CN119527339A - Vehicle lane planning method, device, vehicle and storage medium - Google Patents
Vehicle lane planning method, device, vehicle and storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
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- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
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- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
- B60W40/072—Curvature of the road
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
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Abstract
The application 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, wherein the method comprises the steps of obtaining the current road curvature of a road where a current vehicle is located, the current environment perception calculation power duty ratio and the current lane planning calculation time length; and 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. Therefore, the problems that in the related art, when lane planning is carried out on some more complex driving scenes, the output instantaneity of the lane planning result is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low and the like are solved, so that the instantaneity of the lane planning is greatly improved, and the safety of automatic driving is further improved.
Description
Technical Field
The present application relates to the field of automatic driving technologies, and in particular, to a lane planning method and apparatus for a vehicle, and a storage medium.
Background
In the related art, when a lane is planned, generally, N lane planning results are obtained by planning from a first starting lane to N target lanes respectively, and if a time T required for searching is performed once, a time required for planning N lanes once is n×t.
However, for some more complex driving scenarios, the output real-time performance of the lane planning result in the related technology is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low, and the problem needs to be solved.
Disclosure of Invention
The application provides a lane planning method and device for a vehicle, the vehicle and a storage medium, which are used for solving the problems that in the related art, when lane planning is carried out on some more complex driving scenes, the output instantaneity of a lane planning result is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low, and the like, thereby greatly improving the instantaneity of the lane planning and further improving the safety of automatic driving.
An embodiment of a first aspect of the present application provides a lane planning method for a vehicle, including the steps of:
The method comprises the steps of obtaining a current road curvature, a current environment perception calculation force ratio and a current lane planning calculation time of a road where a current vehicle is located, determining an optimal lane planning strategy of the current vehicle according to the current lane planning calculation time, the current road curvature and the current environment perception calculation force ratio, and adjusting a current lane planning distance and/or a current lane planning number of the current vehicle according to the current optimal lane planning strategy.
Optionally, in some embodiments, the determining the optimal lane planning strategy for the current vehicle according to the current lane planning computation time period, the current road curvature, and the current environment-aware computation power duty cycle includes:
If the calculated time length of the current lane planning is greater than or equal to the first preset time length, matching a first target planned lane number and a first target planned distance of the current vehicle according to the current road curvature, and matching a second target planned lane number and a second target planned distance of the current vehicle according to the current environment perceived computing force duty ratio, wherein the first target planned lane number is smaller than the current planned vehicle number, the first target planned distance is smaller than the current planned distance, the second target planned lane number is smaller than the current planned vehicle number, and the second target planned distance is smaller 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;
and generating the optimal lane planning strategy according to the number of the final planned lanes and the final planned distance.
Optionally, in some embodiments, before the first target planned lane number and the first target planned distance of the current vehicle are matched according to the current road curvature, the method further includes obtaining a calculation number of times that the current lane planning calculation time period is longer than the first preset time period in a second preset time period, and if the calculation number of times is smaller than the preset number of times, maintaining the lane planning strategy of the current vehicle unchanged.
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 method further includes obtaining a new lane planning calculation time length of the current vehicle, reducing the first target planning lane number according to a preset strategy and shortening the first target planning distance if the new lane planning calculation time length is greater than or equal to the first preset time length, and adjusting the current lane planning number according to the shortened first target planning lane number and/or the shortened first target planning distance.
Optionally, in some embodiments, after obtaining the current road curvature, the current environment-aware computing power duty ratio, and the current lane planning computing duration of the road on which the current vehicle is located, the method further includes:
If the calculated time length of the current lane planning is smaller than a second preset time length, matching the number of third target planning lanes and the third target planning distance of the current vehicle according to the curvature of the current road, and matching the number of fourth target planning lanes and the fourth target planning distance of the current vehicle according to the current environment perceived calculated force ratio;
Adjusting the current lane planning number according to the third target planning lane number and/or the fourth target planning vehicle number, and/or adjusting the current lane planning distance according to the first target planning distance and/or the second target planning distance;
the second preset time length is smaller than the first preset time length, the number of the third target planning lanes is larger than the number of the current planning vehicles, the third target planning distance is larger than the current planning distance, the number of the fourth target planning lanes is larger than the number of the current planning vehicles, and the fourth target planning distance is larger than the current planning distance.
Optionally, in some embodiments, after obtaining the current road curvature, the current environment awareness calculation power ratio and the current lane planning calculation time length of the road where the current vehicle is located, the method further includes maintaining the lane planning strategy of the current vehicle unchanged if the current lane planning calculation time length is greater than or equal to the second preset time length and the current lane planning calculation time length is less than the first preset time length.
An embodiment of the second aspect of the present application provides a lane planning apparatus for a vehicle, including:
The vehicle-mounted intelligent road planning system comprises an acquisition module, a determination module and a planning module, wherein the acquisition module is used for acquiring the current road curvature, the current environment perception calculation force ratio and the current lane planning calculation time length of a road where a current vehicle is located, the determination module is used for determining the optimal lane planning strategy of the current vehicle according to the current lane planning calculation time length, the current road curvature and the current environment perception calculation force ratio, and the planning module is used for 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.
