Lane planning method and apparatus for vehicle, and vehicle and storage medium

Abstract

A lane planning method and apparatus for a vehicle, and a vehicle and a storage medium. The method comprises: acquiring the current road curvature of a road where the current vehicle is located, the current environment perception computing power proportion and the current lane planning computing duration (S101); determining an optimal lane planning policy for the current vehicle on the basis of the current lane planning computing duration, the current road curvature and the current environment perception computing power proportion (S102); and on the basis of the current optimal lane planning policy, adjusting the current lane planning distance and / or the current number of planned lanes for the current vehicle (S103). The problems, such as the output real-time performance of a lane planning result being relatively poor during lane planning in some relatively complex driving scenarios, and there being a lack of dynamic optimization methods in lane planning, which results in the relatively low safety of autonomous driving, are solved, thereby significantly improving the real-time performance of lane planning and further improving the safety of autonomous driving.

Description

Vehicle lane planning method, device, vehicle and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on the Chinese patent application with application number 202311092076.7 and application date of August 28, 2023, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby introduced into this application as a reference. Technical Field

[0003] The present application relates to the field of autonomous driving technology, and in particular to a vehicle lane planning method, device, vehicle, and storage medium. Background Art

[0004] In related technologies, when performing lane planning, generally, planning is performed from the first starting lane to N target lanes respectively, and N lane planning results are obtained. If the time required to perform a search is T, then the time required to perform N lane planning is N*T.

[0005] However, for some more complex driving scenarios, the lane planning results in related technologies have poor real-time output, and lane planning lacks dynamic optimization methods, resulting in low safety of autonomous driving, which needs to be urgently addressed.

[0006] Summary of the Invention

[0007] The present application provides a vehicle lane planning method, device, vehicle and storage medium to address the problems in related technologies such as poor real-time output of lane planning results when performing lane planning for some more complex driving scenarios, and lack of dynamic optimization methods for lane planning, resulting in low safety of autonomous driving. This greatly improves the real-time performance of lane planning, thereby enhancing the safety of autonomous driving.

[0008] A first embodiment of the present application provides a vehicle lane planning method, comprising the following steps:

[0009] Obtain the current road curvature, current environmental perception computing power ratio, and current lane planning calculation duration of the road on which the current vehicle is located; determine the optimal lane planning strategy for the current vehicle based on the current lane planning calculation duration, the current road curvature, and the current environmental perception computing power ratio; adjust the current lane planning distance and / or current lane planning number of the current vehicle based on the current optimal lane planning strategy.

[0010] Optionally, in some embodiments, determining the optimal lane planning strategy for the current vehicle based on the current lane planning calculation time, the current road curvature, and the current environmental perception computing power ratio includes:

[0011] If the current lane planning calculation time is greater than or equal to the first preset time, the first target planned lane number and the first target planned distance of the current vehicle are matched according to the current road curvature, and the second target planned lane number and the second target planned distance of the current vehicle are matched according to the current environment perception computing power ratio, wherein the first target planned lane number is less than the current planned number of vehicles, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned number of vehicles, and the second target planned distance is less than the current planned distance;

[0012] Determining a final planned number of lanes for the current vehicle based on the first target planned number of lanes and / or the second target planned number of lanes, and determining a final planned distance for the current vehicle based on the first target planned distance and / or the second target planned distance;

[0013] The optimal lane planning strategy is generated according to the final planned lane number and the final planned distance.

[0014] Optionally, in some embodiments, before matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, it also includes: obtaining the number of calculations within a second preset time length in which the current lane planning calculation time is greater than the first preset time length; if the number of calculations is less than the preset number, maintaining the lane planning strategy of the current vehicle unchanged.

[0015] Optionally, in some embodiments, after adjusting the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy, it also includes: obtaining the new lane planning calculation duration of the current vehicle; if the new lane planning calculation duration is greater than or equal to the first preset duration, reducing the first target planning lane number and shortening the first target planning distance according to the preset strategy; adjusting the current lane planning number and / or adjusting the current lane planning distance according to the shortened first target planning lane number.

[0016] Optionally, in some embodiments, after obtaining the current road curvature, current environment perception computing power ratio, and current lane planning calculation duration of the road on which the current vehicle is located, the method further includes:

[0017] If the current lane planning calculation time is less than the second preset time, matching the third target planned lane number and third target planned distance of the current vehicle according to the current road curvature, and matching the fourth target planned lane number and fourth target planned distance of the current vehicle according to the current environmental perception computing power ratio;

[0018] Adjusting the current lane planning number according to the third target planned lane number and / or the fourth target planned vehicle number, and / or adjusting the current lane planning distance according to the first target planned distance and / or the second target planned distance;

[0019] Among them, the second preset time length is less than the first preset time length, the third target planned lane number is greater than the currently planned vehicle number, the third target planned distance is greater than the currently planned distance, the fourth target planned lane number is greater than the currently planned vehicle number, and the fourth target planned distance is greater than the currently planned distance.

