Vehicle detour identification method and system

Abstract

The invention provides a vehicle detour identification method and system. The method comprises the following steps: acquiring driving related data generated in the driving process of a vehicle; performing data preprocessing on the driving related data to obtain target driving data; analyzing the target driving data in sequence by using a plurality of preset recognition strategies, and judging whether the target driving data meets specific conditions corresponding to the preset recognition strategies or not; if the target driving data meets all specific conditions corresponding to any preset identification strategy, it is considered that the vehicle does not detour in the driving process; and if the target driving data does not meet all specific conditions corresponding to any preset identification strategy, considering that the vehicle detour in the driving process. According to the invention, based on a multi-dimension elimination strategy, multiple possible abnormal behaviors are systematically checked, possible detour behaviors of a driver in a driving process are effectively identified, and powerful support is provided for improving passenger experience and platform credibility.

Description

Technical Field

[0001] The present invention relates to the technical field of online car-hailing operation management, and in particular to a method and system for identifying vehicle detours. Background Art

[0002] With the popularity of ride-sharing and taxi services, drivers' detours have become a growing concern. This behavior not only affects passengers' travel experience, but may also lead to unnecessary costs. Existing technologies usually rely on GPS data and trip monitoring to determine the driver's route, but they have the following defects and shortcomings:

[0003] (1) Insufficient accuracy: Existing methods often rely on simple route comparison and fail to fully consider traffic conditions, road changes, and other dynamic factors;

[0004] (2) Lack of real-time performance: Some systems fail to achieve real-time monitoring and are unable to identify detours in a timely manner, resulting in passengers not discovering the problem until after the trip is over.

[0005] (3) Lack of intelligent analysis: Traditional methods rarely use big data and machine learning technologies, making it difficult to effectively identify and predict detour behavior;

[0006] (4) Poor user experience: Existing monitoring methods often make drivers feel distrustful, which affects their work enthusiasm. Summary of the invention

[0007] To this end, the present invention provides a method and system for identifying vehicle detours, aiming to solve the technical problem in the prior art that accurate identification of driver detour behaviors cannot be achieved.

[0008] To achieve the above objectives, the present invention adopts the following technical solutions:

[0009] According to a first aspect of the present invention, the present invention provides a method for identifying a vehicle detour, the method comprising:

[0010] Acquire driving-related data generated by the vehicle during driving; the driving-related data includes at least one of real-time location information, order information, and passenger feedback information;

[0011] Performing data preprocessing on the driving related data to obtain target driving data;

[0012] Analyzing the target driving data in sequence using a plurality of preset recognition strategies respectively, and determining whether the target driving data meets specific conditions corresponding to each of the preset recognition strategies;

[0013] If the target driving data satisfies all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle did not take a detour during driving;

[0014] If the target driving data does not satisfy all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle has taken a detour during driving.

[0015] According to a second aspect of the present invention, the present invention provides a vehicle detour identification system, the system comprising:

[0016] A data acquisition module, used to acquire driving-related data generated by the vehicle during driving; the driving-related data includes at least one of real-time location information, order information, and passenger feedback information;

[0017] A data processing module, used for performing data preprocessing on the driving related data to obtain target driving data;

[0018] A data analysis module, used to analyze the target driving data in sequence using a plurality of preset recognition strategies respectively, and determine whether the target driving data meets the specific conditions corresponding to each of the preset recognition strategies;

[0019] The detour determination module is used to determine that the vehicle has not taken a detour during driving when the target driving data meets all the specific conditions corresponding to any of the preset recognition strategies; when the target driving data does not meet all the specific conditions corresponding to any of the preset recognition strategies, it is determined that the vehicle has taken a detour during driving.

[0020] The present invention adopts the above technical solution and has at least the following beneficial effects:

[0021] Through the scheme of the present invention, the driving-related data generated by the vehicle during driving is obtained; the driving-related data is preprocessed to obtain target driving data; the target driving data is analyzed in turn using multiple preset identification strategies respectively to determine whether the target driving data meets the specific conditions corresponding to each preset identification strategy; if the target driving data meets all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle did not take a detour during driving; if the target driving data does not meet all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle took a detour during driving. Thus, based on multiple dimensional exclusion strategies, multiple possible abnormal behaviors are systematically checked, and possible detour behaviors of drivers during driving are effectively identified, providing strong support for improving passenger experience and platform trust.