Optionally, in some embodiments, the determining module includes:
The first matching unit is used for matching a first target planned lane number and a first target planned distance of the current vehicle according to the current road curvature when the time length of the current lane planning calculation is greater than or equal to the first preset time length, and matching a second target planned lane number and a second target planned distance of the current vehicle according to the current environment perception calculation force duty ratio, wherein the first target planned lane number is smaller than the current planned vehicle number, the first target planned distance is smaller than the current planned distance, the second target planned lane number is smaller than the current planned vehicle number, and the second target planned distance is smaller than the current planned distance;
The determining unit is used for 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;
and the generating unit is used for generating the optimal lane planning strategy according to the number of the final planned lanes and the final planned distance.
Optionally, in some embodiments, before matching the first target planned number of lanes and the first target planned distance of the current vehicle according to the current road curvature, the first matching unit is further configured to:
Acquiring the calculated times of the current lane planning calculation time length longer than the first preset time length in a second preset time length; and when the calculated times are smaller than preset times, maintaining the lane planning strategy of the current vehicle unchanged.
Optionally, in some embodiments, after adjusting the current lane planning distance and/or the current number of lane plans of the current vehicle according to the current optimal lane planning strategy, the planning module further comprises:
An obtaining unit, configured to obtain a new lane planning calculation duration of the current vehicle;
The first planning unit is used for reducing the number of the first target planned lanes according to a preset strategy and shortening the first target planning distance when the calculated time length of the new lane planning is longer than or equal to the first preset time length;
The first adjusting unit is used for adjusting the current lane planning quantity according to the shortened first target planning lane quantity and/or adjusting the current lane planning distance according to the shortened first target planning distance.
Optionally, in some embodiments, after acquiring the current road curvature, the current environment-aware computing power duty cycle, and the current lane-planning computing duration of the road on which the current vehicle is located, the acquiring module further includes:
The second matching unit is used for matching the number of the third target planned lanes and the third target planned distance of the current vehicle according to the current road curvature when the calculated time length of the current lane planning is smaller than a second preset time length, and matching the number of the fourth target planned lanes and the fourth target planned distance of the current vehicle according to the current environment perceived computing force duty ratio;
The second adjusting unit is used for adjusting the current lane planning quantity according to the third target planning lane quantity and/or the fourth target planning vehicle quantity and/or adjusting the current lane planning distance according to the first target planning distance and/or the second target planning distance;
the second preset time length is smaller than the first preset time length, the number of the third target planning lanes is larger than the number of the current planning vehicles, the third target planning distance is larger than the current planning distance, the number of the fourth target planning lanes is larger than the number of the current planning vehicles, and the fourth target planning distance is larger than the current planning distance.
Optionally, in some embodiments, after acquiring the current road curvature, the current environment-aware computing power duty cycle, and the current lane-planning computing duration of the road on which the current vehicle is located, the acquiring module further includes:
And the second planning unit is used for maintaining the lane planning strategy of the current vehicle unchanged when the current lane planning calculation time length is longer than or equal to the second preset time length and the current lane planning calculation time length is smaller than the first preset time length.
An embodiment of a third aspect of the present application provides a vehicle, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the lane planning method of the vehicle according to the above embodiment.
An embodiment of a fourth aspect of the present application provides a computer-readable storage medium having stored thereon a computer program for execution by a processor for implementing the lane planning method of a vehicle as described in the above embodiment.
Therefore, when the calculated time length of the current lane planning is greater than or equal to a certain time length, the application can calculate the optimal lane planning strategy of the current vehicle according to the curvature of the current road and/or the duty ratio of the current environment perceived computing force, and adjust the current lane planning distance and/or the current lane planning quantity of the current vehicle according to the current optimal lane planning strategy. Therefore, the problems that in the related art, when lane planning is carried out on some more complex driving scenes, the output instantaneity of the lane planning result is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low and the like are solved, so that the instantaneity of the lane planning is greatly improved, and the safety of automatic driving is further improved.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
fig. 1 is a flowchart of a lane planning method for a vehicle according to an embodiment of the present application;
FIG. 2 is a flow chart of a lane planning method of a vehicle according to one embodiment of the application;
Fig. 3 is a schematic block diagram of a lane planning apparatus for a vehicle according to an embodiment of the present application;
Fig. 4 is a block schematic diagram of a vehicle according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The following describes a lane planning method, a lane planning device, a lane planning vehicle and a lane planning storage medium for a vehicle according to embodiments of the present application with reference to the accompanying drawings. Aiming at the problems that in the background art, when a lane planning is carried out on some more complex driving scenes, the output instantaneity of a lane planning result is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low, and the like, the application provides a lane planning method of a vehicle, wherein the method is used for acquiring the current road curvature, the current environment perception calculation power occupation ratio and the current lane planning calculation time length of a road where a current vehicle is located; and 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. Therefore, the problems that in the related art, when lane planning is carried out on some more complex driving scenes, the output instantaneity of the lane planning result is poor, and the lane planning lacks a dynamic optimization method, so that the safety of automatic driving is low and the like are solved, so that the instantaneity of the lane planning is greatly improved, and the safety of automatic driving is further improved.
