Abnormal travel correction method, system and electronic device

Abstract

The application relates to the Internet of Vehicles technical field, in particular to an abnormal trip correction method and system and electronic equipment, the method comprises the following steps: obtaining a trip data set, the trip data set comprises trip data uploaded by at least one vehicle, the trip state in the trip data is in progress, and the trip data comprises a trip duration; if the trip duration is greater than a preset duration threshold, the trip data corresponding to the current trip duration is marked as abnormal trip data; based on a preset trip end determination rule, the abnormal trip data is subjected to trip end verification, and the trip end determination rule is determined based on historical driving data of a target user corresponding to the abnormal trip data; if it is determined that the trip corresponding to the abnormal trip data is an ended trip, the trip corresponding to the current abnormal trip data is ended, so that the abnormal trip correction is completed; the method can accurately complete abnormal trip identification and correction, has high flexibility and low cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, and in particular to an abnormal trip correction method and system and an electronic device. BACKGROUND

[0002] With the rapid development of Internet of Vehicles technology, communication between vehicles and the cloud has become an important part of the intelligent transportation system. In the Internet of Vehicles environment, vehicles can not only upload trip data to the cloud in real time for analysis and management, but also upload trip end signals to mark the formal end of the trip at the end of the trip. This process is usually automated, which can ensure that the trip information of the vehicle is updated in time in the cloud, and provide accurate information support for subsequent scheduling, data analysis, and billing services.

[0003] However, in actual application, there may be a situation where the vehicle fails to upload the trip end signal within the scheduled time. This problem may be caused by various reasons, such as network failure, communication interruption between the vehicle and the cloud, and vehicle-mounted device failure. When the vehicle fails to upload the trip end signal in time at the end of the trip, the cloud cannot correctly identify the end time of the trip, which may cause a series of problems. For example, multiple trips may occur concurrently due to the failure of the previous trip to end. SUMMARY

[0004] The present application provides an abnormal trip correction method, system and electronic device to solve the technical problem that when the vehicle fails to upload the trip end signal in time at the end of the trip, the trip in the cloud may not end normally, which may cause unnecessary impact on subsequent trip display, scheduling, and data analysis.

[0005] The abnormal trip correction method provided by the present application comprises: obtaining a trip data set, the trip data set comprising trip data uploaded by at least one vehicle, the trip state in the trip data being in progress, and the trip data comprising a trip duration;

[0006] If the trip duration is greater than a preset duration threshold, the trip data corresponding to the current trip duration is marked as abnormal trip data;

[0007] Based on a preset trip end determination rule, the abnormal trip data is subjected to trip end verification, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data;

[0008] If it is determined that the trip corresponding to the abnormal trip data is an ended trip, the trip corresponding to the current abnormal trip data is ended, thereby completing the abnormal trip correction.

[0009] In an embodiment of the present application, before the abnormal travel data is checked based on the preset travel end determination rule, the method further comprises:

[0010] The plurality of abnormal travel data is determined as an abnormal travel data set;

[0011] The abnormal travel data in the abnormal travel data set is updated based on real-time travel data uploaded by a target vehicle, the target vehicle being a vehicle corresponding to the abnormal travel data;

[0012] The updated abnormal travel data is checked for a travel end signal, and if no travel end signal is checked, the abnormal travel data is checked for a travel end based on the travel end determination rule.

[0013] In an embodiment of the present application, the abnormal travel data is checked based on the preset travel end determination rule, comprising:

[0014] The target vehicle corresponding to the abnormal travel data is detected for travel and state, and if the target vehicle has two or more travels, or the state of the target vehicle is a charging state, it is determined that the travel corresponding to the current abnormal travel data is an ended travel;

[0015] If the target vehicle has only one travel, and the state of the target vehicle is in travel, a vehicle position signal uploaded by the target vehicle last time is obtained from the abnormal travel data, and if the target vehicle is located in a preset target area, a suspected end label is added to the current abnormal travel data, the target area comprising: an area where a preset general parking point is located, an area where a commonly used parking point of the target user is located, and an area where a target parking point is located, the commonly used parking point being obtained based on historical driving data of the target user, and the target parking point being obtained by statistical analysis on historical parking points of a plurality of users;

[0016] The travel end of the abnormal travel data is checked based on the suspected end label.