[0022] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A schematic diagram showing a flow chart of a method for identifying a vehicle detour provided by an embodiment of the present invention;

[0025] Figure 2 A schematic diagram showing the structure of a vehicle detour identification system provided by an embodiment of the present invention;

[0026] Figure 3 A schematic diagram of the physical structure of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0027] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0028] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0029] The embodiment of the present invention provides a method for identifying a vehicle detour, such as Figure 1 As shown, at least the following steps S101 to S104 may be included:

[0030] Step S101, obtaining driving related data generated by the vehicle during driving.

[0031] The travel-related data in the embodiment of the present invention may include real-time location information, order information, and passenger feedback information.

[0032] The real-time location information can be obtained through a real-time positioning system, such as real-time GPS data. The order information is various types of relevant data generated during the passenger order process, which is used for subsequent feature data extraction. In addition, the embodiment of the present invention also introduces a passenger feedback mechanism, that is, allowing passengers to evaluate the itinerary and obtain passenger feedback information, providing additional data support for detour identification.

[0033] Step S102: preprocess the driving related data to obtain target driving data.

[0034] Before performing detour identification based on driving-related data, the embodiment of the present invention can also perform data preprocessing on the driving-related data to ensure data integrity and accuracy, laying a foundation for subsequent analysis. Data preprocessing can include cleaning, deduplication, missing value processing, outlier processing, etc.

[0035] In addition, preliminary analysis can be performed on driving-related data to obtain target driving data that can be directly used for detour identification. Target driving data may include real-time location information, order status, actual mileage amount, estimated mileage amount, driver settlement information, destination modification information, rerouting information, actual mileage, estimated mileage, actual highway fees, estimated highway fees, parking fees, trajectory similarity between actual driving route and navigation planning route, number of driving deviations, first deviation position, etc.

[0036] Step S103 , analyzing the target driving data in sequence using a plurality of preset recognition strategies respectively, and determining whether the target driving data satisfies a specific condition corresponding to each preset recognition strategy.

[0037] The embodiment of the present invention constructs seven preset identification strategies, namely the first preset identification strategy to the seventh preset identification strategy, to identify 15 special situations that do not meet the detour behavior characteristics. Each preset identification strategy contains multiple specific conditions. When the target driving data corresponding to an order meets all the specific conditions contained in a preset identification strategy, it is considered that the order meets a special situation of the driver not taking a detour corresponding to the preset identification strategy.

[0038] Step S104, if the target driving data meets all the specific conditions corresponding to any preset recognition strategy, it is considered that the vehicle has not taken a detour during driving; if the target driving data does not meet all the specific conditions corresponding to any preset recognition strategy, it is considered that the vehicle has taken a detour during driving.

[0039] After the order status is completed, the situations that do not meet the detour behavior characteristics are eliminated in turn, and a comprehensive analysis of the driver's behavior is achieved through the combination of logical conditions. If the target driving data corresponding to an order does not meet all the specific conditions contained in any preset identification strategy, it means that the order has behaviors that meet the detour characteristics. The embodiment of the present invention can generate a corresponding alarm and record relevant information for subsequent review.

[0040] The following is an explanation of the multiple preset identification strategies including 15 special cases proposed in the embodiment of the present invention:

[0041] First preset identification strategy: The first preset identification strategy is used to identify the low-price difference and low-probability detour behavior that may exist when the vehicle completes the order. The corresponding first specific conditions include:

[0042] ①The order status is completed;

[0043] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0044] ③ The difference between the actual mileage amount and the estimated mileage amount is less than or equal to the first preset difference amount; preferably, the first preset difference amount is 1 yuan;

[0045] ④ The mileage ratio of the actual mileage to the estimated mileage is greater than the first preset mileage ratio; preferably, the first preset mileage ratio is 20%;

[0046] ⑤ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0047] ⑥ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan.

