Path planning method and device based on road surface data fusion, medium and product

Abstract

The invention relates to the technical field of path planning, in particular to a path planning method and device based on road surface data fusion, a medium and a product, and the method comprises the steps: obtaining the real-time road surface data of each road, and determining the road condition type of each road from the real-time road surface data of each road; updating a preset mine road network model in real time according to the road condition type corresponding to each road; obtaining driving road surface data of the target vehicle, and determining a target road where the target vehicle is located and a road condition type of the target road based on the driving road surface data; when the road condition type of the target road is an abnormal road condition, obtaining destination information of the target vehicle, and determining an associated road of the target road based on the destination information, the target road and the updated mine road network model; and when the road condition type of the associated road is a normal road condition, performing path planning on the target vehicle based on the associated road. According to the invention, the accuracy in the path planning process is improved.

Description

Technical Field

[0001] The present application relates to the field of path planning technology, and in particular to a path planning method, device, medium and product based on road surface data fusion. Background Art

[0002] With the rapid development of autonomous driving technology, path planning, as a key component, has become an important means to improve traffic efficiency, reduce traffic congestion, and optimize driving experience. The core of path planning is to calculate an optimal driving path through a reasonable algorithm given the starting point and end point, so as to save driving time and reduce driving costs to the greatest extent.

[0003] However, traditional path planning methods often rely on a single or limited data source, such as static map data or simple real-time traffic information, which may cause them to be unable to cope with complex and changing traffic environments, thus affecting the accuracy of path planning results. Summary of the invention

[0004] In order to improve the accuracy of the path planning process, the present application provides a path planning method, device, medium and product based on road surface data fusion.

[0005] In a first aspect, the present application provides a path planning method based on road surface data fusion, which adopts the following technical solutions: A path planning method based on road surface data fusion, comprising: Acquire real-time road surface data of each road, and determine the road condition type of each road from the real-time road surface data of each road, wherein the road condition type includes normal road condition and abnormal road condition; updating the preset mine road network model in real time according to the road condition type corresponding to each road to obtain an updated mine road network model, wherein the preset mine road network model includes the position association relationship between each road and each road; Acquire the driving road data of the target vehicle, and determine the target road where the target vehicle is located and the road condition type of the target road based on the driving road data, wherein the target vehicle is a vehicle that needs to be routed; When the road condition type of the target road is an abnormal road condition, obtaining the destination information of the target vehicle, and determining the associated roads of the target road based on the destination information, the target road and the updated mine road network model; The road condition type of the associated road is identified, and when the road condition type of the associated road is a normal road condition, a path is planned for the target vehicle based on the associated road.

[0006] By adopting the above technical solution, it is convenient to grasp the latest status of each road by determining the road conditions in real time, so as to provide effective data support for subsequent path planning. In addition, by superimposing the road condition type of each road into the preset mine road network model, the preset mine network road model is updated, so that the actual traffic conditions of the current mine can be intuitively viewed through the updated preset mine road network model, and path planning is performed based on the real-time updated preset mine road network model and the current road condition type of the target road, so as to effectively avoid traffic congestion, slow driving and other problems that may be caused by abnormal road conditions, thereby improving the accuracy of path planning results, and then improving the efficiency of the transportation system.

[0007] In a possible implementation manner, when a plurality of associated roads are included, the method further includes: According to the association relationship between each associated road and the target road, at least one first-level associated road is determined from the plurality of associated roads, wherein the first-level associated road is a road directly connected to the target road; According to the association relationship between each first-level associated road and other associated roads, the other associated roads are grouped to obtain an associated road group corresponding to each first-level associated road, each associated road group contains associated roads of different association levels, wherein the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are other roads among the multiple associated roads except the first-level associated roads; Determine the number of continuous normal road sections corresponding to each associated road group according to the road condition type of each associated road in each associated road group; Determine the driving distance corresponding to each associated road group according to the path distance of each associated road in each associated road group; Based on the preset calculation weight, the number of continuous normal road sections corresponding to each associated road group and the driving distance, the associated score corresponding to each associated road group is determined, and the path planning for the target vehicle is performed based on the associated road group with the highest associated score.

[0008] By adopting the above technical solution, different associated roads are graded according to the connection relationship between the associated roads and the target roads, which is convenient for giving priority to the associated roads closely related to the target roads, and is also convenient for improving the redundancy and indirectness of the path planning results. By grouping the associated roads, it is convenient to intuitively compare the advantages of different associated roads, and it is also convenient to improve the flexibility and diversity in the path planning process. In addition, by quantitatively analyzing the number of consecutive normal sections and the driving distance in each associated road group, it is convenient to comprehensively evaluate the practicality of different associated road groups, and it is also convenient to avoid potential traffic bottlenecks and unfavorable factors, which helps to select routes with better road conditions, thereby improving driving efficiency and safety.

