Driving track processing method, device and equipment

Abstract

The invention provides a driving track processing method, apparatus and device. The method comprises the steps of obtaining a current position of a following vehicle and a historical driving track of a pilot vehicle corresponding to the following vehicle; determining a predicted driving track of the pilot vehicle in the next time period; and determining a target driving track of the following vehicle in the next time period according to the current position, the historical driving track and the predicted driving track. The problem that the driving track of the following vehicle lags behind the driving track of the pilot vehicle to a large extent can be solved, and the accuracy of driving track processing is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of platoon autonomous driving technology, and in particular to a driving trajectory processing method, device and equipment. Background Art

[0002] Platoon autonomous driving allows multiple autonomous vehicles to travel in a coordinated manner to form a tight formation, in which there is usually a pilot vehicle (or, called the head vehicle) responsible for leading the entire formation, and the remaining vehicles are called follower vehicles, which travel by following the pilot vehicle.

[0003] Currently, the vehicle trajectory of the following vehicle, that is, the driving trajectory, only depends on the historical driving trajectory of the leading vehicle. Therefore, there is a problem that the driving trajectory of the following vehicle may lag behind that of the leading vehicle to a large extent. Summary of the invention

[0004] The present application provides a driving trajectory processing method, device and equipment, which can solve the problem that the driving trajectory of a following vehicle lags behind the driving trajectory of a leading vehicle to a large extent, and improve the accuracy of driving trajectory processing.

[0005] In a first aspect, the present application provides a driving trajectory processing method, the method comprising: obtaining a current position of a following vehicle and a historical driving trajectory of a leading vehicle corresponding to the following vehicle; determining a predicted driving trajectory of the leading vehicle in the next time period; and determining a target driving trajectory of the following vehicle in the next time period based on the current position, the historical driving trajectory and the predicted driving trajectory.

[0006] In a second aspect, the present application provides a driving trajectory processing device, which includes: a position acquisition module, used to obtain the current position of a following vehicle and the historical driving trajectory of a leading vehicle corresponding to the following vehicle; a trajectory determination module, used to determine the predicted driving trajectory of the leading vehicle in the next time period; a trajectory processing module, used to determine the target driving trajectory of the following vehicle in the next time period based on the current position, the historical driving trajectory and the predicted driving trajectory.

[0007] In a third aspect, the present application provides an electronic device, comprising: a processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory, and executing the method in the first aspect or its various implementations.

[0008] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program enables a computer to execute the method in the first aspect or its various implementations.

[0009] In a fifth aspect, the present application provides a computer program product, comprising computer program instructions, which enable a computer to execute the method in the first aspect or its various implementations.

[0010] In a sixth aspect, the present application provides a computer program, which enables a computer to execute the method in the first aspect or its various implementations.

[0011] Other technical features and technical effects involved in the present application will be introduced in subsequent embodiments and will not be described here to avoid repetition. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for describing the embodiments are briefly introduced below.

[0013] Figure 1 A flow chart of a driving trajectory processing method provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of a driving trajectory processing method provided in an embodiment of the present application;

[0015] Figure 3 A schematic diagram of another driving trajectory processing method provided in an embodiment of the present application;

[0016] Figure 4 A schematic diagram of a driving trajectory processing device 400 provided in an embodiment of the present application;

[0017] Figure 5 A schematic block diagram of an electronic device 500 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0019] It should be understood that the technical solution of the present application can be applied to the following scenarios, but is not limited to:

[0020] In one embodiment, the technical solution of the present application can be applied to the driving trajectory processing scenario of intelligent vehicles and can be applied to the platoon autonomous driving truck system. For example, it can be applied to the driving trajectory determination scenario of the following vehicle in the field of platoon autonomous driving truck decision planning, and the present application does not limit this.

[0021] In one embodiment, the application scenarios of the present application may include smart vehicles and servers, wherein the server may be a single server, a server cluster consisting of multiple servers, or a cloud platform control center, which is not limited in the present application.