[0048] When the target driving data meets all of the first specific conditions above, it is considered that the corresponding vehicle order meets the requirements of low-price-difference and low-probability detour behavior, that is, the driver does not take any detour behavior.

[0049] Second preset identification strategy: The second preset identification strategy is used to identify the high trajectory similarity prediction deviation detour behavior or low trajectory similarity prediction deviation detour behavior that the vehicle may have when completing an order, and the corresponding second specific conditions include:

[0050] ①The order status is completed;

[0051] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0052] ③ The destination modification information indicates that the passenger has not modified the destination;

[0053] ④ The rerouting information indicates that the passenger did not reroute;

[0054] ⑤ The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the second preset difference amount; preferably, the first preset difference amount is 1 yuan and the second preset difference amount is 20 yuan;

[0055] ⑥ The mileage difference between the actual mileage and the estimated mileage is less than the first preset difference mileage; preferably, the first preset difference mileage is 2000 meters; wherein the actual mileage may be the actual billable mileage of the vehicle; the estimated mileage is the mileage based on the navigation recommendation;

[0056] ⑦ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0057] ⑧ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0058] ⑨ After the driver reaches the order destination, he ends the order within the first preset distance, and the vehicle stays within the second preset distance; preferably, the first preset distance is 200 meters and the second preset distance is 500 meters;

[0059] ⑩ The length of time the vehicle stays within the first preset distance of the order destination is less than the first preset length of time; preferably, the first preset length of time of time is 5 minutes;

[0060] The number of times the driver actively deviates from the course is 0;

[0061] The trajectory similarity is greater than or equal to a first preset trajectory similarity; or, the trajectory similarity is less than the first preset trajectory similarity; preferably, the first preset trajectory similarity is 80%.

[0062] It can be understood that the trajectory similarity is the similarity between the actual driving route and the navigation planning route. When the order loads all the above second specific conditions and the trajectory similarity is greater than or equal to the first preset trajectory similarity, it means that the order has a high trajectory similarity estimated deviation detour behavior; when the order loads all the above second specific conditions and the trajectory similarity is less than the first preset trajectory similarity, it means that the order has a low trajectory similarity estimated deviation detour behavior, that is, the driver does not take a detour.

[0063] The third preset identification strategy: The third preset identification strategy is used to identify the normal deviation behavior of the vehicle at the starting point or the normal deviation behavior at the end point when completing the order. The corresponding third specific conditions include:

[0064] ①The order status is completed;

[0065] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0066] ③ The destination modification information indicates that the passenger has not modified the destination;

[0067] ④ The rerouting information indicates that the passenger did not reroute;

[0068] ⑤ The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; preferably, the first preset difference amount is 1 yuan and the third preset difference amount is 10 yuan;

[0069] ⑥ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0070] ⑦ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0071] ⑧ After the driver reaches the order destination, he ends the order within the first preset distance, and the vehicle stays within the second preset distance; preferably, the first preset distance is 200 meters and the second preset distance is 500 meters;

[0072] ⑨ The driver's stay time within the first preset distance of the order destination is less than the first preset stay time; preferably, the first preset stay time is 5 minutes;

[0073] ⑩The number of times the driver actively deviates from the course is 1;

[0074] The actual driving distance from the first deviation position to the order starting point is less than the first preset deviation distance; or, the actual driving distance from the first deviation position to the order end point is less than the second preset deviation distance; preferably, the first preset deviation distance is 100 meters and the second preset deviation distance is 300 meters.

[0075] It can be understood that when the order load meets all the above third specific conditions, and the actual driving distance of the first deviation position from the starting point of the order is less than the first preset deviation distance, it means that the order has normal deviation behavior from the starting point; when the order load meets all the above third specific conditions, and the actual driving distance of the first deviation position from the end point of the order is less than the second preset deviation distance, it means that the order has normal deviation behavior from the end point, that is, the driver did not take a detour.

