Driving route determination method and device, computer equipment, readable storage medium and program product
By acquiring and analyzing the vehicle network data, determining the target parking point and intermediate driving route, the problem of high computing resources consumption in intelligent driving technology is solved, and efficient driving route planning is achieved.
Patent Information
- Application Number
- CN202411260381.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-10
- Publication Date
- 2024-12-24
AI Technical Summary
The existing intelligent driving technology needs to obtain and analyze a large amount of outdoor environment data and vehicle data in real time in driving route prediction planning, resulting in excessive consumption of computing resources and it is difficult to efficiently save computing resources.
By obtaining the vehicle network data of the vehicle within the preset time period, including the ignition time point, the off time point, the starting point, the end point, the fuel consumption, the average driving speed and the mileage, the target parking point position and the intermediate driving route are determined. Then calculate the target driving route and use historical data to reduce computing resource consumption.
It effectively saves computing resources, obtains target driving routes through historical vehicle network data, and improves the efficiency and accuracy of driving route planning.
Smart Images
Figure CN119181245A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of vehicle route analysis in Internet of Vehicles, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining a driving route. Background Art
[0002] With the development of intelligent driving technology, the prediction and planning of vehicle driving routes in advance has become an increasingly important research focus for relevant technical personnel. In the existing technology, the purpose of intelligent driving is mainly achieved by relying on the intelligent driving instrument based on the computer system in the car. The vehicle is an intelligent car that senses the road environment through the on-board sensor system, automatically plans the driving route and controls the vehicle to reach the predetermined target. However, this method requires real-time acquisition and analysis of various external environment data and vehicle data, and processes a lot of data, which consumes a lot of computing resources. Summary of the invention
[0003] Based on this, it is necessary to provide a driving route determination method, device, computer equipment, computer-readable storage medium and computer program product that can save computing resources in order to solve the above technical problems.
[0004] In a first aspect, the present application provides a method for determining a driving route, the method comprising:
[0005] Acquire vehicle networking data of the vehicle within a preset time period, the vehicle networking data including the ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and driving mileage of the vehicle within each initial driving route;
[0006] Determining a target parking point position based on the ignition time point, the starting position and the end position;
[0007] Acquire an initial driving route with the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route;
[0008] A target driving route is determined based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
[0009] In one embodiment, determining the target parking point position based on the ignition time point, the starting position and the end position includes:
[0010] sorting the initial driving routes based on the order of the ignition time points from front to back;
[0011] The starting point position of the first initial driving route and the end point positions of all initial driving routes in the sorting result are determined as the initial parking point positions, and the repeated initial parking point positions are determined as the target parking point positions.
[0012] In one embodiment, determining the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route includes:
[0013] For each target parking point location, when there are multiple intermediate driving routes corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving routes or the sum of the Internet of Vehicles data corresponding to the intermediate driving routes is determined as the target Internet of Vehicles data;
[0014] Based on the target Internet of Vehicles data, a target driving route is determined.
[0015] In one embodiment, determining a target driving route based on the target Internet of Vehicles data includes:
[0016] The target Internet of Vehicles data is determined as the Internet of Vehicles data corresponding to the target driving route.
[0017] In one embodiment, the method further comprises:
[0018] When there is only one section of the intermediate driving route corresponding to the target parking point position, the intermediate driving route is determined as the target driving route.
[0019] In one embodiment, the method further comprises:
[0020] For each two initial driving routes, obtaining a common route between the two initial driving routes;
[0021] Based on the mileage of the common route, obtaining similarity index values of the two initial driving routes;
[0022] When the similarity index value is greater than a preset value, the two initial driving routes are determined to be similar routes.
[0023] In a second aspect, the present application further provides a driving route determination device, the device comprising:
[0024] A first acquisition module is used to acquire vehicle networking data of the vehicle within a preset time period, wherein the vehicle networking data includes the ignition time point, the ignition time point, the starting position, the end position, the fuel consumption, the average driving speed, the driving time and the driving mileage of the vehicle within each initial driving route;
[0025] A first determination module, configured to determine a target parking point position based on the ignition time point, the starting position and the end position;
[0026] A second acquisition module is used to acquire an initial driving route with the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route;
[0027] The second determination module is used to determine the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
[0028] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in any one of the above embodiments when executing the computer program.
