Path Planning Method, Device, Medium and Product Based on Road Surface Data Fusion

Abstract

The present application relates to the technical field of path planning, and in particular, to a path planning method, device, medium and product based on road surface data fusion. The method includes obtaining 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 the driving road surface data of a target vehicle, and determining the target road where the target vehicle is located and the 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 the destination information of the target vehicle, and determining the associated road of the target road based on the destination information, the target road and the updated mine road network model; 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. The present application facilitates improving the accuracy in the path planning process.

Description

Technical Field

[0001] The present application relates to the technical field of path planning, 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 thereof, has become an important means to improve traffic efficiency, reduce traffic congestion, and optimize the driving experience. The core of path planning lies in calculating an optimal driving path through a reasonable algorithm given the starting point and the ending point, so as to save the driving time and reduce the driving cost 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. Therefore, they may seem inadequate when facing a complex and changeable traffic environment, which may affect the accuracy of the path planning result. Summary of the Invention

[0004] In order to improve the accuracy in 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, adopting the following technical solution:

[0006] A path planning method based on road surface data fusion includes:

[0007] Obtain the 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, where the road condition type includes normal road conditions and abnormal road conditions;

[0008] Update a 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, where the preset mine road network model includes the positions and the associated relationships between each road.

[0009] Obtain the driving road surface data of a 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 surface data, where the target vehicle is a vehicle that needs to perform path planning;

[0010] When the road condition type of the target road is an abnormal road condition, obtain the destination information of the target vehicle, and determine the associated road of the target road based on the destination information, the target road, and the updated mine road network model;

[0011] Identify the road condition type of the associated road. When the road condition type of the associated road is normal, perform path planning for the target vehicle based on the associated road.

[0012] By adopting the above technical solution, it is convenient to master the latest status of each road by determining the road conditions in real time, thereby facilitating providing effective data support for subsequent path planning. In addition, by superimposing the road condition type of each road onto the preset mine road network model, the update of the preset mine road network model is realized, which is convenient for intuitively viewing the actual traffic conditions of the current mine through the updated preset mine road network model. Path planning is carried out based on the real-time updated preset mine road network model and the current road condition type of the target road, which is convenient for effectively avoiding problems such as traffic congestion and slow driving that may be brought by abnormal road conditions, thereby facilitating improving the accuracy of the path planning result and further facilitating improving the efficiency of the traffic system.

[0013] In a possible implementation manner, when there are multiple associated roads, the method further includes:

[0014] According to the association relationship between each associated road and the target road, determine at least one first-level associated road from the multiple associated roads, where the first-level associated road is a road directly connected to the target road;

[0015] According to the association relationship between each first-level associated road and other associated roads, group the other associated roads to obtain an associated road group corresponding to each first-level associated road. Each associated road group contains associated roads with different association levels. Among them, the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are the other roads except the first-level associated roads among the multiple associated roads;

[0016] According to the road condition type of each associated road in each associated road group, determine the number of consecutive normal road sections corresponding to each associated road group;

[0017] According to the path distance of each associated road in each associated road group, determine the driving distance corresponding to each associated road group;

[0018] Based on the pre-designed calculation weight, the number of consecutive normal road sections corresponding to each associated road group, and the driving distance, determine the association score corresponding to each associated road group, and perform path planning for the target vehicle based on the associated road group with the highest association score.

[0019] By adopting the above technical solution, the connection relationship between the associated road and the target road is used to classify different associated roads, which is convenient for giving priority to the associated roads closely related to the target road, and is also convenient for improving the redundancy and indirectness of the path planning result. Grouping the associated roads is convenient for intuitively comparing the advantages between different associated roads, and is also convenient for improving the flexibility and diversity in the process of planning the path. In addition, 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 practicability of different associated road groups, and is also convenient for avoiding potential traffic bottlenecks and adverse factors, which helps to select a route with better road conditions, thereby facilitating the improvement of driving efficiency and safety.

