Driving time analysis method and device based on vehicle navigation, equipment and medium

Abstract

The embodiment of the invention provides a driving time analysis method and device based on vehicle navigation, equipment and a medium. The method comprises the following steps: in response to a navigation request sent by a vehicle, determining a planned driving path and predicted arrival time based on a preset navigation product; wherein the planned driving path represents a driving path, predicted by the preset navigation product, of the vehicle from the starting point position to the final point position; determining an actual driving path and actual arrival time of the vehicle; wherein the actual driving path represents a real driving path of the vehicle from the starting point position to the final point position; if it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition, the driving time of the vehicle is analyzed according to the predicted arrival time and the actual arrival time, and a time analysis result is obtained; wherein the time analysis result represents the accuracy of estimating the driving time by the preset navigation product. The method improves the analysis precision of the driving time, and facilitates the improvement of a preset navigation product.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and medium for analyzing driving time based on vehicle navigation. Background Art

[0002] When a vehicle is driving, it often needs a navigation product to plan a route, so as to guide the vehicle to drive along the planned route. When planning a route, the navigation product will provide multiple routes for users to choose from, and will also estimate the time it takes for the vehicle to arrive at the destination, so that users can choose the best route according to their needs, improve the user's driving experience, and increase travel efficiency.

[0003] However, the estimated travel time of navigation products may be inaccurate, which makes it impossible for users to make accurate travel route decisions. Therefore, it is necessary to analyze navigation products based on travel time to determine whether they can accurately estimate travel time, so as to facilitate iterative improvements to navigation products, thereby providing users with better travel routes and more accurate estimated travel time; at the same time, users can arrange their time reasonably, avoid the inconvenience caused by being late or early, reduce anxiety caused by uncertain factors, and improve the driver and passenger experience. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and medium for analyzing driving time based on vehicle navigation, so as to improve the analysis accuracy of driving time and improve navigation products.

[0005] In a first aspect, an embodiment of the present application provides a method for analyzing driving time based on vehicle navigation, comprising:

[0006] In response to a navigation request from the vehicle, determine a planned driving route and an estimated arrival time based on a preset navigation product;

[0007] Acquire the driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the real path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle to follow the actual driving path;

[0008] If it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition based on the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed based on the estimated arrival time and the actual arrival time to obtain a time analysis result; wherein the time analysis result represents the accuracy of the estimated driving time by the preset navigation product.

[0009] In a possible implementation, the driving information includes driving trajectory points, each driving trajectory point corresponds to a time point and position information, the time point represents the moment when the vehicle arrives at the location of the driving trajectory point, and the position information represents the latitude and longitude coordinates; determining the actual driving path and actual arrival time of the vehicle according to the driving information includes:

[0010] According to the location information and time point of each driving trajectory point, each driving trajectory point is screened to obtain the target trajectory point;

[0011] According to the time point corresponding to the target trajectory point, the actual driving path and actual arrival time of the vehicle are determined.

[0012] In a possible implementation, the driving trajectory points are screened according to the location information and time point of each driving trajectory point to obtain the target trajectory point, including:

[0013] Determine the time point of the trajectory point corresponding to the end point position as the end point moment;

[0014] Screening out the trajectory points corresponding to the time points after the end point to obtain candidate trajectory points;

[0015] The target trajectory point is determined from the candidate trajectory points according to the position information of the candidate trajectory points.

[0016] In a possible implementation, determining the target trajectory point from the candidate trajectory points according to the position information of the candidate trajectory points includes:

[0017] According to the position information of the candidate trajectory points, the candidate trajectory points outside the preset longitude and latitude range are screened out to obtain the target trajectory point.

[0018] In a possible implementation, determining the actual driving path and the actual arrival time of the vehicle according to the time point corresponding to the target trajectory point includes:

[0019] Connecting the target trajectory points according to the time points corresponding to the target trajectory points to obtain the actual driving path of the vehicle;

[0020] The actual arrival time is determined according to the time point of the trajectory point corresponding to the starting position and the time point of the trajectory point corresponding to the end position.

[0021] In a possible implementation, if it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition according to the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result, including:

[0022] Placing the planned driving path and the actual driving path in a preset grid area; wherein the preset grid area is composed of a preset number of cells;

[0023] Determine the cells occupied by the actual driving path in the preset grid area as a first cell area, and determine the cells occupied by the planned driving path in the preset grid area as a second cell area;

[0024] Determining the similarity between the planned driving path and the actual driving path according to the number of overlapping cells in the first cell area and the second cell area;

[0025] If the similarity is greater than a preset similarity threshold, the travel time of the vehicle is analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result.

[0026] In a possible implementation, the time analysis result includes a deviation rate, where the deviation rate represents the degree of deviation between the actual arrival time and the expected arrival time; the deviation rate is represented by:

[0027]

[0028] Among them, P represents the deviation rate, ETA represents the estimated arrival time, and ATA represents the actual arrival time.

[0029] In a possible implementation, it further includes:

[0030] For each of the preset navigation products, the deviation rates of different vehicles under the preset analysis dimensions are obtained, and the average value of the deviation rates under the preset analysis dimensions is determined; wherein the preset analysis dimensions include at least one of a time dimension, a region dimension, a distance dimension, and a speed dimension, the time dimension represents the time period in which the vehicle is traveling, the region dimension represents the geographical area in which the vehicle is traveling, the distance dimension represents the length of the actual driving path, and the speed dimension represents the average driving speed of the vehicle;

[0031] According to the average values ​​corresponding to the preset navigation products, the product analysis results of the preset navigation products under the preset analysis dimensions are determined; wherein the product analysis results represent the differences in navigation effects between different preset navigation products.

[0032] In a possible implementation, obtaining the deviation rates of different vehicles under a preset analysis dimension includes:

[0033] Determine the actual driving paths generated by different vehicles under the preset analysis dimension as the paths to be analyzed;

[0034] The deviation rate corresponding to the path to be analyzed is obtained, which is the deviation rate under the preset analysis dimension.

[0035] In a possible implementation, in response to a navigation request issued by a vehicle, determining a planned driving route and an estimated arrival time based on a preset navigation product includes:

[0036] In response to a navigation request issued by the vehicle, inputting the navigation request into the preset navigation product;

[0037] Obtain the planned driving route and estimated arrival time output by the preset navigation product.