[0009] In one possible implementation, the method further includes: Determine the associated road group with the highest associated score as the target associated road group, and determine the integration order of each associated road based on the association relationship between the associated roads in the target associated road group; Determine the display length corresponding to each path distance according to the mapping relationship between the path distance and the length of each associated road in the target associated road, wherein the length mapping relationship is the corresponding relationship between the path distance and the display length; Based on the integration order and display length of each associated road, each associated road in the target associated road group is connected to obtain a corresponding target planned route; The real-time traffic data of each associated road is identified, and the travel time and abnormal traffic characteristics corresponding to each associated road are determined according to each real-time traffic data, and the travel time and abnormal traffic characteristics of each associated road are superimposed on the target planning route to form a target planning prompt route.

[0010] By adopting the above technical solution, each associated road is integrated to obtain the target planned route corresponding to the target associated road group, so that the actual traffic conditions of the target planned route can be intuitively viewed. By real-time analysis of the traffic data of each associated road and timely superimposition of abnormal traffic characteristics to the target planned route, the driver can be reminded in real time, so as to reduce the probability of accidents during driving, thereby improving safety during driving.

[0011] In one possible implementation, the method further includes: When the abnormal traffic feature is a preset abnormal feature, determining the associated road containing the preset abnormal feature as a concerned associated road; When the association level of the concerned associated road is not higher than a preset level threshold, determining the first abnormality removal time of the concerned associated road according to the real-time traffic data corresponding to the concerned associated road; When the association level of the concerned associated road is higher than a preset level threshold, determining a second abnormality resolution time of the concerned associated road based on a mapping relationship between the preset abnormality feature and resolution time; A countdown time bar is generated based on the first exception resolution time or the second exception resolution time, and the countdown time bar is superimposed on the target planning prompt route.

[0012] By adopting the above technical scheme, it is convenient to timely determine the associated roads containing preset abnormal features through feature recognition, and by timely identifying the associated roads of concern, it is convenient to respond to abnormal situations occurring during vehicle driving, and it is also convenient to improve the safety of the vehicle during driving. In addition, different strategies are adopted according to the association level of the associated roads of concern to determine the corresponding abnormality release time, so as to improve the adaptability between the abnormality release time and the actual situation of the corresponding associated roads of concern, and then by converting the determined abnormality release time into a countdown time bar and displaying the countdown time bar, it is convenient to provide intuitive data prompts to the driver, so as to inform the driver in advance of potential congestion on the route ahead.

[0013] In one possible implementation, the method further includes: Determine the associated road group whose associated score is not less than the preset score as the candidate associated road group; Determine the planned prompt route corresponding to each candidate associated road group, and identify the real-time evaluation parameters corresponding to each planned prompt route in real time, where the real-time evaluation parameters include the number of preset abnormal features and the total time for abnormality resolution; Determine a real-time evaluation value of each candidate associated road group based on the real-time evaluation parameter corresponding to each candidate associated road group, and determine a real-time display position of each planned prompt route based on each real-time evaluation value; Generate an alternative route form based on the real-time display position of each planned route.

[0014] By adopting the above technical solution, the associated road group can be screened for the second time based on the associated score and the preset score to determine the candidate associated road group, so that the relevant driver can change the route at will during driving. Since the candidate associated road group has a high similarity with the target associated road group, it is more suitable for the driver to change the route during driving, thereby facilitating the improvement of the efficiency of changing the planned route. Then, each candidate associated road group is evaluated in real time to understand the actual situation of each section in each candidate associated road group in real time. Finally, based on the real-time data, it is convenient to dynamically adjust the display position of the candidate route corresponding to each candidate associated road group to ensure that the driver first sees the most suitable or optimal route at the moment.

[0015] In a possible implementation manner, after determining the associated road of the target road, the method further includes: Determining the location of the target vehicle according to the road surface data of the target vehicle; Determining a target arrival entrance based on the location and the associated road; forming a guidance route based on the location and the target arrival entrance, and identifying whether there is a preset mark in the guidance route; When there is a preset sign, the display picture and guide slogan of the preset sign are determined according to historical traffic data, the display picture and guide slogan of the preset sign are superimposed on the guide route to form a superimposed guide route, and the superimposed guide route is fed back to the target vehicle.

[0016] By adopting the above technical solution, the appropriate arrival entrance for the target vehicle can be determined based on the vehicle's current location and related roads. This personalized recommendation helps reduce the driver's confusion and unnecessary detours. In addition, by superimposing display images and guide slogans, the driver is provided with more dimensional road condition information, making the navigation information richer and more comprehensive, thereby facilitating improving the driver's efficiency in the process of changing driving routes.

[0017] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned path planning method based on road surface data fusion.

[0018] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the above-mentioned path planning method based on road surface data fusion.