[0020] In a possible implementation manner, the method further includes:

[0021] Determine the target associated road group with the highest associated score, and based on the association relationship between the various associated roads in the target associated road group, determine the integration order of each associated road;

[0022] According to the path distance and length mapping relationship of each associated road in the target associated road, determine the display length corresponding to each path distance, where the length mapping relationship is the corresponding relationship between the path distance and the display length;

[0023] Based on the integration order and display length of each associated road, connect the various associated roads in the target associated road group to obtain the corresponding target planned route;

[0024] Identify the real-time traffic data of each associated road, and determine the passing duration and passing anomaly characteristics corresponding to each associated road according to each real-time traffic data, and superimpose the passing duration and passing anomaly characteristics of each associated road onto the target planned route to form a target planned prompt route.

[0025] By adopting the above technical solution, by integrating each associated road to obtain the target planned route corresponding to the target associated road group, it is convenient to intuitively view the actual passing situation of the target planned route. By analyzing the traffic data of each associated road in real time and timely superimposing the passing anomaly characteristics onto the target planned route, it is convenient to give real-time reminders to the driver, so as to reduce the probability of accidents during driving, thereby facilitating the improvement of safety during driving.

[0026] In a possible implementation manner, the method further includes:

[0027] When the passing anomaly characteristic is a preset anomaly characteristic, determine the associated road containing the preset anomaly characteristic as the concerned associated road;

[0028] 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;

[0029] 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;

[0030] 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.

[0031] 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.

[0032] In one possible implementation, the method further includes:

[0033] Determine the associated road group whose associated score is not less than the preset score as the candidate associated road group;

[0034] 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;

[0035] 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;

[0036] Generate an alternative route form based on the real-time display position of each planned route.

[0037] By adopting the above technical solution, the associated road groups can be secondarily screened based on the association scores and preset scores to determine the candidate associated road groups, so that relevant drivers can randomly change routes during driving. Since the candidate associated road groups have a high similarity with the target associated road groups, it is more suitable for drivers to change routes midway during driving, thus facilitating the improvement of the efficiency when changing the planned route. Then, by evaluating each candidate associated road group in real time, the actual conditions of each section in each candidate associated road group can be understood in real time. Finally, based on the real-time data, it is convenient to dynamically adjust the display positions of the alternative routes corresponding to each candidate associated road group to ensure that the driver first sees the currently most suitable or optimal route.

[0038] In a possible implementation manner, after determining the associated roads of the target road, the method further includes:

[0039] Determine the location of the target vehicle according to the driving road surface data of the target vehicle;

[0040] Based on the location and the associated roads, determine the target arrival entrance;

[0041] Form a guiding route based on the location and the target arrival entrance, and identify whether there is a preset identifier in the guiding route;

[0042] When there is a preset identifier, determine the display screen and guiding slogan of the preset identifier according to historical traffic data, superimpose the display screen and guiding slogan of the preset identifier onto the guiding route to form a superimposed guiding route, and feedback the superimposed guiding route to the target vehicle.

[0043] By adopting the above technical solution, through the location of the vehicle at the current moment and the associated roads, it is convenient to determine the suitable arrival entrance of the target vehicle. This personalized recommendation helps to reduce the driver's confusion and unnecessary detours. In addition, by superimposing the display screen and guiding slogan, more-dimensional road condition information is provided for the driver, making the navigation information richer and more comprehensive, thus also facilitating the improvement of the efficiency of the driver during the process of changing the driving route.

[0044] In a second aspect, the present application provides an electronic device, adopting the following technical solution:

[0045] An electronic device, which includes:

[0046] At least one processor;

[0047] A memory;

[0048] 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.

[0049] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0050] 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.

[0051] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution:

[0052] 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.

[0053] In summary, the present application includes at least one of the following beneficial technical effects:

[0054] 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.

[0055] 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

[0056] 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;

[0057] Figure 2 It is a schematic flowchart of a countdown time bar superposition method in an embodiment of the present application;

[0058] Figure 3 It is a schematic structural diagram of an electronic device in an embodiment of the present application. Detailed implementation manners

[0059] The following will Figure 1 and Figure 3 make a further detailed description of the present application with reference to the appended

[0060] After reading this specification, those skilled in the art can make modifications to this embodiment without creative contributions according to needs, but as long as it is within the scope of the claims of the present application, it is protected by the patent law.