[0038] In a second aspect, an embodiment of the present application provides a device for analyzing driving time based on vehicle navigation, comprising:

[0039] A planning driving unit, used to respond to a navigation request issued by the vehicle and determine a planned driving route and an estimated arrival time based on a preset navigation product;

[0040] an actual driving unit, used to obtain driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the real path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle to follow the actual driving path;

[0041] A result analysis unit is used to analyze the driving time of the vehicle according to the estimated arrival time and the actual arrival time to obtain a time analysis result if it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition according to the area occupied by the planned driving path and the area occupied by the actual driving path; wherein the time analysis result represents the accuracy of the estimated driving time by the preset navigation product.

[0042] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0043] The memory stores computer-executable instructions;

[0044] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the method described in the first aspect and / or various possible implementations of the first aspect.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0047] The embodiment of the present application provides a method, device, equipment and medium for analyzing driving time based on vehicle navigation. By responding to the navigation request of the vehicle, the starting position and the end position of the vehicle can be determined. By using a preset navigation product, the planned driving path and the estimated arrival time predicted by the preset navigation product can be obtained. When the vehicle has finished driving, the actual driving path and the actual arrival time of the vehicle can be obtained. Determine whether the planned driving path and the actual driving path are similar. If so, the estimated arrival time and the actual arrival time can be compared and analyzed to obtain the analysis result. In the embodiment of the present application, the driving path and driving time estimated by the preset navigation product, as well as the actual driving path and driving time of the vehicle are determined. When the two driving paths are similar, the driving time is analyzed to determine whether the driving time estimated by the preset navigation product is accurate, improve the analysis accuracy of the driving time, and help improve the preset navigation product, thereby improving the driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0049] Figure 1 A flowchart of a method for analyzing driving time based on vehicle navigation provided in an embodiment of the present application;

[0050] Figure 2 A flowchart of a method for analyzing driving time based on vehicle navigation provided in an embodiment of the present application;

[0051] Figure 3 A flowchart of a method for analyzing driving time based on vehicle navigation provided in an embodiment of the present application;

[0052] Figure 4 A schematic diagram of a grid area provided in an embodiment of the present application;

[0053] Figure 5 A schematic diagram of comparison between multiple preset navigation products provided in an embodiment of the present application;

[0054] Figure 6 A schematic diagram of the structure of a device for analyzing driving time based on vehicle navigation provided in an embodiment of the present application;

[0055] Figure 7 A schematic diagram of the structure of a device for analyzing driving time based on vehicle navigation provided in an embodiment of the present application;

[0056] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0057] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0058] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0059] With the development of autonomous driving technology, users can use various navigation products to assist vehicle driving. Navigation products can be products such as APP (Application) for vehicle navigation. The user specifies the starting point and end point of the navigation, and the navigation product outputs the driving route and driving time calculated by the navigation product. The vehicle drives along the driving route calculated by the navigation product and arrives at the destination after a certain driving time.

[0060] However, the calculation accuracy of navigation products may have errors, resulting in inaccurate estimated driving time, affecting the user's driving experience. For example, it may cause the user to be late. At present, most methods for analyzing the driving time of navigation products require the participation of testers, which wastes manpower and time, and the accuracy and efficiency of the analysis are low. Therefore, it is necessary to improve the analysis method of the driving time of navigation products to improve the vehicle driving experience.

[0061] The present application provides a method, device, equipment and medium for analyzing travel time based on vehicle navigation, aiming to solve the above technical problems in the prior art.

[0062] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0063] Figure 1 The present invention provides a flow chart of a method for analyzing driving time based on vehicle navigation, which can be performed by an analysis device for driving time based on vehicle navigation, and can be applied to a cloud platform. Figure 1 As shown, the method includes:

[0064] S101, in response to a navigation request issued by a vehicle, determining a planned driving route and an estimated arrival time based on a preset navigation product;

[0065] Among them, the navigation request includes the starting position and the end position, the planned driving path represents the driving path of the vehicle from the starting position to the end position predicted by the preset navigation product, the estimated arrival time represents the time required for the vehicle to follow the planned driving path predicted by the preset navigation product, and the preset navigation product represents the preset software product for vehicle navigation.

[0066] Exemplarily, a vehicle may issue a navigation request during driving, for example, a navigation request may be issued through the vehicle terminal. The navigation request may include a starting point and an end point, that is, a driving path from the starting point to the end point needs to be navigated. A navigation analysis platform may be preset, and the navigation analysis platform is a cloud platform that can be used to execute the driving time analysis method in the embodiment of the present application. The navigation analysis platform is a software platform deployed in an electronic device that can interact with a mobile terminal on the vehicle side or the user side. After receiving the navigation request, the navigation analysis platform can determine the planned driving path and estimated arrival time of the vehicle through a preset navigation product. The preset navigation product is an APP for vehicle navigation. There may be multiple preset navigation products, and each preset navigation product may correspond to its own planned driving path and estimated arrival time.

[0067] The planned driving paths corresponding to different preset navigation products may be different, and the estimated arrival times corresponding to different preset navigation products may also be different. The planned driving path refers to the driving path of the vehicle from the starting position to the end position predicted by the preset navigation product, and the estimated arrival time refers to the driving time required for the vehicle to follow the planned driving path predicted by the preset navigation product. The preset navigation product can be a navigation APP installed on the vehicle terminal, or it can be another third-party navigation APP. In this embodiment, the type of preset navigation product is not specifically limited.

[0068] In this embodiment, in response to a navigation request issued by a vehicle, a planned driving route and an estimated arrival time are determined based on a preset navigation product, including: in response to a navigation request issued by a vehicle, inputting the navigation request into a preset navigation product; and obtaining the planned driving route and estimated arrival time output by the preset navigation product.

[0069] Specifically, the navigation analysis platform can establish data connection with each preset navigation product, so as to obtain the planned driving path and estimated arrival time calculated by each preset navigation product. After receiving the navigation request, the navigation analysis platform can send the navigation request to each preset navigation product. After receiving the navigation request, the preset navigation product calculates the planned driving path and estimated arrival time according to the starting point and the end point, and sends the planned driving path and the estimated arrival time to the navigation analysis platform.

