Dynamic path planning method and device of vehicle, vehicle and storage medium

Abstract

The invention relates to a dynamic path planning method and device for a vehicle, the vehicle and a storage medium, and the method comprises the steps: obtaining the current positioning information and destination positioning information of the vehicle; generating at least one planned path based on the current positioning information and the destination positioning information, and obtaining current traffic information of each intersection in each planned path; predicting the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in the corresponding time period; and obtaining traffic interference information of each intersection, respectively assigning the traffic interference information, the traffic efficiency, the path length of each planned path and the road type, respectively estimating the traffic time consumption of each planned path, and screening out a final planned path meeting a preset efficiency condition from the at least one planned path based on the traffic time consumption. Therefore, the technical problem that the travel arrangement of the user is affected due to the fact that the intersection traffic state is complex and path time consumption is difficult to accurately estimate during path planning in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the technical field of path planning, and in particular to a method, device, vehicle and storage medium for dynamic path planning of a vehicle. Background Art

[0002] It is difficult to avoid complex driving conditions such as intersections when planning a route. Due to the instability of traffic conditions at intersections, it is difficult to obtain a relatively accurate time estimate when planning a route, especially when traffic lights are dynamically adjusted. Traffic lights at intersections will adjust the time of the lights according to changes in traffic flow, making it difficult for users to accurately grasp the time to arrive at the destination, thus affecting their travel arrangements. This needs to be improved. Summary of the invention

[0003] The present application provides a dynamic path planning method, device, vehicle and storage medium for a vehicle to solve the technical problem in the related art that the traffic conditions at intersections are complex and it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangements.

[0004] The first aspect of the present application provides a dynamic path planning method for a vehicle, comprising the following steps: obtaining the current positioning information and destination positioning information of the vehicle; generating at least one planned path based on the current positioning information and the destination positioning information, and obtaining the current traffic information of each intersection in each planned path; predicting the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in a corresponding time period; obtaining the traffic interference information of each intersection, assigning values ​​to the traffic interference information, the traffic efficiency, the path length and the road type of each planned path, respectively estimating the travel time of each planned path, and selecting a final planned path that meets the preset efficiency conditions from the at least one planned path based on the travel time.

[0005] Optionally, in one embodiment of the present application, it also includes: taking each intersection in the final planned path as a node, estimating the predicted time when the vehicle passes each node; recording the actual time when the vehicle passes the current node, and calculating the time deviation between the predicted time and the actual time of the current node; if the time deviation is less than a preset deviation threshold, recording the actual time when the vehicle passes the next node, until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

[0006] Optionally, in one embodiment of the present application, after the time deviation of any node is greater than the preset deviation threshold, it also includes: recording the intersection traffic data when the vehicle passes through any node; determining the current traffic interference information of any node based on the intersection traffic data; updating the traffic interference information using the current traffic interference information, and sending the current traffic interference information to a preset terminal.

[0007] Optionally, in one embodiment of the present application, after the time deviation of any node is greater than the preset deviation threshold, it also includes: generating a new planned path with any node as the starting point; pushing the new planned path to the user, and determining the actual planned path of the vehicle based on the user's response information.

[0008] The second aspect of the present application provides a dynamic path planning device for a vehicle, including: a first acquisition module, used to acquire the current positioning information and destination positioning information of the vehicle; a second acquisition module, used to generate at least one planned path based on the current positioning information and the destination positioning information, and acquire the current traffic information of each intersection in each planned path; a prediction module, used to predict the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in the corresponding time period; a planning module, used to acquire the traffic interference information of each intersection, assign values ​​to the traffic interference information, the traffic efficiency, the path length and road type of each planned path, respectively estimate the travel time of each planned path, and screen out the final planned path that meets the preset efficiency conditions from the at least one planned path based on the travel time.

[0009] Optionally, in one embodiment of the present application, it also includes: an estimation unit, used to take each intersection in the final planned path as a node, and estimate the predicted time when the vehicle passes each node; a calculation unit, used to record the actual time when the vehicle passes the current node, and calculate the time deviation between the predicted time and the actual time of the current node; a recording unit, used to record the actual time when the vehicle passes the next node when the time deviation is less than a preset deviation threshold, until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

[0010] Optionally, in one embodiment of the present application, it also includes: a recording module for recording the intersection traffic data when the vehicle passes through any of the nodes; a determination module for determining the current traffic interference information of any of the nodes based on the intersection traffic data; an update module for updating the traffic interference information using the current traffic interference information, and sending the current traffic interference information to a preset terminal.

