Vehicle control method, device, equipment and storage medium

Abstract

The present application discloses a vehicle control method, apparatus, device, and storage medium. The method includes: obtaining driving data and road detection data corresponding to a target vehicle; determining driving intention information and adjustment distance information corresponding to the target vehicle based on the driving data and road detection data; generating a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is used to adjust the driving speed of the target vehicle; generating a second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle. By setting the above-mentioned distinguishing technical features, it is possible to improve adaptability to dynamic road environments while ensuring the safety of vehicle driving control.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and specifically to a vehicle control method, device, equipment, and storage medium. Background Art

[0002] With the acceleration of urbanization and the surge in car ownership, the proportion of traffic accidents at intersections has increased significantly. Intersections, characterized by diverse participants, complex traffic flows, and non-standardized structures, place higher demands on the perception, decision-making, and control capabilities of driver assistance systems.

[0003] In related technologies, advanced driver assistance systems mainly rely on structured road elements for perception. When faced with unstructured intersection environments such as multi-directional traffic flow, temporary construction or blurred signs, the perception ability is significantly reduced, making it difficult to accurately identify the types, behaviors and relative dynamic relationships of traffic participants, which in turn leads to the risk of collision during vehicle movement and low safety of assisted driving. Summary of the Invention

[0004] The technical problem to be solved by this application is how to improve the adaptability to dynamic road environments while ensuring the safety of vehicle driving control.

[0005] In order to solve at least one of the technical problems raised above, the present application discloses a vehicle control method, device, equipment and storage medium.

[0006] According to one aspect of the present application, a vehicle control method is provided, comprising:

[0007] Obtain driving data and road detection data corresponding to the target vehicle;

[0008] Determine the target vehicle's driving intention information and adjust the distance information based on the driving data and road detection data;

[0009] generating a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is used to adjust the driving speed of the target vehicle;

[0010] A second control instruction is generated based on the driving data, the driving intention information, the first control instruction, and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle.

[0011] Optionally, the driving data includes driving direction and vehicle position data, and the road detection data includes lane line information; determining driving intention information and adjustment distance information corresponding to the target vehicle based on the driving data and the road detection data includes:

[0012] Based on the driving direction and lane line information, the road environment is detected to obtain the road detection results;

[0013] When the road detection result indicates that the current road environment includes at least one intersection, calculating angle data between the driving direction and the at least one intersection to determine driving intention information;

[0014] Based on the vehicle position data and lane line information, the adjustment distance information is determined.

[0015] Optionally, the driving data further includes vehicle speed data; and generating a first control instruction based on the driving intention information and the adjustment distance information includes:

[0016] Determining a driving speed limit based on driving intention information and adjustment distance information;

[0017] A first control command is generated based on the vehicle speed data and the travel speed limit.

[0018] Optionally, the road detection data also includes environmental information;

[0019] The method also includes:

[0020] Adjusting the driving limit speed based on environmental information to obtain a compensated driving limit speed;

[0021] A first control command is generated based on the vehicle speed data and the compensated traveling limit speed.

[0022] Optionally, the driving data includes driving direction and vehicle position data, and the road detection data also includes detection objects and position information and motion information corresponding to the detection objects;

[0023] Generating a second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data includes:

[0024] determining a first motion trajectory of the detected object based on the position information and motion information of the detected object;

[0025] determining an adjusted driving speed corresponding to the target vehicle based on the first control instruction;

[0026] determining a second motion trajectory corresponding to the target vehicle based on the adjusted driving speed, driving direction, vehicle position data, and driving intention information;

[0027] A second control instruction is generated based on the first motion trajectory and the second motion trajectory.

[0028] Optionally, generating a second control instruction based on the first motion trajectory and the second motion trajectory includes:

[0029] Performing a trajectory intersection analysis based on the first motion trajectory and the second motion trajectory to obtain a trajectory intersection result;

[0030] The virtual wall trigger condition is obtained and combined with the track intersection result to generate the second control instruction.