[0022] Exemplarily, when the application scenario of the present application includes an intelligent vehicle, the intelligent vehicle can obtain the current position of the following vehicle, the historical driving trajectory and predicted driving trajectory of the leading vehicle based on its own sensors, processors and other components, and determine the predicted driving trajectory of the following vehicle, that is, the target driving trajectory of the following vehicle in the next time period; when the application scenario of the present application includes an intelligent vehicle and a server, the server and the intelligent vehicle can communicate, the intelligent vehicle can send data collected by the sensor to the server, the server can determine the predicted driving trajectory of the following vehicle based on the data sent by the intelligent vehicle, and return the predicted driving trajectory of the following vehicle to the intelligent vehicle.

[0023] It should be noted that the technical solution of the present application will be described in detail in the following embodiments by taking the electronic device being a smart vehicle as an example. When the electronic device is other devices, the corresponding contents and effects may refer to the corresponding contents and methods here. To avoid repetition, the present application will not elaborate on them here.

[0024] Among them, the intelligent vehicle referred to in the above embodiments may be a following vehicle.

[0025] The technical solution of this application will be described below:

[0026] Figure 1 A flow chart of a driving trajectory processing method provided in an embodiment of the present application, such as Figure 1 As shown, the method may include the following steps:

[0027] S110: Acquire the current position of the following vehicle and the historical driving trajectory of the leading vehicle corresponding to the following vehicle;

[0028] S120: Determine the predicted driving trajectory of the pilot vehicle in the next time period;

[0029] S130: Determine a target driving trajectory of the following vehicle in the next time period according to the current position, the historical driving trajectory and the predicted driving trajectory.

[0030] It should be noted that if Figure 2 As shown, Figure 2 The rectangular box, solid line, thinner dotted line and thicker dotted line in the figure represent the intelligent vehicle, the road sections on both sides of the intelligent vehicle positioning point, the driving trajectory of the intelligent vehicle (or called the vehicle driving reference line), and the lane reference line respectively. Among them, the intelligent vehicle can be a pilot vehicle or a following vehicle. The driving trajectory can be any trajectory of the vehicle based on the road it is traveling on (it can be a straight line or a curve, and this application does not impose any restrictions on this). Specifically, the historical driving trajectory, predicted driving trajectory or target driving trajectory in this application are used to represent the driving route of the vehicle, and can include discrete points or polynomials corresponding to the driving route. This application does not impose any restrictions on this. In addition, the road on which the vehicle is traveling, that is, the driving environment, may include lane reference lines, or may not include lane reference lines.

[0031] In addition, the technical solution of the present application can be executed by the pilot vehicle, and the target driving trajectory of the determined following vehicle (specifically, any following vehicle corresponding to the pilot vehicle in the platoon driving) in the next time period is sent to the following vehicle, so that the following vehicle can drive according to the target driving trajectory; or, the technical solution of the present application can be executed by the following vehicle, and the following vehicle determines the target driving trajectory of the following vehicle in the next time period and drives according to the target driving trajectory. The present application will introduce this in the following embodiment by taking the following vehicle executing the technical solution of the present application as an example.

[0032] It is understandable that a time period may include at least one moment, and the next time period may refer to at least one moment after the current moment. The historical driving trajectory may refer to the driving trajectory at at least one moment before the current moment (specifically, it may refer to the trajectory corresponding to the route that the vehicle has already traveled). The predicted driving trajectory may refer to the driving trajectory at at least one moment after the current moment (specifically, the trajectory predicted for the route that the vehicle is about to travel). The target driving trajectory of the following vehicle in the next time period refers to the driving trajectory of the following vehicle in the next time period (specifically, the trajectory predicted for the route that the following vehicle is about to travel).

[0033] In one embodiment, the current position of the following vehicle may be determined through sensor data (specifically, a real-time positioning sensor) and / or map data of the travel road, but is not limited thereto.

[0034] In one embodiment, if the lead vehicle is an unmanned vehicle, its historical driving trajectory and predicted driving trajectory may be pre-set trajectories, and the following vehicle may directly obtain the historical driving trajectory and predicted driving trajectory (for example, it may be obtained through vehicle networking devices such as vehicle-mounted communication systems).

[0035] In another embodiment, if the pilot vehicle is not an unmanned vehicle, the following vehicle may predict its driving trajectory in the next time period through a decision planning module (or a prediction module) to obtain a predicted driving trajectory.