[0017] In an embodiment of the present application, the abnormal travel data is checked based on the preset travel end determination rule, further comprising:

[0018] If the target vehicle has only one travel, and the state of the target vehicle is in travel, a time of a last reported signal of the target vehicle is obtained from the abnormal travel data;

[0019] If the time when the target vehicle last reports a signal is located in a preset target time period, the suspected end label is added to the current abnormal trip data, and the target time period is obtained by statistical analysis of parking times of multiple users.

[0020] In an embodiment of the present application, based on the suspected end label, trip end verification of the abnormal trip data is completed, including:

[0021] The electronic parking gear, the time of the last uploaded vehicle position signal, the vehicle speed signal, and the vehicle power mode in the abnormal trip data are obtained.

[0022] If the electronic parking gear of the target vehicle is a parking gear and the duration is greater than a preset first threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the difference between the current time and the time of the last uploaded vehicle position signal is greater than a preset second threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip.

[0023] If the speed of the target vehicle is less than a preset speed threshold and the duration is greater than a preset third threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power mode is an off mode or a hibernation mode, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power mode is an engine-off mode and the duration is greater than a preset fourth threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip.

[0024] In an embodiment of the present application, if it is determined that the trip corresponding to the abnormal trip data is an ended trip, the trip corresponding to the current abnormal trip data is ended to complete abnormal trip correction, including:

[0025] If it is determined that the trip corresponding to the abnormal trip data is an ended trip, a type identifier is added to the current abnormal trip data, the type identifier is used to indicate a determination condition adopted when it is determined that the current trip is an ended trip, or is used to indicate a determination condition adopted when it is determined that the current trip is suspected to be ended, and the determination condition is in the trip end determination rule.

[0026] After the type identifier is added, the trip corresponding to the current abnormal trip data is ended to complete abnormal trip correction.

[0027] In an embodiment of the present application, multiple abnormal trip data are determined as an abnormal trip data set, including:

[0028] If a new trip data set is received, trip anomaly analysis is performed on the trip data in the new trip data set to obtain abnormal trip data in the new trip data set.

[0029] The abnormal travel data in the new travel data set and the abnormal travel data that is not corrected in the last abnormal travel correction process are determined as the abnormal travel data set.

[0030] In an embodiment of the present application, the method further comprises:

[0031] After obtaining the current travel data set, if there is a travel data set collected in the last travel collection period, the travel data in the current travel data set is matched with the travel data in the travel data set collected in the last travel collection period;

[0032] If the matching is successful, travel data splicing is performed to obtain spliced travel data, and the matching success means that the two travel data belong to the same travel;

[0033] The spliced travel data is stored in the current travel data set for calling when a new travel data set is collected in the next travel collection period.

[0034] The present application also provides an abnormal travel correction system, the system comprising: a data collection module for obtaining a travel data set, the travel data set comprising travel data uploaded by at least one vehicle, the travel data in the travel data set being in travel progress, the travel data comprising travel duration;

[0035] An abnormal travel marking module for marking the travel data corresponding to the current travel duration as abnormal travel data if the travel duration is greater than a preset duration threshold;

[0036] A travel end verification module for performing travel end verification on the abnormal travel data based on a preset travel end determination rule, the travel end determination rule being determined based on historical driving data of a target user corresponding to the abnormal travel data;

[0037] An abnormal travel correction module for ending the travel corresponding to the abnormal travel data if it is determined that the travel corresponding to the abnormal travel data is an ended travel, to complete abnormal travel correction.

[0038] The present application also provides an electronic device comprising a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to realize the abnormal travel correction method provided in any one of the above embodiments.

[0039] Beneficial effects of the embodiments of the present application: The embodiments of the present application provide an abnormal trip correction method, system, and electronic device. The method obtains a trip data set, which includes trip data uploaded by at least one vehicle. The trip status in the trip data is trip in progress, and the trip data includes trip duration. If the trip duration is greater than a preset duration threshold, the trip data corresponding to the current trip duration is marked as abnormal trip data. The abnormal trip data is checked for trip completion based on a preset trip completion determination rule, which is determined based on the historical driving data of the target user corresponding to the abnormal trip data. If it is determined that the trip corresponding to the abnormal trip data is a completed trip, the trip corresponding to the current abnormal trip data is terminated to complete the abnormal trip correction. This method can relatively accurately complete abnormal trip identification and correction, avoiding a series of problems caused by the vehicle's failure to upload a trip completion signal in a timely manner at the end of the trip. It has high flexibility and low cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flowchart of an abnormal stroke correction method provided in one embodiment of the present application;