Before describing an embodiment of the lane planning method of the vehicle of the present application, a lane planning algorithm according to the present application will be briefly described.
Currently, autopilot algorithms generally include positioning algorithms, sensing algorithms, prediction algorithms, road planning algorithms, lane planning algorithms, decision algorithms, local planning algorithms, control algorithms, and the like. The output resolution of the lane planning result refers to that the lane planning gives a path for a vehicle to travel next, wherein the path is a set of one point and one point, namely the output resolution refers to the distance between one point and the other point in the path; the planned distance is the distance between the start point of the lane planning and the end point of the lane planning when the lane planning is performed.
On a hardware platform with limited cost, due to limited computational power resources, the output timeliness of an algorithm is more challenging when automatic driving planning is performed. As described in the background art above, the current lane planning algorithm is to plan a lane plan with a fixed length of target points from the lane where the current vehicle is located, for example, when driving, consider the future 100m (the distance to be considered may be greater than 100m at high speed, and the distance to be considered may be less than 100m on a crowded road), and how the vehicle is driven.
The application considers that the types of roads for running the automatic driving vehicles are various, including high speed, urban arterial roads, rural roads, urban roadways, mountain curves, bazaar roads, crossroads and the like, and the requirements on the timeliness of the lane planning algorithm are different in different types of scenes, thereby, according to the lane planning method of the vehicle, according to the environment of the vehicle and multiple factors such as calculation power monitoring and road curvature, the planning length of the lane planning is dynamically adjusted, and indexes such as resolution of result output are used, so that the result of the lane planning is more in line with the current state of the vehicle, and the instantaneity of the lane planning is improved.
Specifically, fig. 1 is a flow chart of a lane planning method for a vehicle according to an embodiment of the present application.
As shown in fig. 1, the lane planning method of the vehicle includes the steps of:
In step S101, a current road curvature, a current environment-aware computing power duty ratio, and a current lane planning computing duration of a road on which a current vehicle is located are acquired.
Based on the description in the related art, the current environment sensing calculation force ratio in the embodiment of the application refers to the ratio of the calculation force of the sensing module and the prediction module of the automatic driving to the total calculation force of the automatic driving platform in the current environment scene of the vehicle. The current environment can be identified by positioning to obtain the current position of the vehicle, or by visual perception, namely, the current scene of the vehicle is deduced by taking a camera as a sensor to input the environment information of the vehicle, the current lane planning calculation time length in the embodiment of the application refers to the duration of the automatic driving platform when lane planning is started, and the calculation method of the current road curvature in the embodiment of the application can refer to the related technology, so that redundancy is avoided and no description is repeated here.
It will be appreciated that the output efficiency of the results is related to multiple factors in the course of lane planning. The application considers that the vehicle has larger road curvature in certain scenes, such as a sea-going highway, and has smaller road curvature in high-speed and other road scenes. In addition, when the automatic driving platform performs lane planning, the scenes of the vehicles are different, the calculation force loads for the lane planning are different, if the vehicles are in the scenes of a luxurious intersection and the like, the calculation force demands of the sensing module and the prediction module in the automatic driving algorithm are increased, and therefore, the influence on the output timeliness of the lane planning result is increased as the current environment sensing calculation force ratio is larger.
Therefore, the present application needs to acquire the current road curvature and the current environment-aware computing power ratio of the road where the current vehicle is located before planning the lane, so as to match with a proper lane planning strategy. The application also needs to acquire the current lane planning calculation time length, and when the current lane planning calculation time length is too long, the lane planning strategy is adjusted in time, so that the lane planning efficiency is improved.
In step S102, an optimal lane planning strategy for the current vehicle is determined based on the current lane planning computation time, the current road curvature, and the current ambient awareness computation power ratio.
In the embodiment of the application, the lane planning strategy mainly comprises two aspects of the distance of the current lane planning and the number of the current lane planning.
Specifically, the present application obtains the optimal lane planning strategy of the current vehicle by matching with the lane planning strategy provided by the present application based on the calculated time length of the current lane planning, the curvature of the current road and the perceived computing power duty ratio of the current environment obtained in the step S101, and the optimal lane planning strategy can enable the result of the lane planning to be more consistent with the state of the current vehicle, and improve the instantaneity of the lane planning. The following examples specifically illustrate a number of lane planning strategies provided by the present application.
Optionally, in some embodiments, the optimal lane planning strategy of the current vehicle is determined according to the current lane planning calculation time length, the current road curvature and the current environment awareness calculation force ratio, and the optimal lane planning strategy comprises the steps of matching a first target planning lane number and a first target planning distance of the current vehicle according to the current road curvature and matching a second target planning lane number and a second target planning distance of the current vehicle according to the current environment awareness calculation force ratio if the current lane planning calculation time length is greater than or equal to a first preset time length, wherein the first target planning lane number is smaller than the current planning vehicle number, the first target planning distance is smaller than the current planning distance, the second target planning lane number is smaller than the current planning vehicle number, the second target planning distance is smaller than the current planning distance, determining a final planning lane number of the current vehicle according to the first target planning lane number and/or the second target planning lane number, and generating the optimal lane planning strategy according to the final planning lane number and the final planning distance.