[0070] For example, the navigation APP installed on the vehicle can be instructed to calculate the planned driving route and estimated arrival time so that the vehicle can travel according to the planned driving route. The navigation analysis platform can also be connected to a third-party navigation APP to instruct the third-party navigation APP to calculate the planned driving route and estimated arrival time, thereby obtaining the planned driving route and estimated arrival time corresponding to each preset navigation product. In this embodiment, the estimated arrival time can be referred to as ETA (Estimated Time of Arrival).

[0071] The beneficial effect of such a setting is that different preset navigation products are controlled to calculate the planned driving route and the estimated arrival time, so that multiple preset navigation products can be analyzed to improve the analysis efficiency.

[0072] S102. Acquire driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the actual path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle along the actual driving path.

[0073] For example, a preset navigation product may be installed or connected to the vehicle terminal, and the vehicle may travel according to the planned driving route displayed on the vehicle terminal, or may not travel according to the planned driving route. For example, the driver may independently determine the driving route according to actual driving experience, thereby obtaining an actual driving route that is different from the planned driving route.

[0074] When the vehicle issues a navigation request, the vehicle starts from the starting position and travels to the end position. The driving information of the vehicle from the starting position to the end position is obtained, and the actual driving path and actual arrival time are obtained according to the driving information. The driving information can represent the driving conditions of the vehicle after the navigation request is issued, for example, it can include the driving time, position, speed, etc. The actual driving path refers to the actual path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the actual time taken by the vehicle to reach the end position according to the actual driving path. In this embodiment, the actual arrival time can be referred to as ATA (Actual Time of Arrival).

[0075] The vehicle can record its actual driving path and actual arrival time in real time on the vehicle computer, and can send the actual driving path and actual arrival time to the navigation analysis platform, so that the navigation analysis platform can obtain the actual driving path and actual arrival time.

[0076] S103. If it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition based on the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed based on the estimated arrival time and the actual arrival time to obtain a time analysis result; wherein the time analysis result represents the accuracy of the preset navigation product's estimation of the driving time.

[0077] Exemplarily, after obtaining the planned driving path and the actual driving path, the similarity between the planned driving path and the actual driving path can be determined to determine whether the similarity meets the preset conditions. For example, the area occupied by the planned driving path and the area occupied by the actual driving path can be determined, and the occupied area can be expressed as the actual geographical location range. The similarity can be determined based on the overlap of the areas occupied by the two. The more overlapping areas, the greater the similarity. If the areas occupied by the two are consistent, it is determined that the similarity meets the preset conditions. For another example, the preset condition can be that the planned driving path and the actual driving path are completely consistent after overlapping. If the planned driving path and the actual driving path can be completely overlapped, it is considered that the similarity between the planned driving path and the actual driving path meets the preset conditions; if they cannot be completely overlapped, it is considered that the similarity between the planned driving path and the actual driving path does not meet the preset conditions. For another example, the planned driving path and the actual driving path are overlapped, and the path length of the overlapping part is determined. The path length of the overlapping part can represent the similarity. The longer the length, the greater the similarity. A length threshold may be preset. If the path length of the overlapping portion is equal to or greater than the preset length threshold, it is considered that the similarity between the planned driving path and the actual driving path meets the preset conditions; if the path length of the overlapping portion is less than the preset length threshold, it is considered that the similarity between the planned driving path and the actual driving path does not meet the preset conditions. The proportion of the path length of the overlapping portion to the total path length may also be determined. The greater the proportion, the greater the similarity. A ratio threshold is preset. If the determined ratio is equal to or greater than the preset ratio threshold, it is considered that the similarity between the planned driving path and the actual driving path meets the preset conditions; if the path length of the overlapping portion is less than the preset ratio threshold, it is considered that the similarity between the planned driving path and the actual driving path does not meet the preset conditions.

[0078] If it is determined that the similarity between the planned driving route and the actual driving route does not meet the preset conditions, the subsequent driving time analysis will not be performed; if it is determined that the similarity between the planned driving route and the actual driving route meets the preset conditions, the vehicle driving time can be analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result. The time analysis result can represent the accuracy of the preset navigation product's estimation of the driving time. For example, the difference between the estimated arrival time and the actual arrival time can be calculated and the difference can be used as the time analysis result. The larger the difference, the less accurate the preset navigation product's estimation of the driving time.

[0079] In an embodiment of the present application, the starting position and the end position of the vehicle can be determined by responding to the navigation request of the vehicle. By using a preset navigation product, the planned driving path and the estimated arrival time estimated by the preset navigation product can be obtained. When the vehicle has finished driving, the actual driving path and the actual arrival time of the vehicle can be obtained. Determine whether the planned driving path and the actual driving path are similar. If so, the estimated arrival time and the actual arrival time can be compared and analyzed to obtain an analysis result. In an embodiment of the present application, the driving path and driving time estimated by the preset navigation product, as well as the actual driving path and driving time of the vehicle are determined. When the two driving paths are similar, the driving time is analyzed to determine whether the driving time estimated by the preset navigation product is accurate, thereby improving the analysis accuracy of the driving time, which is conducive to improving the preset navigation product, thereby enhancing the driving experience.

[0080] Figure 2 A flow chart of a method for analyzing driving time based on vehicle navigation provided in an embodiment of the present application is shown as follows: Figure 2 As shown, this embodiment, based on the above embodiment, describes in detail the analysis method of driving time based on vehicle navigation, and the method includes:

[0081] S201. In response to a navigation request issued by a vehicle, a planned driving route and an estimated arrival time are determined based on a preset navigation product; wherein the navigation request includes a starting point location and an end point location, the planned driving route represents the driving route of the vehicle from the starting point location to the end point location estimated by the preset navigation product, the estimated arrival time represents the time required by the preset navigation product for the vehicle to follow the planned driving route, and the preset navigation product represents a preset software product for vehicle navigation.

[0082] Exemplarily, this step may refer to the above-mentioned step S101 and will not be described in detail.

[0083] S202, obtaining driving information of the vehicle; the driving information includes driving trajectory points, each driving trajectory point corresponds to a time point and position information, the time point represents the moment when the vehicle arrives at the location of the driving trajectory point, and the position information represents the latitude and longitude coordinates.