[0031] Optionally, the method further comprises:

[0032] determining a virtual wall duration and a trajectory intersection point based on the trajectory intersection result;

[0033] After the virtual wall duration has elapsed and / or the detected object has passed the track intersection, a third control instruction is generated, and the third control instruction is used to restore the driving authority of the target vehicle.

[0034] Optionally, determining a second motion trajectory corresponding to the target vehicle based on adjusting the driving speed, driving direction, vehicle position data, and driving intention information includes:

[0035] Determine multiple sets of candidate motion trajectories corresponding to the target vehicle based on the adjusted driving speed, driving direction, vehicle position data, and driving intention information;

[0036] Weighted processing is performed on multiple groups of candidate motion trajectories to obtain a second motion trajectory.

[0037] According to a second aspect of the present application, there is provided a vehicle control device, comprising:

[0038] A data acquisition module is used to obtain driving data and road detection data corresponding to the target vehicle;

[0039] A data calculation module is used to determine the driving intention information corresponding to the target vehicle and adjust the distance information based on the driving data and road detection data;

[0040] A first instruction generating module is configured to generate a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is configured to adjust the driving speed of the target vehicle;

[0041] The second instruction generation module is used to generate a second control instruction based on the driving data, the driving intention information, the first control instruction and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle.

[0042] According to the third aspect of the present application, an electronic device is provided, which includes a processor and a memory, wherein the memory stores at least one instruction and at least one program, and the at least one instruction and at least one program are loaded and executed by the processor to implement any of the above vehicle control methods.

[0043] According to a fourth aspect of the present application, a computer storage medium is provided, in which at least one instruction and at least one program are stored. The at least one instruction and at least one program are loaded and executed by a processor to implement any of the above vehicle control methods.

[0044] According to a fifth aspect of the present application, a computer program product is provided, comprising a computer program / instruction, which implements any of the above vehicle control methods when the computer program / instruction is executed by a processor.

[0045] The vehicle control method of the present application obtains the target vehicle's driving data and road detection data to achieve comprehensive perception of the target vehicle's current driving status and surrounding road environment. Furthermore, based on the above data, the target vehicle's driving intention information and adjustment distance information are determined, and a first control instruction is generated to dynamically adjust the target vehicle's driving speed, thereby improving the vehicle's adaptability and safety in complex traffic scenarios. At the same time, a second control instruction is generated by integrating the driving data, driving intention information, the first control instruction, and the road detection data to adjust the target vehicle's driving authority, achieving intelligent decision-making on the vehicle's passable status. This can enhance the responsiveness to dynamic road environments while ensuring driving safety.

[0046] Other features and advantages of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0048] In order to more completely understand the present application and its beneficial effects, the following description will be given in conjunction with the accompanying drawings, wherein the same drawing numbers represent the same parts in the following description.

[0049] Figure 1 A schematic flow chart corresponding to a vehicle control method provided by an exemplary embodiment of the present application;

[0050] Figure 2 Determine a corresponding flow chart for the information provided by the exemplary embodiments of this application;

[0051] Figure 3 A schematic diagram of a corresponding flow chart for generating a second control instruction provided in an exemplary embodiment of the present application;

[0052] Figure 4A schematic diagram of a corresponding flow chart for generating a third control instruction provided in an exemplary embodiment of the present application;

[0053] Figure 5 A schematic structural diagram corresponding to the vehicle control method provided in the exemplary embodiment of the present application. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0055] It should be noted that the terms "first", "second", etc. 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 those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0056] Various exemplary embodiments, features, and aspects of the present application will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0057] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0058] The term "and / or" as used herein describes an association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can represent the existence of A alone, the simultaneous existence of A and B, and the existence of B alone. Furthermore, the term "at least one" as used herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0059] In addition, numerous specific details are provided in the following detailed description to better illustrate the present application. Those skilled in the art will appreciate that the present application can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present application.

[0060] Figure 1 This is a flow chart of the vehicle control method provided by the exemplary embodiment of the present application. The execution subject can be any terminal that can execute the vehicle control method, such as a body processor, a server, etc., and can be applied to the assisted driving scenario of the target vehicle. Figure 1 As shown, the vehicle control method includes:

[0061] Step S101: Acquire driving data and road detection data corresponding to the target vehicle.

