Method and device for determining travelable area, computer equipment and readable storage medium

Abstract

The invention relates to a driving area determination method and device, computer equipment and a readable storage medium, and the method comprises the steps: obtaining a plurality of vehicle tracks of a target road section in a historical period, each vehicle track comprises a plurality of track points, and each track point corresponds to a vehicle position at a moment, the moment corresponding to each track point is a moment in a historical time period, and the target road section comprises at least one lane; and determining a drivable area and a non-drivable area of each lane in the target road section according to the plurality of vehicle tracks. According to the method, the drivable area and the non-drivable area can be quickly and efficiently determined at low cost.

Description

Technical Field

[0001] This application belongs to the field of autonomous driving technology, and particularly relates to a method, device, computer device and readable storage medium for determining a drivable area. Background Art

[0002] With the development of autonomous driving technology, autonomous vehicles have been able to replace the work of drivers in some scenarios. The driving behavior of autonomous vehicles requires lane information and the constraint of the drivable area. The drivable area generally refers to the area around an autonomous vehicle where it can drive, or where planning and control can be performed.

[0003] Currently, the methods for obtaining the drivable area mainly include: determining the drivable area of a vehicle based on lane line information, and obtaining the drivable area through a high-precision map. Among them, determining the drivable area of a vehicle based on lane line information includes: obtaining lane lines through algorithms such as semantic segmentation, and determining the lane center line based on the lane lines; determining the drivable area in front of the host vehicle based on the projections of each obstacle in the obstacle information on the target vertical line; obtaining the drivable area through a high-precision map is to directly obtain the drivable area of the vehicle in the map through the high-precision map. The method of obtaining the drivable area through algorithms such as lane line recognition has high requirements for computing power, so the cost is high; the production cost of high-precision maps is large and certain qualifications are required, so obtaining the drivable area from high-precision maps also has the problem of high cost.

[0004] Therefore, how to obtain the drivable area at low cost has become a technical problem to be solved urgently. Summary of the Invention

[0005] The embodiments of this application provide a method, device, computer device and readable storage medium for determining a drivable area, which solves the technical problem of high cost in the existing methods for determining the drivable area.

[0006] In a first aspect, the embodiments of this application provide a method for determining a drivable area, including: obtaining multiple vehicle trajectories of a target road section in a historical period, each vehicle trajectory includes multiple trajectory points, each trajectory point corresponds to the position of the vehicle at a moment, the moment corresponding to each trajectory point is a moment in the historical period, and the target road section includes at least one lane; determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories.

[0007] In the above method, for a target road section, if many vehicles left a lot of vehicle trajectories at some positions in the target road section during a historical period, it indicates that the probability of these positions being drivable areas is higher. Therefore, based on multiple vehicle trajectories of the target road section during the historical period, the drivable areas and non-drivable areas in the target road section can be determined. By using the vehicle trajectories during the historical period to divide the lanes of the target road section into drivable areas and non-drivable areas, the method is simple and has a small amount of calculation, and can determine the drivable areas and non-drivable areas quickly and efficiently at low cost.

[0008] In one embodiment, determining the drivable areas and non-drivable areas of each lane in the target road section according to multiple vehicle trajectories includes: dividing each lane in the target road section into multiple grids; determining the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in the multiple vehicle trajectories; determining the area where all the first grids are located in each lane as the drivable area of each lane, where the first grid is a grid whose corresponding number of trajectory points is greater than or equal to a preset threshold; determining the area outside the drivable area in each lane as the non-drivable area. In this embodiment, by dividing each lane into multiple grids and determining the number of trajectory points corresponding to each grid, and determining the area where the grids with the corresponding number of trajectory points greater than the preset threshold are located as the drivable area, the division of the drivable area and the non-drivable area is realized by a simple way of counting trajectory points, and the method is simple and efficient.