[0076] Fourth preset identification strategy: The fourth preset identification strategy is used to identify the vehicle's non-deviation behavior, normal deviation behavior at the starting point, or normal deviation behavior at the end point after the order changes the destination. The corresponding fourth specific conditions include:

[0077] ①The order status is completed;

[0078] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0079] ③ The destination modification information means that the passenger has modified the destination but has not modified the waypoints;

[0080] ④ The rerouting information indicates that the passenger did not reroute;

[0081] ⑤ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0082] ⑥ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0083] ⑦ After the driver reaches the modified order destination, he / she ends the order within a second preset distance; preferably, the second preset distance is 500 meters;

[0084] ⑧ The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; preferably, the first preset distance is 200 meters; the first preset stay time is 5 minutes;

[0085] ⑨The passenger does not have a waypoint when placing an order;

[0086] ⑩ The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the second preset difference amount; and the number of times the driver actively deviates from the course is 0;

[0087] or,

[0088] The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; and the number of times the driver actively deviates from the route is 1; and the straight-line distance between the first deviation position and the order starting point is less than the first preset deviation distance;

[0089] or,

[0090] The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; and the number of active driving deviations by the driver is 1; and the straight-line distance between the first deviation position and the order endpoint is less than the second preset deviation distance.

[0091] Preferably, the first preset difference amount is 1 yuan, the second preset difference amount is 20 yuan, the third preset difference amount is 10 yuan, the first preset yaw distance is 100 meters, and the second preset yaw distance is 300 meters.

[0092] It can be understood that, for the fourth specific condition above, when the number of active deviations by the driver is 0, it means that the order has no vehicle deviation after the order destination is modified; when the number of active deviations by the driver is 1, the straight-line distance from the first deviation position to the order start point is less than the first preset deviation distance, indicating that the order has normal vehicle deviation at the start point after the order destination is modified; when the number of active deviations by the driver is 1, the straight-line distance from the first deviation position to the order end point is less than the second preset deviation distance, indicating that the order has normal vehicle deviation at the end point after the order destination is modified. In the above cases, the driver did not take a detour.

[0093] The fifth preset identification strategy: The fifth preset identification strategy is used to identify the situation where the order containing the waypoints when placing an order has a high similarity or a low similarity with the navigation recommendation, and the corresponding fifth specific conditions include:

[0094] ①The order status is completed;

[0095] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0096] ③ The destination modification information means that the passenger has modified the destination but has not modified the waypoints;

[0097] ④ The rerouting information indicates that the passenger did not reroute;

[0098] ⑤ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0099] ⑥ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0100] ⑦ The passenger includes the waypoints when placing the order;

[0101] ⑧The number of times the driver actively deviates is 0;

[0102] ⑨ After the driver reaches the order destination, he ends the order within the first preset distance, and the vehicle stays within the second preset distance; preferably, the first preset distance is 200 meters; the second preset distance is 500 meters;

[0103] ⑩ The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; preferably, the first preset stay time is 5 minutes;

[0104] The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; preferably, the first preset difference amount is 1 yuan and the third preset difference amount is 10 yuan;

[0105] The mileage difference between the actual mileage and the estimated mileage is less than a first preset mileage difference; preferably, the first preset mileage difference is 2000 meters;

[0106] The trajectory similarity is greater than or equal to a first preset trajectory similarity; or, the trajectory similarity is less than the first preset trajectory similarity; preferably, the first preset trajectory similarity is 80%.

[0107] It can be understood that when an order meets all of the above fifth specific conditions and the trajectory similarity is greater than or equal to the first preset trajectory similarity, it means that the order contains waypoints when placing the order and has a high similarity with the navigation recommendation; when an order meets all of the above fifth specific conditions and the trajectory similarity is less than the first preset trajectory similarity, it means that the order contains waypoints when placing the order and has a low similarity with the navigation recommendation, that is, the driver did not take a detour.