[0029] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.
[0030] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.
[0031] The above-mentioned driving route determination method, device, computer equipment, computer-readable storage medium and computer program product obtain the vehicle's Internet of Vehicles data within a preset time period, and the Internet of Vehicles data includes the vehicle's ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and driving mileage in each initial driving route; determine the target parking point location based on the ignition time point, starting position and end position; obtain the initial driving route with the target parking point location as the starting position or the end position, and determine the initial driving route as the intermediate driving route; determine the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route. The method provided by the present application can obtain the target driving route based on historical Internet of Vehicles data, and can effectively save computing resources. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0033] FIG1 is a schematic diagram of a flow chart of a method for determining a driving route in one embodiment;
[0034] FIG2 is a schematic diagram of a flow chart of a method for determining a target parking point position in one embodiment;
[0035] FIG3 is a schematic diagram of a flow chart of a method for determining a driving route in another embodiment;
[0036] FIG4 is a structural block diagram of a driving route determination device in one embodiment;
[0037] FIG. 5 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION
[0038] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0039] In one embodiment, as shown in FIG1 , a method for determining a driving route is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:
[0040] S102. Obtaining Internet of Vehicles data of the vehicle within a preset time period, the Internet of Vehicles data including the ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and mileage of the vehicle within each initial driving route.
[0041] Among them, the initial driving route is the route traveled by the vehicle in a complete process from ignition start to shutdown and parking; the preset time period is a period of time before the current time point, for example, the preset time period can be one month before the current time point; the starting position and the end position can be longitude and latitude data.
[0042] Specifically, the Internet of Vehicles data sent by the vehicle-mounted positioning terminal is received, and the received Internet of Vehicles data is cleaned.
[0043] S104: Determine the target parking point location based on the ignition time point, the starting position and the ending position.
[0044] Among them, based on the ignition time point, a suitable position can be selected from the starting position and the end position as the target parking point position, or other positions can be determined as the target parking point position based on the ignition time point, the starting position and the end position. The embodiments of the present application do not make specific limitations on this.
[0045] S106: Acquire an initial driving route that uses the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route.
[0046] Among them, the starting point position or the end point position of the intermediate driving route can be the target parking point position, and the starting point position and the end point position of the intermediate driving route can also be the target parking point position at the same time. The embodiment of the present application does not make specific limitations on this.
[0047] S108. Determine the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
[0048] Among them, different methods can be used to determine the target driving route based on the number of intermediate driving routes corresponding to each target parking point position.
[0049] In the above driving route determination method, the vehicle's Internet of Vehicles data within a preset time period is obtained, and the Internet of Vehicles data includes the vehicle's ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and driving mileage in each initial driving route; based on the ignition time point, starting position and end position, the target parking point position is determined; the initial driving route with the target parking point position as the starting position or the end position is obtained, and the initial driving route is determined as the intermediate driving route; based on the Internet of Vehicles data, the target parking point position and the intermediate driving route, the target driving route is determined. The method provided by the present application can obtain the target driving route based on historical Internet of Vehicles data, and can effectively save computing resources.
[0050] In some embodiments, as shown in FIG. 2 , determining the target parking point location based on the ignition time point, the starting position, and the ending position includes:
[0051] S202: Sort the initial driving routes based on the order of the ignition time points from front to back.
[0052] S204: Determine the starting point position of the first initial driving route and the end point positions of all initial driving routes in the sorting result as initial parking point positions, and determine the repeated initial parking point positions as target parking point positions.
[0053] The purpose of sorting the initial driving routes is to connect the starting position of each initial driving route with the end position of the next initial driving route. For example, the starting position and end position of the first initial driving route are A and B respectively, and the starting position and end position of the second initial driving route are B and C respectively. By sorting, the two initial driving routes can be connected through position B.
[0054] For example, the starting point and end point of the third section of the initial driving route are C and D respectively, wherein the starting point of the first section of the initial driving route is A, and the end points of the first, second and third sections of the initial driving routes are B, C and D respectively. According to the method of determining the starting point of the first section of the initial driving route and the end points of all the initial driving routes in the sorting results as the initial parking point positions, the determined initial parking point positions include A, B, C and D.