[0009] In one embodiment, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid. In this embodiment, the trajectory points that fall within the boundary range of the first grid are determined as the trajectory points corresponding to the first grid, so that the number of trajectory points corresponding to the first grid obtained can more directly reflect the number of vehicle trajectories passing through the first grid.

[0010] In one embodiment, the trajectory points corresponding to the first grid further include the trajectory points that fall on the boundary of the first grid. In this embodiment, it is clear that the trajectory points that fall on the boundary are counted in the grid to which the boundary belongs, which can make full use of all trajectory points and thus improve the data utilization rate.

[0011] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; a week includes multiple time periods, and the preset threshold is determined according to the time period in which the current moment is located in a week. There will be certain differences in the number of vehicle trajectories in different time periods of a week. In this embodiment, the preset threshold is determined according to the time period in which the current moment is located in a week, so that the obtained drivable area is more in line with the actual situation.

[0012] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; the time period corresponding to the first vehicle trajectory is the t1 time period in a day, the current moment belongs to the t1 time period in the day where it is located, and the first vehicle trajectory is any one of multiple vehicle trajectories. In different time periods of a day, the rules of vehicle trajectories will be different. In this embodiment, the multiple vehicle trajectories are determined according to the specific time period of the current moment in a day. For a day, the time period corresponding to each vehicle trajectory among the multiple vehicle trajectories includes the current moment, so that each vehicle trajectory is associated with the current moment, thereby making the division of the drivable area more in line with the actual situation.

[0013] In one embodiment, the method further includes: performing trajectory planning on the autonomous vehicle in the drivable area of each lane in the target section. In this implementation, after determining the drivable area of each lane, trajectory planning is performed on the autonomous vehicle in the drivable area of each lane in the target section, so that the trajectory planning cost of the autonomous vehicle is lower and the efficiency is higher.

[0014] In a second aspect, an embodiment of the present application provides a drivable area determination device, and the device includes units for executing each step of the method in any one of the above first aspects.

[0015] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method in any one of the above first aspects is implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the method in any one of the above first aspects is implemented.

[0017] Fifth aspect, an embodiment of the present application provides a chip, including: a processor, configured to call and run a computer program from a memory, so that a computer device installed with the chip executes the method described in any one of the above first aspect.

[0018] It can be understood that the beneficial effects of the above second aspect to fifth aspect can be referred to the relevant descriptions in the above first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a schematic diagram of the application environment of the drivable area determination method provided by an embodiment of the present application;

[0021] Figure 2 It is a schematic flowchart of the drivable area determination method provided by an embodiment of the present application;

[0022] Figure 3 It is a structural block diagram of the drivable area determination device provided by an embodiment of the present application;

[0023] Figure 4 It is an internal structure diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] In the following description, specific details such as specific system structures and technologies are proposed for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0025] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0026] It should also be understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0027] As used in the specification of this application and the appended claims, the term "if" may be construed as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be construed as meaning "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context.

[0028] In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0029] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0030] An embodiment of this application provides a method for determining a drivable area, including: obtaining multiple vehicle trajectories of a target road section in a historical period, each vehicle trajectory including multiple trajectory points, each trajectory point corresponding to the vehicle position at a moment, the moment corresponding to each trajectory point being a moment in the historical period, and the target road section including at least one lane; determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories. By using the vehicle trajectories of the target road section in the historical period to divide the drivable area and non-drivable area of each lane on the target road section, the method is simple and has a small amount of calculation, so the drivable area and non-drivable area can be determined at low cost, quickly and efficiently.

[0031] The following will exemplarily illustrate the method for determining a drivable area provided by this application in combination with specific embodiments.

[0032] See Figure 1 , which is a schematic diagram of the application environment of the method for determining a drivable area provided by an embodiment of this application. As Figure 1As shown, in this scenario, it includes a target road segment 101 and a computer device 102. The computer device 102 determines the drivable area of each lane in the target road segment 101 by obtaining multiple vehicle trajectories of the target road segment 101 in a historical period.