[0011] Optionally, in one embodiment of the present application, it also includes: a generation module, used to generate a new planned path with any of the nodes as the starting point; a push module, used to push the new planned path to the user, and determine the actual planned path of the vehicle based on the user's response information.

[0012] The third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the dynamic path planning method for the vehicle as described in the above embodiment.

[0013] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the dynamic path planning method for a vehicle as described in the above embodiments.

[0014] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned dynamic path planning method for a vehicle.

[0015] The embodiment of the present application can perform preliminary route planning based on the current positioning information of the vehicle and the positioning information of the destination, and obtain the current traffic information of each intersection in each planned route, predict the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in the corresponding period, and then assign values ​​to the traffic interference information, traffic efficiency, path length and road type of each planned path, respectively, estimate the travel time of each planned path, and select the final planned path that meets the preset efficiency conditions from at least one planned path based on the travel time, so as to obtain a more accurate travel time, so as to improve the user's travel experience. Thus, the technical problem in the related technology that the traffic status of the intersection is complex, and it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangements, is solved.

[0016] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0018] Figure 1 A flow chart of a dynamic path planning method for a vehicle provided according to an embodiment of the present application;

[0019] Figure 2 is a schematic structural diagram of a vehicle according to an embodiment of the present application;

[0020] Figure 3 A schematic diagram of the principle of calculating the traffic efficiency of a vehicle intersection according to an embodiment of the present application;

[0021] Figure 4 A schematic diagram of the structure of a dynamic path planning device for a vehicle provided according to an embodiment of the present application;

[0022] Figure 5 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0024] The following describes the dynamic path planning method, device, vehicle and storage medium of the vehicle of the embodiment of the present application with reference to the accompanying drawings. In view of the technical problem that the traffic state of the intersection is complex in the related technology mentioned in the above background technology, it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangement, the present application provides a dynamic path planning method for a vehicle, in which the path can be initially planned according to the current positioning information and the destination positioning information of the vehicle, and the current traffic information of each intersection in each planned path is obtained, and the traffic efficiency of each intersection is predicted according to the current traffic information and the historical traffic information of each intersection in the corresponding period, and then the traffic interference information, traffic efficiency, path length and road type of each planned path are assigned to the intersection, and the travel time of each planned path is estimated respectively, and the final planned path that meets the preset efficiency condition is selected from at least one planned path based on the travel time, so as to obtain a more accurate travel time, so as to improve the user's travel experience. Thus, the technical problem that the traffic state of the intersection is complex in the related technology, it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangement is solved.

[0025] Specifically, Figure 1 A flow chart of a dynamic path planning method for a vehicle provided in an embodiment of the present application.

[0026] like Figure 1 As shown, the dynamic path planning method of the vehicle includes the following steps:

[0027] In step S101, the current positioning information and destination positioning information of the vehicle are obtained.

[0028] Before performing route planning, the embodiment of the present application can obtain the current positioning information and destination positioning information of the vehicle.

[0029] Among them, the destination location information can be obtained through manual input by the user, or it can be automatically obtained based on the user's historical driving trajectory in the current period. For example, during the working hours on weekdays, the embodiment of the present application can automatically determine that the planned destination is the company location based on past historical data.

[0030] In step S102, at least one planned path is generated based on the current positioning information and the destination positioning information, and the current traffic information of each intersection in each planned path is obtained.

[0031] Furthermore, the embodiments of the present application can generate multiple planned paths based on the current positioning information and the destination positioning information, and identify the current traffic information of the intersections involved in each planned path, such as the current traffic flow at the intersection, the duration of the current traffic light, whether there is any mixing of the lanes involved (such as mixing of right turns and straight driving), and other information.

[0032] Among them, traffic information on road conditions can be obtained by the infrastructure set up at the intersection, or can be uploaded in real time by vehicles passing through the intersection. In an embodiment of the present application, after obtaining the vehicle-side data uploaded by the vehicle passing through the intersection, the traffic information can be derived based on the vehicle speed, driving data and collected traffic light status.