[0020] Optionally, in some embodiments, after obtaining the current road curvature, current environmental perception computing power ratio and current lane planning calculation time of the road on which the current vehicle is located, it also includes: if the current lane planning calculation time is greater than or equal to the second preset time, and the current lane planning calculation time is less than the first preset time, then the lane planning strategy of the current vehicle is maintained unchanged.

[0021] A second embodiment of the present application provides a vehicle lane planning device, comprising:

[0022] An acquisition module is used to obtain the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located; a determination module is used to determine the optimal lane planning strategy for the current vehicle based on the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio; a planning module is used to adjust the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy.

[0023] Optionally, in some embodiments, the determining module includes:

[0024] A first matching unit is configured to match a first target planned lane number and a first target planned distance of the current vehicle according to the current road curvature when the current lane planning calculation duration is greater than or equal to the first preset duration, and to match a second target planned lane number and a second target planned distance of the current vehicle according to the current environment perception computing power ratio, wherein the first target planned lane number is less than the current planned number of vehicles, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned number of vehicles, and the second target planned distance is less than the current planned distance;

[0025] a determining unit, configured to determine a final planned number of lanes for the current vehicle based on the first target planned number of lanes and / or the second target planned number of lanes, and to determine a final planned distance for the current vehicle based on the first target planned distance and / or the second target planned distance;

[0026] A generating unit is used to generate the optimal lane planning strategy according to the final planned lane number and the final planned distance.

[0027] Optionally, in some embodiments, before matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, the first matching unit is further configured to:

[0028] Obtain the number of calculations within a second preset time period in which the current lane planning calculation duration is greater than the first preset time period; when the number of calculations is less than the preset number, maintain the lane planning strategy of the current vehicle unchanged.

[0029] Optionally, in some embodiments, after adjusting the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy, the planning module further includes:

[0030] An acquiring unit, configured to acquire a new lane planning calculation duration for the current vehicle;

[0031] a first planning unit, configured to reduce the number of the first target planned lanes and shorten the first target planned distance according to a preset strategy when the calculation time of the new lane planning is greater than or equal to the first preset time;

[0032] The first adjustment unit is configured to adjust the current lane planning number according to the shortened first target planned lane number and / or adjust the current lane planning distance according to the shortened first target planned distance.

[0033] Optionally, in some embodiments, after obtaining the current road curvature, current environment perception computing power ratio, and current lane planning calculation duration of the road on which the current vehicle is located, the obtaining module further includes:

[0034] a second matching unit, configured to match a third target planned number of lanes and a third target planned distance of the current vehicle according to the current road curvature when the current lane planning calculation duration is less than a second preset duration, and to match a fourth target planned number of lanes and a fourth target planned distance of the current vehicle according to the current environmental perception computing power ratio;

[0035] a second adjustment unit, configured to adjust the current lane planning number according to the third target planned lane number and / or the fourth target planned vehicle number, and / or adjust the current lane planning distance according to the first target planned distance and / or the second target planned distance;

[0036] Among them, the second preset time length is less than the first preset time length, the third target planned lane number is greater than the currently planned vehicle number, the third target planned distance is greater than the currently planned distance, the fourth target planned lane number is greater than the currently planned vehicle number, and the fourth target planned distance is greater than the currently planned distance.

[0037] Optionally, in some embodiments, after obtaining the current road curvature, current environment perception computing power ratio, and current lane planning calculation duration of the road on which the current vehicle is located, the obtaining module further includes:

[0038] The second planning unit is used to maintain the lane planning strategy of the current vehicle unchanged when the current lane planning calculation time is greater than or equal to the second preset time and the current lane planning calculation time is less than the first preset time.

[0039] The third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle lane planning method as described in the above embodiment.

[0040] The fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored. The program is executed by a processor to implement the vehicle lane planning method as described in the above embodiment.

[0041] Therefore, when the current lane planning calculation time is greater than or equal to a certain time, the present application can calculate the optimal lane planning strategy for the current vehicle based on the current road curvature and / or the current environmental perception computing power ratio, and adjust the current lane planning distance and / or the current number of lanes planned for the current vehicle based on the current optimal lane planning strategy. This solves the problems in the related art of poor real-time output of lane planning results when performing lane planning for some more complex driving scenarios, and the lack of dynamic optimization methods for lane planning, resulting in lower safety of autonomous driving. This greatly improves the real-time performance of lane planning, thereby enhancing the safety of autonomous driving.