[0033] Exemplarily, there is an autonomous vehicle 103 traveling on the target road segment 101, and the autonomous vehicle 103 is communicatively connected to the computer device 102.

[0034] In some embodiments, the computer device 102 can also perform trajectory planning for the autonomous vehicle in the drivable area of each lane in the target road segment, and send the trajectory planning to the autonomous vehicle 103. The autonomous vehicle 103 performs autonomous driving according to the trajectory planning.

[0035] In some other embodiments, the computer device 102 sends the drivable area information of each lane in the determined target road segment 101 to the autonomous vehicle 103. The autonomous vehicle 103 performs trajectory planning in the drivable area of each lane in the target road segment and performs autonomous driving according to the trajectory planning.

[0036] Exemplarily, in the multiple vehicle trajectories, each vehicle trajectory includes multiple trajectory points. Each trajectory point corresponds to the vehicle position at a moment, and the moment corresponding to each trajectory point is a moment in the historical period. The vehicle trajectory is lane-level data.

[0037] It should be understood that the target road segment 101 refers to the road segment on which the autonomous vehicle 103 travels. Figure 1 The shown target road segment 101 is only for illustration and is not a limitation on the target road segment in this application.

[0038] The target road segment in the embodiments of this application can be any road segment that is more complex or simpler than the shown target road segment 101, and this application does not limit this. Figure 1 The shown target road segment 101 is only for illustration and is not a limitation on the target road segment in this application.

[0039] In some embodiments, the multiple vehicle trajectories of the target road segment 101 in the historical period can be obtained from a roadside perception system or from a map vendor, and this application does not limit this.

[0040] Exemplarily, the roadside perception system can be a roadside fusion perception system (also known as a smart base station or a roadside base station), etc., and this application does not limit this. The roadside fusion perception system can achieve precise perception of the target road segment, thereby obtaining vehicle trajectories.

[0041] It can be understood that the computer device 102 can be a computer device in the autonomous driving system of the autonomous vehicle 103, or a cloud server, or the computer device 102 can also be any other terminal device, such as: mobile phone, tablet computer, personal digital assistant, wearable device, vehicle-mounted terminal, etc. The present application does not limit this.

[0042] For ease of understanding, the process of determining the drivable area of the computer device 102 is described below by way of example. The computer device 102 first obtains multiple vehicle trajectories of the target road section in the historical period. Each vehicle trajectory includes multiple trajectory points. Each trajectory point corresponds to the vehicle position at a moment, and the moment corresponding to each trajectory point is a moment in the historical period. The target road section includes at least one lane; then, based on the multiple vehicle trajectories, the drivable area and non-drivable area of each lane in the target road section are determined.

[0043] In some embodiments, if the computer device 102 is a computer device in the autonomous driving system of the autonomous vehicle 103, then after the computer device 102 determines the drivable area corresponding to each lane in the target road section, it performs trajectory planning for the autonomous vehicle 103 in the determined drivable area.

[0044] In some other embodiments, if the computer device 102 is a cloud server, after the computer device 102 determines the drivable area corresponding to each lane in the target road section, the computer device 102 can send the drivable area information of each lane in the target road section to the autonomous driving system of the autonomous vehicle 103, and the autonomous driving system of the autonomous vehicle 103 performs trajectory planning in the determined drivable area.

[0045] Based on the application scenario schematic diagram of the drivable area determination method as Figure 1 shown, in an embodiment of the present application, a drivable area determination method as Figure 2 shown is provided. The following takes the application of this method to the above computer device as an example for description. It can be understood that the following description is only an example and does not constitute a limitation on the protection scope of the present application. As Figure 2 shown, this method may include S201 to S202. Each step is described below.

[0046] S201. Obtain multiple vehicle trajectories of the target road section in the historical period. Each vehicle trajectory includes multiple trajectory points. Each trajectory point corresponds to the vehicle position at a moment, and the moment corresponding to each trajectory point is a moment in the historical period. The target road section includes at least one lane.