[0019] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program, and when the computer program is executed by a processor, the path planning method based on road surface data fusion is implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: By determining the road conditions in real time, it is convenient to grasp the latest status of each road, so as to provide effective data support for subsequent path planning. In addition, by superimposing the road condition type of each road into the preset mine road network model, the preset mine network road model can be updated, so that the actual traffic conditions of the current mine can be intuitively viewed through the updated preset mine road network model. Path planning is performed based on the real-time updated preset mine road network model and the current road condition type of the target road, so as to effectively avoid traffic congestion, slow driving and other problems that may be caused by abnormal road conditions, thereby improving the accuracy of path planning results, and then improving the efficiency of the transportation system.

[0021] By means of feature recognition, it is convenient to timely determine the associated roads containing preset abnormal features. By timely identifying the associated roads of concern, it is convenient to respond to abnormal situations occurring during vehicle driving, and it is also convenient to improve the safety of the vehicle during driving. In addition, different strategies are adopted according to the association level of the associated roads of concern to determine the corresponding abnormality release time, so as to improve the adaptability between the abnormality release time and the actual situation of the corresponding associated roads of concern. Then, by converting the determined abnormality release time into a countdown time bar and displaying the countdown time bar, it is convenient to provide intuitive data prompts to the driver, so as to inform the driver in advance of potential congestion on the route ahead. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a path planning method based on road surface data fusion in an embodiment of the present application; Figure 2 It is a flow chart of a countdown time bar superposition method in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following is combined with Figure 1 To Attachment Figure 3 This application is described in further detail.

[0024] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0027] Specifically, the embodiment of the present application provides a path planning method based on road surface data fusion, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0028] refer to Figure 1 , Figure 1 : is a flow chart of a path planning method based on road surface data fusion in an embodiment of the present application, the method comprises steps S110 to S150, wherein: Step S110: acquiring real-time road surface data of each road, and determining the road condition type of each road from the real-time road surface data of each road, where the road condition type includes normal road condition and abnormal road condition.

[0029] Specifically, different roads correspond to different road surface data. The road surface data corresponding to each road can be collected by a road surface image acquisition device set on the corresponding road and then uploaded to the electronic device, wherein the road surface image acquisition device can be a high-definition camera, a road camera, a vehicle-mounted sensor, a laser radar and other equipment, and the specific device is not specifically limited in the embodiment of this application. The road surface data can be traffic lights, road cracks, construction signs, traffic accidents, etc. By analyzing the real-time road surface data of each road, it is convenient to determine the road condition type of each road, wherein abnormal road conditions can include but are not limited to road congestion, traffic accidents, road closures and dangerous road conditions, etc. By identifying the real-time road surface data of each road, it is convenient to determine the road surface features contained in each real-time road surface data, and then based on the correspondence between the road surface features and the road condition type, the road condition type corresponding to each road can be determined.

[0030] Step S120: updating the preset mine road network model in real time according to the road condition type corresponding to each road to obtain an updated mine road network model, wherein the preset mine road network model includes the position association relationship between each road.

[0031] Specifically, the preset mine road network model can be determined according to the mine map and road planning scheme. The preset mine road network model includes the main production trunk line, production branch line, connecting line and auxiliary line of the current mine, as well as the path distance of each road. Among them, the main production trunk line is used as a common road from each mining step in the mining field to the unloading point or waste rock dump. It is the main artery in the mine road network and undertakes the important task of transporting ore from the mining area to the processing or storage area; the production branch line is the road connecting the mining step or waste rock dump with the production trunk line, or a road connected by an opening. The road from the mining step directly to the unloading point or waste rock dump is used as a supplement to the production trunk line to transport ore or waste rock from the specific mining point to the production trunk line or unloading point; the connecting line is other roads that are often used by dump trucks used in open-pit mine production. It plays a role of communication and connection in the mine road network to ensure smooth connection between different mining areas, processing areas and storage areas; the auxiliary line is the road leading to the auxiliary plants and various auxiliary facilities within the mining area for various types of vehicles to drive, mainly serving the auxiliary facilities and auxiliary plants of the mine, ensuring the effective connection between these areas and the main production area. The preset mine road network model also includes the topography, water system distribution and intersection design of the mine. Among them, the intersection design is set at some important intersections or busy transportation channels. The control form of the signal light is set. The corresponding intersection signal control form may be different for different intersections. For example, intersection a is only equipped with a straight signal light, while intersection b is equipped with a straight and left turn signal light.

[0032] When the preset mine road network model is updated in real time according to the road condition type corresponding to each road, the corresponding simulated road can be located from the preset mine road network model according to each road sign, and then the corresponding road condition type can be marked at the corresponding simulated road. Different road condition types correspond to different marks. The specific marking form is not specifically limited in the embodiment of the present application and can be set by relevant technical personnel as long as different road condition types can be distinguished. The positional association relationship between each road refers to the connectivity relationship between each road. For example, road a is directly connected to road b, road b is directly connected to road c, and road a is indirectly connected to road c. In the updated mine road network model, each simulated road is superimposed with a mark representing the corresponding road condition type. By viewing the updated mine network model, it is convenient to intuitively view the traffic status of the entire mine, thereby facilitating the provision of effective data support for subsequent road planning.

