Vehicle lane planning method and device, vehicle and storage medium

Abstract

The invention relates to the technical field of automatic driving, in particular to a lane planning method and device for a vehicle, the vehicle and a storage medium, and the method comprises the steps: obtaining the current road curvature of a road where the current vehicle is located, the current environment perception calculation power proportion and the current lane planning calculation duration; determining an optimal lane planning strategy of the current vehicle according to the current lane planning calculation duration, the current road curvature and the current environment perception calculation power proportion; and 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. Therefore, the problems that in the related technology, when lane planning is conducted on some complex driving scenes, the output real-time performance of the lane planning result is poor, a dynamic optimization method is lacked in lane planning, and consequently the safety of automatic driving is low are solved, the real-time performance of lane planning is greatly improved, and then the safety of automatic driving is improved.

Description

Technical Field

[0001] 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

[0002] In the related art, when performing lane planning, generally planning is performed from the first starting lane to N target lanes respectively to obtain N lane planning results. If the time required to perform a search is T, the time required to perform N lane planning is N*T.

[0003] However, for some more complex driving scenarios, the output real-time performance of lane planning results in related technologies is poor, and lane planning lacks dynamic optimization methods, resulting in low safety of autonomous driving, which needs to be solved urgently. Summary of the invention

[0004] The present application provides a vehicle lane planning method, device, vehicle and storage medium to solve the problems in the related art that, when performing lane planning for some more complex driving scenarios, the output real-time performance of lane planning results is poor, and the lane planning lacks a dynamic optimization method, resulting in low safety of autonomous driving. This greatly improves the real-time performance of lane planning, thereby improving the safety of autonomous driving.

[0005] The first aspect of the present application provides a vehicle lane planning method, comprising the following steps:

[0006] Obtain 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; 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; adjust the current lane planning distance and / or the current lane planning number of the current vehicle based on the current optimal lane planning strategy.

[0007] Optionally, in some embodiments, 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:

[0008] 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;

[0009] 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;

[0010] The optimal lane planning strategy is generated according to the final planned lane number and the final planned distance.

[0011] 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 when the current lane planning calculation duration 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.

[0012] 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 a new lane planning calculation duration for the current vehicle; if the new lane planning calculation duration is greater than or equal to the first preset duration, reducing the first target planned lane number and shortening the first target planning distance according to the preset strategy; adjusting the current lane planning number and / or the current lane planning distance according to the shortened first target planning lane number.

[0013] Optionally, in some embodiments, after obtaining the current road curvature, the current environment perception computing power ratio and the current lane planning calculation time of the road where the current vehicle is located, it also includes:

[0014] 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;

[0015] 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;

[0016] Among them, the second preset time length is shorter than the first preset time length, the third target planned lane number is larger than the currently planned vehicle number, the third target planned distance is larger than the currently planned distance, the fourth target planned lane number is larger than the currently planned vehicle number, and the fourth target planned distance is larger than the currently planned distance.

[0017] 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.

[0018] A second aspect of the present application provides a vehicle lane planning device, including:

[0019] 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.

[0020] Optionally, in some embodiments, the determining module includes:

[0021] 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;

[0022] 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;

[0023] A generating unit is used to generate the optimal lane planning strategy according to the final planned lane number and the final planned distance.

[0024] 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:

[0025] Obtain the number of calculations within a second preset time period when 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.

[0026] 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:

[0027] An acquisition unit, used to acquire a new lane planning calculation duration of the current vehicle;

[0028] A first planning unit, configured to reduce the number of the first target planning lanes and shorten the first target planning 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;

[0029] The first adjustment unit is used 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.

[0030] Optionally, in some embodiments, after obtaining the current road curvature, the current environment perception computing power ratio and the current lane planning calculation duration of the road where the current vehicle is located, the acquisition module further includes:

[0031] A 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 to match the fourth target planned lane number and the fourth target planned distance of the current vehicle according to the current environment perception computing power ratio;

[0032] 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;

[0033] Among them, the second preset time length is shorter than the first preset time length, the third target planned lane number is larger than the currently planned vehicle number, the third target planned distance is larger than the currently planned distance, the fourth target planned lane number is larger than the currently planned vehicle number, and the fourth target planned distance is larger than the currently planned distance.