[0055] After the initial parking point locations are determined, the distance between each two initial parking points can be calculated using the haversine formula based on the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm, so as to classify the initial parking point locations and delete the noise points in the classification results. Each category in the classification results is associated with the place name of the area where the category is located based on the electronic map.
[0056] Since all initial driving routes with corresponding mileage less than the preset mileage will be classified into the same category during the clustering process, the initial driving routes with corresponding mileage less than the preset mileage need to be deleted from the sorting results before clustering.
[0057] In this embodiment, the starting point position of the first initial driving route in the sorting result and the end point positions of all initial driving routes are determined as the initial parking point positions, so that no position is missed and no position is repeatedly selected.
[0058] In some embodiments, a target driving route is determined based on the Internet of Vehicles data, the target parking point location and the intermediate driving route, including: for each target parking point location, when there are multiple sections of the intermediate driving route corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving route, or the sum of the Internet of Vehicles data corresponding to the intermediate driving route is determined as the target Internet of Vehicles data; based on the target Internet of Vehicles data, the target driving route is determined.
[0059] Among them, for the Internet of Vehicles data such as mileage, fuel consumption rate and driving time, the target Internet of Vehicles data can be obtained by obtaining the sum of the Internet of Vehicles data. For the two Internet of Vehicles data such as average fuel consumption per 100 kilometers and average driving speed, the target Internet of Vehicles data can be obtained by obtaining the median method.
[0060] In this embodiment, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the middle driving route, or the sum of the Internet of Vehicles data corresponding to the middle driving route is determined as the target Internet of Vehicles data, so that the determined target Internet of Vehicles data is more accurate.
[0061] In some embodiments, determining a target driving route based on target Internet of Vehicles data includes: determining the target Internet of Vehicles data as Internet of Vehicles data corresponding to the target driving route.
[0062] Among them, the target driving route can be planned in the electronic map based on the determined target vehicle networking data.
[0063] In this embodiment, the target driving route is determined based on the target Internet of Vehicles data, so that the planned target driving route is more accurate.
[0064] In some embodiments, the method further includes: when there is only one section of the intermediate driving route corresponding to the target parking point position, determining the intermediate driving route as the target driving route.
[0065] Among them, when the intermediate driving route has only one section, there is no need to process the Internet of Vehicles data, and the intermediate driving route can be directly determined as the target driving route.
[0066] In this embodiment, when there is only one section of the intermediate driving route corresponding to the target parking point position, the intermediate driving route is determined as the target driving route, so that the determined target driving route is more consistent with the actual driving situation.
[0067] In some embodiments, the method also includes: for every two initial driving routes, obtaining a common route between the two initial driving routes; based on the mileage of the common route, obtaining a similarity index value of the two initial driving routes; when the similarity index value is greater than a preset value, determining the two initial driving routes as similar routes.
[0068] Among them, Rouge-L (Recall-Oriented Understudy for Gisting Evaluation) can be used as a similarity indicator. Rouge-L is an indicator used to evaluate the similarity between two sequences. It is based on the length of the longest common subsequence in the two sequences. This application selects the F score calculated based on the Rouge-L method as an indicator for evaluating the similarity between two sequences. In other embodiments, other indicators can also be used as similarity indicators, and this application does not make specific limitations on this.
[0069] In this embodiment, by evaluating the similarity between the two initial driving routes, a foundation is laid for the subsequent analysis of the Internet of Vehicles data during the vehicle driving process.
[0070] In one embodiment, as shown in FIG3 , another driving route determination method is provided, the method comprising the following contents:
[0071] (1) First, select the vehicle range and data upload time range for data processing. The process from vehicle startup to shutdown is regarded as a trip segment. The vehicle network data sent back by the corresponding vehicle GPS terminal is received and obtained in units of months. The original data is cleaned, and then the start time, end time, mileage, fuel consumption, time, fuel consumption per 100 kilometers, average driving speed, and latitude and longitude data fields of each trip segment are selected.
[0072] (2) For a single vehicle, the cleaned data is sorted in ascending order according to the start time of the trip, and trips with mileage less than the cluster radius are deleted.
[0073] (3) For a single vehicle, the starting point of the first trip and all the end points of the trip are selected as the parking point list of the vehicle, and the longitude and latitude of the locations in the list are clustered. The DBSCAN algorithm is used, and the Haversine Formula is used to calculate the actual distance between the locations during clustering. The clustering radius is set to 200 meters.
