Path planning method and system

Abstract

The invention provides a path planning method and system. The method comprises the following steps: acquiring real-time position information of a vehicle, parking space information in a destination preset range of the vehicle and traffic flow information; determining a first change trend of the traffic flow and a second change trend of the parking space according to the traffic flow information and the parking space information; determining a vehicle information node according to the real-time position information and the parking space information; determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend; through the change trend of the flow information and the parking space information, the optimal target driving path can be dynamically re-planned when the road is congested or the parking space is changed, so that the time and the oil consumption cost for finding the parking space are reduced, the travel efficiency is improved, and the vehicle overstock in the congested area is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of big data analysis, and in particular, to a path planning method and system. BACKGROUND

[0002] With the rapid growth of the national economy, the domestic automobile ownership is increasing, which leads to the number of parking spaces in many cities in China becoming extremely scarce. In some specific holidays, the parking demand in places with dense human flow such as shopping centers, sports venues, tourist attractions and large event venues far exceeds the carrying capacity of parking lots, often causing users to wait for a long time and long-term congestion of parking lots, affecting the travel experience of citizens and the overall traffic smoothness.

[0003] The related technology plans the optimal path for the vehicle to drive to the target parking space by obtaining the real-time parking space state and the traffic flow inside the parking lot, or uses means such as increasing parking spaces, optimizing the layout of the parking lot, implementing dynamic parking charging and encouraging public transportation to alleviate the problem of parking lot congestion and parking difficulty. However, the above method only considers the internal factors of the parking lot, which is easily affected by the traffic flow at that time, and cannot fundamentally solve the problem of parking lot congestion and parking difficulty. SUMMARY

[0004] In view of the above problems, the embodiments of the present application are proposed to provide a path planning method and system which can overcome the above problems or at least partially solve the above problems.

[0005] According to a first aspect of the present application, a path planning method is provided, the method comprising: obtaining real-time position information of a vehicle, parking space information within a preset range of a destination of the vehicle, and traffic flow information; determining a first change trend of traffic flow and a second change trend of parking space according to the traffic flow information and the parking space information; determining a vehicle information node according to the real-time position information and the parking space information; determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend.

[0006] Optionally, the parking space information includes idle parking space demand information and idle parking space position information within a parking lot within the preset range of the destination. obtaining real-time position information of a vehicle, parking space information within a preset range of a destination of the vehicle, and traffic flow information includes: obtaining the real-time position information according to a positioning system of the vehicle; acquiring the real-time position information collected by a positioning system of the vehicle, first image data collected by a camera of a traffic road where the vehicle is located, and second image data collected by a camera of the parking lot; determining driving data of other vehicles according to the first image data and the second image data; acquiring the idle parking space demand information, the idle parking space position information, and traffic flow information according to the driving data.

[0007] Optionally, determining a first change trend of traffic flow and a second change trend of parking spaces according to the traffic flow information and the parking space information comprises: determining the first change trend of traffic flow according to the traffic flow information and historical traffic flow information; determining the second change trend of idle parking spaces according to the parking space information, the real-time position information, and historical parking data of the parking lot.

[0008] Optionally, the method further comprises: replanning a driving path according to newly determined vehicle information nodes and parking space information in a case where the first change trend, and / or, the second change trend appears a preset change trend.

[0009] Optionally, determining vehicle information nodes according to the real-time position information and the parking space information comprises: determining a straight-line distance between a current position and an idle parking space according to the real-time position information and the parking space information; defining a first circular region with the current position of the vehicle as a center, and defining a second circular region with the idle parking space as a center; a sum of a radius of the first circular region and a radius of the second circular region is the straight-line distance; determining vehicle information nodes of vehicles capable of adjusting stopover positions and routes in the first circular region and the second circular region.

[0010] Optionally, determining a target driving path according to the vehicle information nodes, the parking space information, the first change trend, and the second change trend comprises: determining an idle parking space according to the parking space information; taking a predicted distance between the idle parking space and the real-time position information of the vehicle as a heuristic function value; determining a node weight corresponding to the vehicle information node according to the first change trend, and / or, the second change trend; determining a target driving path according to the heuristic function value and the node weight.

[0011] Optionally, determining the node weight corresponding to the vehicle information node based on the first trend and / or the second trend includes: The traffic congestion situation is determined based on the first trend of change; Based on the second trend, determine the changes in demand for vacant parking spaces and the occupancy status of vacant parking spaces; The node weights are matched based on the congestion situation, and / or based on the demand changes and occupancy status.