[0061] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts belong to the scope of protection of the present application.

[0062] It should be noted that in the optional embodiments of the present application, for relevant data such as object information, when the embodiments in the present application are applied to specific products or technologies, object permission or consent is required, and the collection, use and processing of relevant data need to comply with the relevant laws, regulations and standards of relevant countries and regions. That is to say, if the embodiments in the present application involve data related to objects, it needs to be obtained under the authorization and consent of the objects, the authorization and consent of relevant departments, and compliance with the relevant laws, regulations and standards of relevant countries and regions. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiments also need to be implemented under the authorization and consent of the objects.

[0063] Specifically, the embodiments of the present application provide a path planning method based on road surface data fusion, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, the server can be an independent physical server, a server cluster or a 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 notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, and the embodiments of the present application do not make limitations here.

[0064] Reference Figure 1 , Figure 1 is a schematic flowchart of a path planning method based on road surface data fusion in an embodiment of the present application. The method includes steps S110 - S150, where:

[0065] Step S110: Obtain the 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. The road condition type includes normal road conditions and abnormal road conditions.

[0066] Specifically, the road surface data corresponding to different roads is different. The road surface data corresponding to each road can be collected by a road surface image acquisition device arranged on the corresponding road and then uploaded to an electronic device. Among them, the road surface image acquisition device can be devices such as a high-definition camera, a road camera, a vehicle-mounted sensor, a lidar, etc. The specific device is not specifically limited in the embodiment of the present 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. Among them, 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 included in each real-time road surface data, and then based on the corresponding relationship between the road surface features and the road condition type, the road condition type corresponding to each road can be determined.

[0067] Step S120: Update 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. The preset mine road network model includes the positions and associated relationships between each road.

[0068] Specifically, the preset mine road network model can be determined according to the mine map and the road planning scheme. The preset mine road network model includes the main production trunk lines, production branch lines, connecting lines, auxiliary lines, etc. of the current mine, as well as the path distances of each road. Among them, the main production trunk line is the common road for each mining bench in the mining area to lead to the ore unloading point or the waste rock yard, and it is the main artery in the mine road network, undertaking 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 bench or the waste rock yard with the production trunk line, or the road directly from one mining bench to the ore unloading point or the waste rock yard. As a supplement to the production trunk line, it transports ore or waste rock from the specific mining point to the production trunk line or the ore unloading point; the connecting line is other roads where the dump trucks used in the open-pit mine production often travel, playing the role of communication and connection in the mine road network to ensure the smooth connection between different mining areas, processing areas, and storage areas; the auxiliary line is the road for various types of vehicles to travel to the affiliated factories and various auxiliary facilities within the mining area, mainly serving the auxiliary facilities and affiliated factories of the mine to ensure the effective connection between these areas and the main production area. The preset mine road network model also includes the topography and geomorphology of the mine, the distribution of water systems, and the intersection design, etc. Among them, the intersection design is the control form of traffic lights set at some important intersections or busy transportation channels. The corresponding intersection signal control forms for different intersections may be different. For example, only a straight-ahead traffic light is set at intersection a, while a straight-ahead and left-turn traffic light is set at intersection b.

[0069] When updating the preset mine road network model in real time according to the road condition types corresponding to each road, the corresponding simulated road can be located from the preset mine road network model according to each road identifier first, and then the corresponding road condition type can be marked at the corresponding simulated road. The marks corresponding to different road condition types are different. The specific marking form is not specifically limited in the embodiments 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 and road c are indirectly connected. An identifier representing the corresponding road condition type is superimposed at each simulated road in the updated mine road network model. By viewing the updated mine network model, it is convenient to intuitively view the traffic status of the entire mine, thereby facilitating providing effective data support for subsequent road planning.

[0070] Step S130: Obtain the driving road surface 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 surface data, where the target vehicle is the vehicle for which path planning is required.