It should be noted that, the present application provides a condition for adjusting the lane planning strategy, that is, after the current lane planning calculation time length is obtained in step S101, the current lane planning calculation time length is compared with the first preset time length set in the present application, and when the current lane planning calculation time length exceeds the preset value, it is determined that the timeliness of the result output is not satisfied at this time, and the lane planning strategy needs to be adjusted to improve the efficiency of lane planning.
It can be understood that the traffic flow of the high-speed scene or the urban arterial road scene is larger, and the vehicle speed is slower in the urban crowded intersection scene, such as the urban busy intersection, so that the computational power demands of the sensing module and the prediction module are increased, and the computational power resources of the system for lane planning are reduced, therefore, in order to balance the computational power resources of the system, the automatic driving lane planning output result is more timely.
In addition, considering that the speed of a user may also drive very slowly on an unoccupied road section, the lane planning strategy of the application is to match according to the current road curvature and the current environment perceived computing power ratio so as to obtain a more accurate and reasonable lane planning strategy.
The method and the device calibrate the number of the planned lanes, namely the number of the first target planned lanes obtained through current road curvature matching and the number of the second target planned lanes obtained through current environment perception calculation force duty ratio matching in the embodiment, and are smaller than the number of the current planned vehicles. The present application is not specifically limited to the number of first target planned lanes, the first target planned distance, the number of second target planned lanes, and the second target planned distance, and can be set by a person skilled in the art according to actual situations.
Further, the present application may take the number of the first target planned lanes matched as the number of the final planned lanes, or the number of the second target planned lanes matched as the number of the final planned lanes, or calculate an average value of the number of the first target planned lanes and the number of the second target planned lanes, and take the average value of the number of the first target planned lanes and the number of the second target planned lanes as the number of the final planned lanes, which is not specifically limited herein. Optionally, the calculation of the final planned distance is similar to the above-mentioned manner of the number of final planned lanes, and will not be described here again to avoid redundancy.
For example, the first preset time period is 60 seconds, the number of current planned vehicles is 5, and the current planned distance is 100 meters. After the calculation time of the current lane planning exceeds 60 seconds, the system judges that the curvature value is overlarge when the current road curvature is 500 meters, the number of first target planning lanes is 4 through matching, the first target planning distance is 80 meters, the current environment perceived calculated force ratio is 80%, the number of second target planning lanes is 2 through matching, and the second target planning distance is 60 meters. Three lane planning strategies are obtained, namely the number of the finally planned lanes is determined to be 4, the finally planned distance is 80 meters, the number of the finally planned lanes is determined to be 2, the finally planned distance is determined to be 60 meters, or the number of the finally planned lanes is determined to be 3, the finally planned distance is determined to be 70 meters, and then the optimal lane planning strategy is selected according to actual conditions.
Therefore, the optimal lane planning strategy can be obtained according to the optimal number of the planned lanes and the final planned distance which are matched according to the calculated time length of the current lane planning, the current road curvature and the current environment perception calculation force ratio.
Optionally, in some embodiments, after obtaining the current road curvature, the current environment awareness calculation force ratio and the current lane planning calculation time length of the road where the current vehicle is located, the method further comprises the steps of matching a third target planning lane number and a third target planning distance of the current vehicle according to the current road curvature if the current lane planning calculation time length is smaller than a second preset time length, matching a fourth target planning lane number and a fourth target planning distance of the current vehicle according to the current environment awareness calculation force ratio, adjusting the current lane planning number according to the third target planning lane number and/or the fourth target planning vehicle number, and/or adjusting the current lane planning distance according to the first target planning distance and/or the second target planning distance, wherein the second preset time length is smaller than the first preset time length, the third target planning lane number is larger than the current planning vehicle number, the third target planning distance is larger than the current planning distance, and the fourth target planning lane number is larger than the current planning vehicle number, and the fourth target planning distance is larger than the current planning distance.
It can be understood that in the expressway or trunk scene, the curvature of the road is smaller, the occupation of the environmental perception calculation force is smaller, and the running speed of the vehicle is faster, so that considering the calculation force balance of the system, the distance of the lane planning needs to be properly prolonged under the condition so as to be more in line with the current state of the vehicle, and the real-time performance of the lane planning is improved.
Specifically, the application sets a second preset time period, which is smaller than the first preset time period. And when the calculated time length of the current lane planning is smaller than the second preset time length, the number of the third target planning lanes and the third target planning distance can be obtained through the current road curvature matching, and the calculated force duty ratio is matched to the number of the fourth target planning lanes and the fourth target planning distance based on the current environment perception. In this embodiment, the number of the third target planned lane and the number of the fourth target planned lane are both greater than the number of the current planned vehicles, and the third target planned distance and the fourth target planned distance are both greater than the current planned distance. In addition, the present application is not specifically limited to the number of third target planned lanes, the third target planned distance, the number of fourth target planned lanes and the fourth target planned distance, and can be set by a person skilled in the art according to actual situations.