[0012] Optionally, planning the target driving path based on the heuristic function value and the node weights includes: The first driving path is planned based on the heuristic function value and the node weight; If the congestion situation changes, and / or the demand situation changes and the occupancy situation changes, update the heuristic function value and node weight; The second driving path is planned based on the updated heuristic function value and node weights; The second driving route is taken as the target driving route.

[0013] Optionally, the method further includes: If the traffic conditions on the target travel route meet the preset conditions, the timing scheme of the traffic lights is adjusted according to the traffic flow information and the target travel route, as well as the stop locations and routes of the vehicles corresponding to the vehicle information nodes.

[0014] According to a second aspect of the present invention, a path planning system is provided, the system comprising: The information acquisition module is used to acquire the vehicle's real-time location information, parking space information within a preset range of the vehicle's destination, and traffic flow information. The first processing module is used to determine a first trend of traffic flow and a second trend of parking space change based on the traffic flow information and the parking space information. The second processing module is used to determine the vehicle information node based on the real-time location information and the parking space information; The route planning module is used to determine the target driving route based on the vehicle information node, the parking space information, the first change trend, and the second change trend.

[0015] The embodiments of the present invention have the following advantages: In the embodiment of the present application, by acquiring real-time position information of the vehicle, parking space information in a preset range of the destination of the vehicle and traffic flow information; determining a first change trend of the traffic flow and a second change trend of the parking space according to the traffic flow information and the parking space information; determining a vehicle information node according to the real-time position information and the parking space information; determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend; through the change trends of the flow information and the parking space information, the optimal target driving path can be dynamically replanned when the road is congested or the parking space changes, the time for searching for the parking space and the fuel consumption cost are reduced, the travel efficiency is improved, and the vehicle backlog in the congestion area is reduced.

[0016] The above description is only a summary of the technical scheme of the present application, in order to more clearly understand the technical means of the present application, and can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical scheme of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0018] Figure 1 is a step flow chart of an embodiment of a path planning method of the present application; Figure 2 is a structural block diagram of an embodiment of a path planning system of the present application. DETAILED DESCRIPTION

[0019] The exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be completely conveyed to those skilled in the art.

[0020] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally a class and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" in the specification and claims indicates at least one of the connected objects, and the character " / ", generally indicates that the objects before and after are in an "or" relationship.

[0021] The path planning method provided by the embodiments of the present application will be described in detail below in combination with the drawings, specific embodiments and application scenarios.

[0022] With the rapid growth of the national economy, the number of domestic vehicles is increasing, which leads to a severe shortage of parking spaces in many cities. In some specific holidays, the demand for parking in places with dense human flow such as shopping centers, sports venues, tourist attractions and large event venues far exceeds the carrying capacity of parking lots, often causing users to wait for a long time and parking lots to be congested for a long time, affecting the travel experience of citizens and the overall traffic flow.

[0023] The related technology plans the optimal path for the vehicle to drive to the target parking space by acquiring the real-time parking space status and the vehicle flow inside the parking lot, or uses means such as increasing parking spaces, optimizing the layout of the parking lot, implementing dynamic parking charging and encouraging public transportation to alleviate the problem of parking lot congestion and parking difficulty.

[0024] However, the way of planning the optimal path for the vehicle to drive to the target parking space by acquiring the real-time parking space status and the vehicle flow inside the parking lot is easily affected by the current traffic flow, and it is difficult to perform efficient and accurate matching, and when driving according to the planned path, the emergency situation such as traffic accident in front of the road will aggravate the road congestion, and cannot alleviate the traffic pressure of the main road and reduce the vehicle backlog in the congestion area.

[0025] Referring to Figure 1 , a step flowchart of an embodiment of a path planning method of the present application is shown, which can specifically include the following steps: Step 101, acquiring real-time position information of a vehicle, parking space information within a destination preset range of the vehicle, and traffic flow information.

[0026] Specifically, real-time position information of the vehicle can be obtained from a vehicle positioning system, a destination of the user can be determined according to user intention or navigation data, a parking lot within a preset range of the destination can be determined, and parking space information within the preset range of the destination and traffic flow information of a traffic road can be determined according to image data collected by cameras deployed on the traffic road and the parking lot, wherein the parking space information includes idle parking space demand information and idle parking space position information within the parking lot within the preset range of the destination, and the traffic flow information can include traffic density, vehicle speed, vehicle type, and traffic accident information on the traffic road.

[0027] In step 102, a first change trend of traffic flow and a second change trend of parking space are determined according to the traffic flow information and the parking space information.