[0036] Among them, a locator may be installed in the pilot vehicle, and the locator may obtain the historical positioning data of the pilot vehicle. The pilot vehicle or the following vehicle may draw the historical driving track of the pilot vehicle through the historical positioning data. Alternatively, a vehicle recorder may be installed in the pilot vehicle, and the vehicle recorder may record the driving details of the vehicle, including the driving track, speed and other data. The pilot vehicle or the following vehicle may draw or query the historical driving track of the pilot vehicle through the data recorded by the vehicle recorder.

[0037] Exemplarily, the driving pattern data of the pilot vehicle can be determined based on its historical driving trajectory (specifically, a trajectory prediction model can be trained through machine learning technology, and the driving trajectory of the pilot vehicle in the next time period can be predicted based on the trajectory prediction model and the current position and driving status of the pilot vehicle); and the current position of the pilot vehicle, real-time traffic information (for example, road condition information and traffic light information) and the driving intention information of the pilot vehicle (for example, the destination or a preset driving route) can be obtained; finally, based on the above-mentioned driving pattern data, the current position of the pilot vehicle, real-time traffic information, and at least one of the driving intention information of the pilot vehicle, the driving trajectory of the pilot vehicle in the next time period is predicted to obtain the predicted driving trajectory of the pilot vehicle.

[0038] In one embodiment, determining the target driving trajectory of the following vehicle in the next time period based on the current position, the historical driving trajectory and the predicted driving trajectory may include:

[0039] S130-1: Determine whether the current position belongs to a historical driving trajectory;

[0040] S130-2: In response to the current position belonging to a historical driving trajectory, determining a target driving trajectory according to the historical driving trajectory and the predicted driving trajectory;

[0041] S130-3: In response to the current position not belonging to the historical driving trajectory, determine whether there is a lane reference line in the current driving environment, and obtain a lane reference line determination result; determine the target driving trajectory based on the lane reference line determination result, the historical driving trajectory and the predicted driving trajectory.

[0042] Among them, either S130-2 or S130-3 can be executed.

[0043] For S130-1, exemplarily, S130-1 may include: determining whether the current position belongs to the longitudinal position range corresponding to the historical driving trajectory, and whether the position difference between the current position and the lateral position range corresponding to the historical driving trajectory is less than a set threshold.

[0044] Accordingly, the above-mentioned response that the current position belongs to the historical driving trajectory includes: responding that the current position belongs to the corresponding longitudinal position range and the position difference is less than the set threshold. That is, if the current position belongs to the corresponding longitudinal position range and the position difference is less than the set threshold, it can be determined that the current position belongs to the historical driving trajectory, or that the current position is on the historical driving trajectory.

[0045] Accordingly, in response to the current position not belonging to the historical driving track, it includes: in response to the current position not belonging to the corresponding longitudinal position range, and / or the position difference is greater than or equal to the set threshold. That is, if the current position does not belong to the corresponding longitudinal position range, and / or the position difference is greater than or equal to the set threshold, it can be determined that the current position does not belong to the historical driving track, or that the current position is not on the historical driving track.

[0046] Among them, the current position can specifically be a position coordinate; the historical driving trajectory can be a polynomial, the longitudinal position range corresponding to the historical driving trajectory can refer to the longitudinal coordinate range corresponding to the polynomial; the transverse position range corresponding to the historical driving trajectory can refer to the transverse coordinate range corresponding to the polynomial.

[0047] If the ordinate corresponding to the current position belongs to the ordinate range corresponding to the polynomial, it is determined that the current position belongs to the longitudinal position range corresponding to the historical driving trajectory; if the ordinate corresponding to the current position does not belong to the ordinate range corresponding to the polynomial, it is determined that the current position does not belong to the longitudinal position range corresponding to the historical driving trajectory.

[0048] The position difference may refer to the absolute value of the difference between the horizontal coordinate corresponding to the current position and the minimum horizontal coordinate or the maximum horizontal coordinate in the horizontal position range. Alternatively, if the horizontal coordinate corresponding to the current position belongs to the horizontal position range, the position difference may be directly determined to be 0; if the horizontal coordinate corresponding to the current position does not belong to the horizontal position range, the position difference may be determined to be the absolute value of the difference between the horizontal coordinate corresponding to the current position and the minimum horizontal coordinate or the maximum horizontal coordinate in the horizontal position range.