Further, the present application may take the number of the matched third target planned lanes as the number of the final planned lanes, or the number of the matched fourth target planned lanes as the number of the final planned lanes, or calculate an average value of the number of the third target planned lanes and the number of the fourth target planned lanes, and take the average value of the number of the third target planned lanes and the number of the fourth target planned lanes as the number of the final planned lanes, which is not specifically limited herein. Optionally, the calculation of the final planned distance is similar to the above-mentioned manner of the number of final planned lanes, and will not be described here again to avoid redundancy.
For example, when the current planning vehicle number is 2, the current planning distance is 60 meters, the second preset time length is 50 seconds, when the current lane planning calculation time length is 30 seconds, the number of the matched third target planning lanes is 4, the third target planning distance is 80 meters, the current environment perception calculation force accounts for 40%, the number of the matched fourth target planning lanes is 4, and the fourth target planning distance is 100 meters, so that three lane planning strategies are obtained, namely the number of the final planning lanes is determined to be 4, the final planning distance is 80 meters, the number of the final planning lanes is determined to be 4, the final planning distance is 100 meters, or the number of the final planning lanes is determined to be 4, the final planning distance is 90 meters, and the optimal lane planning strategy is selected according to practical conditions.
Therefore, the application can properly increase the searching distance and the searching times under the condition that the curvature of the vehicle is smaller and the environmental perception calculation force is smaller, dynamically adjust the planning length of the lane planning, lead the result of the lane planning to be more in line with the current state of the vehicle and improve the real-time performance of the lane planning.
Optionally, in some embodiments, after obtaining the current road curvature, the current environment awareness calculation power ratio and the current lane planning calculation time length of the road on which the current vehicle is located, the method further includes maintaining the lane planning strategy of the current vehicle unchanged if the current lane planning calculation time length is greater than or equal to the second preset time length and the current lane planning calculation time length is less than the first preset time length.
After the current lane planning calculation time length is obtained, the time length needs to be judged, namely the current lane planning calculation time length is compared with the first preset time length and the second preset time length, so that the range of the current lane planning calculation time length can be obtained, and the lane is planned, so that the timeliness of lane planning is improved.
Specifically, in this embodiment, the present application considers that the delay of the current lane planning is improved, but in the case that the delay does not exceed a certain amount, in order to avoid wasting resources, the calculation load of the system is balanced, so when the calculation time of the current lane planning is between the second preset time and the first preset time in this embodiment of the present application, the lane planning strategy of the current vehicle is maintained unchanged.
Optionally, in some embodiments, before matching the number of first target planned lanes and the first target planned distance of the current vehicle according to the current road curvature, the method further includes obtaining a calculation number of times that the current lane planning calculation time is longer than the first preset time in the second preset time, and if the calculation number is smaller than the preset number of times, maintaining the lane planning strategy of the current vehicle unchanged.
Based on the above embodiment, it can be known that the condition for performing the lane planning is to compare the calculated time length of the current lane planning with the first preset time length, and when the calculated time length of the current lane planning exceeds the threshold value, start the lane planning strategy. However, the application considers that the system can possibly generate erroneous judgment, so that the lane is planned under the condition that lane delay is generated for a plurality of times, the occurrence of the erroneous judgment is effectively avoided, and the accuracy of lane planning is increased.
Specifically, the method and the device set a second preset time length, count the times that the calculated time length of the current lane planning is longer than the first preset time length in the second preset time length, and judge that the lane planning is not needed at the moment and keep the lane planning strategy of the current vehicle unchanged if the times are smaller than the preset times. Therefore, the application can save the calculation force resource and ensure the stability of the system when the lane planning is not needed. In addition, the present application is not particularly limited with respect to the preset number of times regarding the number of times of calculation, and may be set by those skilled in the art according to actual circumstances.
In step S103, the current lane planning distance and/or the current number of lane plans of the current vehicle are adjusted according to the current optimal lane planning strategy.
Based on the embodiment, the application can be used for matching the current optimal lane planning strategy according to the current road curvature and the current environment perception calculation power ratio and combining the delay statistical data of the output result, so as to adjust the lane planning distance or the lane planning quantity of the current vehicle or adjust the lane planning quantity or both according to the requirements according to the current optimal lane planning strategy, thereby enabling the lane planning result to be more in line with the state of the current vehicle and improving the real-time performance of the lane planning.
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 method further includes obtaining a new lane planning calculation time length of the current vehicle, reducing the number of first target planning lanes according to the preset strategy and shortening the first target planning distance if the new lane planning calculation time length is greater than or equal to the first preset time length, and adjusting the current lane planning number and/or the shortened first target planning distance according to the shortened first target planning lane number.
In order to improve the real-time performance of the lane planning, the method counts the planned time length and judges whether the planned time length is too long, if the planned time length of the lane is too long, the timeliness of the system output is very likely to be affected, and inconvenience is brought to a user.