[0062] In some embodiments, the target vehicle is the target vehicle. The target vehicle may be equipped with a body processor capable of executing the vehicle control method described in the embodiments of the present application, and a laser radar capable of detecting road detection data. The driving data may include at least vehicle position data, driving direction, vehicle speed data, etc. The road detection data may include at least lane line data within the preset detection range of the target vehicle, as well as multiple detection objects and their corresponding position information and motion information. The preset detection range may be determined based on the detection performance of the laser radar and the road detection requirements. The multiple detection objects may include at least pedestrians, motor vehicles and non-motor vehicles within the preset detection range.

[0063] In some embodiments, since the driving data corresponds to the target vehicle and the road detection data can correspond to multiple detection objects and lane line information, etc., the driving data and road detection data can be mapped so that the two are unified in the same coordinate system, thereby enhancing the comparability of the data and improving the accuracy of subsequent vehicle control.

[0064] Step S102: Based on the driving data and the road detection data, the driving intention information and the adjustment distance information corresponding to the target vehicle are determined.

[0065] In some embodiments, driving intention information may include straight driving and turning, such as left turns, right turns, and U-turns. Lane information may include stop lines, their corresponding position data, and intersection polygon feature information. Adjustment distance information may be the distance between the target vehicle and the stop line. Lane information may be obtained through lidar detection or provided by the navigation system on the target vehicle. By determining driving intention information and adjustment distance information, it is possible to determine whether the target vehicle's speed needs to be adjusted, thereby improving driving safety.

[0066] like Figure 2 As shown, step S102 may include:

[0067] Step S201: Based on the driving direction and lane line information, perform road environment detection to obtain a road detection result.

[0068] Step S202: When the road detection result indicates that the current road environment includes at least one intersection, angle data between the driving direction and the at least one intersection is calculated to determine driving intention information.

[0069] Step S203: Determine and adjust distance information based on the vehicle position data and lane line information.

[0070] In some embodiments, road environment detection is used to determine whether the target vehicle's current road environment includes an intersection. By verifying the position of the stop line and the target vehicle, and checking the topological connectivity between the stop line and the intersection, the reliability of road environment recognition can be improved. If an intersection is included, driving intention information and adjustment distance information are required to determine whether the target vehicle's speed needs to be adjusted.

[0071] Specifically, the driving direction refers to the vehicle's forward direction. By verifying the perpendicular relationship between the driving direction and the stop line, and if a valid stop line is detected within 150 meters of the vehicle's forward direction, the system then determines whether the current road environment includes an intersection based on the intersection polygon feature information. The number of intersections can be one or more. For example, for the target vehicle, the intersection environment includes three intersections, allowing for straight driving, left turns, right turns, and U-turns.

[0072] When there is an intersection, the angle between the vehicle's forward direction and the exit of each intersection is calculated, and the intersection with the smallest angle is determined as the intersection to be entered by the target vehicle. Based on the intersection to be entered, the driving intention information can be determined as one of going straight, turning left, turning right, and making a U-turn.

[0073] Furthermore, because the driving data and road detection data have already been processed and converted to the same coordinate system, projection can be used to combine the vehicle's position data with the stop line's position data to determine the actual distance between the target vehicle and the stop line. This information, called adjusted distance, improves the accuracy of distance determination. The accuracy of this adjusted distance information can reach ±0.5 meters on straight roads and ±1.2 meters on curves with a radius of curvature less than 100 meters.

[0074] In other embodiments, when the target vehicle uses navigation to plan its route while driving, the navigation will also indicate whether there is an intersection near the target vehicle, as well as navigation driving intention information corresponding to the target vehicle. The navigation driving intention information is the target vehicle's indication of whether the navigation-planned route indicates that it should go straight, turn left, turn right, or make a U-turn. The driving intention information can be cross-verified with the navigation driving intention information to determine whether the driving intention information determination and navigation driving intention information planning are accurate. The two can be combined to improve driving safety. When the vehicle driving intention indicated by the driving intention information is inconsistent with the vehicle driving intention indicated by the navigation driving intention information, the navigation driving intention information can be used as the basis, and a warning can be issued to the driver.