[0034] Optionally, in some embodiments, after obtaining the current road curvature, the current environment perception computing power ratio and the current lane planning calculation duration of the road where the current vehicle is located, the acquisition module further includes:

[0035] The second planning unit is used to maintain the lane planning strategy of the current vehicle unchanged when the current lane planning calculation duration is greater than or equal to the second preset duration and the current lane planning calculation duration is less than the first preset duration.

[0036] A 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.

[0037] The fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the vehicle lane planning method as described in the above embodiment.

[0038] 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 according to the current road curvature and / or the current environmental perception computing power ratio, and 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. This solves the problems in the related technology that when performing lane planning for some more complex driving scenarios, 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. This greatly improves the real-time performance of lane planning, thereby improving the safety of autonomous driving.

[0039] 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 the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] 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:

[0041] Figure 1 A flowchart of a vehicle lane planning method provided according to an embodiment of the present application;

[0042] Figure 2 A flowchart of a vehicle lane planning method according to an embodiment of the present application;

[0043] Figure 3 A block diagram of a lane planning device for a vehicle provided according to an embodiment of the present application;

[0044] Figure 4 It is a block diagram of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] Embodiments of the present application are described in detail below, and examples of the embodiments 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.

[0046] The following describes the lane planning method, device, vehicle and storage medium of the vehicle of the embodiment of the present application with reference to the accompanying drawings. In view of the above-mentioned 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 vehicle lane planning method, in which 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 are obtained; 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; 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 that the output real-time performance of the lane planning results is poor when performing lane planning for some more complex driving scenes in the related technology, and the lane planning lacks a dynamic optimization method, resulting in low safety of autonomous driving, etc., is solved, thereby greatly improving the real-time performance of lane planning, and thus improving the safety of autonomous driving.

[0047] Before introducing the embodiment of the lane planning method for the vehicle of the present application, a brief introduction is first given to the lane planning algorithm involved in the present application.

[0048] At present, autonomous driving algorithms generally include positioning algorithms, perception algorithms, prediction algorithms, road planning algorithms, lane planning algorithms, decision algorithms, local planning algorithms, and control algorithms, etc. Among them, the output resolution of lane planning results means that lane planning will give a path that the vehicle will take next. The path is a collection of points, that is, the output resolution refers to the distance between one point and another point in the path; the planning distance refers to the distance between the starting point of lane planning and the end point of lane planning when performing lane planning.

[0049] On a cost-constrained hardware platform, due to limited computing resources, there are great challenges in the timeliness of the algorithm output when planning autonomous driving. As introduced in the above background technology, the current lane planning algorithm is to plan a lane with a forward fixed length as the target point from the lane where the vehicle is currently located. For example, when driving, it is necessary to consider the approximate location of the vehicle and how to drive past it 100 meters in the future (the distance to be considered on the highway may be greater than 100 meters, while on crowded roads, the distance to be considered may be less than 100 meters).

[0050] 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 results of lane planning are more in line with the current state of the vehicle, thereby improving the real-time performance of lane planning.

[0051] Specifically, Figure 1 A flowchart of a vehicle lane planning method provided in an embodiment of the present application.

[0052] like Figure 1 As shown, the lane planning method for the vehicle includes the following steps:

[0053] 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 current vehicle is located are obtained.

[0054] 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 the prediction module of the autonomous driving to the total computing power of the autonomous driving platform in the current environment 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 repeated here to avoid redundancy.

[0055] 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 of the vehicle 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 busy intersection or other scenario, the computing power requirements of the perception module and the prediction module in the autonomous driving algorithm increase. 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.

[0056] Therefore, before planning the lane, this application needs to obtain the current road curvature and the current environmental perception computing power ratio of the road where the current vehicle is located to match the appropriate lane planning strategy. This application also needs to obtain the current lane planning calculation time. When the current lane planning calculation time is too long, the lane planning strategy is adjusted in time to improve the efficiency of lane planning.

[0057] 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.

[0058] 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.

[0059] Specifically, the present application is based on the current lane planning calculation time, current road curvature and current environmental perception computing power ratio obtained in step S101, and matches them with the lane planning strategy provided by the present application to obtain the best lane planning strategy for the current vehicle. The best lane planning strategy can make the lane planning result more consistent with the current vehicle status and improve the real-time performance of lane planning. The following examples specifically illustrate the multiple lane planning strategies provided by the present application.