[0049] For S130-2, exemplarily, S130-2 may include: determining a first preset sampling interval; sampling the historical driving trajectory and the predicted driving trajectory according to the first preset sampling interval to obtain multiple first sampling points; and determining the target driving trajectory according to the multiple first sampling points.

[0050] Among them, the first preset sampling interval can be an equally spaced sampling interval or an unequally spaced sampling interval; in addition, the first preset sampling interval can include two different sampling intervals for sampling the historical driving trajectory and the predicted driving trajectory respectively; or, it can include one sampling interval for sampling the historical driving trajectory and the predicted driving trajectory at the same sampling interval.

[0051] The sampling point specifically refers to the location point in the driving trajectory where the sample is taken.

[0052] Specifically, the above-mentioned determination of the target driving trajectory according to the plurality of first sampling points includes: performing polynomial fitting (or curve fitting or linear interpolation) on the plurality of first sampling points to obtain the target driving trajectory. Wherein, a piecewise polynomial can be used to fit the plurality of first sampling points. For example, the coordinates of the plurality of first sampling points can be determined to obtain a plurality of first sampling coordinates; the plurality of first sampling coordinates can be segmented (for example, uniform segmentation, segmentation based on curvature change, etc.); the first sampling coordinates of each segment are respectively subjected to polynomial fitting (for example, least square method, etc.), and then the polynomials obtained by fitting each segment are spliced ​​to obtain the target driving trajectory. Wherein, the piecewise polynomial can refer to: dividing the entire definition domain (the definition domain of the original function, that is, the sum of the definition domains corresponding to each segment of the first sampling coordinates) into a plurality of small intervals (or referred to as segments, that is, the definition domains corresponding to each segment of the first sampling coordinates), and using a polynomial to represent the original function in each small interval, and these polynomials are continuous in their respective intervals, and may satisfy certain connection conditions (such as continuity, differentiability, etc.) at the endpoints of the intervals.

[0053] Alternatively, multiple first sampling points may be directly connected to obtain the target driving trajectory.

[0054] For S130-3, illustratively, the following two situations may be included for S130-3:

[0055] In case 1, the lane reference line judgment result is that there is no lane reference line in the current driving environment, and a first spliced ​​trajectory is determined according to a current coordinate point corresponding to the current position and a specific coordinate point corresponding to a specific position in the historical driving trajectory; and a target driving trajectory is determined according to the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory;

[0056] The specific coordinate point corresponding to the specific position in the historical driving trajectory may be the coordinate point corresponding to the first position point in the historical driving trajectory, but is not limited thereto. The first position point may be the first position point in the time sequence. For example, assuming that the historical driving trajectory includes the coordinates of the position point at the 1st second and the coordinates of the position point at the 2nd second, the first position point may be the position point at the 1st second.

[0057] Specifically, determining the first spliced ​​trajectory according to the current coordinate point corresponding to the current position and the specific coordinate point corresponding to the specific position in the historical driving trajectory may include: performing polynomial fitting, curve fitting, or linear interpolation on the current coordinate point and the specific coordinate point to obtain the first spliced ​​trajectory. Alternatively, directly connecting the current coordinate point and the specific coordinate point to obtain the first spliced ​​trajectory.

[0058] Specifically, the above-mentioned determining the target driving trajectory according to the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory includes: determining a second preset sampling interval; sampling the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory according to the second preset sampling interval to obtain multiple second sampling points; determining the target driving trajectory according to the multiple second sampling points (specifically, using a piecewise polynomial to fit the multiple second sampling points).

[0059] Among them, the specific process of the second preset sampling interval, the second sampling point and determining the target driving trajectory based on multiple second sampling points can all refer to the above S130-2, and to avoid repetition, they will not be described in detail.

[0060] Case 2: The lane reference line judgment result is that there is a lane reference line in the current driving environment. According to the lane reference line, the current coordinate point corresponding to the current position and the specific coordinate point corresponding to the specific position in the historical driving trajectory are converted to obtain the first coordinate points of the current coordinate point and the specific coordinate point in the first coordinate system corresponding to the lane reference line respectively; according to each first coordinate point, the second spliced ​​trajectory in the first coordinate system is determined; the second spliced ​​trajectory is converted to the coordinate system to obtain the second spliced ​​trajectory in the second coordinate system corresponding to the target driving trajectory (specifically, it can be the coordinates according to the lane reference line); according to the second spliced ​​trajectory in the second coordinate system, the historical driving trajectory and the predicted driving trajectory, the target driving trajectory is determined.