[0028] In the embodiment, after obtaining the real-time position information of the vehicle, the parking space information, and the traffic flow information, the first change trend of the traffic flow on the driving path can be predicted according to the traffic flow information in combination with the real-time position information of the vehicle, and the second change trend of the idle parking space in the parking lot can be analyzed and predicted according to the parking space information, thereby avoiding the problem that the traditional scheme only considers local factors of the parking lot and the entrance of the parking lot to plan the driving path, and is easily affected by the traffic flow of the main road and traffic accidents, and aggravates the problem of vehicle accumulation in the congestion area.

[0029] In step 103, a vehicle information node is determined according to the real-time position information and the parking space information.

[0030] In the embodiment, the acquisition range of the vehicle information node is determined according to the real-time position information of the vehicle and the parking space information, a dispatch request is sent to the vehicles in the range, real-time data collected by the vehicles in the range at a time point closest to the dispatch request is obtained, the obtained real-time data is analyzed, it is determined whether the vehicle corresponding to the real-time data can currently perform a dispatch task, and the vehicle information node of the vehicle that can perform the dispatch task is screened out. In actual application, the dispatch task can include adjusting the stopover location and route of the vehicle.

[0031] In step 104, a target driving path is determined according to the vehicle information node, the parking space information, the first change trend, and the second change trend.

[0032] In the embodiment, the target driving path is determined according to the vehicle information node, the parking space information, the first change trend, and the second change trend, the first change trend of the flow information and the second change trend of the parking space information are used to dynamically re-plan the optimal target driving path when the traffic condition or the parking space changes, thereby avoiding that the user is trapped in long waiting, and improving the travel efficiency.

[0033] The path planning method provided by the embodiment of the application comprises the following steps: acquiring real-time position information of a vehicle, parking space information in a preset range of a destination of the vehicle, and traffic flow information; determining a first change trend of the traffic flow and a second change trend of the parking space according to the traffic flow information and the parking space information; determining a vehicle information node according to the real-time position information and the parking space information; determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend; and dynamically re-planning the optimal target driving path when road congestion or parking space change occurs, so as to reduce the time for searching for parking space and fuel consumption cost, improve travel efficiency, and reduce vehicle backlog in the congestion area.

[0034] In an embodiment of the application, the parking space information comprises idle parking space demand information and idle parking space position information in a parking lot in the preset range of the destination. The acquiring of the real-time position information of the vehicle, the parking space information in the preset range of the destination of the vehicle, and the traffic flow information comprises: The real-time position information is acquired by a positioning system of the vehicle. The real-time position information collected by the positioning system of the vehicle, first image data collected by a camera of a traffic road where the vehicle is located, and second image data collected by a camera of the parking lot are acquired. The driving data of other vehicles are determined according to the first image data and the second image data. The idle parking space demand information, the idle parking space position information and the traffic flow information are acquired according to the driving data.

[0035] In the embodiment of the application, cameras are arranged on the traffic road and the parking lot, and the first image data collected by the camera of the traffic road where the vehicle is located and the second image data collected by the camera of the parking lot in the preset range of the destination are acquired; after the first image data and the second image data are acquired, license plate recognition and video analysis are performed on the first image data and the second image data, idle parking spaces are recognized, and the moving tracks of the vehicles in the image data in the traffic road and the parking lot are determined, the idle parking space demand information and the idle parking space position information are determined according to the moving tracks of the vehicles in the image data in the parking lot and the recognized idle parking spaces, and the traffic flow information of the traffic road is determined according to the moving tracks of the vehicles in the image data in the traffic road and the number of the vehicles.

[0036] In practical applications, a geomagnetic sensor, an ultrasonic sensor, or an infrared sensor can be used to assist the camera in collecting image data to monitor the parking space status and detect the occupancy of the parking space in real time. Traffic flow sensors such as microwave radars, laser radars, and video monitoring systems can be deployed at road entrances and parking lot entrances to monitor the vehicle entry and exit conditions and traffic flow data in real time, and collect information such as traffic density, vehicle speed, and vehicle type on the road.

[0037] Optionally, a three-dimensional dynamic data model can be constructed based on the image data collected by the camera, the dynamic data model can be transmitted to the vehicle host, and feedback can be provided to the master screen to display the dynamic planning path and the current driving vehicle, pedestrian, or obstacle on the path, and to autonomously determine the probability of entering the idle vehicle and assist the driver in determining the best path and the corresponding idle parking space.