[0075] Step S103: generating a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is used to adjust the driving speed of the target vehicle.

[0076] In some embodiments, after determining the driving intention information and adjusting the distance information, it is necessary to adjust the driving speed of the target vehicle accordingly, that is, adjust the driving speed corresponding to the vehicle speed data. Specifically, step S103 may at least include:

[0077] A driving speed limit is determined based on the driving intention information and the adjustment distance information; and a first control instruction is generated based on the vehicle speed data and the driving speed limit.

[0078] In some embodiments, a one-to-many-to-many mapping relationship can be considered between driving intention information, adjusted distance information, and speed limits. That is, one piece of driving intention information can correspond to multiple pieces of adjusted distance information, and each piece of adjusted distance information corresponds to a speed limit. The first control instruction is used to instruct the target vehicle to adjust the speed corresponding to the vehicle speed data so that the target vehicle's speed is less than or equal to the speed limit. The first control instruction includes a valid range of ±5m to ensure the accuracy and adaptability of the speed adjustment.

[0079] For example, if the driving intention information indicates straight ahead and the adjusted distance information is between 50m and 100m, the speed limit can be 60km / h; if the adjusted distance information is between 30m and 50m, the speed limit can be 45km / h; if the adjusted distance information is less than 30m, the speed limit can be 30km / h. If the driving intention information indicates turning (including left turn, right turn, and U-turn), the adjusted distance information is between 40m and 80m, the speed limit can be 50km / h; if the adjusted distance information is between 20m and 40m, the speed limit can be 35km / h; if the adjusted distance information is less than 20m, the speed limit can be 25km / h.

[0080] In some embodiments, the ranges corresponding to the speed limit and the adjustment distance information can be adjusted according to different scenarios to improve the adaptability of vehicle control to different driving scenarios. For example, the position of the stop line can be used as the starting point and the position of the target vehicle as the end point to perform reverse trajectory deduction calculation to determine the speed limit. Specifically, with a step size of 0.1 seconds, according to v 2 =(v0 2 +2ax) formula to calculate the speed value corresponding to each trajectory point. Where x is the distance between the starting point and the end point, v is the driving speed limit, v0 is the driving speed corresponding to the vehicle speed data of the target vehicle, and the standard deceleration a is 0.3m / s 2 , can reach 0.6m / s in emergency 2 .

[0081] In other embodiments, if the driving speed corresponding to the vehicle speed data of the target vehicle is less than the driving speed limit, there is no need to adjust the driving speed of the target vehicle, and in this case, there is no need to generate the first control instruction.

[0082] In other embodiments, the method further includes: adjusting the driving speed limit based on the environmental information to obtain a compensated driving speed limit; and generating a first control instruction based on the vehicle speed data and the compensated driving speed limit.

[0083] Road detection data also includes environmental information. This information can include real-time weather and lighting conditions, such as sunny, rainy, or snowy, and normal, overly bright, or dim. Because weather and lighting conditions can affect driving safety, they can be factored into the speed limit to further improve driving safety.

[0084] For example, in rainy conditions, the compensatory driving limit speed can be reduced by 15% based on the driving limit speed; in dark environments (such as night driving environments), the compensatory driving limit speed can be reduced by 10% based on the driving limit speed.

[0085] The above process enables intersection scene recognition, ensuring accuracy while reducing computing resource usage. Furthermore, after determining the intersection scene, the system adjusts driving speed based on different driving intentions, employing a graded deceleration strategy that creates a smooth deceleration curve, aligns with driving habits, and ensures safety.

[0086] Step S104: generating a second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle.

[0087] In some embodiments, when the target vehicle's speed data is less than the driving speed limit or the compensated driving speed limit, a second control instruction is generated to adjust the target vehicle's driving authority. The driving authority is the target vehicle's passage authority and is used to instruct the target vehicle to brake or drive.

[0088] like Figure 3 As shown, step S104 may include:

[0089] Step S301: determining a first motion trajectory of the detection object based on the position information and motion information of the detection object.