[0047] It should be understood that the historical period can be any period before the current moment.

[0048] Exemplarily, the historical period can be two hours before the current moment, or it can also be one day before the current moment, or it can also be one week before the current moment, etc.

[0049] It can be understood that the closer the historical period corresponding to multiple vehicle trajectories is to the current moment, the closer the finally obtained drivable area is to the actual situation.

[0050] It can be understood that the vehicle trajectory is a vehicle that leaves a driving trajectory on the target road section during the historical period, where the vehicle is mainly a motor vehicle, such as a motor vehicle, such as a car, a bus, or a truck, etc. The specific type of the vehicle in the embodiments of the present application is not specifically limited.

[0051] It can be understood that the vehicle trajectory in the embodiments of the present application can be represented by discrete trajectory points or can also be represented by a trajectory line. The trajectory line is a line formed by connecting multiple trajectory points in chronological order. The present application does not elaborate and limit this.

[0052] It should be understood that assuming vehicle A passes through the target road section twice during the historical period, then there may be two driving trajectories belonging to vehicle A among the multiple vehicle trajectories.

[0053] In addition, among the multiple vehicle trajectories, there may also be vehicle trajectories that only include part of the road sections in the target road section. For example, vehicle B only travels a part of the target road section during the historical period on the target road section. At this time, the vehicle trajectory corresponding to vehicle B is only the driving trajectory of vehicle B on the part of the road section.

[0054] In the embodiments of the present application, the information of the trajectory point can include position information and time information, where the position information can be coordinate information or longitude and latitude information, etc. The present application does not limit this.

[0055] S202. Determine the drivable area and non-drivable area of each lane in the target road section according to multiple vehicle trajectories.

[0056] It can be understood that trajectory frequency analysis is performed according to multiple vehicle trajectories, and the drivable area and non-drivable area of each lane in the target road section are determined according to the frequency analysis result.

[0057] The drivable area determination method in the above embodiments divides the drivable area and non-drivable area of the lanes in the target road section through the vehicle trajectories in the historical period. The method is simple, the calculation amount is small, and the drivable area and non-drivable area can be determined at low cost, quickly and efficiently.

[0058] In some embodiments, the drivable area determination method may further include: performing trajectory planning for the autonomous vehicle in the drivable area of each lane in the target road section. It should be understood that any feasible method can be adopted for trajectory planning, and the present application will not elaborate on this.

[0059] In some embodiments, step S202 includes: dividing each lane in the target road section into a plurality of grids; determining the number of trajectory points corresponding to each grid in each lane according to the position information of the plurality of grids in each lane and the vehicle positions corresponding to each trajectory point in the plurality of vehicle trajectories; determining the area where all the first grids are located in each lane as the drivable area of each lane, where the first grid is a grid whose corresponding number of trajectory points is greater than or equal to a preset threshold; determining the area outside the drivable area in each lane as the non-drivable area. In this embodiment, by dividing each lane into grids and according to the position information of the plurality of grids in each lane and the vehicle positions corresponding to each trajectory point in the plurality of vehicle trajectories, the number of trajectory points corresponding to each grid is determined. This is equivalent to counting the trajectory points for each grid. By counting the trajectory points corresponding to the grids to determine the drivable area and the non-drivable area, the method is simple and the calculation amount is small, so the efficiency is high.

[0060] In some embodiments, when the number of trajectory points corresponding to a grid is greater than or equal to the preset threshold, it indicates that the number of vehicles passing through this grid during the historical period is large, so the area corresponding to this grid is determined as part of the drivable area; when the number of trajectory points corresponding to a grid is less than the preset threshold, it indicates that the number of vehicles passing through this grid during the historical period is small, so the area corresponding to this grid is determined as part of the non-drivable area.