[0033] Step S130: Acquire the driving road data of the target vehicle, and determine the target road where the target vehicle is located and the road condition type of the target road based on the driving road data. The target vehicle is a vehicle that needs to be routed.

[0034] Specifically, the target vehicle is a vehicle that needs to be routed. The target vehicle's road surface data can be identified by an image acquisition device installed at the target vehicle and uploaded to an electronic device. Feature recognition of the road surface data can determine the target road where the target vehicle is located. Different roads may have different corresponding road features. Road features can be road names, road numbers, and surrounding buildings. The specific road features are not specifically limited in the embodiments of this application, as long as each road can be identified and distinguished. When determining the road condition type of the target road, the simulated road corresponding to the target road can be identified from the updated mine road network model, and then determined according to the road condition type mark corresponding to the simulated road.

[0035] Step S140: When the road condition type of the target road is an abnormal road condition, the destination information of the target vehicle is obtained, and based on the destination information, the target road and the updated mine road network model, the associated roads of the target road are determined.

[0036] Specifically, when the road condition type of the target road is normal, it indicates that the road on which the target vehicle is traveling does not have congestion, maintenance, accidents, etc., and the target vehicle can continue to travel along the current road; when the road condition type of the target road is abnormal, it indicates that the road on which the target vehicle is traveling may have congestion, maintenance, accidents, etc. If the target vehicle continues to travel along the current road, the time to reach the destination may be prolonged. Therefore, it is necessary to determine the associated roads based on the updated mine road network model, destination information and target road. By choosing a smoother road, the driver can reach the destination more easily and enjoy a more pleasant driving process. It is also convenient to help the driver avoid these potential dangers or uncertainties to ensure driving safety.

[0037] Step S150: Identify the road condition type of the associated road, and when the road condition type of the associated road is normal, perform path planning for the target vehicle based on the associated road.

[0038] Specifically, in order to ensure the driving safety of the driver on the new route, after determining the associated roads of the target road, the road condition type of the associated roads also needs to be identified. Only when the road condition type of the associated roads is normal, a new path planning will be performed based on the associated roads. The number of associated roads may be one or more. When the number of associated roads is multiple and the road condition type of each associated road is normal, one associated road can be randomly determined from the multiple associated roads, and path planning can be performed based on the associated road.

[0039] For the embodiments of the present application, by determining the road conditions in real time, it is convenient to grasp the latest status of each road, thereby facilitating the provision of effective data support for subsequent route planning. In addition, by superimposing the road condition type of each road into the preset mine road network model, the preset mine network road model is updated, so that the actual traffic conditions of the current mine can be intuitively viewed through the updated preset mine road network model. Route planning is performed based on the real-time updated preset mine road network model and the current road condition type of the target road, so as to effectively avoid traffic congestion, slow driving and other problems that may be caused by abnormal road conditions, thereby facilitating the improvement of the accuracy of the route planning results, and further facilitating the improvement of the efficiency of the transportation system.

[0040] Furthermore, in order to avoid potential traffic bottlenecks and unfavorable factors, when multiple associated roads are involved, the method provided in the embodiment of the present application may also include: According to the association relationship between each associated road and the target road, at least one first-level associated road is determined from the plurality of associated roads, and the first-level associated road is a road directly connected to the target road.

[0041] Specifically, the associated road of the target road is a road that is directly or indirectly connected to the target road. In order to facilitate the distinction, different associated roads can be graded according to the connectivity between the associated road and the target road. For example, the road directly connected to the target road can be determined as the first-level associated road of the target road, and the road directly connected to the first-level associated road can be determined as the second-level associated road of the target road, and so on. Since there may be more than one associated road directly connected to the target road, there may be more than one first-level associated road of the target road, and the specific number is not specifically limited in the embodiment of the present application. The association relationship between each associated road and the target road can be determined by the updated mine road network model, which can be specifically from the target road as the starting point to different associated roads, and after arriving at the associated road, the number of passing roads is marked as the route weight at the corresponding arrival position, and finally the association level of each associated road is determined based on the weight mark. The way to determine the association level of each associated road can also use the depth traversal method, and the specific way is not specifically limited in the embodiment of the present application.

[0042] According to the association relationship between each first-level associated road and other associated roads, the other associated roads are grouped to obtain an associated road group corresponding to each first-level associated road, and each associated road group contains associated roads of different association levels, wherein the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are other roads among the multiple associated roads except the first-level associated roads.

[0043] Specifically, for any first-level associated road, other associated roads of the target road based on the first-level associated road can be determined. Other associated roads can be second-level associated roads, third-level associated roads, fourth-level associated roads, etc. of the target road. For example, the target road is road X, associated road a is directly connected to the target road X, associated road b is directly connected to associated road a, and associated road c is directly connected to associated road b, that is, associated road a is the first-level associated road of the target road X, associated road b is the second-level associated road of the target road X, and associated road c is the third-level associated road of the target road X. For the convenience of management, other associated roads that are directly or indirectly connected to the first-level associated road can be grouped and managed to obtain an associated road group corresponding to each first-level associated road. Since a road may be directly or indirectly connected to different roads, the same associated roads may exist in the associated road groups corresponding to different first-level associated roads.