[0038] By fusing real-time image data of traffic roads and parking lots, a dynamic traffic information perception network is constructed, and based on license plate recognition and trajectory tracking, the parking space occupancy change rule and the moving trend of vehicles are mastered in real time, so that the bidirectional prediction of parking demand and traffic flow is realized. By analyzing the trajectory characteristics of vehicles in the parking lot, the spatial distribution and demand state of idle parking spaces can be accurately positioned, and by combining with the road traffic density, the traditional single road optimization can be upgraded to "road-parking lot" collaborative optimization. By predicting the traffic peak at the parking lot entrance and the traffic road, vehicles can be guided in advance, effectively alleviating the secondary congestion caused by the accumulation of vehicles searching for parking spaces around the parking lot, and forming the spatiotemporal balance of traffic flow and parking demand.

[0039] In an embodiment of the present application, determining a first change trend of traffic flow and a second change trend of parking spaces according to the traffic flow information and the parking space information comprises: determining a first change trend of traffic flow according to the traffic flow information and historical traffic flow information; determining a second change trend of idle parking spaces according to the parking space information, the real-time location information, and historical parking data of the parking lot.

[0040] In an embodiment of the present application, according to the traffic flow information, the congestion of each traffic road is monitored, the future traffic trend is predicted based on the historical traffic flow information, the first change trend is obtained, the road conditions of the corresponding traffic road are determined according to the first change trend, and dynamic traffic control suggestions are provided. Secondly, according to the parking space information and the real-time location information of the vehicle, the time when the vehicle reaches the idle parking space can be estimated, the second change trend is predicted by combining the historical parking data, and whether the parking space is occupied by other vehicles before the vehicle arrives can be determined by the second change trend, so as to determine the parking lot which is not occupied or has an idle parking space before the vehicle arrives, and the resource allocation and use efficiency of the parking lot can also be optimized according to the second change trend.

[0041] In practical applications, the clustering analysis algorithm can be used to predict the change trend of the traffic flow information and the parking space information, and the formula is as follows:

[0042] Wherein, J is a target function to be minimized, indicating the sum of the square distances of all data points to respective centroids; Indicates a data point, including traffic flow information and parking space information; Is an indicator function, indicating that when the data point Belongs to cluster j, 1 is taken, otherwise 0 is taken; Indicates the centroid of the jth cluster; Indicates the Euclidean distance of the data point To the centroid Square.

[0043] Optionally, dynamic path planning suggestions can also be provided for the driver based on the real-time updated traffic flow information combined with the historical traffic flow information.

[0044] The first change trend provides real-time traffic signal optimization suggestions and traffic jam avoidance strategies for route planning, effectively reducing the path dynamic adjustment delay. At the same time, based on the second change trend, the spatiotemporal matching degree of the ego vehicle and the target parking space can be accurately calculated: by analyzing the historical turnover rate of the parking space, the surrounding vehicle motion trajectory and the arrival time prediction, the high-confidence parking space that remains idle during the journey period is intelligently selected, and the prediction result is combined with the real-time traffic to reduce the time and fuel consumption cost of finding a parking space, improve the travel efficiency, and reduce the vehicle backlog in the congestion area.

[0045] In an embodiment of the present application, the method further comprises: In the case where the first change trend, and / or, the second change trend appears a preset change trend, the driving path is re-planned according to the newly determined vehicle information node and parking space information.

[0046] In the embodiment of the present application, in the case where the first change trend, and / or, the second change trend appears a preset change trend, the latest real-time position information is acquired, and then the parking space information and the vehicle information node are re-determined, and the driving path is re-planned according to the newly determined parking space information and vehicle information node.

[0047] When the driving path is adjusted by the first change trend and / or the second change trend, the optimal route can be re-planned in time to avoid the user being trapped in long waiting.

[0048] In actual application, when serious road congestion occurs on the originally planned travel path, and / or all free parking spaces in the original parking lot are occupied, and the second change trend predicts that no free parking space will appear before the ego vehicle arrives, in order to avoid vehicle accumulation in the congestion area and reduce the time for searching for a parking space, the latest real-time position information is acquired, the corresponding vehicle information node and parking space information are determined again, and the travel path is re-planned according to the newly determined vehicle information node and parking space information.

[0049] In an embodiment of the present application, determining the vehicle information node according to the real-time position information and the parking space information comprises: determining the straight-line distance between the current position and the free parking space according to the real-time position information and the parking space information; defining a first circular region with the current position of the vehicle as the center and defining a second circular region with the free parking space as the center; the sum of the radius of the first circular region and the radius of the second circular region is the straight-line distance; determining the vehicle information node of the vehicle capable of adjusting the stopover position and the route in the first circular region and the second circular region.