[0084] For example, the vehicle continues to drive after issuing a navigation request, and all driving trajectory points of the vehicle after issuing the navigation request can be obtained in real time or at a fixed time. Each driving trajectory point can correspond to a time point, and the time point indicates the moment when the vehicle is located at the driving trajectory point. For example, a driving trajectory point can be obtained every two seconds, that is, the time interval between the time points corresponding to two adjacent driving trajectory points is two seconds.

[0085] The first driving trajectory point can be obtained when the vehicle issues a navigation request. The position represented by the driving trajectory point is the starting point, and the time point corresponding to the driving trajectory point is the departure time of the vehicle.

[0086] S203: Determine the actual driving path and actual arrival time of the vehicle according to the location information and time point of each driving trajectory point.

[0087] For example, according to the time points corresponding to the various driving trajectory points, starting from the first driving trajectory point, the driving trajectory points are connected in sequence in chronological order until the driving trajectory point at the terminal position is reached. The connected path is used as the actual driving path of the vehicle. The time point corresponding to the driving trajectory point at the terminal position is determined, and the time point is used as the time when the vehicle arrives at the terminal position. According to the time point of the first driving trajectory point and the time point corresponding to the driving trajectory point at the terminal position, the time taken by the vehicle from the starting position to the terminal position can be obtained as the actual arrival time.

[0088] In this embodiment, each driving trajectory point is screened according to the position information and time point of each driving trajectory point to obtain a target trajectory point; and the actual driving path and actual arrival time of the vehicle are determined according to the time point corresponding to the target trajectory point.

[0089] Specifically, each track point has its own location information, which represents the actual geographical location of the vehicle, and can be represented by longitude and latitude coordinates. The location information and time point corresponding to each driving track point are determined, wherein the location information of the first driving track point, that is, the driving track point with the earliest time point, is the starting point.

[0090] According to the location information and time points of all driving trajectory points, these driving trajectory points are screened, and the driving trajectory points retained after screening are used as target trajectory points. For example, a geographical range can be set in advance, and the driving trajectory points with location information outside the geographical range are screened out, and the driving trajectory points with location information within the geographical range are retained. For another example, a time range can be set in advance, and the driving trajectory points with time points outside the time range are screened out, and the driving trajectory points with time points within the time range are retained.

[0091] Multiple target trajectory points can be screened and connected in sequence according to the time points corresponding to the target trajectory points to obtain the actual driving path of the vehicle. The actual arrival time can be obtained according to the time points corresponding to the first and last driving trajectory points in the actual driving path. For example, the time of two time points can be subtracted, and the difference is the actual arrival time.

[0092] The beneficial effect of such a setting is that the vehicle's driving trajectory points are cleaned to obtain a true and effective actual driving path and ATA, thereby avoiding the influence of redundant data on the analysis and improving the accuracy of subsequent analysis.

[0093] In this embodiment, each driving trajectory point is screened according to the position information and time point of each driving trajectory point to obtain the target trajectory point, including: determining the time point of the driving trajectory point corresponding to the terminal position as the terminal moment; filtering out the driving trajectory points corresponding to the time point after the terminal moment to obtain candidate trajectory points; and determining the target trajectory point from the candidate trajectory points according to the position information of the candidate trajectory points.

[0094] Specifically, according to the position information of each driving trajectory point, the driving trajectory point located at the terminal position is determined. The time point corresponding to the driving trajectory point is determined, and the time point is used as the terminal time. If there are multiple driving trajectory points located at the terminal position, the earliest time point is determined from the time points corresponding to these driving trajectory points as the terminal time.

[0095] All driving trajectory points after the end time are screened out, that is, the trajectory points from the first starting position to the first end position are retained as candidate trajectory points. The position information of each candidate trajectory point is determined, and a secondary screening process is performed based on the position information of the candidate trajectory point to determine the target trajectory point from the candidate trajectory points. For example, the candidate trajectory points at the same position information at adjacent time points can be screened out, and only one candidate trajectory point at the position information is retained as the target trajectory point. For example, if the user stays at a certain location for a long time, one of the candidate trajectory points at that location can be randomly retained. For the end position, if the user stays at the end position for a long time, the first candidate trajectory point at that location is retained.

[0096] The beneficial effect of such a setting is that the driving trajectory points that the vehicle passes through after reaching the terminal position are screened out, thereby avoiding redundancy in the actual driving path, improving the accuracy of determining the actual driving path, and further improving the accuracy of analyzing the driving time.

[0097] In this embodiment, the target trajectory point is determined from the candidate trajectory points according to the position information of the candidate trajectory points, including: according to the position information of the candidate trajectory points, the candidate trajectory points located outside the preset longitude and latitude range are screened out to obtain the target trajectory point.

[0098] Specifically, when the vehicle is recording driving trajectory points, errors or faults may occur, resulting in the location of the driving trajectory points being obviously unreasonable. Therefore, such obviously unreasonable driving trajectory points need to be screened out.

[0099] A latitude and longitude range is preset to determine whether the location information of each candidate trajectory point is within the latitude and longitude range. If so, it means that the candidate trajectory point is reasonable and can be retained; if not, it means that the candidate trajectory point is unreasonable and needs to be screened out. For example, if the preset latitude and longitude range is the regional range of city A, and there is a candidate trajectory point located in city B, then the candidate trajectory point is obviously unreasonable and can be screened out.

[0100] The beneficial effect of such a setting is that unreasonable driving trajectory points are eliminated, the accuracy of determining the actual driving path is improved, and then the accuracy of analyzing the driving time is improved.

[0101] In this embodiment, the actual driving path and actual arrival time of the vehicle are determined according to the time points corresponding to the target trajectory points, including: connecting the target trajectory points according to the time points corresponding to the target trajectory points to obtain the actual driving path of the vehicle; determining the actual arrival time according to the time points of the trajectory points corresponding to the starting position and the time points of the trajectory points corresponding to the end position.

[0102] Specifically, determine the time points corresponding to each target trajectory point, connect the target trajectory points in sequence according to the time sequence of the time points, and obtain a complete actual driving path. The first driving trajectory point in the actual driving path is located at the starting point, and the last driving trajectory point is located at the end point. Subtract the time point of the driving trajectory point corresponding to the starting point from the time point of the driving trajectory point corresponding to the end point to obtain the actual arrival time.