[0033] In step S103, the traffic efficiency of each intersection is predicted based on the current traffic information and the historical traffic information of each intersection in the corresponding time period.

[0034] In the actual implementation process, the embodiment of the present application can use the current traffic information of a certain intersection and the historical traffic information of the intersection in the same time period to predict the traffic efficiency of the road condition.

[0035] Among them, the traffic efficiency can be calculated based on data such as the time from when the vehicle is a certain distance away from the stop line of the intersection to when it passes through the intersection, the vehicle's speed, etc., and because different vehicles have different power performance planning when passing through an intersection, the embodiment of the present application can perform a comprehensive prediction through data from multiple vehicles.

[0036] For example, for a vehicle in comfort driving mode, the speed and efficiency when passing through an intersection can be as follows: Figure 2 and Figure 3 shown.

[0037] like Figure 2 As shown, the vehicle may include the following structures:

[0038] Vehicle stability controller 1: Receives traffic lights, radar, wheel speed and other related signals, controls the brakes and engine to control the acceleration and deceleration of the vehicle;

[0039] Front camera 2: Identify traffic light status;

[0040] Millimeter wave radar 3: measures the distance between the vehicle and the traffic light;

[0041] Wheel speed sensor 4: collects wheel speed pulse signals and provides them to the brake controller;

[0042] Function switch 5: Controls the on / off of this function. When the function switch is on, the vehicle stability controller is authorized to control the acceleration and deceleration of the vehicle.

[0043] Instrument 6: Use images or sounds to remind the driver that the vehicle is being controlled to accelerate or decelerate;

[0044] Brake 7: executes the deceleration request of the vehicle stability controller and controls the vehicle;

[0045] Engine controller 8: receives acceleration request from vehicle stability controller and controls vehicle acceleration.

[0046] like Figure 3 As shown, when passing through an intersection, a vehicle in the comfort driving mode can use the body stability controller 1 to cut off the engine power when the front camera 2 recognizes the red light at the intersection ahead, and calculate the most comfortable deceleration (uniform deceleration is the most comfortable) according to the distance detected by the millimeter wave radar 3 and the vehicle speed measured by the wheel speed sensor 4, thereby avoiding the driver from accelerating continuously and then decelerating suddenly when approaching the traffic light, thereby avoiding increased fuel consumption and discomfort caused by sudden braking; the deceleration calculation process is as follows:

[0047] Using the uniformly accelerated motion formula V 2 -V 2 0=2ax, where V0 is the vehicle speed measured by the current wheel speed sensor 4, V is the vehicle speed when the vehicle reaches the traffic light, the speed when the vehicle reaches the traffic light is 0, a is the required deceleration, and x is the distance between the vehicle and the traffic light measured by the millimeter wave radar 3. Therefore, the formula is transformed as follows: a=-V 2 0 / 2x, thus we get the required deceleration a;

[0048] When the vehicle is driving, the front camera 2 recognizes that the red light at the intersection ahead is about to turn green, the vehicle stability controller 1 reduces or cancels the braking force of the brake 7, and calculates the most comfortable acceleration (uniform acceleration is the most comfortable) according to the distance detected by the millimeter wave radar 3 and the vehicle speed measured by the wheel speed sensor 4, and controls the vehicle acceleration. This avoids the driver's unreasonable deceleration, increased fuel consumption and discomfort caused by sudden acceleration; the acceleration calculation process is as follows:

[0049] Using the uniformly accelerated motion formula V 2 -V 2 0=2ax, where V is the current road speed limit (no clear speed limit sign, the default speed limit is 30km / h), V0 is the vehicle speed measured by the wheel speed sensor 4, a is the required acceleration, and x is the distance between the vehicle and the traffic light measured by the millimeter wave radar 3. Therefore, the formula is transformed as follows: a=V 2 / 2x, thus we get the required acceleration a;