[0042] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0044] FIG1 is a flow chart of a vehicle lane planning method according to an embodiment of the present application;

[0045] FIG2 is a flow chart of a vehicle lane planning method according to one embodiment of the present application;

[0046] FIG3 is a block diagram of a vehicle lane planning device according to an embodiment of the present application;

[0047] FIG4 is a block diagram of a vehicle according to an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0049] The following describes the lane planning method, device, vehicle and storage medium of the vehicle embodiment of the present application with reference to the accompanying drawings. In view of the above background technology, when performing lane planning for some more complex driving scenes, the output real-time performance of the lane planning results is poor, and the lane planning lacks a dynamic optimization method, resulting in low safety of autonomous driving. The present application provides a lane planning method for a vehicle, in which the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located are obtained; the optimal lane planning strategy of the current vehicle is determined based on the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio; and the current lane planning distance and / or the current lane planning number of the current vehicle are adjusted according to the current optimal lane planning strategy. Thus, the problem in the related art that when performing lane planning for some more complex driving scenes, the output real-time performance of the lane planning results is poor, and the lane planning lacks a dynamic optimization method, resulting in low safety of autonomous driving is solved, thereby greatly improving the real-time performance of lane planning and thus improving the safety of autonomous driving.

[0050] Before introducing the embodiment of the lane planning method for a vehicle of the present application, a brief introduction to the lane planning algorithm involved in the present application is first given.

[0051] Currently, autonomous driving algorithms generally include positioning algorithms, perception algorithms, prediction algorithms, path planning algorithms, lane planning algorithms, decision algorithms, local planning algorithms, and control algorithms. The output resolution of lane planning results refers to the path that the vehicle will follow, which is a collection of points. In other words, the output resolution is the distance between one point and another in the path. The planning distance refers to the distance between the starting point and the end point of the lane planning process.

[0052] On cost-constrained hardware platforms, limited computing resources pose significant challenges to the timeliness of algorithm output during autonomous driving planning. As described in the background technology section above, current lane planning algorithms plan a lane with a fixed forward distance as the target point, starting from the current lane where the vehicle is located. For example, when driving, the algorithm needs to consider the approximate location of the vehicle and how to navigate to it 100 meters in the future (the distance to be considered may be greater than 100 meters on highways and less than 100 meters on congested roads).

[0053] This application takes into account the various types of roads on which autonomous vehicles operate, including highways, urban trunk roads, rural roads, urban alleys, winding mountain roads, market roads and intersections. Different types of scenarios have different timeliness requirements for lane planning algorithms. Therefore, a vehicle lane planning method is proposed. According to the vehicle's environment, combined with multiple factors such as computing power monitoring and road curvature, the planning length of lane planning, the resolution of the result output and other indicators are dynamically adjusted, so that the lane planning results are more in line with the current vehicle status and the real-time performance of lane planning is improved.

[0054] Specifically, Figure 1 is a flow chart of a vehicle lane planning method provided in an embodiment of the present application.

[0055] As shown in FIG1 , the vehicle lane planning method includes the following steps:

[0056] In step S101, the current road curvature, current environmental perception computing power ratio and current lane planning calculation time of the road on which the vehicle is currently located are obtained.

[0057] Among them, based on the introduction in the above-mentioned related technologies, the current environment perception computing power ratio of the embodiment of the present application refers to the ratio of the computing power of the perception module and prediction module of the autonomous driving to the total computing power of the autonomous driving platform in the current environmental scene of the vehicle. The recognition of the current environment can be obtained by positioning the current position of the vehicle, or by visual perception, that is, by using the camera as a sensor to input the environmental information of the vehicle and infer the current scene of the vehicle; the current lane planning calculation duration of the embodiment of the present application refers to the duration of the autonomous driving platform from the beginning of lane planning; the calculation method of the current road curvature of the embodiment of the present application can refer to the relevant technology and will not be described here to avoid redundancy.

[0058] It is understandable that in the process of lane planning, the output efficiency of the results is related to multiple factors. This application takes into account that in certain scenarios, such as the coastal highway, the road curvature is large, while in road scenarios such as highways, the road curvature is small. In addition, when the autonomous driving platform is performing lane planning, the computing power load used for lane planning is different depending on the scenario in which the vehicle is located. If the vehicle is in a scene such as a busy intersection, the computing power demand of the perception module and the prediction module in the autonomous driving algorithm increases. It can be understood that the greater the proportion of the current environmental perception computing power, the greater the impact on the timeliness of the output of the lane planning results.

[0059] Therefore, before planning lanes, this application needs to obtain the current road curvature and the current environmental perception computing power ratio of the road the vehicle is currently on to match the appropriate lane planning strategy. This application also needs to obtain the current lane planning calculation time. If the current lane planning calculation time is too long, the lane planning strategy can be adjusted in a timely manner to improve the efficiency of lane planning.