[0061] It should be understood that the size of the grid can be set as needed, and the present application will not limit and elaborate on this.

[0062] For ease of understanding, the following gives an exemplary description of the determination method of the trajectory corresponding to the grid.

[0063] In some embodiments, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid.

[0064] It can be understood that after dividing each lane into a plurality of grids, the range of the area corresponding to each grid is known. When the vehicle position of a trajectory point falls within the range corresponding to grid G1, it is determined that this trajectory point is the trajectory point corresponding to grid G1.

[0065] In some embodiments, in addition to the trajectory points that fall within the range corresponding to grid G1, for the trajectory points located on the boundary of grid G1, such trajectory points are also the trajectory points corresponding to the boundary of grid G1.

[0066] In other embodiments, only the trajectory points that fall within the range corresponding to grid G1 are the trajectory points corresponding to grid G1, while the trajectory points located on the boundary of grid G1 are not the trajectory points corresponding to grid G1.

[0067] Suppose grid G1 is adjacent to grid G2, and there is a trajectory point M on the boundary between the two grids. In some embodiments, trajectory point M is both the trajectory point corresponding to grid G1 and the trajectory point corresponding to grid G2. In other embodiments, trajectory point M is not the trajectory point corresponding to any grid. Of course, for trajectory point M, it can also be randomly determined that trajectory point M is the trajectory point of grid G1 or grid G2, which is not elaborated and restricted in this application.

[0068] In some embodiments, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane of the target section; a week includes multiple time periods, and the preset threshold is determined according to the time period in which the current moment is located in a week.

[0069] Exemplarily, a week is divided into multiple time periods. For example: each day from Monday to Friday can be divided into: the first time period (0:00 - 6:00), the second time period (6:00 - 9:00), the third time period (9:00 - 14:00), the fourth time period (14:00 - 19:00), and the fifth time period (19:00 - 24:00); each day from Saturday to Sunday can be divided into: the sixth time period (0:00 - 9:00), the seventh time period (9:00 - 19:00), and the eighth time period (19:00 - 24:00). Among them: the first time period to the eighth time period can respectively correspond to a preset threshold, that is, the preset thresholds corresponding to different time periods are different. For example, the second time period and the fourth time period are the peak periods of going to and from work, and the traffic flow is relatively large. Therefore, the preset thresholds corresponding to the second time period and the fourth time period are greater than the preset thresholds of other time periods.

[0070] It should be understood that a preset threshold is set for each time period in advance. When determining the drivable area and non-drivable area of the first lane at the current moment, the preset threshold can be determined according to the specific time period to which the current moment belongs. Since the traffic flow of the target section may be different in different time periods, by determining different preset thresholds for different time periods, the drivable area determined is related to the specific time period to which the current moment belongs, so that the determined drivable area is closer to the actual situation.

[0071] Of course, thresholds can also be determined for different time periods in a week based on the analysis of multiple vehicle trajectories, which will not be elaborated in this application.

[0072] In some embodiments, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; the time period corresponding to the first vehicle trajectory is the t1 period in a day, the current moment is within the t1 period in a day, and the first vehicle trajectory is any one of multiple vehicle trajectories. In this embodiment, by defining that the time period corresponding to each vehicle trajectory among multiple vehicle trajectories includes the current moment, each vehicle trajectory has a strong correlation with the current moment, so the accuracy of the drivable area division result can be improved.

[0073] Exemplarily, in this embodiment, the time period of each day is divided. The first vehicle trajectory is any one of multiple vehicle trajectories, and the first vehicle trajectory satisfies the following conditions: the time period corresponding to the first vehicle trajectory refers to the time period of the start time and end time of the first vehicle trajectory in a day. For example, the time period corresponding to the first vehicle trajectory can be: 8:30 to 9:00, that is, the earliest time corresponding to multiple trajectory points of the first vehicle trajectory is 8:30, the latest time is 9:00, and the current moment is any moment between 8:30 and 9:00.