[0050] When the front camera 2 recognizes the green light at the intersection ahead during vehicle driving, the vehicle stability controller 1 reduces or cancels the braking force of the brake 7, and calculates the most comfortable acceleration based on the distance detected by the millimeter wave radar 3 and the vehicle speed measured by the wheel speed sensor 4, and controls the vehicle acceleration. This avoids the driver's unreasonable deceleration, increased fuel consumption and discomfort caused by sudden acceleration. The acceleration calculation formula a=V 2 / 2x;

[0051] When the vehicle is driving, the front camera 2 recognizes that the green light at the intersection ahead is about to turn red, the vehicle stability controller 1 cuts off the engine power, and calculates the most comfortable deceleration based on the distance detected by the millimeter wave radar 3 and the speed measured by the wheel speed sensor 4, and controls the vehicle to decelerate. This prevents the driver from accelerating irrationally, increasing fuel consumption and discomfort caused by sudden deceleration. The deceleration calculation formula a=-V 2 0 / 2x.

[0052] Based on the above situation, the embodiment of the present application can calculate the traffic efficiency by combining the vehicle speed, the time it takes to pass through the intersection, and the path distance.

[0053] In step S104, traffic interference information of each intersection is obtained, and the traffic interference information, traffic efficiency, path length and road type of each planned path are assigned values ​​respectively, and the travel time of each planned path is estimated respectively, and the final planned path that meets the preset efficiency conditions is selected from at least one planned path based on the travel time.

[0054] It is understandable that there are many types of traffic interference at intersections, such as road construction, increased traffic volume on holidays, traffic light failures, traffic accidents, dynamic changes in traffic light cycles, weather conditions, road types, road speed limits, etc.

[0055] The embodiment of the present application can use traffic interference information as a constraint, and assign corresponding weights to the traffic interference information, traffic efficiency, path length of each planned path, and road type, so as to calculate the travel time.

[0056] Among them, the embodiment of the present application can use historical data analysis to sort the impact ratios of the above data on traffic efficiency, and then obtain corresponding weights.

[0057] Furthermore, the embodiments of the present application can calculate the travel time of all intersections in each planned path, and then obtain the overall travel time of each planned path, and screen the paths according to the time consumption to obtain the final planned path with the highest efficiency, wherein the preset efficiency conditions can be set accordingly by technical personnel in this field according to actual conditions, and no specific restrictions are made here.

[0058] Optionally, in one embodiment of the present application, it also includes: taking each intersection in the final planned path as a node, estimating the predicted time when the vehicle passes each node; recording the actual time when the vehicle passes the current node, and calculating the time deviation between the predicted time and the actual time of the current node; if the time deviation is less than a preset deviation threshold, recording the actual time when the vehicle passes the next node, until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

[0059] Since traffic data is constantly changing, it is difficult to avoid the situation where the actual driving time exceeds the planned time during driving.

[0060] In some embodiments, each intersection in the final planned path can be taken as a node, and the predicted time of arrival at each node is estimated based on the vehicle's current driving speed and / or the vehicle's driving mode, the actual time when the vehicle actually arrives at the node is recorded, and the predicted time and actual time are calculated to determine whether the deviation time is within a certain range. If it exceeds the deviation threshold, it can be considered that the predicted time deviation of the current path is large. If it does not exceed the deviation threshold, the actual time of the next node continues to be recorded until the node with a large deviation is reached or the navigation planning is terminated.

[0061] The preset deviation threshold may be set by those skilled in the art according to actual conditions and is not specifically limited here.

[0062] Optionally, in one embodiment of the present application, after the time deviation of any node is greater than a preset deviation threshold, it also includes: recording the intersection traffic data when the vehicle passes through any node; determining the current traffic interference information of any node based on the intersection traffic data; updating the traffic interference information using the current traffic interference information, and sending the current traffic interference information to a preset terminal.

[0063] Furthermore, the embodiment of the present application can update the traffic interference information according to the actual situation when the deviation is large.

[0064] For example, when the actual time is later than the predicted time, it can be considered that the current node may have traffic congestion, accidents, or unrecorded construction, etc. At this time, the embodiment of the present application can update the traffic interference information of the node for subsequent calculations.

[0065] For another example, when the actual time is earlier than the predicted time, it can be considered that the traffic interference in the historical record can be eliminated, such as the construction has been completed, etc. At this time, the embodiment of the present application can also update the traffic interference information of the node.