[0103] A time compensation strategy can also be preset, and the time compensation strategy is used to adjust the calculated actual arrival time. For example, the calculated actual arrival time can be appropriately increased or decreased. Considering that the vehicle will pass through traffic lights and wait at traffic lights when driving, it can be determined how many traffic lights will be passed in the actual driving path. A time compensation length is preset, and the time compensation length can represent the time length compensated for each traffic light. The number of traffic lights is multiplied by the time compensation length to obtain the total length of compensation. The calculated actual arrival time is subtracted from the total length to obtain the lower limit of the actual arrival time, and the calculated actual arrival time is added to the total length to obtain the upper limit of the actual arrival time. All values ​​between the lower limit and the upper limit can be used as the final actual arrival time. By performing time compensation, the actual driving situation can be taken into account, the flexibility of determining the actual arrival time can be improved, and the accuracy of time analysis can be improved. The time compensation strategy can also be used to fit the user's psychology. Users are more inclined to see a relatively long actual arrival time to reasonably arrange travel time to avoid being late. Therefore, the time compensation strategy can be used to appropriately increase the actual arrival time and improve the user's driver and passenger experience.

[0104] The beneficial effect of such a setting is that multiple trajectory points are automatically connected to obtain a complete actual driving path, and the time difference between the starting position and the end position is used as ATA, which improves the efficiency and accuracy of determining the actual driving path and ATA, thereby improving the efficiency and accuracy of time analysis.

[0105] S204. If it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition based on the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed based on the estimated arrival time and the actual arrival time to obtain a time analysis result; wherein the time analysis result represents the accuracy of the preset navigation product's estimation of the driving time.

[0106] Exemplarily, this step may refer to the above-mentioned step S103 and will not be described in detail.

[0107] In an embodiment of the present application, the starting position and the end position of the vehicle can be determined by responding to the navigation request of the vehicle. By using a preset navigation product, the planned driving path and the estimated arrival time estimated by the preset navigation product can be obtained. When the vehicle has finished driving, the actual driving path and the actual arrival time of the vehicle can be obtained. Determine whether the planned driving path and the actual driving path are similar. If so, the estimated arrival time and the actual arrival time can be compared and analyzed to obtain an analysis result. In an embodiment of the present application, the driving path and driving time estimated by the preset navigation product, as well as the actual driving path and driving time of the vehicle are determined. When the two driving paths are similar, the driving time is analyzed to determine whether the driving time estimated by the preset navigation product is accurate, thereby improving the analysis accuracy of the driving time, which is conducive to improving the preset navigation product, thereby enhancing the driving experience.

[0108] Figure 3 A flow chart of a method for analyzing driving time based on vehicle navigation provided in an embodiment of the present application is shown as follows: Figure 3 As shown, this embodiment, based on the above embodiment, describes in detail the analysis method of driving time based on vehicle navigation, and the method includes:

[0109] S301. In response to a navigation request issued by a vehicle, a planned driving route and an estimated arrival time are determined based on a preset navigation product; wherein the navigation request includes a starting point location and an end point location, the planned driving route represents the driving route of the vehicle from the starting point location to the end point location predicted by the preset navigation product, the estimated arrival time represents the time required for the vehicle to follow the planned driving route predicted by the preset navigation product, and the preset navigation product represents a preset software product for vehicle navigation.

[0110] Exemplarily, this step may refer to the above-mentioned step S101 and will not be described in detail.

[0111] S302. Acquire driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the actual path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle along the actual driving path.

[0112] Exemplarily, this step may refer to the above-mentioned step S102 and will not be described in detail.

[0113] S303: Determine the similarity between the planned driving path and the actual driving path.

[0114] For example, after obtaining the planned driving path and the actual driving path, the similarity between the planned driving path and the actual driving path can be calculated, that is, the consistency between the planned driving path and the actual driving path can be determined. For example, the similarity can be calculated by using the cosine similarity calculation method. In this embodiment, the method for calculating the similarity is not specifically limited.

[0115] In this embodiment, determining the similarity between the planned driving path and the actual driving path includes: placing both the planned driving path and the actual driving path in a preset grid area; wherein the preset grid area is composed of a preset number of cells; determining the cells occupied by the actual driving path in the preset grid area as a first cell area, and determining the cells occupied by the planned driving path in the preset grid area as a second cell area; and determining the similarity between the planned driving path and the actual driving path based on the number of overlapping cells in the first cell area and the second cell area.

[0116] Specifically, a grid area is pre-set, and both the planned driving path and the actual driving path are placed in the grid area. The grid area includes multiple cells. Figure 4 A schematic diagram of the grid area. Figure 4 L1 is the actual driving path, and L2 is the planned driving path.

[0117] When determining the similarity, the cells occupied by the actual driving path in the grid area can be determined, and the area where these cells are located is used as the first cell area, and the cells occupied by the planned driving path in the grid area can be determined, and the area where these cells are located is used as the second cell area. For example, the Bresenham straight line algorithm, the buffer zone algorithm, etc. can be used to determine the cells passed by the driving path.

[0118] Determine whether there are overlapping cells in the first cell area and the second cell area. If not, determine that the similarity between the planned driving path and the actual driving path is 0; if so, determine the similarity between the planned driving path and the actual driving path based on the number of overlapping cells. For example, the number of overlapping cells can be divided by the total number of cells in the first cell area to obtain the similarity. Figure 4 As shown, the number of overlapping cells is 3, and the number of cells in the first cell area is 15, so the similarity can be 0.2.

[0119] After obtaining the first cell region, the first cell region may be expanded. For example, for each cell in the first cell region, the region range of one cell is increased to the left, and the entire region after expansion is determined as the third cell region. That is, the third cell region includes the first cell region. The number of cells overlapping the third cell region and the second cell region is determined, and the number is divided by the total number of cells in the first cell region to obtain the similarity.

[0120] The beneficial effect of such a setting is that the driving path is divided into grids, the expression of the driving path is refined, the calculation accuracy of the similarity is improved, and the analysis accuracy of the driving time is further improved.

[0121] S304: If the similarity is greater than a preset similarity threshold, the travel time of the vehicle is analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result.