[0060] In step S102, the optimal lane planning strategy for the current vehicle is determined based on the current lane planning calculation time, the current road curvature, and the current environmental perception computing power ratio.

[0061] In the embodiment of the present application, the lane planning strategy mainly includes two aspects: the distance of the current lane planning and the number of the current lane planning.

[0062] Specifically, this application uses the current lane planning calculation duration, current road curvature, and current environmental perception computing power ratio obtained in step S101 to match the lane planning strategy provided by this application to obtain the optimal lane planning strategy for the current vehicle. This optimal lane planning strategy can make the lane planning results more consistent with the current vehicle state and improve the real-time performance of lane planning. The following examples specifically illustrate the multiple lane planning strategies provided by this application.

[0063] Optionally, in some embodiments, the optimal lane planning strategy for the current vehicle is determined based on the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio, including: if the current lane planning calculation time is greater than or equal to the first preset time, matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, and matching the second target planned lane number and the second target planned distance of the current vehicle according to the current environmental perception computing power ratio, wherein the first target planned lane number is less than the current planned number of vehicles, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned number of vehicles, and the second target planned distance is less than the current planned distance; determining the final planned lane number of the current vehicle according to the first target planned lane number and / or the second target planned lane number, and determining the final planned distance of the current vehicle according to the first target planned distance and / or the second target planned distance; generating the optimal lane planning strategy based on the final planned lane number and the final planned distance.

[0064] It should be noted that the present application provides conditions for adjusting the lane planning strategy, that is, after obtaining the current lane planning calculation duration in step S101, it is compared with the first preset duration set in the present application. When the current lane planning calculation duration exceeds the preset value, it is determined that the timeliness of the result output is not met at this time, and the lane planning strategy needs to be adjusted to improve the efficiency of lane planning.

[0065] It is understandable that the traffic volume in high-speed scenarios or urban main road scenarios is large, and in urban crowded intersection scenarios, such as busy urban intersections, the vehicle speed is slow, so the computing power requirements of the perception module and the prediction module increase, resulting in a reduction in the computing power resources provided by the system for lane planning. Therefore, in order to balance the system's computing power resources and make the lane planning output results of autonomous driving more timely, this application makes the number of planned lanes less than the number of currently planned vehicles and the planned distance less than the current planned distance in scenarios that will reduce computing power resources.

[0066] In addition, considering that users may drive very slowly on uncongested roads, the lane planning strategy of this application is matched according to the current road curvature and the current proportion of environmental perception computing power to obtain a more accurate and reasonable lane planning strategy.

[0067] Specifically, this application calibrates the number of planned lanes, that is, the first target planned lane number obtained by matching the current road curvature and the second target planned lane number obtained by matching the current environmental perception computing power ratio in this embodiment, and both are less than the current planned number of vehicles; this application calibrates the planned distance, that is, the first target planned distance obtained by matching the current road curvature and the second target planned distance obtained by matching the current environmental perception computing power ratio in this embodiment, and both are less than the current planned distance. This application does not make specific limitations on the first target planned lane number, the first target planned distance, the second target planned lane number, and the second target planned distance. Those skilled in the art can set them according to actual conditions.

[0068] Furthermore, the present application may use the matched first target planned lane number as the final planned lane number, or use the matched second target planned lane number as the final planned lane number, or calculate the average of the first target planned lane number and the second target planned lane number, and use the average of the two as the final planned lane number, without specific limitation here. Optionally, the method for calculating the final planned distance is similar to the method for calculating the final planned lane number described above, and to avoid redundancy, it is not described here.

[0069] For example, the first preset duration is 60 seconds, the current number of planned vehicles is 5, and the current planned distance is 100 meters. After the current lane planning calculation time exceeds 60 seconds, when the current road curvature is 500 meters, the system determines that the curvature value is too large. Through matching, the first target planned lane number is 4, the first target planned distance is 80 meters, and the current environmental perception computing power accounts for 80%. Through matching, the second target planned lane number is 2, and the second target planned distance is 60 meters. Therefore, three lane planning strategies are obtained, namely, determining the final planned lane number to be 4 and the final planned distance to be 80 meters; or determining the final planned lane number to be 2 and the final planned distance to be 60 meters; or determining the final planned lane number to be 3 and the final planned distance to be 70 meters, and then selecting the best lane planning strategy according to the actual situation.

[0070] Therefore, this application can match the optimal number of planned lanes and final planned distance based on the current lane planning calculation time, current road curvature and current environmental perception computing power ratio, thereby obtaining the optimal lane planning strategy.