[0074] (4) Remove the noise points in the clustering results of the parking spot list and associate the location information from longitude and latitude to the city name at the municipal level. Count the parking spots that each vehicle visits most frequently and have a cumulative arrival frequency greater than 2, which are used as the vehicle's "base camp".
[0075] (5) Delete the adjacent duplicate cities in the list of vehicle parking points to prepare the data for statistical closed-loop routes and vehicle route similarity measurement.
[0076] (6) Obtaining a closed-loop route: Based on the data from the previous step, the vehicle's "base camp" is processed in two situations: one is that the vehicle has only one "base camp", then in the vehicle's parking point list, find a route with the "base camp" as the starting point and the end point; the other is that the vehicle has multiple "base camps", in the vehicle's parking point list, find a route with any city in the "base camp" as the starting point and the end point as the closed-loop route of the vehicle.
[0077] (7) Statistical closed-loop route information: For the closed-loop route obtained in the previous step, the start time of the trip segment corresponding to the route start point and the end time of the trip segment corresponding to the destination point are used as the start and end times of the closed-loop route. From the initial trip information, all trips corresponding to the closed-loop route are indexed by time, and the mileage, fuel consumption, and time of the closed-loop route are obtained in a cumulative manner; the fuel consumption per 100 kilometers and the average driving speed of the closed-loop route are obtained by taking the median. Then, the data of all closed-loop routes can be statistically analyzed to obtain information such as the closed-loop routes with the most frequent vehicle operations.
[0078] (8) Route similarity measurement: Based on the data from the fifth step, the Rouge-L F score is used as an indicator to measure route similarity. The calculation of this indicator is based on the longest common subsequence of the two compared objects. For the vehicles in the data, their route similarities are compared pairwise. According to the recognition effect, routes with a score greater than 0.7 are judged to have a high similarity.
[0079] It should be understood that the steps in the flowcharts of the above-mentioned embodiments are sequentially displayed as indicated by the arrows. Moreover, at least a portion of the steps in the flowcharts of the above-mentioned embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but may be executed at different times.
[0080] Based on the same inventive concept, the embodiment of the present application also provides a driving route determination device for implementing the driving route determination method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more driving route determination device embodiments provided below can refer to the limitations of the driving route determination method above, and will not be repeated here.
[0081] In an exemplary embodiment, as shown in FIG. 4 , a driving route determination device 400 is provided, comprising: a first acquisition module 401, a first determination module 402, a second acquisition module 403 and a second determination module 404, wherein:
[0082] The first acquisition module 401 is used to obtain the vehicle networking data of the vehicle within a preset time period, and the vehicle networking data includes the ignition time point, the ignition off time point, the starting position, the end position, the fuel consumption, the average driving speed, the driving time and the driving mileage of the vehicle in each initial driving route.
[0083] The first determination module 402 is used to determine the target parking point position based on the ignition time point, the starting position and the end position.
[0084] The second acquisition module 403 is used to acquire an initial driving route with the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route.
[0085] The second determination module 404 is used to determine the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
[0086] In some embodiments, the first determination module 402 is also used to sort the initial driving routes based on the order of the ignition time points from front to back; determine the starting position of the first initial driving route and the end position of all initial driving routes in the sorting result as the initial parking point position, and determine the repeated initial parking point position as the target parking point position.
[0087] In some embodiments, the second determining module 404 includes:
[0088] The first determination unit is used to determine, for each target parking point location, when there are multiple sections of the intermediate driving routes corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving routes, or the sum of the Internet of Vehicles data corresponding to the intermediate driving routes as the target Internet of Vehicles data.
[0089] The second determination unit is used to determine a target driving route based on the target Internet of Vehicles data.
[0090] In some embodiments, the second determination unit is further used to determine the target Internet of Vehicles data as the Internet of Vehicles data corresponding to the target driving route.
[0091] In some embodiments, the driving route determining device 400 is specifically used to determine the intermediate driving route as the target driving route when there is only one section of the intermediate driving route corresponding to the target parking point position.
[0092] In some embodiments, the driving route determination device 400 is also used to obtain a common route between each two initial driving routes; based on the mileage of the common route, obtain a similarity index value of the two initial driving routes; when the similarity index value is greater than a preset value, determine the two initial driving routes as similar routes.