[0108] Sixth preset identification strategy: The sixth preset identification strategy is used to identify the possible non-deviation behavior, normal deviation behavior at the starting point, or normal deviation behavior at the end point for orders containing waypoints when placing orders. The corresponding sixth specific conditions include:

[0109] ①The order status is completed;

[0110] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0111] ③ The destination modification information means that the passenger has modified the destination but has not modified the waypoints;

[0112] ④ The rerouting information indicates that the passenger did not reroute;

[0113] ⑤ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0114] ⑥ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0115] ⑦ The passenger includes the waypoints when placing the order;

[0116] ⑧ After the driver reaches the order destination, the order is completed within the first preset distance, and the vehicle stays within the second preset distance; preferably, the first preset distance is 200 meters and the second preset distance is 500 meters;

[0117] ⑨ The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; preferably, the first preset stay time is 5 minutes;

[0118] ⑩ The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; preferably, the first preset difference amount is 1 yuan and the third preset difference amount is 10 yuan;

[0119] The number of times the driver actively deviates from the course is 0;

[0120] or,

[0121] The number of times the driver actively deviates is 1; and the straight-line distance between the first deviation position and the order starting point is less than a first preset deviation distance; preferably, the first preset deviation distance is 100 meters;

[0122] or,

[0123] The number of times the driver actively deviates is 1; and the straight-line distance between the first deviation position and the order end point is less than the second preset deviation distance; preferably, the second preset deviation distance is 300 meters.

[0124] It can be understood that, for the sixth specific condition, when the number of active deviations by the driver is 0, it means that the order contains a waypoint when the order is placed and no deviation occurs after the destination is modified; when the number of active deviations by the driver is 1, the straight-line distance from the first deviation position to the order starting point is less than the first preset deviation distance, indicating that the order contains a waypoint when the order is placed and the order deviates normally at the starting point after the destination is modified; when the number of active deviations by the driver is 1, the straight-line distance from the first deviation position to the order end point is less than the second preset deviation distance, indicating that the order contains a waypoint when the order is placed and the order deviates normally at the end point after the destination is modified. In the above cases, the driver did not take a detour.

[0125] The seventh preset identification strategy: The seventh preset identification strategy is used to identify normal deviation behavior of the terminal position that may exist after the destination is modified in an order containing a waypoint. The corresponding seventh specific condition includes:

[0126] ①The order status is completed;

[0127] ② The driver settlement information shows that the driver did not settle according to the suggested settlement price;

[0128] ③ The destination modification information means that the passenger has modified the destination and the waypoints;

[0129] ④ The rerouting information indicates that the passenger did not reroute;

[0130] ⑤ The difference between the actual expressway fee and the estimated expressway fee is less than the first preset difference fee; preferably, the first preset difference fee is 2 yuan;

[0131] ⑥ The parking fee is less than the first preset parking fee; preferably, the first preset parking fee is 2 yuan;

[0132] ⑦ The passenger includes the waypoints when placing the order;

[0133] ⑧ After the driver reaches the order destination, the order is completed within the first preset distance, and the vehicle stays within the second preset distance; preferably, the first preset distance is 200 meters and the second preset distance is 500 meters;

[0134] ⑨ The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; preferably, the first preset stay time is 5 minutes;

[0135] ⑩ The difference between the actual mileage amount and the estimated mileage amount is greater than the first preset difference amount and less than or equal to the third preset difference amount; preferably, the first preset difference amount is 1 yuan and the third preset difference amount is 10 yuan;

[0136] The number of times the driver actively deviates from the course is 1;

[0137] The straight-line distance between the first yaw position and the order end point is less than the first preset yaw distance; or, the straight-line distance between the first yaw position and the order end point is less than the second preset yaw distance; preferably, the first preset yaw distance is 100 meters and the second preset yaw distance is 300 meters.

[0138] It can be understood that when the order load meets all of the above seventh specific conditions, and the straight-line distance between the first deviation position and the order terminal is less than the first preset deviation distance, it means that the destination of the order has been modified after the vehicle arrived at the terminal normally; when the order load meets all of the above seventh specific conditions, and the actual driving distance between the first deviation position and the order terminal is less than the second preset deviation distance, it means that the other terminal positions in the order containing the waypoints after the destination is modified have normal deviation behavior, that is, the driver did not take a detour.