[0050] In the embodiment, the plurality of free parking spaces are allocated to different vehicles, each vehicle corresponds to a vehicle information node, the plurality of free parking spaces are connected to each other, and an intelligent parking space system is formed; and the real-time data of each vehicle is periodically collected. Before path planning, a dispatch request is sent, the dispatch request including the current position information of the dispatch task, the position of the determined free parking space, and the time upper limit of the dispatch task; after receiving the dispatch request, the straight-line distance between the real-time position information of the ego vehicle and the position of the determined free parking space is determined, a first circular region is defined with the current position of the ego vehicle as the center, and a second circular region is defined with the position of the determined free parking space as the center; the sum of the radius of the first circular region and the radius of the second circular region is the straight-line distance; then information acquisition instructions are sent to the vehicle information nodes corresponding to each vehicle in the first circular region and the second circular region, respectively, to acquire the real-time data collected at the time point closest to the current time point, the acquired real-time data are analyzed to determine whether the vehicle corresponding to the real-time data can currently perform the dispatch task, and the vehicle information nodes of the vehicles capable of performing the dispatch task are screened out, wherein the dispatch task can include adjusting the stopover position and the route.

[0051] In actual application, if at least one vehicle in the first and second circumferential regions takes the same idle parking space as the end of travel, the priority of each vehicle can be determined according to the traffic flow information of the road where each vehicle is located and the distance from the idle parking space, the vehicle with a short distance and a small traffic road congestion condition is taken as the first priority, the vehicle with a long distance and a serious traffic road congestion condition is taken as the second priority, and the target travel path is planned according to the vehicle of the first priority, and the idle parking space determined by the vehicle of the second priority is adjusted if necessary, so as to avoid repeated locking of the same idle parking space, and to cause low parking efficiency and traffic road congestion.

[0052] After the vehicle information node of the vehicle capable of performing the dispatch task is determined, the path of the current dispatch task is planned using a preset path planning algorithm according to the screened vehicle information node, the obtained vehicle information node and the idle parking space are constructed into a target travel path, and the idle parking space is reached within the planning time.

[0053] By screening the vehicle information node with the dispatch condition in real time, the target travel path is generated by combining the path planning algorithm, the planning efficiency of the parking route is effectively optimized, and based on the real-time matching of the vehicle information node and the idle parking space, the optimal path from the current position to the idle parking space can be quickly constructed, the invalid travel mileage caused by blind detours is reduced, the selected vehicle information node can be adjusted to stop at the place and the route if necessary, the congestion of the traffic road is reduced, and the ego vehicle can reach the determined idle parking space within the preset time.

[0054] In an embodiment of the present application, determining the target travel path according to the vehicle information node, the parking space information, the first change trend and the second change trend comprises: determining the idle parking space according to the parking space information; taking the expected distance between the idle parking space and the real-time position information of the vehicle as a heuristic function value; determining the node weight corresponding to the vehicle information node according to the first change trend and / or the second change trend; determining the target travel path according to the heuristic function value and the node weight.

[0055] In this embodiment, since the parking space information includes the demand information and location information of available parking spaces within the preset range of the destination, available parking spaces can be determined based on the parking space information. Then, the estimated distance between the available parking space and the real-time location information of the vehicle is used as a heuristic function value. By estimating the cost of the remaining path, nodes closer to the target are prioritized for expansion to reduce unnecessary search range. The node weights corresponding to the vehicle information nodes are determined based on the first trend and / or the second trend. Finally, the target driving path is determined based on the heuristic function value and the node weights.

[0056] In practical applications, the preset route planning algorithm calculates the parking route based on traffic flow information and parking space information, setting the distance from the starting point to the vehicle to 0, i.e. The estimated distance from the starting point to the end point of the available parking space is set as the heuristic function value, i.e. Initialize a priority queue Q containing all nodes; extract the node u with the smallest distance from Q, using the following formula for each adjacent node v:

[0057]

[0058] in: Representing an edge The weight, This represents the heuristic estimate of the cost from node v to an available parking space, i.e., the distance. and This represents the actual cost from the starting point to points u and v.

[0059] Specifically, node weight Adjustments can be made based on the first trend (such as traffic congestion levels, speed limits, etc.) and / or the second trend (the demand for and changes in available parking spaces). For example, the greater the traffic congestion, the higher the weight. As the weight increases, the path planning algorithm will avoid high-weight paths. The mapping relationship between node weights and the first and / or second trend can be set according to the local city's traffic conditions and parking space demand; this invention does not impose any restrictions on this.