[0090] Step S302: determining an adjusted driving speed corresponding to the target vehicle based on the first control instruction.

[0091] Step S303: Determine a second motion trajectory corresponding to the target vehicle based on the adjusted driving speed, driving direction, vehicle position data, and driving intention information.

[0092] Step S304: generating a second control instruction based on the first motion trajectory and the second motion trajectory.

[0093] In some embodiments, the first control instruction and the second control instruction can be considered to independently control the target vehicle, that is, the first control instruction is used to adjust the driving speed of the target vehicle, and the second control instruction is used to control the braking and driving of the target vehicle. Since the first control instruction can determine the adjusted driving speed of the target vehicle, and the second control instruction is generated based on the adjusted driving speed, it can also be considered that the second control instruction is determined based on the first control instruction. Here, the first control instruction plays the role of determining the adjusted driving speed. The adjusted driving speed, that is, the driving speed of the target vehicle after adjustment based on the first control instruction, can be less than or equal to the driving limit speed or the compensated driving limit speed.

[0094] In addition, if the target vehicle's driving speed corresponding to its vehicle speed data is less than or equal to the driving speed limit or the compensated driving speed limit before the driving speed is adjusted based on the first control instruction, the adjusted driving speed is the driving speed corresponding to the vehicle speed data.

[0095] In some embodiments, trajectory prediction is performed based on the position information and motion information of each detected object to obtain a first motion trajectory corresponding to each detected object. The first motion trajectory can be a motion trajectory within a certain period of time in the future, for example, the next 8 seconds. In addition, trajectory prediction is performed based on adjusting the driving speed, driving direction, vehicle position data, and driving intention information to obtain a second motion trajectory of the target vehicle. The second motion trajectory can be a motion trajectory within the next 5 seconds, with a resolution of 0.1 seconds. Specifically, based on the first motion trajectory and the second motion trajectory, a second control instruction is generated, including:

[0096] A trajectory intersection analysis is performed based on the first motion trajectory and the second motion trajectory to obtain a trajectory intersection result.

[0097] The virtual wall trigger condition is obtained and combined with the track intersection result to generate the second control instruction.

[0098] In some embodiments, the driving data and road detection data are unified in the same coordinate system, so the first and second motion trajectories are also located in the same coordinate system. Based on this shared coordinate system, the second motion trajectory can be temporally and spatially compared with the first motion trajectory corresponding to each detected object using an interactive analysis model of the spatiotemporal occupancy grid. The spatial overlap at each moment can be calculated to identify conflict points between the first and second motion trajectories. The conflict point detection algorithm can utilize an R-tree index structure, enabling real-time processing of trajectory intersection analysis for over 20 moving targets (i.e., the detected objects in this embodiment).

[0099] In some embodiments, the track intersection result represents information such as the track intersection point, overlapping area, and minimum distance between the first motion track and the second motion track. The virtual wall trigger condition may include any of the following conditions:

[0100] 1) The intersection area of ​​the tracks is larger than 0.5 square meters for 3 seconds;

[0101] 2) When the detection object is a pedestrian, the minimum distance between the second motion trajectory and the first motion trajectory corresponding to the pedestrian is less than 1.2 meters;

[0102] 3) There are two or more conflict points and the time interval is less than 2 seconds.

[0103] In some embodiments, when a virtual stop wall is generated based on a trajectory intersection, the generated second control instruction corresponds to the driving authority: braking the target vehicle at the virtual stop wall. A conservative strategy can be used to calculate the virtual stop wall's location. Specifically, the virtual stop wall's location can be determined 2 meters before the first trajectory intersection, or the 1.5-second braking distance calculated based on the target vehicle's current speed can be used as the virtual stop wall's location. The duration of the virtual stop wall is dynamically adjusted based on the motion trends of the target vehicle and each detected object, with a maximum duration not exceeding the remaining time of the current signal cycle.