[0061] The first coordinate system corresponding to the lane reference line may be a curved coordinate system of the lane reference line (which may take into account the shape and curvature of the lane reference line); the second coordinate system corresponding to the target driving trajectory may be a Cartesian coordinate system, but is not limited thereto. In addition, both the historical driving trajectory and the predicted driving trajectory may be trajectories in a Cartesian coordinate system.

[0062] Specifically, the determination of the second splicing trajectory in the first coordinate system for each of the first coordinate points may include: performing polynomial fitting or curve fitting on the first coordinate point corresponding to the current coordinate point in the first coordinate system and the first coordinate point corresponding to the specific coordinate point in the first coordinate system to obtain the second splicing trajectory. Alternatively, directly connecting each of the second coordinate points to obtain the second splicing trajectory.

[0063] Specifically, the above-mentioned determining the target driving trajectory according to the second spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory in the second coordinate system includes: determining a third preset sampling interval; sampling the second spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory in the second coordinate system according to the third preset sampling interval to obtain multiple third sampling points; and determining the target driving trajectory according to the multiple third sampling points.

[0064] Among them, the specific process of the third preset sampling interval, the third sampling point and determining the target driving trajectory according to multiple third sampling points can all refer to the above S130-2, and to avoid repetition, they are not described in detail.

[0065] The lane reference line may be a lane reference line closest to the following vehicle.

[0066] In one embodiment, Figure 3 As shown, the current position of the following vehicle (i.e., the following vehicle) and the historical trajectory (i.e., the historical driving trajectory) of the leading vehicle (i.e., the leading vehicle) can be obtained first, and it is determined whether the following vehicle is on the historical trajectory of the leading vehicle: if the current position of the following vehicle is within the longitudinal range of the historical trajectory of the leading vehicle and the absolute value of the difference with its lateral range is less than a set threshold, it is determined that the following vehicle is on the historical trajectory of the leading vehicle, and the historical trajectory of the leading vehicle and the predicted trajectory (i.e., the predicted driving trajectory) are sampled respectively according to the set sampling interval, and then the obtained sampling points are fitted using a piecewise polynomial to generate a driving reference line of the following vehicle, i.e., the target driving trajectory.

[0067] If the current position of the following vehicle is not within the longitudinal range of the historical trajectory of the leading vehicle, and / or the absolute value of the difference with its lateral range is greater than or equal to a set threshold, it is determined that the following vehicle is not on the historical trajectory of the leading vehicle. A polynomial curve can be used to connect the current position of the following vehicle and the first trajectory point in the historical trajectory of the leading vehicle to determine the target driving trajectory.

[0068] Specifically, we can first determine whether the current driving environment (such as the driving road) has a lane reference line: if there is no lane reference line, we can perform polynomial curve fitting in the Cartesian coordinate system. Specifically, we can fit a cubic polynomial y=f(x) based on the current position of the following vehicle (x1, y1, θ1) and the position of the first trajectory point in the historical trajectory of the pilot vehicle (x2, y2, θ2), that is, the first spliced ​​trajectory; then, the first spliced ​​trajectory, the historical trajectory of the pilot vehicle, and the predicted trajectory of the pilot vehicle are sampled at equal intervals, and the obtained sampling points are fitted using a piecewise polynomial to generate a driving reference line for the following vehicle. If there is a lane line, determine the lane reference line closest to the following vehicle, and calculate the current position of the following vehicle (x1, y1, θ1) (which can be the coordinates in the Cartesian coordinate system) and the position of the first point in the historical trajectory of the pilot vehicle (x2, y2, θ2), the coordinate points (s1, l1, dl1, ddl1) and (s2, l2, dl2, ddl2) in the curvilinear coordinate system of the lane reference line, where dl1, ddl1, dl2, ddl2 can be set to 0 (where dl and ddl are the first and second derivatives of the lateral offset, respectively) to improve the stability of the second spliced ​​trajectory; then fit (s1, l1, dl1, ddl1) and (s2, l2, dl2, ddl2) to obtain the quintic polynomial l = f (s), i.e., the second spliced ​​trajectory, and then transform the second spliced ​​trajectory into the Cartesian coordinate system according to the coordinates of the lane reference line. Then, the second spliced ​​trajectory in the Cartesian coordinate system, the historical trajectory of the leading vehicle, and the predicted trajectory of the leading vehicle are sampled at equal intervals, and then the obtained adopted points are fitted using a piecewise polynomial to generate a driving reference line for the following vehicle.