[0060] The node weight and the heuristic function value are cooperated to realize efficient search. The node weight reflects the actual path cost, such as the congestion degree of the real-time traffic road, the speed limit and the like, and dynamically adjusts the moving cost between nodes (for example, the weight of the congested road section is increased to avoid the inefficient path). The heuristic function estimates the remaining cost from the current node to the end point (such as Manhattan distance or Euclidean distance), and guides to preferentially expand the area closer to the target, and balances the size of the search parking distance. The two together constitute the total cost, and ensure that the selection of the final target driving path takes into account the congestion degree of the traffic road and the size of the parking distance.

[0061] In an embodiment of the present application, the node weight corresponding to the vehicle information node is determined according to the first change trend and / or the second change trend, which comprises: determining the congestion of the traffic road according to the first change trend; determining the demand change of the idle parking space and the occupation of the idle parking space according to the second change trend; matching the corresponding node weight through the congestion, and / or matching the corresponding node weight through the demand change and the occupation.

[0062] In actual application, the congestion of the traffic road, the demand change of the idle parking space and the occupation of the idle parking space have great influence on the planning of the parking path. If the idle parking space is occupied or the driving road is in the rush hour during driving, the traffic road is congested seriously, which should affect the travel experience and the parking efficiency. Therefore, the corresponding node weight can be matched through the congestion, and / or the corresponding node weight can be matched through the demand change and the occupation.

[0063] Specifically, the congestion of the traffic road in a period of time in the future is determined through the first change trend, and the demand change of the idle parking space and the occupation of the idle parking space in a period of time in the future are determined through the second change trend, which is predicted according to the parking space information, the real-time position information of the vehicle and the historical parking data. In this embodiment, the traffic road with serious congestion and the corresponding time period are matched with the first node weight, the traffic road with almost no congestion is matched with the second node weight, or the idle parking space with serious demand change and occupation is matched with the third node weight, and the idle parking space with good demand change and occupation is matched with the fourth node weight. The first node weight, the second node weight, the third node weight and the fourth node weight can be set with corresponding numerical values or priorities according to specific conditions.

[0064] By determining the target driving path according to the size and priority of the node weight and the path planning algorithm, the node weight can be processed according to the size of the node weight, so that the shortest path can be quickly found, and the user can avoid traffic congestion and find an idle parking space.

[0065] In an embodiment of the present application, planning the target driving path according to the heuristic function value and the node weight comprises: planning a first driving path according to the heuristic function value and the node weight; updating the heuristic function value and the node weight when the congestion condition changes, and / or the demand change condition and the occupancy condition change; planning a second driving path according to the updated heuristic function value and the node weight; taking the second driving path as the target driving path.

[0066] In the embodiment, the first driving path is planned according to the heuristic function value and the node weight, in the case of a serious traffic accident or traffic control leading to traffic congestion, and / or the demand change condition of the idle parking space becomes large and the idle parking space is occupied, the current vehicle information node that meets the condition is determined according to the real-time position of the ego vehicle, and then the heuristic function value and the node weight are updated, the second driving path is planned according to the updated heuristic function value and the node weight, and the second driving path is taken as the target driving path.

[0067] Since the traffic flow information of the traffic road can be obtained, the real-time traffic road condition can be determined, in the first change trend, the traffic accident or traffic control is determined according to the related announcement and the traffic flow information, or in the second change trend, the demand for idle parking spaces is predicted to increase dramatically, and it is determined that all idle parking spaces in the parking lot are occupied, the driving path can be dynamically replanned, the latest driving path is taken as the target driving path, the user can reduce the time and fuel consumption cost of finding a parking space, improve the travel efficiency, and improve the user experience.

[0068] Optionally, the parking space reservation function can be used to allow the user to reserve an idle parking space in advance, in the case of a serious traffic accident or traffic control on the first driving path, the second driving path is switched to, the remaining optional idle parking space is driven into, and the indicator on the corresponding idle parking space is controlled in advance to prompt that the current idle parking space has been selected.

[0069] In an embodiment of the present application, the method further comprises: In the case that the traffic condition on the target driving path meets the preset condition, the timing scheme of the traffic signal lamp is adjusted according to the traffic flow information and the target driving path, and the stop location and route of the vehicle corresponding to the vehicle information node are adjusted.

[0070] In the embodiment, in the case that the traffic condition on the target driving path meets the preset condition, the timing scheme of the traffic signal lamp can be adjusted according to the traffic flow information and the target driving path, and the stop location and route of the vehicle corresponding to the vehicle information node are adjusted.