[0044] According to the road condition type of each associated road in each associated road group, the number of continuous normal road sections corresponding to each associated road group is determined.

[0045] Specifically, for any associated road group, different associated roads in the associated road group may correspond to different road condition types, which can be determined based on the updated mine road network model. The number of continuous normal road sections is the number of times the road condition type of the associated roads in the associated road group is normal and continuous. For example, the associated road group includes associated road a, associated road b and associated road c, wherein the road condition type corresponding to associated road a and associated road b is normal, and associated road a and associated road b are directly connected, so the number of continuous normal road sections corresponding to the associated road group is 2. According to the above method, the number of continuous normal road sections corresponding to each associated road group can be determined.

[0046] According to the path distance of each associated road in each associated road group, the driving distance corresponding to each associated road group is determined.

[0047] Specifically, the path distances corresponding to each associated road in each associated road group are summed up and calculated to obtain the driving distance corresponding to each associated road group. The path distance of each associated road can be obtained from the updated mine road network model, and can also be obtained from a third-party website. The specific acquisition method is not specifically limited in the embodiments of the present application.

[0048] Based on the preset calculation weights, the number of consecutive normal road sections corresponding to each associated road group and the driving distance, the associated score corresponding to each associated road group is determined, and the path planning for the target vehicle is performed based on the associated road group with the highest associated score.

[0049] Specifically, the preset calculation weights can be determined by relevant staff based on actual route planning experience and uploaded to the electronic device. The specific calculation weights are not specifically limited in the embodiments of the present application. For any associated road group, the first score corresponding to the number of consecutive normal sections is first determined according to the first numerical conversion relationship, and then the second score corresponding to the driving distance is determined according to the second numerical conversion relationship, wherein the first numerical conversion relationship is the corresponding relationship between the number of consecutive normal sections and the first score, and the second numerical conversion relationship is the corresponding relationship between the driving distance and the second score. The specific contents of the two corresponding relationships are not specifically limited in the embodiments of the present application. After determining the first score and the second score, the associated score of the associated road group is calculated based on the preset calculation weights, the first score and the second score. The associated scores corresponding to all associated road groups are determined in the above manner, and the associated road group with the highest associated score is determined therefrom, and finally the path planning is performed for the target vehicle based on the associated road group with the highest associated score.

[0050] By quantitatively analyzing the number of consecutive normal road sections and the driving distance in each associated road group, it is convenient to comprehensively evaluate the practicality of different associated road groups, which helps to select routes with better road conditions, thereby improving driving efficiency and safety.

[0051] Furthermore, in order to improve the safety during driving, the method provided in the embodiment of the present application also includes: The associated road group with the highest associated score is determined as the target associated road group, and based on the association relationship between the associated roads in the target associated road group, the integration order of each associated road is determined.

[0052] Specifically, after determining to perform path planning according to the target associated road group, the associated roads included in the target associated road group can be integrated, that is, according to the association relationship between each associated road, which is directly connected or indirectly connected, each associated road is sequentially connected to form a continuous road, that is, a planned route.

[0053] According to the path distance and length mapping relationship of each associated road in the target associated road, the display length corresponding to each path distance is determined, and the length mapping relationship is the corresponding relationship between the path distance and the display length.

[0054] Specifically, in order to improve the intuitiveness of the display process to the driver, different display lengths can be used to represent associated roads with different path distances. For any associated road, the display length corresponding to the path distance of each associated road can be determined according to the length mapping relationship. The length mapping relationship is the display length corresponding to different path distances. The specific content can be determined by relevant staff based on historical operating experience.

[0055] Based on the integration order and display length of each associated road, each associated road in the target associated road group is connected to obtain the corresponding target planning route.

[0056] Identify the real-time traffic data of each associated road, and determine the travel time and abnormal traffic characteristics corresponding to each associated road based on each real-time traffic data, and superimpose the travel time and abnormal traffic characteristics of each associated road into the target planning route to form a target planning prompt route.

[0057] Specifically, the target planning route includes each associated road in the target associated road group, and each associated road is displayed with a corresponding display length. Real-time traffic data can be collected by an image acquisition device set at each road and uploaded to an electronic device. The real-time traffic data of each associated road can reflect the traffic conditions of each associated road. Real-time traffic data can also be obtained based on the on-board sensors and on-board image acquisition devices of the detection vehicle. The specific acquisition method is not specifically limited in the embodiments of the present application.