In order for those skilled in the art to further understand the lane planning method of the vehicle of the present application, the following examples schematically illustrate the flow of the method.
Specifically, fig. 2 is a flow chart of a lane planning method of a vehicle according to an embodiment of the present application, and as shown in fig. 2, the lane planning method of a vehicle may include the following steps:
Step S201, calculating that the vehicle is currently in a scene scen (a plurality of intersections of pedestrians, urban arterial roads with traffic jam, smooth expressways, curved sea-surrounding roads and the like) through the current position or visual perception;
step S202, monitoring the delay of the output of the lane planning result and carrying out statistics;
Step S203, for the current scene scen1, estimating whether the current calculation load is increased, whether the curvature of the future road is overlarge, judging whether the delay is increased and exceeds a threshold value, if the delay is increased but not exceeding the threshold value, executing step S204, otherwise, executing step S205;
step S204, changing the distance and the number of lane planning according to the scene scen 1;
Step S205, combining the scene where the vehicle is located and the delay statistical data of the output result, and according to the matching of the scene listed in the List and the lane planning strategy, properly increasing the searching distance and the searching times when the vehicle is in a high-speed scene, properly reducing the searching distance and the searching times when the vehicle is in an urban arterial road scene due to large traffic flow, properly reducing the searching distance and the searching times when the vehicle is in an urban crowded intersection scene due to large perceived and predicted load, and properly reducing the searching distance when the vehicle is in a sea-surrounding highway scene due to large road curvature;
step S206, carrying out lane planning according to the optimal lane planning strategy.
According to the lane planning method of the vehicle, the optimal lane planning strategy of the current vehicle is determined according to the current lane planning calculation time length, the current road curvature and the current environment perception calculation force ratio by acquiring the current road curvature, the current environment perception calculation force ratio and the current lane planning calculation time length of the road where the current vehicle is located, and the current lane planning distance and/or the current lane planning quantity of the current vehicle are adjusted according to the current optimal lane planning strategy. Therefore, the application dynamically adjusts the planning length of the lane planning by combining the environment sensing calculation power ratio of the environment where the vehicle is located, namely the calculation power monitoring of the system and the factors of the road curvature, solves the problems that the real-time output of the result of the lane planning is not considered, and a control or dynamic optimization method is not available in the related technology, so that certain influence on the safety of automatic driving is possibly caused, and the like, controls the lane planning in real time according to the scene where the vehicle is located, ensures that the result of the lane planning is more in line with the state of the current vehicle, and improves the timeliness of the lane planning.
Next, a lane planning apparatus for a vehicle according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 3 is a block schematic diagram of a lane planning apparatus of a vehicle according to an embodiment of the present application.
As shown in fig. 3, the lane planning apparatus 10 of the vehicle includes an acquisition module 100, a determination module 200, and a planning module 300.
The system comprises an acquisition module 100 for acquiring the current road curvature, the current environment perceived computing power ratio and the current lane planning computing time length of the road where the current vehicle is located, a determination module 200 for determining the optimal lane planning strategy of the current vehicle according to the current lane planning computing time length, the current road curvature and the current environment perceived computing power ratio, and a planning module 300 for 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.
Optionally, in some embodiments, the determining module 200 includes a first matching unit, a determining unit, and a generating unit.
The first matching unit is used for matching the number of first target planning lanes and the first target planning distance of the current vehicle according to the curvature of the current road when the time length of the current lane planning calculation is longer than or equal to a first preset time length, and matching the number of second target planning lanes and the second target planning distance of the current vehicle according to the current environment perceived computing force duty ratio, wherein the number of the first target planning lanes is smaller than the number of the current planning vehicles, the first target planning distance is smaller than the current planning distance, the number of the second target planning lanes is smaller than the number of the current planning vehicles, and the second target planning distance is smaller than the current planning distance; the system comprises a first target planning lane number, a second target planning lane number, a determining unit, a generating unit and a generating unit, wherein the first target planning lane number is used for determining the first target planning lane number, the second target planning lane number is used for determining the second target planning lane number, the generating unit is used for generating the optimal lane planning strategy according to the first target planning distance and the second target planning distance.
Optionally, in some embodiments, before matching the first target planned number of lanes and the first target planned distance of the current vehicle according to the current road curvature, the first matching unit is further configured to:
And when the calculated times are smaller than the preset times, maintaining the lane planning strategy of the current vehicle unchanged.
Optionally, in some embodiments, the planning module 300 further comprises an acquisition unit, a first planning unit and a first adjustment unit after adjusting the current lane planning distance and/or the current number of lane plans of the current vehicle according to the current optimal lane planning strategy.
The system comprises an acquisition unit, a first planning unit and a first adjustment unit, wherein the acquisition unit is used for acquiring new lane planning calculation time of a current vehicle, the first planning unit is used for reducing the number of first target planning lanes and shortening the first target planning distance according to a preset strategy when the new lane planning calculation time is longer than or equal to a first preset time, and the first adjustment unit is used for adjusting the current lane planning number and/or the shortened first target planning distance according to the shortened first target planning lane number.