[0066] Optionally, in one embodiment of the present application, after the time deviation of any node is greater than a preset deviation threshold, it also includes: generating a new planned path with any node as the starting point; pushing the new planned path to the user, and determining the actual planned path of the vehicle based on the user's response information.

[0067] When the actual time is much later than the predicted time, the embodiment of the present application can re-plan the path and push the new path to the user. If the user chooses the new path, the path will be updated. If the user does not choose the new path, a time-consuming re-estimation can be performed based on the current time.

[0068] According to the dynamic path planning method for vehicles proposed in the embodiment of the present application, preliminary path planning can be performed based on the current positioning information of the vehicle and the positioning information of the destination, and the current traffic information of each intersection in each planned path can be obtained. The traffic efficiency of each intersection is predicted based on the current traffic information and the historical traffic information of each intersection in the corresponding time period, and then the traffic interference information, traffic efficiency, path length and road type of the intersection are assigned respectively, and the travel time of each planned path is estimated respectively. Based on the travel time, the final planned path that meets the preset efficiency conditions is selected from at least one planned path, so as to obtain a more accurate travel time, so as to improve the user's travel experience. In this way, the technical problem in the related technology that the traffic status of the intersection is complex, and it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangements, is solved.

[0069] Next, a dynamic path planning device for a vehicle according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0070] Figure 4 It is a block diagram of a dynamic path planning device for a vehicle according to an embodiment of the present application.

[0071] like Figure 4 As shown, the dynamic path planning device 10 of the vehicle includes: a first acquisition module 100, a second acquisition module 200, a prediction module 300 and a planning module 400.

[0072] Specifically, the first acquisition module 100 is used to acquire the current positioning information and the destination positioning information of the vehicle.

[0073] The second acquisition module 200 is used to generate at least one planned path based on the current positioning information and the destination positioning information, and to acquire the current traffic information of each intersection in each planned path.

[0074] The prediction module 300 is used to predict the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in the corresponding time period.

[0075] The planning module 400 is used to obtain the traffic interference information of each intersection, assign values ​​to the traffic interference information, traffic efficiency, path length and road type of each planned path, estimate the travel time of each planned path, and select the final planned path that meets the preset efficiency conditions from at least one planned path based on the travel time.

[0076] Optionally, in one embodiment of the present application, the dynamic path planning device 10 of the vehicle further includes: an estimation unit, a calculation unit and a recording unit.

[0077] The estimation unit is used to take each intersection in the final planned path as a node and estimate the predicted time when the vehicle passes each node.

[0078] The calculation unit is used to record the actual time when the vehicle passes the current node and calculate the time deviation between the predicted time and the actual time of the current node.

[0079] The recording unit is used to record the actual time when the vehicle passes the next node when the time deviation is less than a preset deviation threshold, until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

[0080] Optionally, in one embodiment of the present application, the dynamic path planning device 10 for a vehicle further includes: a recording module, a determination module and an updating module.

[0081] Among them, the recording module is used to record the intersection traffic data when the vehicle passes through any node.

[0082] The determination module is used to determine the current traffic interference information of any node based on the intersection traffic data.

[0083] The updating module is used to update the traffic interference information using the current traffic interference information and send the current traffic interference information to a preset terminal.

[0084] Optionally, in one embodiment of the present application, the dynamic path planning device 10 for a vehicle further includes: a generation module and a push module.

[0085] The generation module is used to generate a new planning path with any node as the starting point.

[0086] The push module is used to push the new planned path to the user and determine the actual planned path of the vehicle based on the user's response information.

[0087] It should be noted that the above explanation of the embodiment of the dynamic path planning method for a vehicle is also applicable to the dynamic path planning device for a vehicle in this embodiment, and will not be repeated here.

[0088] According to the dynamic path planning device for a vehicle proposed in the embodiment of the present application, a preliminary path planning can be performed based on the current positioning information of the vehicle and the positioning information of the destination, and the current traffic information of each intersection in each planned path can be obtained. The traffic efficiency of each intersection is predicted based on the current traffic information and the historical traffic information of each intersection in the corresponding time period, and then the traffic interference information, traffic efficiency, path length and road type of the intersection are assigned respectively, and the travel time of each planned path is estimated respectively. Based on the travel time, the final planned path that meets the preset efficiency conditions is selected from at least one planned path, thereby obtaining a more accurate travel time to improve the user's travel experience. In this way, the technical problem in the related technology that the traffic status of the intersection is complex and it is difficult to accurately estimate the path time during path planning, thereby affecting the user's travel arrangements, is solved.