[0071] Optionally, in some embodiments, after obtaining the current road curvature, current environmental perception computing power ratio and current lane planning calculation time of the road on which the current vehicle is located, it also includes: if the current lane planning calculation time is less than the second preset time, matching the third target planned lane number and third target planned distance of the current vehicle according to the current road curvature, and matching the fourth target planned lane number and fourth target planned distance of the current vehicle according to the current environmental perception computing power ratio; adjusting the current lane planning number according to the third target planned lane number and / or the fourth target planned vehicle number, and / or adjusting the current lane planning distance according to the first target planned distance and / or the second target planned distance; wherein, the second preset time is less than the first preset time, the third target planned lane number is greater than the current planned vehicle number, the third target planned distance is greater than the current planned distance, the fourth target planned lane number is greater than the current planned vehicle number, and the fourth target planned distance is greater than the current planned distance.

[0072] It is understandable that in highway or trunk road scenarios, the road curvature is small, the proportion of environmental perception computing power is small, and the vehicle's driving speed is fast. Therefore, considering the system's computing power balance, in this case it is necessary to appropriately extend the lane planning distance to better suit the current vehicle status and improve the real-time performance of lane planning.

[0073] Specifically, the present application sets a second preset duration, which is less than the above-mentioned first preset duration. When the current lane planning calculation duration is less than the second preset duration, the third target planning lane number and the third target planning distance can be obtained by matching the current road curvature, and the fourth target planning lane number and the fourth target planning distance can be matched based on the current environment perception computing power ratio. In this embodiment, the third target planning lane number and the fourth target planning lane number are both greater than the current planned number of vehicles, and the third target planning distance and the fourth target planning distance are both greater than the current planned distance. In addition, the present application does not make specific limitations on the third target planning lane number, the third target planning distance, the fourth target planning lane number and the fourth target planning distance, and those skilled in the art can set them according to actual conditions.

[0074] Furthermore, the present application may use the matched third target planned lane number as the final planned lane number, or use the matched fourth target planned lane number as the final planned lane number, or calculate the average of the third target planned lane number and the fourth target planned lane number, and use the average of the two as the final planned lane number, without specific limitation herein. Optionally, the method for calculating the final planned distance is similar to the method for calculating the final planned lane number described above, and to avoid redundancy, it is not described here.

[0075] For example, the current planned number of vehicles is 2, the current planned distance is 60 meters, and the second preset time is 50 seconds. When the current lane planning calculation time is 30 seconds and the road curvature is 100 meters, the third target planned lane number is 4, and the third target planned distance is 80 meters. The current environmental perception computing power accounts for 40%, then the fourth target planned lane number is 4, and the fourth target planned distance is 100 meters. Therefore, three lane planning strategies are obtained, namely, determining the final planned lane number to be 4 and the final planned distance to be 80 meters; or determining the final planned lane number to be 4 and the final planned distance to be 100 meters; or determining the final planned lane number to be 4 and the final planned distance to be 90 meters, and then selecting the best lane planning strategy according to the actual situation.

[0076] Therefore, when the vehicle is in a small curvature and the proportion of environmental perception computing power is small, this application can appropriately increase the search distance and number of times, dynamically adjust the planning length of lane planning, make the lane planning results more in line with the current vehicle status, and improve the real-time performance of lane planning.

[0077] Optionally, in some embodiments, after obtaining the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located, it also includes: if the current lane planning calculation time is greater than or equal to the second preset time, and the current lane planning calculation time is less than the first preset time, then the lane planning strategy of the current vehicle is maintained unchanged.

[0078] It should be noted that after obtaining the current lane planning calculation time, this application needs to judge the time, that is, compare the current lane planning calculation time with the first preset time and the second preset time set by this application, thereby obtaining the range of the current lane planning calculation time, and then planning the lane to improve the timeliness of lane planning.

[0079] Specifically, in this embodiment, the present application takes into account that although the delay of the current lane planning has increased, it has not exceeded a certain amount. In order to avoid wasting resources and balance the computing load of the system, when the current lane planning calculation duration is between the second preset duration and the first preset duration of the embodiment of the present application, the lane planning strategy of the current vehicle is maintained unchanged.

[0080] Optionally, in some embodiments, before matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, it also includes: obtaining the number of calculations in which the current lane planning calculation duration within the second preset duration is greater than the first preset duration; if the number of calculations is less than the preset number, maintaining the lane planning strategy of the current vehicle unchanged.

[0081] Based on the above examples, lane planning is initiated by comparing the current lane planning calculation duration with a first preset duration. When the current lane planning calculation duration exceeds this threshold, the lane planning strategy is initiated. However, this application takes into account the possibility of misjudgment by the system and, therefore, requires lane planning to be performed only after multiple lane delays occur. This effectively avoids misjudgments and increases lane planning accuracy.