[0074] It can also be understood that the multiple vehicle trajectories in this embodiment are determined according to the specific time period of the current moment in a day. For example, if the current moment is determined to be 8:40, then when selecting multiple vehicle trajectories, the vehicle trajectories whose corresponding time period includes 8:40 are determined as available vehicle trajectories.

[0075] It should be understood that the time periods in a day corresponding to different vehicle trajectories among multiple vehicle trajectories may be the same or different, and this application does not limit this.

[0076] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of this application.

[0077] Corresponding to a method for determining a drivable area in the above embodiment, Figure 3 The structural block diagram of a drivable area determination device provided by an embodiment of this application is shown. For the sake of convenience of description, only the parts related to the embodiments of this application are shown.

[0078] Referring to Figure 3 , the drivable area determination device 300 includes: a trajectory acquisition unit 310 and an area determination unit 320, where:

[0079] A trajectory acquisition unit 310, configured to acquire multiple vehicle trajectories of a target road section in a historical period. Each vehicle trajectory includes multiple trajectory points, and each trajectory point corresponds to the position of a vehicle at a moment. The moment corresponding to each trajectory point is a moment in the historical period. The target road section includes at least one lane;

[0080] A region determination unit 320, configured to determine a drivable region and a non-drivable region of each lane in the target road section according to the multiple vehicle trajectories.

[0081] In one embodiment, the region determination unit 320 is configured to determine a drivable region and a non-drivable region of each lane in the target road section according to the multiple vehicle trajectories, including: dividing each lane in the target road section into multiple grids; determining the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in the multiple vehicle trajectories; determining the region where all the first grids are located in each lane as the drivable region of each lane, where the first grid is a grid whose corresponding number of trajectory points is greater than or equal to a preset threshold; and determining the region outside the drivable region in each lane as the non-drivable region.

[0082] In one embodiment, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid.

[0083] In one embodiment, the trajectory points corresponding to the first grid further include the trajectory points that fall on the boundary of the first grid.

[0084] In one embodiment, the drivable region and the non-drivable region of the first lane are the drivable region and the non-drivable region of the first lane at the current moment. The first lane is any one of the at least one lane; a week includes multiple periods, and the preset threshold is determined according to the period in which the current moment is located in a week.

[0085] In one embodiment, the drivable region and the non-drivable region of the first lane are the drivable region and the non-drivable region of the first lane at the current moment. The first lane is any one of the at least one lane; the time period corresponding to the first vehicle trajectory is the t1 period in a day, the current moment belongs to the t1 period in the day where it is located, and the first vehicle trajectory is any one of the multiple vehicle trajectories.

[0086] In one embodiment, the device further includes a trajectory acquisition unit, where: the trajectory acquisition unit is configured to perform trajectory planning on an autonomous vehicle in the drivable region of each lane in the target road section.

[0087] Figure 4 The structural schematic diagram of a computer device 40 provided in an embodiment of the present application is asFigure 4 As shown, the computer device 40 of this embodiment includes: at least one processor 400 ( Figure 4 only one processor is shown in the figure), a memory 401, and a computer program 402 stored in the memory 401 and executable on at least one processor 400. When the processor 400 executes the computer program 402, it implements the steps in any of the above-described embodiments of the drivable area determination method.

[0088] The computer device may include, but is not limited to, a processor 400 and a memory 401. Those skilled in the art can understand that Figure 4 this is merely an example of the computer device 40 and does not constitute a limitation on the computer device 40. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0089] The so-called processor 400 may be a central processing unit (CPU), and the processor 400 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0090] In some embodiments, the memory 401 may be an internal storage unit, such as a hard disk or memory. In other embodiments, the memory 401 may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 401 may also include both an internal storage unit and an external storage device. The memory 401 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 401 may also be used to temporarily store data that has been output or will be output.