[0060] 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 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; generating the optimal lane planning strategy based on the final planned lane number and the final planned distance.

[0061] 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.

[0062] It is understandable that the traffic volume in high-speed scenarios or urban main road scenarios is large, and the vehicle speed in crowded urban intersection scenarios, such as busy urban intersections, 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 output results of autonomous driving lane planning 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 where computing power resources will be reduced.

[0063] 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.

[0064] Specifically, this application calibrates the number of planned lanes, that is, the first target number of planned lanes obtained by matching the current road curvature and the second target number of planned lanes 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 number of planned lanes, the first target planning distance, the second target number of planned lanes, and the second target planning distance, and those skilled in the art can set them according to actual conditions.

[0065] 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 calculation method of the final planned distance is similar to the above-mentioned method of the final planned lane number, and will not be repeated here to avoid redundancy.

[0066] 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 number of planned lanes is 4, the first target planning distance is 80 meters, and the current environmental perception computing power accounts for 80%. Through matching, the second target number of planned lanes is 2, and the second target planning distance is 60 meters. Therefore, three lane planning strategies are obtained, namely, determining the final number of planned lanes to be 4 and the final planning distance to be 80 meters; or determining the final number of planned lanes to be 2 and the final planning distance to be 60 meters; or determining the final number of planned lanes to be 3 and the final planning distance to be 70 meters, and then selecting the best lane planning strategy according to the actual situation.

[0067] Therefore, this application can match the optimal number of planned lanes and the final planned distance according to the current lane planning calculation time, the current road curvature and the current environmental perception computing power ratio, so as to obtain the optimal lane planning strategy.

[0068] 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 less than the second preset time, matching the third target planned lane number and the third target planned distance of the current vehicle according to the current road curvature, and matching 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; 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.

[0069] 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 travels at a fast speed. 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.

[0070] 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 are matched based on the current environmental 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, this 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.

[0071] Furthermore, the present application may use the number of matched third target planned lanes as the final number of planned lanes, or use the number of matched fourth target planned lanes as the final number of planned lanes, or calculate the average of the third target planned lanes and the fourth target planned lanes, and use the average of the two as the final number of planned lanes, without specific limitation. Optionally, the method for calculating the final planned distance is similar to the method for calculating the final number of planned lanes, and will not be described here to avoid redundancy.

[0072] 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, the final planned lane number is determined to be 4 and the final planned distance is 80 meters; or the final planned lane number is determined to be 4 and the final planned distance is 100 meters; or the final planned lane number is determined to be 4 and the final planned distance is 90 meters, and then the best lane planning strategy is selected according to the actual situation.

[0073] Therefore, when the vehicle is in a situation where the curvature is small and the environmental perception computing power accounts for a small proportion, the present application can appropriately increase the search distance and number of times, dynamically adjust the planning length of lane planning, make the lane planning result more in line with the current vehicle status, and improve the real-time performance of lane planning.

[0074] 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.

[0075] It should be noted that after obtaining the current lane planning calculation time, the present application needs to judge the time, that is, to compare the current lane planning calculation time with the first preset time and the second preset time set by the present application, thereby obtaining the range of the current lane planning calculation time, and then planning the lane to improve the timeliness of lane planning.

[0076] 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.

[0077] 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 the second preset time length when the current lane planning calculation duration 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.

[0078] Based on the above embodiments, it can be known that the condition for lane planning is to compare the current lane planning calculation time with the first preset time. When the current lane planning calculation time exceeds the threshold, the lane planning strategy is started. However, this application takes into account that the system may make misjudgments, so it is set to plan the lanes when lane delays occur multiple times, effectively avoiding misjudgments and increasing the accuracy of lane planning.

[0079] Specifically, the present application sets a second preset duration, and counts the number of times the current lane planning calculation duration is greater than the first preset duration within the second preset duration. If the number is less than the preset number, it is determined that lane planning is not required at this time, and the lane planning strategy of the current vehicle needs to be maintained unchanged. As a result, the present application can save computing resources and ensure the stability of the system when lane planning is not required. In addition, the present application does not make specific restrictions on the preset number of calculation times, and those skilled in the art can set it according to actual conditions.

[0080] In step S103, the current lane planning distance and / or the current lane planning number of the current vehicle is adjusted according to the current optimal lane planning strategy.