[0071] Specifically, if the ego vehicle has an emergency (for example, emergency medical treatment or emergency task), the timing scheme of the traffic signal lamp can be dynamically adjusted by the intelligent traffic signal control system in the case that the local traffic management department allows, the intersection passing efficiency is optimized, the signal lamp cycle is adjusted in real time by using the vehicle sensor and data analysis, the main road and the direction with larger traffic flow are preferentially passed, and the public traffic tools such as shared cars, taxis and buses are intelligently dispatched, the vehicle resources are reasonably allocated, the over-concentration of vehicles in the vicinity of the target driving path and the destination terminal is avoided, the operation route and the stop site of the vehicle are dynamically adjusted, and the traffic road congestion of the target driving path is relieved to the maximum extent.

[0072] Optionally, the application can also formulate and implement a dynamic shunting strategy according to real-time traffic data, guide the vehicle flow to relatively smooth roads, relieve the traffic pressure of the main road, publish the shunting suggestions and bypass routes by using the electronic signboard and the mobile application, and reduce the vehicle accumulation in the congestion area.

[0073] In the embodiment of the application, the real-time position information of the vehicle, the parking space information within the preset range of the destination of the vehicle and the traffic flow information are acquired, the first change trend of the traffic flow and the second change trend of the parking space are determined according to the traffic flow information and the parking space information, the vehicle information node is determined according to the real-time position information and the parking space information, the target driving path is determined according to the vehicle information node, the parking space information, the first change trend and the second change trend, the optimal target driving path can be dynamically replanned when the road is congested or the parking space changes according to the change trends of the flow information and the parking space information, the time and the fuel consumption cost for finding the parking space are reduced, the travel efficiency is improved, and the vehicle accumulation in the congestion area is reduced.

[0074] Referring to Figure 2 , a structural block diagram of an embodiment of a path planning system of the application is shown, which can specifically include the following modules: The information acquisition module 201 is used for acquiring the real-time position information of the vehicle, the parking space information within the preset range of the destination of the vehicle and the traffic flow information. The first processing module 202 is used for determining a first change trend of traffic flow and a second change trend of parking spaces according to the traffic flow information and the parking space information. The second processing module 203 is used for determining a vehicle information node according to the real-time position information and the parking space information. The path planning module 204 is used for determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend.

[0075] In the embodiments of the present application, the path planning system provided by the embodiments of the present application acquires real-time position information of a vehicle, parking space information in a preset range of a destination of the vehicle and traffic flow information; determines a first change trend of traffic flow and a second change trend of parking spaces according to the traffic flow information and the parking space information; determines a vehicle information node according to the real-time position information and the parking space information; and determines a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend. The change trends of the traffic flow information and the parking space information can be used to dynamically re-plan an optimal target driving path when road congestion or parking space change occurs, so as to reduce the time for searching for parking spaces and fuel consumption cost, improve travel efficiency and reduce vehicle accumulation in congestion areas.

[0076] For the system embodiments, the description is relatively simple because the system embodiments are basically similar to the method embodiments, and the related parts can be referred to the part of the description of the method embodiments.

[0077] The embodiments of the present application further provide a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement each process of the path planning method embodiments and achieve the same technical effects. To avoid repetition, no further description is given here.

[0078] The embodiments of the present application further provide a vehicle terminal, which comprises a processor, a memory and a communication bus. The communication bus is used to connect the processor and the memory. The processor is used to execute a computer program stored in the memory. The computer program is executed by the processor to implement each process of the path planning method embodiments and achieve the same technical effects. To avoid repetition, no further description is given here.

[0079] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to the embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to be interpreted as including all the changes and modifications falling within the scope of the embodiments of the present application.

[0080] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, apparatus, or computer program product. Accordingly, embodiments of the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, and the like) embodying computer program code thereon for use by or in connection with an instruction execution system. For the purposes of this description, a computer-usable or computer readable storage medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

[0081] Embodiments of the present application are described herein with reference to the drawings, which are as follows: Figure 1 one or more functions specified by one or more blocks Figure 1 one or more functions specified by one or more blocks

[0082] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 one or more functions specified by one or more blocks Figure 1 one or more functions specified by one or more blocks

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more functions specified by one or more blocks Figure 1 one or more functions specified by one or more blocks

[0084] While preferred embodiments of the present application have been described, additional variations and modifications can be made to these embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to cover all such modifications and variations as fall within the scope of the present application.

[0085] Finally, it needs to be explained that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant national and regional laws, regulations and standards, and provide corresponding operation portal for user to choose authorization or refusal.