[0122] For example, a similarity threshold is preset. If the calculated similarity is less than or equal to the similarity threshold, it is considered that the actual driving route and the planned driving route are greatly different, and the estimated arrival time of the planned driving route cannot be analyzed, and the planned driving route sample is discarded. If the calculated similarity is greater than the preset similarity threshold, the estimated arrival time and the actual arrival time can be compared to obtain the time analysis result.

[0123] In this embodiment, the time analysis result includes a deviation rate, which represents the degree of deviation between the actual arrival time and the expected arrival time; the deviation rate is represented by:

[0124]

[0125] Among them, P represents the deviation rate, ETA represents the estimated arrival time, and ATA represents the actual arrival time.

[0126] Specifically, the deviation rate can be calculated based on the estimated arrival time and the actual arrival time, and the deviation rate can be used as the time analysis result. The deviation rate can represent the degree of deviation between the actual arrival time and the estimated arrival time, that is, the accuracy of the preset navigation product's estimation of the travel time.

[0127] The beneficial effect of this setting is that the denominator in the above formula is the mean of ETA and ATA, which takes into account the overall situation of the two data, ensures that the deviation rate can comprehensively evaluate the relative relationship between the two data, and improves the accuracy of analysis. It also avoids the problem of excessive calculation results caused by too small ATA, making the indicator more robust. Adding absolute values ​​to the formula to deal with the positive and negative effects of errors makes the error penalties for predicted values ​​higher than the actual value and lower than the actual value more balanced.

[0128] In this embodiment, the time analysis result includes a deviation rate, and the deviation rate represents the degree of deviation between the actual arrival time and the expected arrival time; the method also includes: for each preset navigation product, obtaining the deviation rate of different vehicles under the preset analysis dimension, and determining the average value of the deviation rate under the preset analysis dimension; wherein the preset analysis dimension includes at least one of the time dimension, the geographical dimension, the distance dimension, and the speed dimension, the time dimension represents the time period in which the vehicle is traveling, the geographical dimension represents the geographical area in which the vehicle is traveling, the distance dimension represents the length of the actual driving path, and the speed dimension represents the average driving speed of the vehicle; according to the average value corresponding to each preset navigation product, determine the product analysis result of each preset navigation product under the preset analysis dimension; wherein the product analysis result represents the difference in navigation effects between different preset navigation products.

[0129] Specifically, there may be multiple preset navigation products, and for each preset navigation product, multiple analysis dimensions may be preset. The preset analysis dimension may include at least one of the time dimension, the region dimension, the distance dimension, and the speed dimension. The time dimension represents the time period in which the vehicle is traveling, the region dimension represents the geographical area in which the vehicle is traveling, the distance dimension represents the length of the actual driving path, and the speed dimension represents the average driving speed of the vehicle. For example, if the time dimension is the time period from 10 to 11 o'clock, the deviation rate between each actual driving path generated between 10 to 11 o'clock and the corresponding planned driving path may be determined; if the region dimension may be city A, the deviation rate between each actual driving path generated in city A and the corresponding planned driving path may be determined; if the distance dimension is 2 km, the deviation rate between each actual driving path within 2 km in length and the corresponding planned driving path may be determined; if the speed dimension is 60 km / h, the deviation rate between each actual driving path generated by a vehicle with a speed within 60 km / h and the corresponding planned driving path may be determined. The deviation rate between the actual driving path and the planned driving path is the deviation rate between the actual arrival time of the actual driving path and the estimated arrival time of the planned driving path.

[0130] The analysis dimension to be analyzed is pre-set. Under the analysis dimension, for each preset navigation product, the deviation rate between each actual driving path and the planned driving path generated by the preset navigation product is calculated. The actual driving paths of multiple vehicles can be recorded, and each vehicle can travel multiple actual driving paths. For each actual driving path, a deviation rate can be calculated for the preset navigation product. That is, each preset navigation product can correspond to multiple deviation rates. Calculate the average value of the deviation rate corresponding to the preset navigation product, that is, for each preset navigation product, determine the average value of the deviation rate under the preset analysis dimension.

[0131] The average values ​​corresponding to the preset navigation products are compared, and the preset navigation products are analyzed to obtain product analysis results of the preset navigation products. The product analysis results can represent the difference in navigation effects between different preset navigation products, that is, the difference in the accuracy of driving time estimation. Figure 5 A schematic diagram showing the comparison between multiple preset navigation products. Figure 5 The preset analysis dimension in is the geographical dimension of city A. The actual driving paths of each vehicle traveling in city A every day are determined. For each preset navigation product, the average deviation rate of each day is determined. The average values ​​of adjacent dates are connected to obtain a line chart of the average values ​​of the preset navigation products in city A. The deviation rate line charts of various preset navigation products are compared to realize the analysis of each preset navigation product. Figure 5 The solid and dotted lines in the figure represent the average values ​​of the two preset navigation products.

[0132] The beneficial effect of this setting is that a large sample size can be counted according to multiple dimensions such as time period, city, travel distance, etc., which improves the accuracy of product analysis. Comparative analysis of multiple navigation products does not require preset absolute standard values, allowing users to intuitively view the navigation effects of different navigation products, making it easier to improve navigation products.

[0133] In this embodiment, the deviation rate of different vehicles under the preset analysis dimension is obtained, including: determining the actual driving paths generated by different vehicles under the preset analysis dimension, which is the path to be analyzed; and obtaining the deviation rate corresponding to the path to be analyzed, which is the deviation rate under the preset analysis dimension.

[0134] Specifically, there may be multiple vehicles on the road, and after the analysis dimension is preset, for each vehicle, an actual driving path generated under the analysis dimension may be obtained, and the actual driving path under the analysis dimension is determined as the path to be analyzed.

[0135] Each actual driving path can correspond to its own deviation rate. For each preset navigation product, the deviation rate corresponding to the path to be analyzed is calculated. Each deviation rate obtained is the deviation rate of the vehicle under this analysis dimension.

[0136] The beneficial effect of this setting is that the respective deviation rates are calculated for different analysis dimensions, which facilitates product analysis under different analysis dimensions, improves the accuracy and flexibility of the analysis, and thus makes targeted improvements to the preset navigation products.