[0058] The travel time of each associated road can be determined according to the average driving speed and path distance of the target vehicle. Since the traffic data corresponding to different moments may be different, for example, a certain associated road section is in normal road condition at the current moment, and may be in abnormal road condition at the next moment. Therefore, although the target planning route is determined based on the number of consecutive normal road sections, in the process of driving according to the target planning route, there may still be abnormal traffic features in the target planning route. The abnormal traffic features may be road maintenance, vehicle collision, etc. The specific features are not specifically limited in the embodiment of the present application. The travel time and abnormal traffic features corresponding to each associated road are superimposed on the corresponding position of the target planning route. Since the traffic data changes in real time, the superimposed content at each associated road in the target planning route also changes in real time. By analyzing the traffic data of each associated road in real time and superimposing the abnormal traffic features on the target planning route in a timely manner, the driver can be reminded in real time to reduce the probability of accidents during driving.

[0059] Furthermore, the method provided in the embodiment of the present application further includes steps S1 to S4, such as Figure 2 As shown, where: Step S1: When the abnormal traffic feature is a preset abnormal feature, the associated road containing the preset abnormal feature is determined as a concerned associated road.

[0060] Specifically, the preset abnormal feature can be a traffic jam or other features that affect vehicle driving, and the specific content can be set by relevant technical personnel. When the abnormal traffic feature corresponding to the associated road is identified as the preset abnormal feature, the associated road is determined as a concerned associated road, and the number of concerned associated roads can be 0, 1, or multiple, and the specific number is not specifically limited in the embodiment of this application.

[0061] Step S2: when the association level of the concerned associated road is not higher than the preset level threshold, determining the first abnormality removal time length of the concerned associated road according to the real-time traffic data corresponding to the concerned associated road.

[0062] Step S3: when the association level of the concerned associated road is higher than a preset level threshold, a second abnormality resolution time of the concerned associated road is determined based on a preset abnormality feature and resolution time mapping relationship.

[0063] Specifically, different strategies are adopted to determine the abnormality removal time according to the different association levels of the concerned associated roads. For concerned associated roads whose association levels are not higher than the preset level threshold, the first abnormality removal time is dynamically calculated through real-time traffic data. The use of real-time traffic data can accurately reflect the current traffic conditions of the concerned associated roads, including the cause and degree of traffic jams and the expected relief time, which helps to more accurately predict the time required for the target vehicle to pass the concerned associated road.

[0064] As for the concerned associated roads whose association level is higher than the preset level threshold, it takes a certain amount of time for the target vehicle to reach the target concerned road. If real-time traffic data is used to determine the corresponding abnormality release time, the data validity is low. Therefore, the traffic mode, time and frequency of congestion in historical data can be used to predict the congestion that may occur in the future. The mapping relationship between the preset abnormal characteristics and the release time is determined based on the historical data. The first abnormality release time is real-time data, and the second abnormality release time is predicted data. Among them, the preset level threshold is not specifically limited in the embodiment of the present application, and can be the third level or the fourth level. The specific preset level threshold can be set by relevant technical personnel.

[0065] Step S4: Generate a countdown time bar based on the first exception resolution time or the second exception resolution time, and superimpose the countdown time bar on the target planning prompt route.

[0066] Specifically, when the association level of the concerned associated road is not higher than the preset level threshold, the duration corresponding to the countdown time bar is the first abnormality removal duration; when the association level of the concerned associated road is higher than the preset level threshold, the duration corresponding to the countdown time bar is the second abnormality removal duration. By converting the determined abnormality removal duration into a countdown time bar and displaying the countdown time bar, it is convenient to provide intuitive data prompts to the driver, so as to inform the driver in advance of the potential congestion on the route ahead.

[0067] Furthermore, in order to improve the efficiency of the driver in changing the planned route during driving, the method provided in the embodiment of the present application also includes: The associated road groups whose associated scores are not less than the preset scores are determined as candidate associated road groups; the planned prompt routes corresponding to each candidate associated road group are determined, and the real-time evaluation parameters corresponding to each planned prompt route are identified in real time, and the real-time evaluation parameters include the preset number of abnormal features and the total time for abnormality resolution; the real-time evaluation value of each candidate associated road group is determined based on the real-time evaluation parameters corresponding to each candidate associated road group, and the real-time display position of each planned prompt route is determined based on each real-time evaluation value; based on the real-time display position of each planned prompt route, a candidate route form is generated.

[0068] Specifically, after determining the associated road group with the highest associated score as the target associated road group, the data corresponding to other non-target associated road groups are not discarded, but the associated road group with a score not lower than the preset score is screened out from other non-target associated road groups according to the preset score, and the associated road group with a score not lower than the preset score is determined as the candidate associated road group, so that the driver can change the driving route at any time according to his own needs. Since the candidate associated road group has a high similarity with the target associated road group, when the driver needs to adjust or change the route, the route corresponding to the candidate associated road group is fed back to the driver, so as to improve the driver's experience and satisfaction. In addition, determining the candidate associated road group through other non-target associated road groups can also reduce data calculation pressure.