[0071] Specifically, the target vehicle is the vehicle that needs to perform path planning. The driving road surface data of the target vehicle can be recognized by an image acquisition device arranged at the target vehicle and uploaded to the electronic device. Feature recognition of the driving road surface data can determine the target road where the target vehicle is located. The corresponding road features of different roads may be different. The road features can be road names, road numbers, surrounding buildings, etc. The specific road features are not specifically limited in the embodiments of the present application, as long as each road can be recognized and distinguished. When determining the road condition type of the target road, the simulated road corresponding to the target road can be recognized from the updated mine road network model, and then determined according to the corresponding road condition type mark at the simulated road.

[0072] Step S140: When the road condition type of the target road is an abnormal road condition, obtain the destination information of the target vehicle, and based on the destination information, the target road, and the updated mine road network model, determine the associated road of the target road.

[0073] Specifically, when the road condition type of the target road is a normal road condition, it means that there are no congestion, maintenance, accidents, etc. on the road where the target vehicle is driving, and it can continue to drive along the current road; when the road condition type of the target road is an abnormal road condition, it means that there may be congestion, maintenance, accidents, etc. on the road where the target vehicle is driving. If it continues to drive along the current road, it may extend the arrival time at the destination. Therefore, it is necessary to determine the associated road according to the updated mine road network model, the destination information, and the target road. By choosing a smoother road, the driver can reach the destination more easily, enjoy a more pleasant driving process, and it is also convenient to help the driver avoid these potential dangers or uncertain factors and ensure driving safety.

[0074] Step S150: Identify the road condition type of the associated road. When the road condition type of the associated road is a normal road condition, perform path planning for the target vehicle based on the associated road.

[0075] Specifically, in order to ensure the driving safety of the driver on the new route, it is also necessary to identify the road condition type of the associated road after determining the associated road of the target road. Only when the road condition type of the associated road is a normal road condition, will a new path planning be performed based on the associated road. Among them, the number of associated roads may be one or more. When the number of associated roads is more than one and the road condition type of each associated road is a normal road condition, one associated road can be randomly determined from the multiple associated roads and path planning can be performed based on this associated road.

[0076] For the embodiments of the present application, by determining the road conditions in real time, it is convenient to master the latest status of each road, so as to provide effective data support for subsequent route planning. In addition, by superimposing the road condition types of each road onto the preset mine road network model, the update of the preset mine road network model is realized, which is convenient for intuitively viewing the actual traffic conditions of the current mine through the updated preset mine road network model. Based on the real-time updated preset mine road network model and the current road condition type of the target road, route planning is carried out, which is convenient for effectively avoiding problems such as traffic congestion and slow driving that may be brought by abnormal road conditions, thus facilitating the improvement of the accuracy of the route planning result, and further facilitating the improvement of the efficiency of the traffic system.

[0077] Further, in order to facilitate avoiding potential traffic bottlenecks and adverse factors, when there are multiple associated roads, the method provided by the embodiments of the present application may further include:

[0078] According to the association relationship between each associated road and the target road, at least one first-level associated road is determined from the multiple associated roads, and the first-level associated road is a road directly connected to the target road.

[0079] Specifically, the associated roads of the target road are roads directly or indirectly connected to the target road. In order to facilitate differentiation, different associated roads can be classified 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 quantity is not specifically limited in the embodiments 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. Specifically, it can be starting from the target road and reaching different associated roads, and after reaching the associated road, the number of roads passed through is used as the route weight and marked at the corresponding arrival position. Finally, based on the weight marking, the association level of each associated road is determined. The method for determining the association level of each associated road can also use the depth-first traversal method, and the specific method is not specifically limited in the embodiments of the present application.

[0080] 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 with different association levels, where the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are the other roads among the multiple associated roads except the first-level associated roads.

[0081] Specifically, for any first-level associated road, other associated roads of the target road based on the first-level associated road can be determined. The other associated roads can be the second-level associated road, third-level associated road, fourth-level associated road, etc. of the target road. For example, if the target road is Road X, associated road a is directly connected to 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 target road X, associated road b is the second-level associated road of target road X, and associated road c is the third-level associated road of 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, there may be the same associated roads in the associated road groups corresponding to different first-level associated roads.

[0082] Determine the number of consecutive normal road sections corresponding to each associated road group according to the road condition type of each associated road in each associated road group.