[0104] Furthermore, if Figure 4 As shown, the method further includes:

[0105] Step S401: determining the virtual wall duration and the track intersection point based on the track intersection result;

[0106] Step S402: After the duration of the virtual wall has elapsed and / or the detection object has passed the track intersection, a third control instruction is generated, and the third control instruction is used to restore the driving authority of the target vehicle.

[0107] In some embodiments, when it is found through continuous observation that the conflict risk has been resolved and the detection object has passed the trajectory intersection, for example, when a pedestrian has completely passed the lane, or after the virtual wall duration has passed, a third control instruction is generated. The third control instruction is used to restore the driving authority of the target vehicle so that the target vehicle resumes driving at the position of the virtual stop wall.

[0108] In addition, when the virtual stop wall is triggered, a multi-level safety level label is generated to characterize the priority between the first motion trajectories corresponding to the detection objects, so as to determine the detection objects that need to be avoided more among multiple detection objects, so as to provide differentiated processing for downstream modules.

[0109] In some embodiments, determining a second motion trajectory corresponding to the target vehicle based on adjusting the driving speed, driving direction, vehicle position data, and driving intention information includes:

[0110] Based on the adjusted driving speed, driving direction, vehicle position data and driving intention information, multiple sets of candidate motion trajectories corresponding to the target vehicle are determined.

[0111] Weighted processing is performed on multiple groups of candidate motion trajectories to obtain a second motion trajectory.

[0112] In other embodiments, in order to further improve driving safety and reduce collision risk, the first motion trajectory and the second motion trajectory may be combined for decision optimization. In this embodiment, the second control instruction is also used to control the target vehicle to travel according to the second motion trajectory.

[0113] Specifically, after determining the first motion trajectories corresponding to the multiple detection objects, the trajectory is converted so that the trajectory data corresponding to the first motion trajectory is in the Frenet coordinate system (Frenet-Serret Frame, orthogonal coordinate system). Further, based on the multiple candidate motion trajectories, combined with the maximum deceleration, for example, 2.5m / s 2Based on the safety and comfort constraints, three sets of candidate longitudinal trajectories are generated: conservative, balanced, and aggressive. The cost of each candidate longitudinal trajectory is calculated and evaluated from the perspectives of safety (minimum TTC value), comfort (jerk integral), and efficiency (transit time). The optimal trajectory is determined as the second trajectory, which is then transformed so that the trajectory data corresponding to the second trajectory and the target are in the Frenet coordinate system (orthogonal coordinate system). The weight ratio of safety, comfort, and efficiency is 5:3:2. Through iterative calculation, the IDM cost functions corresponding to the first and second trajectories are found to satisfy a locally optimal equilibrium solution. A second control command is then generated, which controls the target vehicle based on the locally optimal equilibrium solution and the second trajectory.

[0114] Furthermore, if the iterative calculation time exceeds 200ms, a conservative candidate longitudinal trajectory is automatically selected to ensure safe driving. In typical unprotected left-turn scenarios, this method can improve traffic efficiency at intersections, reduce the number of sudden braking attempts, and enhance the passenger experience and comfort.

[0115] Correspondingly, the technical solution of this application also discloses a vehicle control device. Figure 5 As shown, the device includes:

[0116] The data acquisition module 510 is used to acquire the driving data and road detection data corresponding to the target vehicle;

[0117] A data calculation module 520 is used to determine the driving intention information and adjustment distance information corresponding to the target vehicle based on the driving data and the road detection data;

[0118] The first instruction generating module 530 is configured to generate a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is configured to adjust the driving speed of the target vehicle;

[0119] The second instruction generation module 540 is used to generate a second control instruction based on the driving data, the driving intention information, the first control instruction and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle.

[0120] In some embodiments, the data calculation module 520 includes:

[0121] The environment detection module is used to perform road environment detection based on the driving direction and lane line information to obtain road detection results;

[0122] an intention determination module, configured to calculate angle data between the driving direction and the at least one intersection to determine driving intention information when the road detection result indicates that the current road environment includes at least one intersection;

[0123] The distance determination module is used to determine and adjust distance information based on vehicle position data and lane line information.