[0082] Specifically, this application sets a second preset duration and counts the number of times within the second preset duration that the current lane planning calculation duration exceeds the first preset duration. If this number is less than the preset number, it is determined that lane planning is not necessary at this time and the lane planning strategy for the current vehicle must be maintained unchanged. This allows the application to conserve computing resources and ensure system stability when lane planning is not required. Furthermore, this application does not specify a specific preset number of calculations, and those skilled in the art can set this number based on actual circumstances.

[0083] In step S103, the current lane planning distance and / or the current lane planning number of the current vehicle are adjusted according to the current optimal lane planning strategy.

[0084] Based on the above embodiments, the present application can match the current optimal lane planning strategy based on the current road curvature and the current environmental perception computing power ratio, combined with the delay statistics of the output results, and then adjust the lane planning distance or lane planning number of the current vehicle or both according to the current optimal lane planning strategy, thereby making the lane planning results more in line with the current vehicle status and improving the real-time performance of lane planning.

[0085] Optionally, in some embodiments, after adjusting the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy, it also includes: obtaining the new lane planning calculation time of the current vehicle; if the new lane planning calculation time is greater than or equal to the first preset time, reducing the number of first target planned lanes and shortening the first target planning distance according to the preset strategy; adjusting the current lane planning number and / or adjusting the current lane planning distance according to the shortened first target planning lane number.

[0086] It should be noted that in order to improve the real-time performance of lane planning, this application counts the time after planning and determines whether it is too long. If the lane planning time is too long, it is very likely to affect the timeliness of the system output and bring inconvenience to the user. Therefore, in this case, this application plans the lane again and appropriately reduces the search distance and number of times to improve the efficiency of the output results.

[0087] In order to enable those skilled in the art to further understand the vehicle lane planning method of the present application, the following examples are listed to schematically illustrate the process of the method.

[0088] Specifically, FIG2 is a flow chart of a vehicle lane planning method according to an embodiment of the present application. As shown in FIG2 , the vehicle lane planning method may include the following steps:

[0089] Step S201: Calculate the vehicle's current location in scene scen1 (a busy intersection, a congested urban main road, a smooth highway, a winding coastal highway, etc.) based on the vehicle's current location or visual perception.

[0090] Step S202: monitoring the delay of outputting the lane planning results and making statistics;

[0091] Step S203: For the current scene scen1, estimate whether the current computing load will increase, whether the curvature of the future road is too large, and determine whether the delay increases and exceeds the threshold. If the delay increases but does not exceed the threshold, execute step S204; otherwise, execute step S205.

[0092] Step S204, changing the distance and number of lane planning according to scene scen1;

[0093] Step S205: Combine the vehicle's scene and the output delay statistics, and match the scene listed in the list with the lane planning strategy: when the vehicle is in a high-speed scene, appropriately increase the search distance and number of times; when the vehicle is in a city main road scene, due to the heavy traffic volume, appropriately reduce the search distance and number of times; when the vehicle is in a congested city intersection scene, due to the heavy perception prediction load, appropriately reduce the search distance and number of times; when the vehicle is in a coastal highway scene, due to the large road curvature, appropriately reduce the search distance;

[0094] Step S206: perform lane planning according to the optimal lane planning strategy.

[0095] According to the vehicle lane planning method proposed in the embodiment of the present application, by obtaining the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road where the current vehicle is located, the optimal lane planning strategy of the current vehicle is determined according to the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio, and the current lane planning distance and / or the current lane planning number of the current vehicle are adjusted according to the current optimal lane planning strategy. Therefore, the present application combines the environmental perception computing power ratio of the vehicle's environment, that is, the system's computing power monitoring, and the road curvature factor to dynamically adjust the planning length of lane planning, solving the problems in the related technology that the real-time output of lane planning results is not considered, and there is a lack of control or dynamic optimization methods, which may have a certain impact on the safety of autonomous driving. Lane planning is controlled in real time according to the scene in which the vehicle is located, so that the results of lane planning are more in line with the current state of the vehicle, thereby improving the timeliness of lane planning.

[0096] Next, a lane planning device for a vehicle proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0097] FIG3 is a block diagram of a lane planning device for a vehicle according to an embodiment of the present application.

[0098] As shown in FIG3 , the vehicle lane planning device 10 includes: an acquisition module 100 , a determination module 200 and a planning module 300 .

[0099] Among them, the acquisition module 100 is used to obtain the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located; the determination module 200 is used to determine the optimal lane planning strategy for the current vehicle based on the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio; the planning module 300 is used to adjust the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy.

[0100] Optionally, in some embodiments, the determination module 200 includes: a first matching unit, a determination unit, and a generation unit.