[0139] After the order status is completed, the embodiment of the present invention excludes the situations that do not meet the detour behavior characteristics in turn based on the 15 special situations included in the seven preset identification strategies stated above, and considers that the orders that do not meet all the specific conditions included in any preset identification strategy have behaviors that meet the detour characteristics, generates corresponding alarms, and records relevant information. Through the above steps, the embodiment of the present invention effectively identifies the possible detour behaviors of drivers during driving, and provides strong support for improving passenger experience and platform trust. In addition, the embodiment of the present invention can also regularly update and adjust the identification strategy based on passenger feedback information, and combine big data analysis and machine learning technology to improve self-learning ability and adaptability.

[0140] The embodiment of the present invention provides a method for identifying a vehicle detour, which obtains driving-related data generated by the vehicle during driving; performs data preprocessing on the driving-related data to obtain target driving data; respectively uses multiple preset recognition strategies to analyze the target driving data in turn to determine whether the target driving data meets the specific conditions corresponding to each preset recognition strategy; if the target driving data meets all the specific conditions corresponding to any preset recognition strategy, it is considered that the vehicle did not take a detour during driving; if the target driving data does not meet all the specific conditions corresponding to any preset recognition strategy, it is considered that the vehicle took a detour during driving. The method includes at least the following advantages:

[0141] (1) Improved recognition accuracy: By integrating multiple data sources and intelligent algorithms, the recognition accuracy of detour behavior is significantly improved;

[0142] (2) Real-time monitoring: The system can monitor the driver’s route in real time, identify and respond to detours in a timely manner, and improve the passenger experience;

[0143] (3) Intelligent analysis: Using machine learning technology, the intelligent analysis capability of driver driving behavior is enhanced, reducing the misjudgment rate;

[0144] (4) Enhance driver trust: Through transparent monitoring methods, reduce driver anxiety and distrust and promote good driver-passenger relations.

[0145] Further, as Figure 1 In a specific implementation, an embodiment of the present invention provides a vehicle detour identification system, such as Figure 2 As shown, the system may include: a data acquisition module 210 , a data processing module 220 , a data analysis module 230 and a detour determination module 240 .

[0146] The data acquisition module 210 may be used to acquire driving-related data generated by the vehicle during driving; the driving-related data includes at least one of real-time location information, order information, and passenger feedback information;

[0147] The data processing module 220 may be used to perform data preprocessing on the driving related data to obtain target driving data;

[0148] The data analysis module 230 may be used to analyze the target driving data in sequence using a plurality of preset recognition strategies respectively, and determine whether the target driving data satisfies the specific conditions corresponding to each preset recognition strategy;

[0149] The detour determination module 240 can be used to determine that the vehicle has not taken a detour during driving when the target driving data meets all the specific conditions corresponding to any preset recognition strategy; when the target driving data does not meet all the specific conditions corresponding to any preset recognition strategy, it is determined that the vehicle has taken a detour during driving.

[0150] It should be noted that for other corresponding descriptions of the functional modules involved in the vehicle detour identification system provided in the embodiment of the present invention, reference can be made to Figure 1 The corresponding description of the method shown will not be repeated here.

[0151] Based on the above Figure 1 The method shown, accordingly, an embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the vehicle detour identification method of any of the above embodiments are implemented.

[0152] Based on the above Figure 1 The method shown and Figure 2 The embodiment of the system shown in the figure, the embodiment of the present invention also provides a physical structure diagram of a computer device, such as Figure 3 As shown, the computer device may include a communication bus, a processor, a memory and a communication interface, and may also include an input / output interface and a display device, wherein each functional unit may communicate with each other through the bus. The memory stores a computer program, and the processor is used to execute the program stored in the memory and execute the steps of the vehicle detour identification method of the above embodiment.

[0153] Those skilled in the art can clearly understand that the specific working processes of the systems, devices, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and for the sake of brevity, they are not further described here.

[0154] In addition, the functional units in various embodiments of the present invention may be physically independent of each other, or two or more functional units may be integrated together, or all functional units may be integrated into one processing unit. The above integrated functional units may be implemented in the form of hardware, or in the form of software or firmware.

[0155] Those skilled in the art can understand that if the integrated functional unit is implemented in the form of software and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can essentially or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, which includes a number of instructions to enable a computing device (such as a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention when running the instructions. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes.