[0069] Through the technical solution of this application, when determining the target driving trajectory, the lane reference line is taken into account, which can prevent the following vehicle's driving trajectory from exceeding the lane driving range, and ensure that when the following vehicle is not on the historical trajectory of the pilot vehicle, the shape of the generated spliced ​​trajectory is similar to the shape of the lane line, thereby ensuring the quality of the generated driving trajectory; the predicted driving trajectory of the pilot vehicle is taken into account, which can prevent the following vehicle from lagging behind the pilot vehicle significantly, and ensure that the following vehicle follows the driving behavior of the pilot vehicle more timely. Therefore, the quality of the generated driving trajectory can be improved to meet the computing power requirements.

[0070] It should be noted that all the above technical solutions can be combined in any way to form optional embodiments of the present application, which will not be described one by one here.

[0071] Figure 4 Schematic diagram of a driving trajectory processing device 400 provided in an embodiment of the present application. Figure 4 As shown, the driving trajectory processing device 400 includes: a position acquisition module 410 , a trajectory determination module 420 , and a trajectory processing module 430 .

[0072] In one embodiment, the position acquisition module 410 is used to obtain the current position of the following vehicle and the historical driving trajectory of the leading vehicle corresponding to the following vehicle; the trajectory determination module 420 is used to determine the predicted driving trajectory of the leading vehicle in the next time period; the trajectory processing module 430 is used to determine the target driving trajectory of the following vehicle in the next time period based on the current position, the historical driving trajectory and the predicted driving trajectory.

[0073] In one embodiment, the trajectory processing module 430 is specifically used to: determine whether the current position belongs to a historical driving trajectory; in response to the current position belonging to the historical driving trajectory, determine the target driving trajectory according to the historical driving trajectory and the predicted driving trajectory; or, in response to the current position not belonging to the historical driving trajectory, determine whether there is a lane reference line in the current driving environment, and obtain a lane reference line judgment result; determine the target driving trajectory according to the lane reference line judgment result, the historical driving trajectory and the predicted driving trajectory.

[0074] In one embodiment, the trajectory processing module 430 is specifically used to: determine whether the current position belongs to the longitudinal position range corresponding to the historical driving trajectory, and whether the position difference between the current position and the lateral position range corresponding to the historical driving trajectory is less than a set threshold; in response to the current position belonging to the corresponding longitudinal position range and the position difference being less than the set threshold, determine the target driving trajectory according to the historical driving trajectory and the predicted driving trajectory; or, in response to the current position not belonging to the corresponding longitudinal position range, and / or the position difference being greater than or equal to the set threshold, determine whether there is a lane reference line in the current driving environment, and obtain a lane reference line judgment result; determine the target driving trajectory according to the lane reference line judgment result, the historical driving trajectory and the predicted driving trajectory.

[0075] In one embodiment, the trajectory processing module 430 is specifically used to: determine a first preset sampling interval; sample the historical driving trajectory and the predicted driving trajectory according to the first preset sampling interval to obtain multiple first sampling points; and determine the target driving trajectory according to the multiple first sampling points.

[0076] In one embodiment, the trajectory processing module 430 is specifically used to perform polynomial fitting on the multiple first sampling points to obtain the target driving trajectory.

[0077] In one embodiment, the trajectory processing module 430 is specifically used to: if the lane reference line judgment result is that there is no lane reference line in the current driving environment, determine the first spliced ​​trajectory according to the current coordinate point corresponding to the current position and the specific coordinate point corresponding to the specific position in the historical driving trajectory; determine the target driving trajectory according to the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory; if the lane reference line judgment result is that there is a lane reference line in the current driving environment, perform coordinate conversion on the current coordinate point corresponding to the current position and the specific coordinate point corresponding to the specific position in the historical driving trajectory according to the lane reference line, and obtain the first coordinate point of the current coordinate point and the specific coordinate point in the first coordinate system corresponding to the lane reference line; determine the second spliced ​​trajectory in the first coordinate system according to each first coordinate point; perform coordinate system conversion on the second spliced ​​trajectory to obtain the second spliced ​​trajectory in the second coordinate system corresponding to the target driving trajectory; determine the target driving trajectory according to the second spliced ​​trajectory in the second coordinate system, the historical driving trajectory and the predicted driving trajectory.