[0101] Among them, the first matching unit is used to match the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature when the current lane planning calculation time is greater than or equal to the first preset time, and match the second target planned lane number and the second target planned distance of the current vehicle according to the current environmental perception computing power ratio, wherein the first target planned lane number is less than the current planned number of vehicles, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned number of vehicles, and the second target planned distance is less than the current planned distance; the determination unit is used to determine the final planned lane number of the current vehicle according to the first target planned lane number and / or the second target planned lane number, and determine the final planned distance of the current vehicle according to the first target planned distance and / or the second target planned distance; the generation unit is used to generate the optimal lane planning strategy according to the final planned lane number and the final planned distance.

[0102] Optionally, in some embodiments, before matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, the first matching unit is further configured to:

[0103] Obtain the number of calculations within the second preset time period in which the current lane planning calculation duration is greater than the first preset time period; when the number of calculations is less than the preset number, maintain the lane planning strategy of the current vehicle unchanged.

[0104] Optionally, in some embodiments, after adjusting the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy, the planning module 300 further includes: an acquisition unit, a first planning unit and a first adjustment unit.

[0105] Among them, the acquisition unit is used to obtain the new lane planning calculation time of the current vehicle; the first planning unit is used to reduce the number of first target planned lanes and shorten the first target planning distance according to the preset strategy when the new lane planning calculation time is greater than or equal to the first preset time; the first adjustment unit is used to adjust the current lane planning number and / or the current lane planning distance according to the shortened first target planning lane number.

[0106] Optionally, in some embodiments, after obtaining the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located, the acquisition module 100 further includes: a second matching unit and a second adjustment unit.

[0107] Among them, the second matching unit is used to match the third target planned lane number and the third target planned distance of the current vehicle according to the current road curvature when the current lane planning calculation time is less than the second preset time, and match the fourth target planned lane number and the fourth target planned distance of the current vehicle according to the current environmental perception computing power ratio; the second adjustment unit is used to adjust the current lane planning number according to the third target planned lane number and / or the fourth target planned vehicle number, and / or adjust the current lane planning distance according to the first target planned distance and / or the second target planned distance; wherein, the second preset time is less than the first preset time, the third target planned lane number is greater than the current planned vehicle number, the third target planned distance is greater than the current planned distance, the fourth target planned lane number is greater than the current planned vehicle number, and the fourth target planned distance is greater than the current planned distance.

[0108] Optionally, in some embodiments, after obtaining the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road on which the current vehicle is located, the acquisition module 100 further includes: a second planning unit.

[0109] Among them, the second planning unit is used to maintain the lane planning strategy of the current vehicle unchanged when the current lane planning calculation time is greater than or equal to the second preset time and the current lane planning calculation time is less than the first preset time.

[0110] It should be noted that the above explanation of the vehicle lane planning method embodiment is also applicable to the vehicle lane planning device of this embodiment, and will not be repeated here.

[0111] According to the lane planning device for a vehicle proposed in an embodiment of the present application, by obtaining the current road curvature, the current environmental perception computing power ratio and the current lane planning calculation time of the road where the current vehicle is located, the optimal lane planning strategy for the current vehicle is determined according to the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio, and the current lane planning distance and / or the current lane planning number of the current vehicle are adjusted according to the current optimal lane planning strategy. Therefore, the present application dynamically adjusts the planning length of lane planning based on the environmental perception computing power ratio of the vehicle's environment, that is, the system's computing power monitoring, and the factors of road curvature, solving the problems in related technologies that do not consider the real-time output of lane planning results and lack control or dynamic optimization methods, which may have a certain impact on the safety of autonomous driving. Lane planning is controlled in real time according to the scene in which the vehicle is located, so that the results of lane planning are more in line with the current state of the vehicle, thereby improving the timeliness of lane planning.

[0112] FIG4 is a schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0113] Memory 401 , processor 402 , and computer programs stored in the memory 401 and executable on the processor 402 .

[0114] When the processor 402 executes the program, the vehicle lane planning method provided in the above embodiment is implemented.

[0115] Furthermore, the vehicle further comprises:

[0116] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0117] The memory 401 is used to store computer programs that can be run on the processor 402 .

[0118] The memory 401 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0119] If memory 401, processor 402, and communication interface 403 are implemented independently, communication interface 403, memory 401, and processor 402 can be interconnected via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. Buses can be divided into address buses, data buses, control buses, etc. For ease of illustration, FIG4 shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0120] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0121] The processor 402 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0122] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned vehicle lane planning method.