[0137] In an embodiment of the present application, the starting position and the end position of the vehicle can be determined by responding to the navigation request of the vehicle. By using a preset navigation product, the planned driving path and the estimated arrival time estimated by the preset navigation product can be obtained. When the vehicle has finished driving, the actual driving path and the actual arrival time of the vehicle can be obtained. Determine whether the planned driving path and the actual driving path are similar. If so, the estimated arrival time and the actual arrival time can be compared and analyzed to obtain an analysis result. In an embodiment of the present application, the driving path and driving time estimated by the preset navigation product, as well as the actual driving path and driving time of the vehicle are determined. When the two driving paths are similar, the driving time is analyzed to determine whether the driving time estimated by the preset navigation product is accurate, thereby improving the analysis accuracy of the driving time, which is conducive to improving the preset navigation product, thereby enhancing the driving experience.

[0138] Figure 6 A schematic diagram of a driving time analysis device based on vehicle navigation provided in an embodiment of the present application is provided. The device can be applied to a cloud platform, such as Figure 6As shown, the analysis device 60 based on vehicle navigation travel time provided in this embodiment includes:

[0139] The planned driving unit 601 is used to determine the planned driving path and the estimated arrival time based on the preset navigation product in response to the navigation request issued by the vehicle; wherein the navigation request includes the starting position and the end position, the planned driving path represents the driving path of the vehicle from the starting position to the end position predicted by the preset navigation product, the estimated arrival time represents the time required for the vehicle to follow the planned driving path predicted by the preset navigation product, and the preset navigation product represents a preset software product for vehicle navigation;

[0140] The actual driving unit 602 is used to obtain the driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the real path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle to follow the actual driving path;

[0141] The result analysis unit 603 is used to analyze the driving time of the vehicle according to the estimated arrival time and the actual arrival time to obtain a time analysis result if it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition based on the area occupied by the planned driving path and the area occupied by the actual driving path; wherein the time analysis result represents the accuracy of the preset navigation product's estimation of the driving time.

[0142] Figure 7 A structural block diagram of a driving time analysis device based on vehicle navigation provided in an embodiment of the present application, such as Figure 7 As shown, the driving time analysis device 70 based on vehicle navigation includes a planned driving unit 701, an actual driving unit 702 and a result analysis unit 703, wherein the driving information includes driving trajectory points, each driving trajectory point corresponds to a time point and position information, the time point represents the moment when the vehicle arrives at the location of the driving trajectory point, and the position information represents the longitude and latitude coordinates; the actual driving unit 702 includes a trajectory point determination module 7021 and a path determination module 7022.

[0143] The track point determination module 7021 is used to filter each driving track point according to the position information and time point of each driving track point to obtain a target track point;

[0144] The path determination module 7022 is used to determine the actual driving path and actual arrival time of the vehicle according to the time point corresponding to the target trajectory point.

[0145] In a possible implementation, the trajectory point determination module 7021 is specifically configured to:

[0146] Determine the time point of the driving trajectory point corresponding to the terminal position as the terminal moment;

[0147] The driving trajectory points corresponding to the time points after the end point are screened out to obtain candidate trajectory points;

[0148] The target trajectory point is determined from the candidate trajectory points according to the position information of the candidate trajectory points.

[0149] In a possible implementation, the path determination module 7022 is specifically configured to:

[0150] Connecting the target trajectory points according to the time points corresponding to the target trajectory points to obtain the actual driving path of the vehicle;

[0151] The actual arrival time is determined according to the time point of the trajectory point corresponding to the starting position and the time point of the trajectory point corresponding to the end position.

[0152] In a possible implementation, the result analysis unit 703 includes:

[0153] A grid division module, used to place the planned driving path and the actual driving path in a preset grid area; wherein the preset grid area is composed of a preset number of cells;

[0154] An area determination module, used to determine the cells occupied by the actual driving path in the preset grid area as a first cell area, and to determine the cells occupied by the planned driving path in the preset grid area as a second cell area;

[0155] a similarity determination module, configured to determine the similarity between the planned driving path and the actual driving path according to the number of overlapping cells in the first cell area and the second cell area;

[0156] The result obtaining module is used for analyzing the travel time of the vehicle according to the estimated arrival time and the actual arrival time to obtain a time analysis result if the similarity is greater than a preset similarity threshold.

[0157] In a possible implementation, the time analysis result includes a deviation rate, which represents the degree of deviation between the actual arrival time and the estimated arrival time; the deviation rate is represented by:

[0158]

[0159] Among them, P represents the deviation rate, ETA represents the estimated arrival time, and ATA represents the actual arrival time.

[0160] In a possible implementation, the time analysis result includes a deviation rate, and the deviation rate represents the degree of deviation between the actual arrival time and the expected arrival time; the device further includes:

[0161] an average value determination unit, for each of the preset navigation products, obtaining the deviation rates of different vehicles under the preset analysis dimensions, and determining the average value of the deviation rates under the preset analysis dimensions; wherein the preset analysis dimensions include at least one of a time dimension, a region dimension, a distance dimension, and a speed dimension, the time dimension represents the time period in which the vehicle is traveling, the region dimension represents the geographical area in which the vehicle is traveling, the distance dimension represents the length of the actual driving path, and the speed dimension represents the average driving speed of the vehicle;

[0162] The product analysis unit is used to determine the product analysis results of each preset navigation product under the preset analysis dimension according to the average value corresponding to each preset navigation product; wherein the product analysis results represent the difference in navigation effects between different preset navigation products.

[0163] In a possible implementation manner, the average value determination unit is specifically configured to:

[0164] Determine the actual driving paths generated by different vehicles under the preset analysis dimension as the paths to be analyzed;

[0165] The deviation rate corresponding to the path to be analyzed is obtained, which is the deviation rate under the preset analysis dimension.

[0166] In a possible implementation, the travel planning unit 701 includes:

[0167] a request response module, configured to respond to a navigation request issued by a vehicle and input the navigation request into the preset navigation product;

[0168] The path output module is used to obtain the planned driving path and estimated arrival time output by the preset navigation product.

[0169] Figure 8 A structural block diagram of an electronic device provided in an embodiment of the present application, such as Figure 8 As shown, the electronic device includes: a memory 81 and a processor 82; the memory 81 is a memory for storing instructions executable by the processor 82.