[0124] In some embodiments, the first instruction generation module 530 includes:

[0125] a first speed determination module, configured to determine a driving speed limit based on driving intention information and adjustment distance information;

[0126] The third instruction generating module is used to generate a first control instruction based on the vehicle speed data and the driving speed limit.

[0127] In some embodiments, the apparatus further comprises:

[0128] a second speed determination module, configured to adjust the driving speed limit based on environmental information to obtain a compensated driving speed limit;

[0129] The fourth instruction generating module is configured to generate a first control instruction based on the vehicle speed data and the compensated running speed limit.

[0130] In some embodiments, the second instruction generation module 540 includes:

[0131] a first trajectory determination module, configured to determine a first motion trajectory of the detection object based on the position information and motion information of the detection object;

[0132] a third speed determination module, configured to determine an adjusted driving speed corresponding to the target vehicle based on the first control instruction;

[0133] a second trajectory determination module, configured to determine a second motion trajectory corresponding to the target vehicle based on the adjusted driving speed, driving direction, vehicle position data, and driving intention information;

[0134] The fifth instruction generating module is configured to generate a second control instruction based on the first motion trajectory and the second motion trajectory.

[0135] In some embodiments, the fifth instruction generation module includes:

[0136] A trajectory analysis module, configured to perform trajectory intersection analysis based on the first motion trajectory and the second motion trajectory to obtain a trajectory intersection result;

[0137] The sixth instruction generation module is used to obtain the virtual wall trigger condition and generate the second control instruction in combination with the track intersection result.

[0138] In some embodiments, the apparatus further comprises:

[0139] an information determination module, configured to determine a virtual wall duration and a track intersection point based on the track intersection result;

[0140] The seventh instruction generation module is used to generate a third control instruction after the virtual wall duration has passed and / or after the detection object passes the track intersection, and the third control instruction is used to restore the driving authority of the target vehicle.

[0141] In some embodiments, the second trajectory determination module includes:

[0142] a candidate trajectory determination module for determining multiple sets of candidate motion trajectories corresponding to the target vehicle based on the adjusted driving speed, driving direction, vehicle position data, and driving intention information;

[0143] The trajectory processing module is used to perform weighted processing on multiple groups of candidate motion trajectories to obtain a second motion trajectory.

[0144] The device and method embodiments in the device embodiment are based on the same inventive concept and are used to implement the above-mentioned vehicle control method.

[0145] An embodiment of the present application also provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement a vehicle control method as described in any of the method embodiments.

[0146] An embodiment of the present application also provides a computer storage medium, which can be set in a server to store at least one instruction, at least one program, code set or instruction set for implementing the method embodiment, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the vehicle control method as described in any one of the method embodiments.

[0147] Optionally, the computer storage medium may be located on at least one of a plurality of network servers in a computer network. Computer storage media may include, but are not limited to, various media capable of storing program code, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a removable hard drive, a magnetic disk, or an optical disk.

[0148] An embodiment of the present application also provides a computer program product, including a computer program / instruction, which implements the vehicle control method as described in any one of the method embodiments when the computer program / instruction is executed by a processor.

[0149] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "plurality" means two or more, unless otherwise specifically defined.

[0150] In the above embodiments, the description of each embodiment has its own focus. For parts not described in detail in one embodiment, please refer to the relevant description of other embodiments. The embodiments, implementation methods and related technical features of this application can be combined and replaced with each other without conflict.

[0151] The above are only preferred embodiments of the present application and are not intended to limit the present application in any form. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application shall still fall within the scope of the technical solution of the present application. The selection of terms used in this article is intended to best explain the principles, practical applications, or technical improvements of each embodiment in the market, or to enable other ordinary technicians in this technical field to understand the embodiments disclosed herein.