[0083] Specifically, for any associated road group, the road condition types corresponding to different associated roads within the associated road group may be different, and it can be determined based on the updated mine road network model. The number of consecutive normal road sections is the number of times that the road condition type of the associated road in the associated road group is normal and consecutive. For example, the associated road group includes associated road a, associated road b, and associated road c, where the road condition types corresponding to associated road a and associated road b are normal, and associated road a and associated road b are directly connected. Therefore, the number of consecutive normal road sections corresponding to this associated road group is 2. According to the above method, the number of consecutive normal road sections corresponding to each associated road group can be determined.

[0084] Determine the driving distance corresponding to each associated road group according to the path distance of each associated road in each associated road group.

[0085] Specifically, by summing up the path distances corresponding to each associated road in each associated road group, the driving distance corresponding to each associated road group can be obtained. Among them, the path distance of each associated road can be obtained from the updated mine road network model, or it can also be obtained from a third-party website. The specific acquisition method is not specifically limited in the embodiments of the present application.

[0086] Based on the pre-designed calculation weight, the number of consecutive normal road sections and the driving distance corresponding to each associated road group, determine the associated score corresponding to each associated road group, and perform path planning for the target vehicle based on the associated road group with the highest associated score.

[0087] Specifically, the pre-designed calculation weights can be determined by relevant staff according to 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, first determine the first score corresponding to the number of consecutive normal road sections according to the first numerical conversion relationship, and then determine the second score corresponding to the driving distance according to the second numerical conversion relationship. The first numerical conversion relationship is the corresponding relationship between the number of consecutive normal road 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 content of the two corresponding relationships is not specifically limited in the embodiments of the present application. After determining the first score and the second score, calculate the associated score of the associated road group based on the pre-designed calculation weights, the first score, and the second score. Determine the associated scores corresponding to all associated road groups in the above manner, and determine the associated road group with the highest associated score from them. Finally, perform route planning for the target vehicle based on the associated road group with the highest associated score.

[0088] By quantifying and analyzing the number of consecutive normal road sections and the driving distance in each associated road group, it is convenient to comprehensively evaluate the practicability of different associated road groups, which helps to select a route with better road conditions, thereby facilitating the improvement of driving efficiency and safety.

[0089] Furthermore, in order to improve the safety during driving, the method provided in the embodiments of the present application further includes:

[0090] 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.

[0091] Specifically, after determining the route 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 direct or indirect connection association relationship between each associated road, each associated road is sequentially connected to form a continuous road, that is, the planned route.

[0092] According to the path distance and length mapping relationship of each associated road in the target associated road, determine the display length corresponding to each path distance. The length mapping relationship is the corresponding relationship between the path distance and the display length.

[0093] Specifically, in order to improve the intuitiveness during the display 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 that different path distances correspond to different display lengths, and the specific content can be determined by relevant staff according to historical operation experience.

[0094] Based on the integration order and display length of each associated road, connect each associated road in the target associated road group to obtain the corresponding target planned route.

[0095] Identify the real-time traffic data of each associated road, and determine the passing duration and passing anomaly characteristics corresponding to each associated road according to each real-time traffic data. Superimpose the passing duration and passing anomaly characteristics of each associated road into the target planned route to form a target planned prompt route.

[0096] Specifically, the target planned route contains each associated road in the target associated road group, and each associated road is displayed with the corresponding display length. The real-time traffic data can be collected by the image acquisition devices set at each road and then uploaded to the electronic device. The real-time traffic data of each associated road can reflect the passing conditions of each associated road. The real-time traffic data can also be obtained according to the in-vehicle sensors and in-vehicle image acquisition devices of the detected vehicles. The specific acquisition method is not specifically limited in the embodiments of the present application.