[0069] The method for determining the planning prompt route corresponding to each candidate associated road group can refer to the method for determining the target planning prompt route in the above embodiment, which will not be described in detail here. As the target vehicle travels, the real-time traffic data of each associated road may change. At this time, each planning prompt route can be evaluated in real time according to the number of preset abnormal features and the total time for abnormality removal in each planning prompt route, and different planning prompt routes are sorted according to the real-time evaluation value of each planning prompt route, that is, the real-time display position of each planning prompt route is determined, and feedback is given to the driver based on the real-time display position. The higher the real-time evaluation value, the higher the corresponding real-time display position. For example, the real-time evaluation value of planning prompt route a is 10 points, the real-time evaluation value of planning prompt route b is 8 points, and the real-time evaluation value of planning prompt route c is 6 points. Then, the display position of planning prompt route a is higher than that of planning prompt route b and higher than that of planning prompt route c. The candidate route form contains all the planning prompt routes corresponding to the candidate associated road groups, and the display position of each planning prompt route in the candidate route form is determined based on the real-time evaluation value of each planning prompt route. Based on real-time data, it is convenient to dynamically adjust the display position of the alternative routes corresponding to each candidate associated road group to ensure that the driver first sees the most suitable or optimal route at the moment.

[0070] Furthermore, in order to improve the efficiency of the driver in changing the driving route, the method provided in the embodiment of the present application also includes: The location of the target vehicle is determined based on the target vehicle's driving road surface data; the target arrival entrance is determined based on the location and the associated roads; a guidance route is formed based on the location and the target arrival entrance, and it is identified whether there is a preset mark in the guidance route.

[0071] Specifically, when determining the position of the target vehicle based on the target vehicle's driving road surface data, the road surface features can be identified from the target vehicle's formal road surface data, and the target vehicle's position can be determined based on the road surface features and the updated mine road network model. When determining the position of the target vehicle, the map matching algorithm and map service API can also be used for determination, wherein the map matching algorithm includes but is not limited to hidden Markov models and particle filters.

[0072] There may be multiple arrival entrances for the associated road, but when determining that the target vehicle arrives at the associated road from the current position, a better arrival intersection can be determined from the multiple arrival entrances. The target arrival entrance can be selected from the multiple arrival entrances based on factors such as the vehicle's current position, driving direction, traffic flow, and distance to the destination. The target arrival entrance may be a specific ramp entrance or intersection.

[0073] After determining the target arrival entrance, a guidance route can be generated based on the current position and the target arrival entrance. When generating the guidance route, a suitable path planning algorithm can be selected first, and then the path planning can be performed based on the selected algorithm, the current position and the target arrival entrance. The path planning algorithm can be the Dijkstra algorithm or an algorithm based on heuristic search. The specific path planning algorithm is not specifically limited in the embodiments of the present application, as long as the shortest or optimal path from the current position of the target vehicle to the target arrival entrance can be found in the updated mine road network model.

[0074] Preset signs can be multi-ramp intersections, uninstructed sections, non-standard road signs, etc. The specific preset signs can be determined by relevant staff based on historical operating experience and uploaded to electronic devices. When drivers encounter preset signs during driving, they are more likely to be confused or lost. For example, when some sections lack necessary traffic signs, markings or signs, drivers may not be able to accurately determine the driving direction or route, which may cause them to get lost.

[0075] When there is a preset sign, the display image and guide slogan of the preset sign are determined according to historical traffic data, the display image and guide slogan of the preset sign are superimposed on the guidance route to form a superimposed guidance route, and the superimposed guidance route is fed back to the target vehicle.

[0076] Specifically, in order to enhance the driver's navigation experience and reduce the possibility of getting lost, when it is recognized that the guidance route contains a preset sign, a suitable display screen and guide slogan can be designed for the preset sign based on historical traffic data and the characteristics of the preset sign. For example, when the preset sign is a multi-ramp intersection, a clear road layout map and turn arrows can be determined as the display screen of the preset sign based on the multi-ramp intersection and the guidance route, and the guide slogan can be "Multiple ramp intersections ahead, please pay attention". Different preset signs correspond to different guide slogans, which can be entered into the electronic device in advance by relevant staff and called from the electronic device based on the preset sign when needed. The specific content of the guide slogan corresponding to the preset sign is not specifically limited in the embodiment of the present application.

[0077] The display screen of the preset sign and the guide slogan are superimposed on the original guide route at the position where the preset sign appears. This can be achieved through the interface design of the navigation software or the vehicle system. During the display process, highlighting, magnification or animation effects can be used to highlight the importance of the preset sign. At the same time, the font size of the guide slogan needs to be adjusted through the size of the display interface to ensure that the guide slogan is coordinated with the display screen and does not interfere with the driver's sight and attention. The superimposed guidance route is fed back to the target vehicle in real time, which can be achieved through channels such as vehicle navigation equipment, smartphone applications or vehicle display screens. By superimposing the display screen and guide slogans, the driver is provided with more dimensional road condition information, making the navigation information richer and more comprehensive, which is also convenient for improving the driver's efficiency in the process of changing the driving route.