[0081] Based on the above embodiments, the present application can match the current optimal lane planning strategy according to the current road curvature and the current proportion of environmental perception computing power, combined with the delayed statistical data 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 result more in line with the current vehicle status and improving the real-time performance of lane planning.

[0082] 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 a new lane planning calculation duration for the current vehicle; if the new lane planning calculation duration is greater than or equal to a first preset duration, 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 the current lane planning distance according to the shortened first target planning lane number.

[0083] 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 cause inconvenience to users. 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.

[0084] 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.

[0085] Specifically, Figure 2 A flow chart of a vehicle lane planning method according to an embodiment of the present application is shown in FIG. Figure 2 As shown, the lane planning method for the vehicle may include the following steps:

[0086] Step S201, calculating that the vehicle is currently in scene scen1 (a road intersection with many pedestrians, a main road in a city with heavy traffic, a smooth highway, a curved road around the sea, etc.) through the current position or visual perception;

[0087] Step S202, monitoring the delay of outputting the lane planning results and making statistics;

[0088] 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;

[0089] Step S204, changing the distance and number of lane planning according to scene scen1;

[0090] Step S205, combining the scene where the vehicle is located and the delayed statistical data of the output results, according to the matching of 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; when the vehicle is in a city trunk road scene, due to the heavy traffic volume, appropriately reduce the search distance and number; when the vehicle is in a crowded city intersection scene, due to the heavy perception prediction load, appropriately reduce the search distance and number; when the vehicle is in a coastal highway scene, due to the large road curvature, appropriately reduce the search distance;

[0091] Step S206: perform lane planning according to the optimal lane planning strategy.

[0092] 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 factor of road curvature to dynamically adjust the planning length of lane planning, solving the problems in the related technology that the real-time output of the 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. The lane planning is controlled in real time according to the scene where the vehicle is located, so that the result of lane planning is more in line with the current state of the vehicle, and the timeliness of lane planning is improved.

[0093] 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.

[0094] Figure 3 It is a block diagram of a lane planning device for a vehicle according to an embodiment of the present application.

[0095] like Figure 3 As shown, the vehicle lane planning device 10 includes: an acquisition module 100 , a determination module 200 and a planning module 300 .

[0096] 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 where 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.

[0097] Optionally, in some embodiments, the determination module 200 includes: a first matching unit, a determination unit and a generation unit.

[0098] 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 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; 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.

[0099] 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:

[0100] Obtain the number of calculations within the second preset time period when 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.

[0101] 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.

[0102] Among them, the acquisition unit is used to obtain the new lane planning calculation duration 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 a preset strategy when the new lane planning calculation duration is greater than or equal to the first preset duration; the first adjustment unit is used to adjust the current lane planning number according to the shortened first target planning lane number and / or adjust the current lane planning distance according to the shortened first target planning distance.

[0103] Optionally, in some embodiments, after obtaining the current road curvature of the road on which the current vehicle is located, the current environmental perception computing power ratio and the current lane planning calculation time, the acquisition module 100 further includes: a second matching unit and a second adjustment unit.

[0104] 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.

[0105] Optionally, in some embodiments, after obtaining the current road curvature of the road on which the current vehicle is located, the current environmental perception computing power ratio and the current lane planning calculation time, the acquisition module 100 further includes: a second planning unit.

[0106] 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.

[0107] 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.

[0108] According to the lane planning device for a vehicle 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 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 in combination with the environmental perception computing power ratio of the vehicle's environment, that is, the system's computing power monitoring, and the factor of road curvature, solves the problems in the related technology that the real-time output of the 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, and the like, and controls the lane planning in real time according to the scene where the vehicle is located, so that the results of lane planning are more in line with the current state of the vehicle, and the timeliness of lane planning is improved.

[0109] Figure 4 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0110] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0111] When the processor 402 executes the program, the vehicle lane planning method provided in the above embodiment is implemented.

[0112] Furthermore, the vehicle also includes:

[0113] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0114] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0115] 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.

[0116] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through 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, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0117] 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.

[0118] 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.

[0119] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned vehicle lane planning method is implemented.

[0120] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. 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 are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0121] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0122] 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 the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0123] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0124] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0125] 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, configured to determine an optimal lane planning strategy for the current vehicle according to the current lane planning calculation time, the current road curvature, and the current environmental 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.

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