[0097] The passing duration 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 section may be in normal traffic conditions at the current moment and may be in abnormal traffic conditions at the next moment. Therefore, although the target planned route is determined based on the number of consecutive normal sections, during the driving process according to the target planned route, there may still be passing anomaly characteristics in the target planned route. The passing anomaly characteristics can be road maintenance, vehicle collision, etc. The specific characteristics are not specifically limited in the embodiments of the present application. Superimpose the passing duration and passing anomaly characteristics corresponding to each associated road at the corresponding positions of the target planned route. Since the traffic data changes in real time, the superimposed content at each associated road in the target planned route also changes in real time. By analyzing the traffic data of each associated road in real time and timely superimposing the passing anomaly characteristics into the target planned route, it is convenient to give real-time reminders to the driver, so as to reduce the probability of accidents during the driving process.

[0098] Further, the method provided in the embodiments of the present application further includes steps S1 - S4, as Figure 2 shown, where:

[0099] Step S1: When the passing anomaly characteristic is a preset anomaly characteristic, determine the associated road containing the preset anomaly characteristic as the concerned associated road.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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 abnormal release 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 abnormal release duration. By converting the determined abnormal release duration into a countdown time bar and displaying the countdown time bar, it is convenient to give intuitive data prompts to the driver, so as to inform the driver in advance of the potential congestion situation on the forward driving route.

[0107] Furthermore, in order to improve the efficiency of the driver in changing the planned route during driving, the method provided by the embodiment of the present application further includes:

[0108] Determine the candidate associated road group with an association score not lower than the preset score; determine the planned prompt route corresponding to each candidate associated road group, and real-time identify the real-time evaluation parameters corresponding to each planned prompt route, the real-time evaluation parameters include the preset abnormal feature quantity and the total abnormal release duration; determine the real-time evaluation value of each candidate associated road group based on the real-time evaluation parameters corresponding to each candidate associated road group, and determine the real-time display position of each planned prompt route based on each real-time evaluation value; generate a candidate route form based on the real-time display position of each planned prompt route.

[0109] Specifically, after determining the target associated road group with the highest association score, instead of discarding the data corresponding to other non-target associated road groups, filter out the associated road groups not lower than the preset score from other non-target associated road groups according to the preset score, and determine the associated road groups not lower than the preset score as the candidate associated road groups, so as to facilitate the driver to change the driving route at any time according to his own needs. Since the candidate associated road groups are highly similar to the target associated road group, when the driver needs to adjust or change the route, feedback the route corresponding to the candidate associated road group to the driver, which is convenient to improve the driver's experience and satisfaction. In addition, by determining the candidate associated road groups through other non-target associated road groups, the data operation pressure can also be reduced.

[0110] 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.

[0111] 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:

[0112] 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.

[0113] 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.

[0114] 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.

[0115] After determining the target arrival entrance, a guiding route can be generated based on the current location and the target arrival entrance. When generating the guiding route, a suitable path planning algorithm can be selected first, and then path planning can be performed according to the selected algorithm, the current location, and the target arrival entrance. Among them, the path planning algorithm can be Dijkstra's 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 it can find the shortest or optimal path from the current location of the target vehicle to the target arrival entrance in the updated mine road network model.

[0116] The preset identifiers can be multi-ramp intersections, unmarked sections, non-standard road signs, etc. The specific preset identifiers can be determined by relevant staff based on historical operation experience and then uploaded to the electronic device. When a driver encounters a preset identifier during driving, it is more likely to cause confusion or getting lost. For example, when some sections lack necessary traffic signs, markings or guiding signs, it may lead to the driver being unable to accurately judge the driving direction or route, and thus may cause the driver to get lost.

[0117] When there is a preset identifier, determine the display screen and guiding slogan of the preset identifier according to historical traffic data, superimpose the display screen and guiding slogan of the preset identifier onto the guiding route to form a superimposed guiding route, and feedback the superimposed guiding route to the target vehicle.

[0118] Specifically, in order to improve the driver's navigation experience and reduce the possibility of getting lost, when it is recognized that the guiding route contains a preset identifier, a suitable display screen and guiding slogan can be designed for the preset identifier according to historical traffic data and the characteristics of the preset identifier. For example, when the preset identifier is a multi-ramp intersection, a clear road layout diagram and turning arrows can be determined based on the multi-ramp intersection and the guiding route as the display screen of the preset identifier, and the guiding slogan can be "Multi-ramp intersection ahead, please pay attention". Different preset identifiers correspond to different guiding slogans, which can be pre-entered into the electronic device by relevant staff. When needed, they are called from the electronic device based on the preset identifier. The specific content of the guiding slogan corresponding to the preset identifier is not specifically limited in the embodiments of the present application.