[0078] In one embodiment, the trajectory processing module 430 is specifically used to: determine a second preset sampling interval; according to the second preset sampling interval, sample the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory to obtain multiple second sampling points; determine the target driving trajectory according to the multiple second sampling points; the trajectory processing module 430 is specifically used to: determine a third preset sampling interval; according to the third preset sampling interval, sample the second spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory in the second coordinate system to obtain multiple third sampling points; determine the target driving trajectory according to the multiple third sampling points.

[0079] It should be understood that the embodiments of the device are similar to the embodiments of the above method, and the contents and effects thereof can refer to the contents and effects of the above method, which will not be described in detail in this application. Figure 4 The device 400 shown can execute the above method embodiments, and the above and other operations and / or functions of each module in the device 400 are respectively for implementing the corresponding processes in the above methods, which will not be repeated here for the sake of brevity.

[0080] The above describes the device 400 of the embodiment of the present application from the perspective of the functional module in conjunction with the accompanying drawings. It should be understood that the functional module can be implemented in hardware form, can be implemented by instructions in software form, and can also be implemented by a combination of hardware and software modules. Specifically, the steps of the method embodiment in the embodiment of the present application can be completed by the hardware integrated logic circuit and / or software form instructions in the processor, and the steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or a combination of hardware and software modules in the decoding processor to perform. Optionally, the software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory, and completes the steps in the above method embodiment in conjunction with its hardware.

[0081] Figure 5 A schematic block diagram of an electronic device 500 provided in an embodiment of the present application.

[0082] like Figure 5 As shown, the electronic device 500 may include:

[0083] The memory 510 and the processor 520, the memory 510 is used to store the computer program and transmit the program code to the processor 520. In other words, the processor 520 can call and run the computer program from the memory 510 to implement the method in the embodiment of the present application.

[0084] For example, the processor 520 may be configured to execute the above method embodiments according to instructions in the computer program.

[0085] In some embodiments of the present application, the processor 520 may include but is not limited to:

[0086] General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.

[0087] In some embodiments of the present application, the memory 510 includes but is not limited to:

[0088] Volatile memory and / or non-volatile memory. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM) and direct RAM bus random access memory (DR RAM).

[0089] In some embodiments of the present application, the computer program may be divided into one or more modules, which are stored in the memory 510 and executed by the processor 520 to complete the method provided by the present application. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0090] like Figure 5 As shown, the electronic device may also include:

[0091] The transceiver 530 may be connected to the processor 520 or the memory 510 .

[0092] The processor 520 may control the transceiver 530 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices. The transceiver 530 may include a transmitter and a receiver. The transceiver 530 may further include an antenna, and the number of antennas may be one or more.

[0093] It should be understood that the various components in the electronic device are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

[0094] The present application also provides a computer storage medium on which a computer program is stored, and when the computer program is executed by a computer, the computer can perform the method of the above method embodiment. In other words, the present application embodiment also provides a computer program product containing instructions, and when the instructions are executed by a computer, the computer can perform the method of the above method embodiment.

[0095] When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instruction is loaded and executed on a computer, the computer can be made to perform the corresponding flow in each method in the embodiment of the present application in whole or in part, and generate the functions that can be realized by each method in the embodiment of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instruction can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instruction can be transmitted from a website site, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disk (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0096] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0097] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the system, device or module can be electrical, mechanical or other forms.

[0098] The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. For example, each functional module in each embodiment of the present application may be integrated into a processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

Claims

1. A driving trajectory processing method, characterized in that: include: Acquire the current position of the following vehicle and the historical driving track of the leading vehicle corresponding to the following vehicle; Determining a predicted driving trajectory of the pilot vehicle in a next time period; The target driving trajectory of the following vehicle in the next time period is determined according to the current position, the historical driving trajectory and the predicted driving trajectory.