[0156] Alternatively, all or part of the steps of implementing the aforementioned method embodiments may be accomplished by hardware associated with program instructions (such as a computing device such as a personal computer, a server, or a network device), and the program instructions may be stored in a computer-readable storage medium. When the program instructions are executed by a processor of a computing device, the computing device executes all or part of the steps of the methods described in the embodiments of the present invention.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that within the spirit and principles of the present invention, the technical solutions described in the aforementioned embodiments can still be modified, or some or all of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate from the protection scope of the present invention.

Claims

1. A method for identifying a vehicle detour, characterized in that: The method comprises: Acquire driving-related data generated by the vehicle during driving; the driving-related data includes at least one of real-time location information, order information, and passenger feedback information; Performing data preprocessing on the driving related data to obtain target driving data; Analyzing the target driving data in sequence using a plurality of preset recognition strategies respectively, and determining whether the target driving data meets specific conditions corresponding to each of the preset recognition strategies; If the target driving data satisfies all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle did not take a detour during driving; If the target driving data does not satisfy all the specific conditions corresponding to any of the preset identification strategies, it is considered that the vehicle has taken a detour during driving.

2. The method according to claim 1, characterized in that The target driving data includes at least one of real-time location information, order status, actual mileage amount, estimated mileage amount, driver settlement information, destination modification information, rerouting information, actual mileage, estimated mileage, actual highway fees, estimated highway fees, parking fees, trajectory similarity between the actual driving route and the navigation planned route, number of driving deviations, and first deviation position.

3. The method according to claim 2, characterized in that The plurality of preset identification strategies include a first preset identification strategy, wherein the first preset identification strategy is used to identify a low-price-difference, low-probability detour behavior that may exist when the vehicle completes an order; The first specific condition corresponding to the first preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The difference between the actual mileage amount and the estimated mileage amount is less than or equal to a first preset difference amount; The mileage ratio of the actual mileage to the estimated mileage is greater than a first preset mileage ratio; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee.

4. The method according to claim 2, characterized in that: The plurality of preset identification strategies include a second preset identification strategy, the second preset identification strategy being used to identify a high trajectory similarity estimated deviation detour behavior or a low trajectory similarity estimated deviation detour behavior that may exist when the vehicle completes an order; The second specific condition corresponding to the second preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information indicates that the passenger has not modified the destination; The rerouting information is that the passenger did not reroute; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a second preset difference amount; The mileage difference between the actual mileage and the estimated mileage is less than a first preset mileage difference; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; After the driver reaches the order destination, the driver completes the order within a first preset distance, and the vehicle stays within a second preset distance; The length of time that the vehicle stays within the first preset distance from the order destination is less than a first preset length of time; The number of times the driver actively deviates from the course is 0; The trajectory similarity is greater than or equal to a first preset trajectory similarity; or, the trajectory similarity is less than the first preset trajectory similarity.

5. The method according to claim 2, characterized in that: The plurality of preset identification strategies include a third preset identification strategy, and the third preset identification strategy is used to identify normal deviation behavior of the vehicle at the starting position or normal deviation behavior at the end position that may exist when the vehicle completes an order; The third specific condition corresponding to the third preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information indicates that the passenger has not modified the destination; The rerouting information is that the passenger did not reroute; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; After the driver reaches the order destination, the driver completes the order within a first preset distance, and the vehicle stays within a second preset distance; The driver's stay time within the first preset distance from the order destination is less than a first preset stay time; The number of times the driver actively deviates from the course is 1; The actual driving distance between the first deviation position and the order starting point is less than the first preset deviation distance; or the actual driving distance between the first deviation position and the order end point is less than the second preset deviation distance.

6. The method according to claim 2, characterized in that The plurality of preset identification strategies include a fourth preset identification strategy, and the fourth preset identification strategy is used to identify the vehicle's possible non-deviation behavior, normal deviation behavior at the starting position, or normal deviation behavior at the end position after the order modifies the destination; The fourth specific condition corresponding to the fourth preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information means that the passenger has modified the destination but has not modified the waypoints; The rerouting information is that the passenger did not reroute; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; The driver completes the order within a second preset distance after reaching the modified order destination; The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; The passenger did not have a waypoint when placing the order; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a second preset difference amount; and the number of times the driver actively deviates from the course is 0; or, The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; and the number of active deviations by the driver is 1; and the straight-line distance between the first deviation position and the order starting point is less than a first preset deviation distance; or, The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; and the number of active driving deviations by the driver is 1; and the straight-line distance between the first deviation position and the order endpoint is less than a second preset deviation distance.