[0119] Overlay the display screen with a preset identifier and the guiding slogan at the position where the preset identifier appears on the original guiding route. This can be achieved through the interface design of a navigation software or an in-vehicle system. During the display process, highlighting, magnification, or animation effects can be used to emphasize the importance of the preset identifier. At the same time, the font size of the guiding slogan needs to be adjusted through the size of the display interface to ensure that the guiding slogan is coordinated with the display screen and does not interfere with the driver's line of sight and attention. The overlaid guiding route is fed back to the target vehicle in real time, which can be achieved through channels such as in-vehicle navigation devices, smartphone applications, or in-vehicle display screens. By overlaying the display screen and the guiding slogan, more-dimensional road condition information is provided to the driver, making the navigation information richer and more comprehensive, thereby facilitating the improvement of the driver's efficiency during the process of changing the driving route.

[0120] In an embodiment of the present application, an electronic device is provided, such as Figure 3 shown. Figure 3 The electronic device 300 shown in the figure includes a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as connected through a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation to the embodiment of the present application.

[0121] The processor 301 may be a CPU (Central Processing Unit, central processing unit), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in combination with the disclosure of the present application. The processor 301 may also be a combination that realizes computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0122] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation,Figure 3 It is represented by only one line in the figure, but it does not mean that there is only one bus or one type of bus.

[0123] The memory 303 can 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. It can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, 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.

[0124] The memory 303 is used to store the application program code for implementing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0125] Among them, the electronic device includes but is 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), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0126] The embodiments of this application provide a computer-readable storage medium, on which a computer program is stored. When it runs on a computer, it enables the computer to execute the corresponding content in the foregoing method embodiments.

[0127] The embodiments of this application provide a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the method in any of the above embodiments.

[0128] It should be understood that although the steps in the flowchart of the accompanying drawings are shown sequentially according to the indication of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this document, there is no strict order restriction for 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. 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 alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0129] The above are only some embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A path planning method based on road surface data fusion, characterized in that, Including: Obtain the 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, where the road condition type includes normal road conditions and abnormal road conditions; Update the preset mine road network model in real time according to the road condition type corresponding to each road to obtain the updated mine road network model, and the preset mine road network model includes the position association relationship between each road; Obtain the driving road surface 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 surface data, where the target vehicle is a vehicle that needs to perform path planning; When the road condition type of the target road is abnormal, obtain the destination information of the target vehicle, and determine the associated road of the target road based on the destination information, the target road, and the updated mine road network model; Identify the road condition type of the associated road. When the road condition type of the associated road is normal, perform path planning for the target vehicle based on the associated road; Wherein, when there are multiple associated roads, it further includes: Determine at least one first-level associated road from multiple associated roads according to the association relationship between each associated road and the target road, and the first-level associated road is a road directly connected to the target road; Group the other associated roads according to the association relationship between each first-level associated road and the other associated roads to obtain an associated road group corresponding to each first-level associated road. Each associated road group includes associated roads with different association levels. Among them, the second-level associated road is a road directly connected to the first-level associated road, and the other associated roads are the other roads among the multiple associated roads except the first-level associated roads; Determine the number of consecutive 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 consecutive normal road sections and the driving distance corresponding to each associated road group, determine the association score corresponding to each associated road group, and perform path planning for the target vehicle based on the associated road group with the highest association score.

2. The path planning method based on road surface data fusion according to claim 1, characterized in that It further includes: Determine the target associated road group with the highest association score, 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 path distance and length mapping relationship of each associated road in the target associated road, where 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, connect the associated roads in the target associated road group to obtain the 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.

3. The path planning method based on road surface data fusion according to claim 2, 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 abnormality resolution time or the second abnormality resolution time, and the countdown time bar is superimposed on the target planning prompt route.

4. A path planning method based on road surface data fusion according to claim 3, 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.

5. A 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.

6. 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 1-5.

7. 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 1-5.

8. 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 5.

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