Optionally, in some embodiments, the obtaining module 100 further includes a second matching unit and a second adjusting unit after obtaining the current road curvature, the current environment awareness calculation power ratio, and the current lane planning calculation time period of the road on which the current vehicle is located.
The system comprises a first matching unit, a second adjusting unit and/or a current lane planning distance, wherein the first matching unit is used for matching the number of third target planning lanes and the third target planning distance of a current vehicle according to the curvature of the current road when the calculated time length of the current lane planning is smaller than a second preset time length, and matching the number of fourth target planning lanes and the fourth target planning distance of the current vehicle according to the current environment perceived calculated force ratio, the second adjusting unit is used for adjusting the number of the current lanes according to the number of the third target planning lanes and/or the number of the fourth target planning vehicles, and/or adjusting the current lane planning distance according to the first target planning distance and/or the second target planning distance, the second preset time length is smaller than the first preset time length, the number of the third target planning lanes is larger than the number of the current planning vehicles, the third target planning distance is larger than the current planning distance, the number of the fourth target planning lanes is larger than the number of the current planning vehicles, and the fourth target planning distance is larger than the current planning distance.
Optionally, in some embodiments, the obtaining module 100 further includes a second planning unit after obtaining the current road curvature, the current environment-aware power duty cycle, and the current lane-planning calculation time period of the road on which the current vehicle is located.
The second planning unit is used for maintaining the lane planning strategy of the current vehicle unchanged when the current lane planning calculation time is longer than or equal to a second preset time length and the current lane planning calculation time length is smaller than the first preset time length.
It should be noted that the foregoing explanation of the embodiments of the lane planning method for a vehicle is also applicable to the lane planning apparatus for a vehicle of this embodiment, and will not be repeated here.
According to the lane planning device for the vehicle, provided by the embodiment of the application, the optimal lane planning strategy of the current vehicle is determined according to the current lane planning calculation time length, the current road curvature and the current environment perception calculation force ratio by acquiring the current road curvature, the current environment perception calculation force ratio and the current lane planning calculation time length of the road where the current vehicle is located, and the current lane planning distance and/or the current lane planning quantity of the current vehicle are adjusted according to the current optimal lane planning strategy. Therefore, the application dynamically adjusts the planning length of the lane planning by combining the environment sensing calculation power ratio of the environment where the vehicle is located, namely the calculation power monitoring of the system and the factors of the road curvature, solves the problems that the real-time output of the result of the lane planning is not considered, and a control or dynamic optimization method is not available in the related technology, so that certain influence on the safety of automatic driving is possibly caused, and the like, controls the lane planning in real time according to the scene where the vehicle is located, ensures that the result of the lane planning is more in line with the state of the current vehicle, and improves the timeliness of the lane planning.
Fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:
memory 401, processor 402, and a computer program stored on memory 401 and executable on processor 402.
The processor 402 implements the lane planning method of the vehicle provided in the above-described embodiment when executing the program.
Further, the vehicle further includes:
A communication interface 403 for communication between the memory 401 and the processor 402.
A memory 401 for storing a computer program executable on the processor 402.
Memory 401 may include high-speed RAM (Random Access Memory ) memory, and may also include non-volatile memory, such as at least one disk memory.
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 may be connected to each other by a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture ) bus, a PCI (PERIPHERAL COMPONENT, external device interconnect) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
Alternatively, 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 may perform communication with each other through internal interfaces.
The processor 402 may be a CPU (Central Processing Unit ) or an ASIC (Application SPECIFIC INTEGRATED Circuit, application specific integrated Circuit) or one or more integrated circuits configured to implement embodiments of the present application.
The embodiment of the application also provides a computer-readable storage medium on which a computer program is stored which, when executed by a processor, implements the lane planning method of a vehicle as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, for example, two, three, etc., unless specifically defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware as in another embodiment, it may be implemented in any one or combination of techniques known in the art, discrete logic circuits with logic gates for performing logic functions on data signals, application specific integrated circuits with appropriate combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. A lane planning method of a vehicle, comprising the steps of:
acquiring the current road curvature, the current environment perception calculation power duty ratio and the current lane planning calculation time of the road where the current vehicle is located;
Determining an optimal lane planning strategy of the current vehicle according to the current lane planning calculation time length, the current road curvature and the current environment perception calculation force ratio, and
And 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.
2. The method of claim 1, wherein the determining the optimal lane planning strategy for the current vehicle based on the current lane planning computation time period, the current road curvature, and the current context aware computing power duty cycle comprises:
If the calculated time length of the current lane planning is greater than or equal to a first preset time length, matching a first target planned lane number and a first target planned distance of the current vehicle according to the current road curvature, and matching a second target planned lane number and a second target planned distance of the current vehicle according to the current environment perceived computing force duty ratio, wherein the first target planned lane number is smaller than the current planned vehicle number, the first target planned distance is smaller than the current planned distance, the second target planned lane number is smaller than the current planned vehicle number, and the second target planned distance is smaller 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;
and generating the optimal lane planning strategy according to the number of the final planned lanes and the final planned distance.