[0093] Each module in the above-mentioned driving route determination device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.
[0094] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG5. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, a near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for determining a driving route is implemented.
[0095] Those skilled in the art will understand that the structure shown in FIG. 5 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.
[0096] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining vehicle networking data of a vehicle within a preset time period, the vehicle networking data including an ignition time point, an ignition off time point, a starting position, an end position, fuel consumption, an average driving speed, a driving duration and a driving mileage of the vehicle in each initial driving route; determining a target parking point position based on the ignition time point, the starting position and the end position; obtaining an initial driving route with the target parking point position as the starting position or the end position, and determining the initial driving route as an intermediate driving route; determining a target driving route based on the vehicle networking data, the target parking point position and the intermediate driving route.
[0097] In one embodiment, the processor determines the target parking point position based on the ignition time point, the starting position and the end position when executing the computer program, including: sorting the initial driving routes based on the order of the ignition time points from front to back; determining the starting position of the first initial driving route and the end positions of all initial driving routes in the sorting results as the initial parking point positions, and determining the repeated initial parking point positions as the target parking point positions.
[0098] In one embodiment, the processor determines the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route when executing a computer program, including: for each target parking point location, when there are multiple sections of the intermediate driving route corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving route or the sum of the Internet of Vehicles data corresponding to the intermediate driving route is determined as the target Internet of Vehicles data; based on the target Internet of Vehicles data, the target driving route is determined.
[0099] In one embodiment, the determination of the target driving route based on the target Internet of Vehicles data implemented by the processor when executing the computer program includes: determining the target Internet of Vehicles data as the Internet of Vehicles data corresponding to the target driving route.
[0100] In one embodiment, the method implemented when the processor executes the computer program further includes: when there is only one section of the intermediate driving route corresponding to the target parking point position, determining the intermediate driving route as the target driving route.
[0101] In one embodiment, the method implemented when the processor executes the computer program also includes: for each two initial driving routes, obtaining a common route between the two initial driving routes; based on the mileage of the common route, obtaining a similarity index value between the two initial driving routes; and when the similarity index value is greater than a preset value, determining the two initial driving routes as similar routes.
[0102] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: obtaining vehicle networking data of a vehicle within a preset time period, the vehicle networking data including the ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and mileage of the vehicle in each initial driving route; determining a target parking point position based on the ignition time point, the starting position and the end position; obtaining an initial driving route with the target parking point position as the starting position or the end position, and determining the initial driving route as an intermediate driving route; determining a target driving route based on the vehicle networking data, the target parking point position and the intermediate driving route.
[0103] In one embodiment, the computer program implemented when executed by the processor determines the target parking point position based on the ignition time point, the starting position and the end position, including: sorting the initial driving routes based on the order of the ignition time points from front to back; determining the starting position of the first initial driving route and the end positions of all initial driving routes in the sorting results as the initial parking point positions, and determining the repeated initial parking point positions as the target parking point positions.
[0104] In one embodiment, the computer program implemented when executed by the processor determines the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route, including: for each target parking point location, when there are multiple sections of the intermediate driving route corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving route, or the sum of the Internet of Vehicles data corresponding to the intermediate driving route is determined as the target Internet of Vehicles data; based on the target Internet of Vehicles data, the target driving route is determined.
[0105] In one embodiment, the computer program implemented when executed by the processor determines the target driving route based on the target Internet of Vehicles data, including: determining the target Internet of Vehicles data as the Internet of Vehicles data corresponding to the target driving route.
[0106] In one embodiment, the method implemented when the computer program is executed by the processor further includes: when there is only one section of the intermediate driving route corresponding to the target parking point position, determining the intermediate driving route as the target driving route.
[0107] In one embodiment, the method implemented when the computer program is executed by the processor also includes: for each two initial driving routes, obtaining a common route between the two initial driving routes; based on the mileage of the common route, obtaining a similarity index value between the two initial driving routes; and when the similarity index value is greater than a preset value, determining the two initial driving routes as similar routes.
[0108] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps: obtaining vehicle networking data of a vehicle within a preset time period, the vehicle networking data including an ignition time point, an ignition off time point, a starting position, an end position, fuel consumption, an average driving speed, a driving duration and a driving mileage of the vehicle in each initial driving route; determining a target parking point position based on the ignition time point, the starting position and the end position; obtaining an initial driving route with the target parking point position as the starting position or the end position, and determining the initial driving route as an intermediate driving route; determining a target driving route based on the vehicle networking data, the target parking point position and the intermediate driving route.
