory starting point of the initial predicted trajectory and an ending lane corresponding to an ending point of the trajectory; a direction optimization module, used for determining an optimized lane of the end lane according to the position of the starting lane and the position of the end lane, and performing direction optimization on the initial predicted trajectory according to the starting lane and the optimized lane to obtain an intermediate predicted trajectory; A preceding vehicle determining module, configured to determine a preceding vehicle of the surrounding vehicles according to the intermediate predicted trajectory; A trajectory point optimization module, used to determine the interactive trajectory points between the surrounding vehicles and the front vehicle based on the intermediate predicted trajectory, and move the interactive trajectory points to obtain optimized trajectory points of the interactive trajectory points; A speed optimization module is used to optimize the speed of the intermediate predicted trajectory based on the optimized trajectory point to obtain the target predicted trajectory of the surrounding vehicles.

14. A vehicle, characterized in that: The vehicle comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for optimizing the predicted trajectories of surrounding vehicles as described in any one of claims 1 to 12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for optimizing the predicted trajectories of surrounding vehicles as claimed in any one of claims 1 to 12 is implemented.

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