[0123] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0124] Furthermore, 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. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0125] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0126] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0127] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0128] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A vehicle lane planning method, characterized in that: The following steps are involved: Obtain the current road curvature, current environment perception computing power ratio, and current lane planning calculation time of the road where the vehicle is currently located; Determining the optimal lane planning strategy for the current vehicle according to the current lane planning calculation time, the current road curvature and the current environment perception computing power ratio; as well as The current lane planning distance and / or the current lane planning number of the current vehicle are adjusted according to the current optimal lane planning strategy.

2. The method according to claim 1, characterized in that The determining the optimal lane planning strategy for the current vehicle according to the current lane planning calculation time, the current road curvature and the current environment perception computing power ratio includes: If the current lane planning calculation time is greater than or equal to the first preset time, the first target planned lane number and the first target planned distance of the current vehicle are matched according to the current road curvature, and the second target planned lane number and the second target planned distance of the current vehicle are matched according to the current environment perception computing power ratio, wherein the first target planned lane number is less than the current planned vehicle number, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned vehicle number, and the second target planned distance is less than the current planned distance; Determining the final planned lane number of the current vehicle according to the first target planned lane number and / or the second target planned lane number, and determining the final planned distance of the current vehicle according to the first target planned distance and / or the second target planned distance; The optimal lane planning strategy is generated according to the final planned lane number and the final planned distance.

3. The method according to claim 1 or 2, characterized in that: Before matching the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature, the method further includes: Obtaining the number of calculations within the second preset time period during which the current lane planning calculation time period is greater than the first preset time period; If the number of calculations is less than a preset number, the lane planning strategy of the current vehicle is maintained unchanged.

4. The method according to claim 1 or 2, characterized in that: After adjusting the current lane planning distance and / or the current lane planning quantity of the current vehicle according to the current optimal lane planning strategy, the method further includes: Obtaining a new lane planning calculation duration for the current vehicle; If the calculation time of the new lane planning is greater than or equal to the first preset time, reducing the number of first target planning lanes and shortening the first target planning distance according to a preset strategy; The current lane planning number is adjusted according to the shortened first target planned lane number and / or the current lane planning distance is adjusted according to the shortened first target planned distance.

5. The method according to claim 1, characterized in that After obtaining the current road curvature of the road on which the current vehicle is located, the current environment perception computing power ratio and the current lane planning calculation time, it also includes: If the current lane planning calculation time is less than the second preset time, matching the third target planning lane number and the third target planning distance of the current vehicle according to the current road curvature, and matching the fourth target planning lane number and the fourth target planning distance of the current vehicle according to the current environment perception computing power ratio; Adjusting the current lane planning number according to the third target planned lane number and / or the fourth target planned vehicle number, and / or adjusting the current lane planning distance according to the first target planned distance and / or the second target planned distance; Among them, the second preset time length is shorter than the first preset time length, the third target planned lane number is greater than the currently planned vehicle number, the third target planned distance is greater than the currently planned distance, the fourth target planned lane number is greater than the currently planned vehicle number, and the fourth target planned distance is greater than the currently planned distance.

6. The method according to claim 1, characterized in that After obtaining the current road curvature of the road on which the current vehicle is located, the current environment perception computing power ratio and the current lane planning calculation time, it also includes: If the current lane planning calculation time is greater than or equal to the second preset time, and the current lane planning calculation time is less than the first preset time, the lane planning strategy of the current vehicle is maintained unchanged.

7. A vehicle lane planning device, characterized in that: include: The acquisition module is used to obtain the current road curvature of the road where the vehicle is currently located, the current environmental perception computing power ratio and the current lane planning calculation time; A determination module, used to determine the optimal lane planning strategy for the current vehicle according to the current lane planning calculation time, the current road curvature and the current environment perception computing power ratio; as well as A planning module is used to adjust the current lane planning distance and / or the current lane planning number of the current vehicle according to the current optimal lane planning strategy.

8. The device according to claim 7, characterized in that The determining module comprises: A first matching unit is used to match the first target planned lane number and the first target planned distance of the current vehicle according to the current road curvature when the current lane planning calculation duration is greater than or equal to the first preset duration, and to match the second target planned lane number and the second target planned distance of the current vehicle according to the current environment perception computing power ratio, wherein the first target planned lane number is less than the current planned vehicle number, the first target planned distance is less than the current planned distance, the second target planned lane number is less than the current planned vehicle number, and the second target planned distance is less than the current planned distance; a determination unit, configured to determine the final planned number of lanes for the current vehicle according to the first target planned number of lanes and / or the second target planned number of lanes, and to determine the final planned distance of the current vehicle according to the first target planned distance and / or the second target planned distance; A generating unit is used to generate the optimal lane planning strategy according to the final planned lane number and the final planned distance.

9. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle lane planning method as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the lane planning method for a vehicle as described in any one of claims 1-6.

Images