3. The method of claim 1 or 2, further comprising, prior to matching the first target planned number of lanes and first target planned distance of the current vehicle according to the current road curvature:
acquiring the calculated times of the current lane planning calculation time length longer than the first preset time length in the second preset time length;
And if the calculated times are smaller than the preset times, maintaining the lane planning strategy of the current vehicle unchanged.
4. Method according to claim 1 or 2, characterized in that after adjusting the current lane planning distance and/or the current number of lane plans of the current vehicle according to the current optimal lane planning strategy, it further comprises:
Acquiring new lane planning calculation time length of the current vehicle;
If the calculated time length of the new lane planning is longer than or equal to a first preset time length, reducing the number of first target planning lanes according to a preset strategy, and shortening the first target planning distance;
and adjusting the current lane planning quantity according to the shortened first target planning lane quantity and/or adjusting the current lane planning distance according to the shortened first target planning distance.
5. The method of claim 1, further comprising, after obtaining a current road curvature, a current context-aware power duty cycle, and a current lane-planning calculation time period for a road on which the current vehicle is located:
If the calculated time length of the current lane planning is smaller than a second preset time length, matching the number of third target planning lanes and the third target planning distance of the current vehicle according to the curvature of the current road, and matching the number of fourth target planning lanes and the fourth target planning distance of the current vehicle according to the current environment perceived calculated force ratio;
The current lane planning quantity is adjusted according to the third target planning lane quantity and/or the fourth target planning vehicle quantity, and/or the current lane planning distance is adjusted according to the first target planning distance and/or the second target planning distance;
the second preset duration is smaller than the first preset duration, the number of the third target planning lanes is larger than the number of the current planning vehicles, the third target planning distance is larger than the current planning distance, the number of the fourth target planning lanes is larger than the number of the current planning vehicles, and the fourth target planning distance is larger than the current planning distance.
6. The method of claim 1, further comprising, after obtaining a current road curvature, a current context-aware power duty cycle, and a current lane-planning calculation time period for a road on which the current vehicle is located:
And if the calculated time length of the current lane planning is greater than or equal to the second preset time length and the calculated time length of the current lane planning is less than the first preset time length, maintaining the lane planning strategy of the current vehicle unchanged.
7. A lane planning apparatus for a vehicle, comprising:
the acquisition module is used for acquiring the current road curvature, the current environment perception calculation power occupation ratio and the current lane planning calculation time length of the road where the current vehicle is located;
A determining module for determining an optimal lane planning strategy of the current vehicle according to the current lane planning calculation time length, the current road curvature and the current environment perception calculation force ratio, and
And the planning module is used for 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.
8. The apparatus of claim 7, wherein the determining module comprises:
The first matching unit is used for matching a first target planned lane number and a first target planned distance of the current vehicle according to the current road curvature when the calculated time length of the current lane planning is greater than or equal to a first preset time length, and matching a second target planned lane number and a second target planned distance of the current vehicle according to the current environment perceived computing power duty ratio, wherein the first target planned lane number is smaller than the current planned vehicle number, the first target planned distance is smaller than the current planned distance, the second target planned lane number is smaller than the current planned vehicle number, and the second target planned distance is smaller than the current planned distance;
The determining unit is used for 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;
and the generating unit is used for generating the optimal lane planning strategy according to the number of the final planned lanes and the final planned distance.
9. A vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the lane planning method of the vehicle of any one of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a lane planning method of a vehicle according to any one of claims 1-6.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311092076.7A CN119527339A (en) | 2023-08-28 | 2023-08-28 | Vehicle lane planning method, device, vehicle and storage medium |
| PCT/CN2023/139891 WO2025043974A1 (en) | 2023-08-28 | 2023-12-19 | Lane planning method and apparatus for vehicle, and vehicle and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202311092076.7A CN119527339A (en) | 2023-08-28 | 2023-08-28 | Vehicle lane planning method, device, vehicle and storage medium |
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| CN119527339A true CN119527339A (en) | 2025-02-28 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202311092076.7A Pending CN119527339A (en) | 2023-08-28 | 2023-08-28 | Vehicle lane planning method, device, vehicle and storage medium |
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| WO (1) | WO2025043974A1 (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP5705422B2 (en) * | 2009-07-16 | 2015-04-22 | パイオニア株式会社 | Route search device, route search method, route search program, and recording medium |
| CN109739219B (en) * | 2018-12-05 | 2022-02-11 | 阿波罗智能技术(北京)有限公司 | Method, device and equipment for planning passing path and readable storage medium |
| CN114511438A (en) * | 2020-10-29 | 2022-05-17 | 华为技术有限公司 | Method, device and equipment for controlling load |
| CN115218902B (en) * | 2022-04-02 | 2024-02-02 | 广州汽车集团股份有限公司 | Track planning method, device, equipment and storage medium |
| CN116148890A (en) * | 2022-11-30 | 2023-05-23 | 武汉中海庭数据技术有限公司 | High-precision map lane planning method, system, electronic equipment and storage medium |
| CN116521374A (en) * | 2023-05-15 | 2023-08-01 | 集度科技有限公司 | Data processing method, device, vehicle and computer program product |
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