[0086] It also needs to be explained that in this paper, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the term "includes", "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or terminal device. Without more limitation, the element defined by the statement "includes a" does not exclude the existence of other same elements in the process, method, article or terminal device including the element.

[0087] The above provides a kind of path planning method and a kind of path planning system provided by the present application, the principle and implementation mode of the present application are described in this paper by applying specific examples, the above example is only for helping to understand the method of the present application and its core idea;For those skilled in the art, according to the idea of the present application, there will be changes in specific implementation mode and application range, and the above description should not be understood as the limitation of the present application.

Claims

1. A path planning method characterized by, The method comprises: acquiring real-time position information of a vehicle, parking space information within a preset range of a destination of the vehicle, and traffic flow information; determining a first change trend of traffic flow and a second change trend of parking space according to the traffic flow information and the parking space information; determining a vehicle information node according to the real-time position information and the parking space information; determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend.

2. The method of claim 1, wherein, The parking space information comprises idle parking space demand information and idle parking space position information within a parking lot within the preset range of the destination; acquiring real-time position information of a vehicle, parking space information within a preset range of a destination of the vehicle, and traffic flow information comprises: acquiring the real-time position information according to a positioning system of the vehicle; acquiring first image data collected by a camera of a traffic road where the vehicle is located and second image data collected by a camera of the parking lot according to the real-time position information collected by the positioning system of the vehicle; determining driving data of other vehicles according to the first image data and the second image data; acquiring the idle parking space demand information, the idle parking space position information and the traffic flow information according to the driving data.

3. The method of claim 1, wherein, determining a first change trend of traffic flow and a second change trend of parking space according to the traffic flow information and the parking space information comprises: determining the first change trend of traffic flow according to the traffic flow information and historical traffic flow information; determining the second change trend of idle parking space according to the parking space information, the real-time position information and historical parking data of the parking lot.

4. The method of claim 3, wherein, The method further comprises: replanning a driving path according to newly determined vehicle information node and parking space information in a case where the first change trend and / or the second change trend appears a preset change trend.

5. The method of claim 1, wherein, determining a vehicle information node according to the real-time position information and the parking space information comprises: determining a straight-line distance between a current position and an idle parking space according to the real-time position information and the parking space information; defining a first circumferential region with the current position of the vehicle as a center and a second circumferential region with the idle parking space as a center; a sum of a radius of the first circumferential region and a radius of the second circumferential region is the straight-line distance; determining a vehicle information node of a vehicle capable of adjusting a stopover position and a route within the first circumferential region and the second circumferential region.

6. The method of claim 1, wherein, determining a target driving path according to the vehicle information node, the parking space information, the first change trend and the second change trend comprises: determining an idle parking space according to the parking space information; taking a predicted distance between the idle parking space and the real-time position information of the vehicle as a heuristic function value; determining a node weight corresponding to the vehicle information node according to the first change trend and / or the second change trend; determining a target driving path according to the heuristic function value and the node weight.

7. The method of claim 6, wherein, determining a node weight corresponding to the vehicle information node according to the first change trend and / or the second change trend comprises: determine a congestion condition of a traffic road according to the first change trend; determine a demand change condition of a vacant parking space and an occupancy condition of the vacant parking space according to the second change trend; match a corresponding node weight according to the congestion condition, and / or match a corresponding node weight according to the demand change condition and the occupancy condition.

8. The method of claim 7, wherein, planning a target driving path according to the heuristic function value and the node weight includes: planning a first driving path according to the heuristic function value and the node weight; updating a heuristic function value and a node weight in a case where the congestion condition changes, and / or the demand change condition and the occupancy condition change; planning a second driving path according to the updated heuristic function value and the node weight; taking the second driving path as the target driving path.

9. The method of claim 1, wherein, The method further includes: adjusting a timing scheme of a traffic signal lamp and a stop location and a route of a vehicle corresponding to the vehicle information node according to the traffic flow information and the target driving path in a case where a traffic condition on the target driving path meets a preset condition.

10. A path planning system characterized by, The system includes: an information acquisition module, configured to acquire real-time position information of a vehicle, parking space information within a preset range of a destination of the vehicle, and traffic flow information; a first processing module, configured to determine a first change trend of traffic flow and a second change trend of a parking space according to the traffic flow information and the parking space information; a second processing module, configured to determine a vehicle information node according to the real-time position information and the parking space information; a path planning module, configured to determine a target driving path according to the vehicle information node, the parking space information, the first change trend, and the second change trend.

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