[0091] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented: obtaining multiple vehicle trajectories of a target road section in a historical period, each vehicle trajectory including multiple trajectory points, each trajectory point corresponding to the vehicle position at a moment, the moment corresponding to each trajectory point being a moment in the historical period, and the target road section including at least one lane; determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories.

[0092] In one embodiment, when the processor executes the computer program, the following steps are implemented: dividing each lane in the target road section into multiple grids; determining the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in the multiple vehicle trajectories; determining the area where all the first grids are located in each lane as the drivable area of each lane, the first grid being a grid where the number of corresponding trajectory points is greater than or equal to a preset threshold; determining the area outside the drivable area in each lane as the non-drivable area.

[0093] In one embodiment, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid.

[0094] In one embodiment, the trajectory points corresponding to the first grid further include the trajectory points that fall on the boundary of the first grid.

[0095] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, the first lane being any one of the at least one lane; a week includes multiple periods, and the preset threshold is determined according to the period in which the current moment is located in a week.

[0096] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, the first lane being any one of the at least one lane; the time period corresponding to the first vehicle trajectory is the t1 period in a day, the current moment belongs to the t1 period in the day where it is located, and the first vehicle trajectory is any one of the multiple vehicle trajectories.

[0097] In one embodiment, when the processor executes the computer program, the following steps are implemented: performing trajectory planning on an autonomous vehicle in the drivable area of each lane in the target road section.

[0098] The implementation principles and technical effects of the steps implemented when the processor executes the computer program in this embodiment are similar to those of the above-mentioned drivable area determination method, and will not be elaborated here.

[0099] Those skilled in the art can understand that Figure 4 the structure shown in Figure 4 is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0100] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be described herein again.

[0101] The embodiment of this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the foregoing method embodiments can be implemented.

[0102] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining multiple vehicle trajectories of a target road section in a historical period, each vehicle trajectory includes multiple trajectory points, each trajectory point corresponds to the vehicle position at a moment, the moment corresponding to each trajectory point is a moment in the historical period, and the target road section includes at least one lane; determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories.

[0103] In one embodiment, when the computer program is executed by a processor, the following steps are implemented: dividing each lane in the target road section into multiple grids; determining the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in the multiple vehicle trajectories; determining the area where all the first grids in each lane are located as the drivable area of each lane, where the first grid is a grid whose corresponding number of trajectory points is greater than or equal to a preset threshold; determining the area outside the drivable area in each lane as the non-drivable area.

[0104] In one embodiment, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid.

[0105] In one embodiment, the trajectory points corresponding to the first grid further include the trajectory points that fall on the boundary of the first grid.

[0106] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; a week includes multiple time periods, and the preset threshold is determined according to the time period in which the current moment is located in a week.

[0107] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; the time period corresponding to the first vehicle trajectory is the t1 time period in a day, the current moment belongs to the t1 time period in the day where it is located, and the first vehicle trajectory is any one of multiple vehicle trajectories.

[0108] In one embodiment, when the computer program is executed by a processor, the following steps are implemented: perform trajectory planning for the autonomous vehicle in the drivable area of each lane in the target section.

[0109] The implementation principles and technical effects of the steps implemented when the computer program in this embodiment is executed by a processor are similar to the principles of the above-mentioned drivable area determination method, and will not be elaborated here.

[0110] The embodiments of the present application provide a computer program product, when the computer program product runs on a computer device, it causes the computer device to execute the steps in the above-mentioned various method embodiments.

[0111] In one embodiment, a computer program product is provided, when the computer program product runs on a computer device, it causes the computer device to execute the following steps: obtain multiple vehicle trajectories of the target section in a historical time period, each vehicle trajectory includes multiple trajectory points, each trajectory point corresponds to the vehicle position at a moment, and the moment corresponding to each trajectory point is a moment in the historical time period, and the target section includes at least one lane; determine the drivable area and non-drivable area of each lane in the target section according to the multiple vehicle trajectories.