7. The method according to claim 2, characterized in that The plurality of preset identification strategies include a fifth preset identification strategy, and the fifth preset identification strategy is used to identify a situation where an order containing waypoints when placing an order has a high similarity or a low similarity with the navigation recommendation; The fifth specific condition corresponding to the fifth preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information means that the passenger has modified the destination but has not modified the waypoints; The rerouting information is that the passenger did not reroute; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; The passenger includes waypoints when placing an order; The number of times the driver actively deviates from the course is 0; After the driver reaches the order destination, the driver completes the order within a first preset distance, and the vehicle stays within a second preset distance; The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; The mileage difference between the actual mileage and the estimated mileage is less than a first preset mileage difference; The trajectory similarity is greater than or equal to a first preset trajectory similarity; or, the trajectory similarity is less than the first preset trajectory similarity.

8. The method according to claim 2, characterized in that: The plurality of preset identification strategies include a sixth preset identification strategy, and the sixth preset identification strategy is used to identify possible non-deviation behavior, normal deviation behavior at the starting position, or normal deviation behavior at the end position for an order containing a waypoint when placing an order; The sixth specific condition corresponding to the sixth preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information means that the passenger has modified the destination but has not modified the waypoints; The rerouting information is that the passenger did not reroute; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; The passenger includes waypoints when placing an order; After the driver reaches the order destination, the driver completes the order within a first preset distance, and the vehicle stays within a second preset distance; The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; The number of times the driver actively deviates from the course is 0; or, The number of times the driver actively deviates is 1; and the straight-line distance between the first deviation position and the order starting point is less than a first preset deviation distance; or, The number of times the driver actively deviates from the course is 1; and the straight-line distance between the first deviation position and the end point of the order is less than a second preset deviation distance.

9. The method according to claim 1, characterized in that: The plurality of preset identification strategies include a seventh preset identification strategy, and the seventh preset identification strategy is used to identify normal deviation behavior of the terminal position that may exist after the destination is modified in an order containing a waypoint; The seventh specific condition corresponding to the seventh preset identification strategy includes: The order status is completed; The driver settlement information is that the driver did not settle according to the suggested settlement price; The destination modification information indicates that the passenger has modified the destination and the waypoints; The rerouting information is that the passenger did not reroute; The difference between the actual expressway fee and the estimated expressway fee is less than a first preset difference fee; The parking fee is less than a first preset parking fee; The passenger includes waypoints when placing an order; After the driver reaches the order destination, the driver completes the order within a first preset distance, and the vehicle stays within a second preset distance; The driver's stay time within the first preset distance of the modified order destination is less than the first preset stay time; The difference between the actual mileage amount and the estimated mileage amount is greater than a first preset difference amount and less than or equal to a third preset difference amount; The number of times the driver actively deviates from the course is 1; The straight-line distance between the first deviation position and the order end point is less than the first preset deviation distance; or the straight-line distance between the first deviation position and the order end point is less than the second preset deviation distance.

10. A vehicle detour identification system, characterized in that: The system comprises: A data acquisition module, used to acquire driving-related data generated by the vehicle during driving; the driving-related data includes at least one of real-time location information, order information, and passenger feedback information; A data processing module, used for performing data preprocessing on the driving related data to obtain target driving data; A data analysis module, used to analyze the target driving data in sequence using a plurality of preset recognition strategies respectively, and determine whether the target driving data meets the specific conditions corresponding to each of the preset recognition strategies; The detour determination module is used to determine that the vehicle has not taken a detour during driving when the target driving data meets all the specific conditions corresponding to any of the preset recognition strategies; when the target driving data does not meet all the specific conditions corresponding to any of the preset recognition strategies, it is determined that the vehicle has taken a detour during driving.

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