[0089] Figure 5 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0090] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0091] When the processor 502 executes the program, the dynamic path planning method for the vehicle provided in the above embodiment is implemented.

[0092] Furthermore, the vehicle also includes:

[0093] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0094] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0095] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0096] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0097] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0098] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0099] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the dynamic path planning method for the vehicle as described above is implemented.

[0100] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the dynamic path planning method for a vehicle provided in an embodiment of the present invention.

[0101] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0102] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0103] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0105] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0106] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0107] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A dynamic path planning method for a vehicle, characterized in that: The following steps are involved: Obtain the vehicle's current location information and destination location information; Generate at least one planned path based on the current positioning information and the destination positioning information, and obtain current traffic information of each intersection in each planned path; Predicting the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in a corresponding period of time; The traffic interference information of each intersection is obtained, and the traffic interference information, the traffic efficiency, the path length and the road type of each planned path are assigned respectively, and the travel time of each planned path is estimated respectively, and based on the travel time, a final planned path that meets the preset efficiency conditions is selected from the at least one planned path.

2. The method according to claim 1, characterized in that Also includes: Taking each intersection in the final planned path as a node, estimating the predicted time when the vehicle passes each node; Recording the actual time when the vehicle passes the current node, and calculating the time deviation between the predicted time and the actual time of the current node; If the time deviation is less than the preset deviation threshold, the actual time when the vehicle passes the next node is recorded until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

3. The method according to claim 2, characterized in that After the time deviation of any node is greater than the preset deviation threshold, the method further includes: Recording the intersection traffic data when the vehicle passes through any of the nodes; Determine the current traffic interference information of any node based on the intersection traffic data; The traffic interference information is updated using the current traffic interference information, and the current traffic interference information is sent to a preset terminal.

4. The method according to claim 2, characterized in that: After the time deviation of any node is greater than the preset deviation threshold, the method further includes: Taking any of the nodes as a starting point, generating a new planning path; The new planned path is pushed to the user, and the actual planned path of the vehicle is determined based on the user's response information.

5. A dynamic path planning device for a vehicle, characterized in that: include: A first acquisition module is used to acquire the current location information and destination location information of the vehicle; A second acquisition module, used to generate at least one planned path based on the current positioning information and the destination positioning information, and to acquire current traffic information of each intersection in each planned path; A prediction module, configured to predict the traffic efficiency of each intersection based on the current traffic information and the historical traffic information of each intersection in a corresponding period of time; A planning module is used to obtain the traffic interference information of each intersection, assign values ​​to the traffic interference information, the traffic efficiency, the path length and road type of each planned path, respectively estimate the travel time of each planned path, and screen out a final planned path that meets the preset efficiency conditions from the at least one planned path based on the travel time.

6. The device according to claim 5, characterized in that Also includes: An estimation unit, used to take each intersection in the final planned path as a node and estimate the predicted time when the vehicle passes each node; A calculation unit, used to record the actual time when the vehicle passes the current node, and calculate the time deviation between the predicted time and the actual time of the current node; A recording unit is used to record the actual moment when the vehicle passes the next node when the time deviation is less than a preset deviation threshold, until the time deviation of any node is greater than the preset deviation threshold, or until the vehicle travels to the destination of the final planned path.

7. The device according to claim 6, characterized in that Also includes: A recording module, used to record the intersection traffic data when the vehicle passes through any of the nodes; A determination module, configured to determine the current traffic interference information of any node based on the intersection traffic data; An updating module is used to update the traffic interference information using the current traffic interference information, and send the current traffic interference information to a preset terminal.

8. The device according to claim 6, characterized in that Also includes: A generation module, used to generate a new planning path with any of the nodes as a starting point; The push module is used to push the new planned path to the user and determine the actual planned path of the vehicle based on the user's response information.

9. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the dynamic path planning method for a vehicle as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the dynamic path planning method for a vehicle as described in any one of claims 1 to 4.

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