[0112] In one embodiment, when the computer program product runs on a computer device, the computer device is caused to perform the following steps: divide each lane in the target road section into multiple grids; determine the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in multiple vehicle trajectories; determine the area where all the first grids in each lane are located as the drivable area of each lane, where the first grid is a grid for which the number of corresponding trajectory points is greater than or equal to a preset threshold; and determine the area outside the drivable area in each lane as the non-drivable area.

[0113] In one embodiment, the trajectory points corresponding to the first grid include the trajectory points that fall within the boundary range of the first grid.

[0114] In one embodiment, the trajectory points corresponding to the first grid further include the trajectory points that fall on the boundary of the first grid.

[0115] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; a week includes multiple time periods, and the preset threshold is determined according to the time period in which the current moment is located in a week.

[0116] In one embodiment, the drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, and the first lane is any one of at least one lane; the time period corresponding to the first vehicle trajectory is the t1 time period in a day, the current moment belongs to the t1 time period in the day to which it belongs, and the first vehicle trajectory is any one of the multiple vehicle trajectories.

[0117] In one embodiment, when the computer program product runs on a computer device, the computer device is caused to perform the following step: perform trajectory planning for the autonomous vehicle in the drivable area of each lane in the target road section.

[0118] The implementation principles and technical effects of the steps implemented when the computer program in this embodiment is executed by the processor are similar to those of the above-mentioned drivable area determination method, and will not be elaborated here.

[0119] An embodiment of the present application further provides a chip, including: a processor for calling and running a computer program from a memory, so that a computer device installed with the chip executes the steps in the above-mentioned various method embodiments.

[0120] In the above embodiments, the descriptions of the various embodiments have their own focuses. For parts not described in detail or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0121] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0122] In the embodiments provided in this application, it should be understood that the disclosed apparatus / devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of the apparatus or unit can be in an electrical, mechanical or other form.

[0123] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0124] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0125] When the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0126] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining a drivable area, characterized in that, The method includes: Obtaining multiple vehicle trajectories of a target road section in a historical period, each vehicle trajectory including multiple trajectory points, each trajectory point corresponding to the position of a vehicle at a moment, the moment corresponding to each trajectory point being a moment in the historical period, and the target road section including at least one lane; Determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories.

2. The method according to claim 1, characterized in that The determining the drivable area and non-drivable area of each lane in the target road section according to the multiple vehicle trajectories includes: Dividing each lane in the target road section into multiple grids; Determining the number of trajectory points corresponding to each grid in each lane according to the position information of the multiple grids in each lane and the vehicle positions corresponding to each trajectory point in the multiple vehicle trajectories; Determining the area where all first grids in each lane are located as the drivable area of each lane, the first grid being a grid corresponding to which the number of trajectory points is greater than or equal to a preset threshold; Determining the area other than the drivable area in each lane as the non-drivable area.

3. The method according to claim 2, wherein The trajectory points corresponding to the first grid include the trajectory points falling within the boundary range of the first grid.

4. The method according to claim 3, wherein The trajectory points corresponding to the first grid further include the trajectory points falling on the boundary of the first grid.

5. The method according to claim 2, wherein The drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, the first lane being any one of the at least one lane; a week includes multiple periods, and the preset threshold is determined according to the period in which the current moment is located in a week.

6. The method according to claim 1, wherein The drivable area and non-drivable area of the first lane are the drivable area and non-drivable area of the first lane at the current moment, the first lane being any one of the at least one lane; the time period corresponding to the first vehicle trajectory is the t1 period in a day, the current moment belongs to the t1 period in the day where it is located, and the first vehicle trajectory is any one of the multiple vehicle trajectories.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Performing trajectory planning on an autonomous vehicle in the drivable area of each lane in the target road section.

8. A travelable area determination device, characterized in that, The device includes units for performing each step of the method according to any one of claims 1 to 7.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the method according to any one of claims 1 to 7 is implemented.

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