[0078] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0079] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0080] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The fact that only one line is used in the diagram does not mean that there is only one bus or only one type of bus.

[0081] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0082] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0083] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0084] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0085] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method in any of the above embodiments is implemented.

[0086] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0087] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A path planning method based on road surface data fusion, characterized in that: include: Acquire real-time road surface data of each road, and determine the road condition type of each road from the real-time road surface data of each road, wherein the road condition type includes normal road condition and abnormal road condition; updating the preset mine road network model in real time according to the road condition type corresponding to each road to obtain an updated mine road network model, wherein the preset mine road network model includes the position association relationship between each road and each road; Acquire the driving road data of the target vehicle, and determine the target road where the target vehicle is located and the road condition type of the target road based on the driving road data, wherein the target vehicle is a vehicle that needs to be routed; When the road condition type of the target road is an abnormal road condition, obtaining the destination information of the target vehicle, and determining the associated roads of the target road based on the destination information, the target road and the updated mine road network model; The road condition type of the associated road is identified, and when the road condition type of the associated road is a normal road condition, a path is planned for the target vehicle based on the associated road.

2. A path planning method based on road surface data fusion according to claim 1, characterized in that: When multiple associated roads are included, it also includes: According to the association relationship between each associated road and the target road, at least one first-level associated road is determined from the plurality of associated roads, wherein the first-level associated road is a road directly connected to the target road; According to the association relationship between each first-level associated road and other associated roads, the other associated roads are grouped to obtain an associated road group corresponding to each first-level associated road, each associated road group contains associated roads of different association levels, wherein the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are other roads among the multiple associated roads except the first-level associated roads; Determine the number of continuous normal road sections corresponding to each associated road group according to the road condition type of each associated road in each associated road group; Determine the driving distance corresponding to each associated road group according to the path distance of each associated road in each associated road group; Based on the preset calculation weight, the number of continuous normal road sections corresponding to each associated road group and the driving distance, the associated score corresponding to each associated road group is determined, and the path planning for the target vehicle is performed based on the associated road group with the highest associated score.

3. The path planning method based on road surface data fusion according to claim 2 is characterized in that: Also includes: Determine the associated road group with the highest associated score as the target associated road group, and determine the integration order of each associated road based on the association relationship between the associated roads in the target associated road group; Determine the display length corresponding to each path distance according to the mapping relationship between the path distance and the length of each associated road in the target associated road, wherein the length mapping relationship is the corresponding relationship between the path distance and the display length; Based on the integration order and display length of each associated road, each associated road in the target associated road group is connected to obtain a corresponding target planned route; The real-time traffic data of each associated road is identified, and the travel time and abnormal traffic characteristics corresponding to each associated road are determined according to each real-time traffic data, and the travel time and abnormal traffic characteristics of each associated road are superimposed on the target planning route to form a target planning prompt route.

4. The path planning method based on road surface data fusion according to claim 3 is characterized in that: Also includes: When the abnormal traffic feature is a preset abnormal feature, determining the associated road containing the preset abnormal feature as a concerned associated road; When the association level of the concerned associated road is not higher than a preset level threshold, determining the first abnormality removal time of the concerned associated road according to the real-time traffic data corresponding to the concerned associated road; When the association level of the concerned associated road is higher than a preset level threshold, determining a second abnormality resolution time of the concerned associated road based on a mapping relationship between the preset abnormality feature and resolution time; A countdown time bar is generated based on the first exception resolution time or the second exception resolution time, and the countdown time bar is superimposed on the target planning prompt route.

5. The path planning method based on road surface data fusion according to claim 4 is characterized in that: Also includes: Determine the associated road group whose associated score is not less than the preset score as the candidate associated road group; Determine the planned prompt route corresponding to each candidate associated road group, and identify the real-time evaluation parameters corresponding to each planned prompt route in real time, where the real-time evaluation parameters include the number of preset abnormal features and the total time for abnormality resolution; Determine a real-time evaluation value of each candidate associated road group based on the real-time evaluation parameter corresponding to each candidate associated road group, and determine a real-time display position of each planned prompt route based on each real-time evaluation value; Generate an alternative route form based on the real-time display position of each planned route.

6. The path planning method based on road surface data fusion according to claim 1, characterized in that: After determining the associated roads of the target road, the method further includes: Determining the location of the target vehicle according to the road surface data of the target vehicle; Determining a target arrival entrance based on the location and the associated road; forming a guidance route based on the location and the target arrival entrance, and identifying whether there is a preset mark in the guidance route; When there is a preset sign, the display picture and guide slogan of the preset sign are determined according to historical traffic data, the display picture and guide slogan of the preset sign are superimposed on the guide route to form a superimposed guide route, and the superimposed guide route is fed back to the target vehicle.

7. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a path planning method based on road surface data fusion as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and executes a path planning method based on road surface data fusion as described in any one of claims 1 to 6.

9. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the steps of a path planning method based on road surface data fusion according to any one of claims 1 to 6.

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