[0170] The processor 82 is configured to execute the method provided in the above embodiment.

[0171] The electronic device further includes a receiver 83 and a transmitter 84. The receiver 83 is used to receive instructions and data sent by other devices, and the transmitter 84 is used to send instructions and data to external devices.

[0172] An exemplary embodiment of this solution shows a terminal device, which can be connected to Figure 6-8 A terminal device for interacting with the device or electronic device shown in any of the figures, which can be deployed on a vehicle side or a mobile terminal on the user side, for cooperating with Figure 6-8 The device or electronic device shown implements the method in the above-mentioned embodiment of the present scheme.

[0173] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory including instructions, and the above instructions can be executed by a processor of an apparatus or electronic device to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0174] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a device or electronic device, enables the device or electronic device to perform the above-mentioned analysis method of driving time based on vehicle navigation.

[0175] The present application also discloses a computer program product, including a computer program, which implements the method described in this embodiment when executed by a processor.

[0176] Various embodiments of the systems and techniques described above in the present application can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor, which can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0177] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or electronic device.

[0178] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing.

[0179] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

[0180] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0181] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for analyzing driving time based on vehicle navigation, characterized in that: include: In response to a navigation request from the vehicle, determine a planned driving route and an estimated arrival time based on a preset navigation product; Acquire the driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the real path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle to follow the actual driving path; If it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition based on the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed based on the estimated arrival time and the actual arrival time to obtain a time analysis result; wherein the time analysis result represents the accuracy of the estimated driving time by the preset navigation product.

2. The method according to claim 1, characterized in that The driving information includes driving track points, each driving track point corresponds to a time point and position information, the time point represents the moment when the vehicle arrives at the location of the driving track point, and the position information represents the longitude and latitude coordinates; The determining the actual driving path and the actual arrival time of the vehicle according to the driving information includes: According to the location information and time point of each driving trajectory point, each driving trajectory point is screened to obtain the target trajectory point; According to the time point corresponding to the target trajectory point, the actual driving path and actual arrival time of the vehicle are determined.

3. The method according to claim 2, characterized in that The method of screening each driving trajectory point according to the location information and time point of each driving trajectory point to obtain the target trajectory point includes: Determine the time point of the driving trajectory point corresponding to the terminal position as the terminal moment; The driving trajectory points corresponding to the time points after the end point are screened out to obtain candidate trajectory points; The target trajectory point is determined from the candidate trajectory points according to the position information of the candidate trajectory points.

4. The method according to claim 2, characterized in that: The determining the actual driving path and the actual arrival time of the vehicle according to the time point corresponding to the target trajectory point includes: Connecting the target trajectory points according to the time points corresponding to the target trajectory points to obtain the actual driving path of the vehicle; The actual arrival time is determined according to the time point of the trajectory point corresponding to the starting position and the time point of the trajectory point corresponding to the end position.

5. The method according to claim 1, characterized in that If it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition according to the area occupied by the planned driving path and the area occupied by the actual driving path, the driving time of the vehicle is analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result, including: Placing the planned driving path and the actual driving path in a preset grid area; wherein the preset grid area is composed of a preset number of cells; Determine the cells occupied by the actual driving path in the preset grid area as a first cell area, and determine the cells occupied by the planned driving path in the preset grid area as a second cell area; Determining the similarity between the planned driving path and the actual driving path according to the number of overlapping cells in the first cell area and the second cell area; If the similarity is greater than a preset similarity threshold, the travel time of the vehicle is analyzed according to the estimated arrival time and the actual arrival time to obtain a time analysis result.

6. The method according to any one of claims 1 to 5, characterized in that The time analysis result includes a deviation rate, which represents the degree of deviation between the actual arrival time and the expected arrival time; the method further includes: For each of the preset navigation products, the deviation rates of different vehicles under the preset analysis dimensions are obtained, and the average value of the deviation rates under the preset analysis dimensions is determined; wherein the preset analysis dimensions include at least one of a time dimension, a region dimension, a distance dimension, and a speed dimension, the time dimension represents the time period in which the vehicle is traveling, the region dimension represents the geographical area in which the vehicle is traveling, the distance dimension represents the length of the actual driving path, and the speed dimension represents the average driving speed of the vehicle; According to the average values ​​corresponding to the preset navigation products, the product analysis results of the preset navigation products under the preset analysis dimensions are determined; wherein the product analysis results represent the differences in navigation effects between different preset navigation products.

7. The method according to claim 6, characterized in that The obtaining of the deviation rates of different vehicles under the preset analysis dimensions includes: Determine the actual driving paths generated by different vehicles under the preset analysis dimension as the paths to be analyzed; The deviation rate corresponding to the path to be analyzed is obtained, which is the deviation rate under the preset analysis dimension.

8. The method according to any one of claims 1 to 5, characterized in that The step of responding to a navigation request issued by the vehicle and determining a planned driving route and an estimated arrival time based on a preset navigation product includes: In response to a navigation request issued by the vehicle, inputting the navigation request into the preset navigation product; Obtain the planned driving route and estimated arrival time output by the preset navigation product.

9. A driving time analysis device based on vehicle navigation, characterized in that: include: A planning driving unit, used to respond to a navigation request issued by the vehicle and determine a planned driving route and an estimated arrival time based on a preset navigation product; an actual driving unit, used to obtain driving information of the vehicle, and determine the actual driving path and actual arrival time of the vehicle according to the driving information; wherein the driving information represents the driving condition of the vehicle after the navigation request is issued, the actual driving path represents the real path traveled by the vehicle from the starting position to the end position, and the actual arrival time represents the time taken by the vehicle to follow the actual driving path; A result analysis unit is used to analyze the driving time of the vehicle according to the estimated arrival time and the actual arrival time to obtain a time analysis result if it is determined that the similarity between the planned driving path and the actual driving path meets a preset condition according to the area occupied by the planned driving path and the area occupied by the actual driving path; wherein the time analysis result represents the accuracy of the estimated driving time by the preset navigation product.

10. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 8.

11. A computer-readable storage medium / computer program product, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor; and / or, The computer program product comprises a computer program, which implements the method according to any one of claims 1 to 8 when executed by a processor.

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