2. The method according to claim 1, characterized in that The step of determining the target driving trajectory of the following vehicle in the next time period according to the current position, the historical driving trajectory and the predicted driving trajectory comprises: Determining whether the current position belongs to the historical driving trajectory; In response to the current position belonging to the historical driving trajectory, determining the target driving trajectory according to the historical driving trajectory and the predicted driving trajectory; or, In response to the current position not belonging to the historical driving trajectory, it is determined whether there is a lane reference line in the current driving environment, and a lane reference line determination result is obtained; and the target driving trajectory is determined according to the lane reference line determination result, the historical driving trajectory and the predicted driving trajectory.

3. The method according to claim 2, characterized in that The determining whether the current position belongs to the historical driving trajectory includes: Determine whether the current position belongs to the longitudinal position range corresponding to the historical driving trajectory, and whether the position difference between the current position and the lateral position range corresponding to the historical driving trajectory is less than a set threshold; Accordingly, in response to the current position belonging to the historical driving trajectory, the method includes: In response to the current position belonging to the corresponding longitudinal position range and the position difference being less than the set threshold; Accordingly, in response to the current position not belonging to the historical driving trajectory, the method includes: In response to the current position not belonging to the corresponding longitudinal position range, and / or the position difference is greater than or equal to the set threshold.

4. The method according to claim 2, characterized in that: In response to the current position belonging to the historical driving trajectory, determining the target driving trajectory according to the historical driving trajectory and the predicted driving trajectory includes: Determining a first preset sampling interval; According to the first preset sampling interval, sampling the historical driving trajectory and the predicted driving trajectory to obtain a plurality of first sampling points; The target driving trajectory is determined according to the multiple first sampling points.

5. The method according to claim 4, characterized in that The step of determining the target driving trajectory according to the plurality of first sampling points includes: Polynomial fitting is performed on the multiple first sampling points to obtain the target driving trajectory.

6. The method according to claim 2, characterized in that The determining the target driving trajectory according to the lane reference line judgment result, the historical driving trajectory and the predicted driving trajectory includes: If the lane reference line judgment result is that there is no lane reference line in the current driving environment, determining a first spliced ​​trajectory according to a current coordinate point corresponding to the current position and a specific coordinate point corresponding to a specific position in the historical driving trajectory; determining the target driving trajectory according to the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory; If the lane reference line judgment result is that there is a lane reference line in the current driving environment, then according to the lane reference line, coordinate conversion is performed on the current coordinate point corresponding to the current position and the specific coordinate point corresponding to the specific position in the historical driving trajectory to obtain first coordinate points of the current coordinate point and the specific coordinate point in the first coordinate system corresponding to the lane reference line respectively; according to each of the first coordinate points, a second spliced ​​trajectory in the first coordinate system is determined; the second spliced ​​trajectory is converted into a coordinate system to obtain a second spliced ​​trajectory in the second coordinate system corresponding to the target driving trajectory; according to the second spliced ​​trajectory in the second coordinate system, the historical driving trajectory and the predicted driving trajectory, the target driving trajectory is determined.

7. The method according to claim 6, characterized in that The step of determining the target driving trajectory according to the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory includes: determining a second preset sampling interval; According to the second preset sampling interval, sampling the first spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory to obtain a plurality of second sampling points; Determining the target driving trajectory according to the plurality of second sampling points; The determining the target driving trajectory according to the second spliced ​​trajectory in the second coordinate system, the historical driving trajectory and the predicted driving trajectory includes: determining a third preset sampling interval; According to the third preset sampling interval, sampling the second spliced ​​trajectory, the historical driving trajectory and the predicted driving trajectory in the second coordinate system to obtain a plurality of third sampling points; The target driving trajectory is determined according to the multiple third sampling points.

8. A driving trajectory processing device, characterized in that: include: A position acquisition module, used to acquire the current position of the following vehicle and the historical driving track of the leading vehicle corresponding to the following vehicle; A trajectory determination module, used to determine the predicted driving trajectory of the pilot vehicle in the next time period; The trajectory processing module is used to determine the target driving trajectory of the following vehicle in the next time period according to the current position, the historical driving trajectory and the predicted driving trajectory.

9. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

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

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