[0109] In one embodiment, the computer program implemented when executed by the processor determines the target parking point position based on the ignition time point, the starting position and the end position, including: sorting the initial driving routes based on the order of the ignition time points from front to back; determining the starting position of the first initial driving route and the end positions of all initial driving routes in the sorting results as the initial parking point positions, and determining the repeated initial parking point positions as the target parking point positions.
[0110] In one embodiment, the computer program implemented when executed by the processor determines the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route, including: for each target parking point location, when there are multiple sections of the intermediate driving route corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving route, or the sum of the Internet of Vehicles data corresponding to the intermediate driving route is determined as the target Internet of Vehicles data; based on the target Internet of Vehicles data, the target driving route is determined.
[0111] In one embodiment, the computer program implemented when executed by the processor determines the target driving route based on the target Internet of Vehicles data, including: determining the target Internet of Vehicles data as the Internet of Vehicles data corresponding to the target driving route.
[0112] In one embodiment, the method implemented when the computer program is executed by the processor further includes: when there is only one section of the intermediate driving route corresponding to the target parking point position, determining the intermediate driving route as the target driving route.
[0113] In one embodiment, the method implemented when the computer program is executed by the processor also includes: for each two initial driving routes, obtaining a common route between the two initial driving routes; based on the mileage of the common route, obtaining a similarity index value between the two initial driving routes; and when the similarity index value is greater than a preset value, determining the two initial driving routes as similar routes.
[0114] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0115] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.
[0116] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0117] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for determining a driving route, characterized in that: The method comprises: Acquire vehicle networking data of the vehicle within a preset time period, the vehicle networking data including the ignition time point, ignition off time point, starting position, end position, fuel consumption, average driving speed, driving time and driving mileage of the vehicle within each initial driving route; Determining a target parking point position based on the ignition time point, the starting position and the end position; Acquire an initial driving route with the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route; A target driving route is determined based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
2. The method according to claim 1, characterized in that The determining of the target parking point position based on the ignition time point, the starting position and the end position includes: sorting the initial driving routes based on the order of the ignition time points from front to back; The starting point position of the first initial driving route and the end point positions of all initial driving routes in the sorting result are determined as the initial parking point positions, and the repeated initial parking point positions are determined as the target parking point positions.
3. The method according to claim 1, characterized in that The determining of the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route includes: For each target parking point location, when there are multiple intermediate driving routes corresponding to the target parking point location, for each item of Internet of Vehicles data, the median of the Internet of Vehicles data corresponding to the intermediate driving routes or the sum of the Internet of Vehicles data corresponding to the intermediate driving routes is determined as the target Internet of Vehicles data; Based on the target Internet of Vehicles data, a target driving route is determined.
4. The method according to claim 3, characterized in that The determining of a target driving route based on the target Internet of Vehicles data includes: The target Internet of Vehicles data is determined as the Internet of Vehicles data corresponding to the target driving route.
5. The method according to claim 3, characterized in that: The method further comprises: When there is only one section of the intermediate driving route corresponding to the target parking point position, the intermediate driving route is determined as the target driving route.
6. The method according to claim 1, characterized in that The method further comprises: For each two initial driving routes, obtaining a common route between the two initial driving routes; Based on the mileage of the common route, obtaining similarity index values of the two initial driving routes; When the similarity index value is greater than a preset value, the two initial driving routes are determined to be similar routes.
7. A driving route determination device, characterized in that: The device comprises: A first acquisition module is used to acquire vehicle networking data of the vehicle within a preset time period, wherein the vehicle networking data includes the ignition time point, the ignition time point, the starting position, the end position, the fuel consumption, the average driving speed, the driving time and the driving mileage of the vehicle within each initial driving route; A first determination module, configured to determine a target parking point position based on the ignition time point, the starting position and the end position; A second acquisition module is used to acquire an initial driving route with the target parking point as a starting point or an end point, and determine the initial driving route as an intermediate driving route; The second determination module is used to determine the target driving route based on the Internet of Vehicles data, the target parking point location and the intermediate driving route.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.