Claims

1. A vehicle control method, characterized in that: The method comprises: Obtain driving data and road detection data corresponding to the target vehicle; Determining driving intention information and adjustment distance information corresponding to the target vehicle based on the driving data and the road detection data; the road detection data includes a detection object and position information and motion information corresponding to the detection object, and the driving data includes a driving direction and vehicle position data; generating a first control instruction based on the driving intention information and the adjustment distance information; wherein the first control instruction is used to adjust the driving speed of the target vehicle; Generating a second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle; generating the second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data, includes: determining a first motion trajectory of the detected object based on the position information and the motion information of the detected object; determining an adjusted driving speed corresponding to the target vehicle based on the first control instruction; determining a second motion trajectory corresponding to the target vehicle based on the adjusted driving speed, the driving direction, the vehicle position data, and the driving intention information; performing a trajectory intersection analysis based on the first motion trajectory and the second motion trajectory to obtain a trajectory intersection result; A virtual wall trigger condition is obtained, and the second control instruction is generated in combination with the track intersection result.

2. The vehicle control method according to claim 1, characterized in that: The driving data includes driving direction and vehicle position data, and the road detection data includes lane line information; and determining the driving intention information corresponding to the target vehicle based on the driving data and the road detection data includes: Performing road environment detection based on the driving direction and the lane line information to obtain a road detection result; When the road detection result indicates that the current road environment includes at least one intersection, calculating the angle between the driving direction and each of the exit roads of the at least one intersection to determine the driving intention information; The adjusted distance information is determined based on the vehicle position data and the lane line information.

3. The vehicle control method according to claim 2, characterized in that: The driving data further includes vehicle speed data; and generating the first control instruction based on the driving intention information and the adjustment distance information includes: determining a driving speed limit based on the driving intention information and the adjusted distance information; The first control instruction is generated based on the vehicle speed data and the traveling speed limit.

4. The vehicle control method according to claim 3, characterized in that: The road detection data also includes environmental information; The method further comprises: adjusting the driving speed limit based on the environmental information to obtain a compensated driving speed limit; The first control instruction is generated based on the vehicle speed data and the compensated traveling speed limit.

5. The vehicle control method according to claim 1, characterized in that: The method further comprises: determining a virtual wall duration and a track intersection point based on the track intersection result; After the virtual wall duration has elapsed and / or after the detection object has passed the track intersection, a third control instruction is generated, where the third control instruction is used to restore the driving authority of the target vehicle.

6. The vehicle control method according to claim 1, characterized in that: The determining, based on the adjusted driving speed, the driving direction, the vehicle position data, and the driving intention information, a second motion trajectory corresponding to the target vehicle includes: determining a plurality of candidate motion trajectories corresponding to the target vehicle based on the adjusted driving speed, the driving direction, the vehicle position data, and the driving intention information; Weighted processing is performed on the multiple groups of candidate motion trajectories to obtain the second motion trajectory.

7. A vehicle control device, characterized in that: The device comprises: A data acquisition module is used to obtain driving data and road detection data corresponding to the target vehicle; a data calculation module for determining driving intention information and adjustment distance information corresponding to the target vehicle based on the driving data and the road detection data; the road detection data including the detected object and the corresponding position information and motion information of the detected object; and the driving data including the driving direction and vehicle position data; a first instruction generating module, configured to generate a first control instruction based on the driving intention information and the adjustment distance information; the first control instruction is used to adjust the driving speed of the target vehicle; A second instruction generation module is configured to generate a second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data; the second control instruction is used to adjust the driving authority of the target vehicle; and the generating of the second control instruction based on the driving data, the driving intention information, the first control instruction, and the road detection data includes: determining a first motion trajectory of the detected object based on the position information and the motion information of the detected object; determining an adjusted driving speed corresponding to the target vehicle based on the first control instruction; determining a second motion trajectory corresponding to the target vehicle based on the adjusted driving speed, the driving direction, the vehicle position data, and the driving intention information; performing a trajectory intersection analysis based on the first motion trajectory and the second motion trajectory to obtain a trajectory intersection result; A virtual wall trigger condition is obtained, and the second control instruction is generated in combination with the track intersection result.

8. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction and at least one program, and the at least one instruction and the at least one program are loaded and executed by the processor to implement the vehicle control method according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that The computer storage medium stores at least one instruction and at least one program, and the at least one instruction and the at least one program are loaded and executed by the processor to implement the vehicle control method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the vehicle control method according to any one of claims 1 to 6 is implemented.

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