[0041] Figure 2 Schematic diagram of the process of abnormal stroke judgment and correction in the abnormal stroke correction method provided in one embodiment of the present application;

[0042] Figure 3 A schematic diagram of a flow chart of fusion condition judgment in an abnormal stroke correction method provided in an embodiment of the present application;

[0043] Figure 4 A schematic diagram of iterative correction of full data and incremental data in the abnormal stroke correction method provided in one embodiment of the present application;

[0044] Figure 5 An exemplary schematic diagram of traditional stroke splicing provided in one embodiment of the present application;

[0045] Figure 6 This is an exemplary schematic diagram of stroke splicing in the abnormal stroke correction method provided in one embodiment of the present application;

[0046] Figure 7 A flowchart of an exemplary embodiment of an abnormal stroke correction method provided in one embodiment of the present application;

[0047] Figure 8 A schematic structural diagram of an abnormal stroke correction system provided in one embodiment of the present application;

[0048] Figure 9 A schematic structural diagram of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0049] Those skilled in the art will readily owe other advantages and purposes of the present application from the disclosure of the present application without departing from the spirit of the present application. The present application can also be implemented or applied in other different embodiments, and various modifications or changes can be made to the details without departing from the spirit of the present application based on different views and applications. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0050] It should be noted that the diagrams provided in the following embodiments only schematically illustrate the basic concepts of the present application, and only the components related to the present application are shown in the diagrams, not the number, shape and size of the components when actually implemented. The shapes, numbers and proportions of the components when actually implemented can be arbitrarily changed, and the layout pattern of the components can be more complex.

[0051] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application, however, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details, and in other embodiments, the known structures and devices are shown in the form of block diagrams rather than in the form of details to avoid making the embodiments of the present application difficult to understand.

[0052] The following will be described in conjunction with Figures 1 to 9 The abnormal trip correction method, system and electronic device provided by the present application are explained and described.

[0053] Please refer to Figure 1 , Figure 1 The flowchart of the abnormal trip correction method provided by an embodiment of the present application is shown in Figure 1 The method comprises the following steps:

[0054] S110: Obtain a trip data set, the trip data set comprising trip data uploaded by at least one vehicle, the trip state in the trip data being in progress, and the trip data comprising a trip duration.

[0055] In some examples of the present embodiment, the trip data further comprises a trip state, an electronic parking gear, a time of the last uploaded vehicle position signal, a vehicle speed signal, and a vehicle power mode, etc.

[0056] It can be understood that the trip data in the present embodiment does not include a trip end signal sent by the vehicle.

[0057] S120: If the trip duration is greater than a preset duration threshold, mark the trip data corresponding to the current trip duration as abnormal trip data.

[0058] In some embodiments, if the trip data corresponds to a trip with a manual abnormality label, the trip data is determined as abnormal trip data, and the manual abnormality label is a label manually uploaded or added. It can be understood that the determination method of the abnormal trip data in step S120 is a passive method, and the method of manually uploading or adding a label is an active method.

[0059] In some examples of the present embodiment, the duration threshold can be set according to actual conditions, such as 24 hours, etc.

[0060] Through the above steps S110 and S120, the abnormal trip data has been identified, and the abnormal trip data does not necessarily represent that the trip has ended, so the following trip end verification is performed on the abnormal trip data to determine whether the trip corresponding to the abnormal trip data has ended and whether trip end processing is needed.

[0061] S130: performing trip end verification on the abnormal trip data based on a preset trip end determination rule, and the trip end determination rule is determined based on historical driving data of a target user corresponding to the abnormal trip data.

[0062] In some examples of the present embodiment, the target user refers to a user associated with a target vehicle uploading the abnormal trip data. The historical driving data can include speed information, driving behavior data, driving time, road condition information, and vehicle condition of the target user, etc.

[0063] In some examples of the present embodiment, determining the trip end determination rule based on the historical driving data of the target user corresponding to the abnormal trip data can include: obtaining an integrated data set by integrating the historical driving data; extracting features in the data set to obtain speed features, acceleration behavior features, sudden braking behavior features, and parking time features, etc.; determining the trip end determination rule based on the extracted features, for example: if sudden braking behaviors frequently occur in a short time and there is no normal driving, it can mean that the driver anticipates a sudden situation, and thus determines that the trip has ended, etc.

[0064] S140: if it is determined that the trip corresponding to the abnormal trip data is an ended trip, ending the trip corresponding to the abnormal trip data to complete the abnormal trip correction.

[0065] Through the above abnormal trip correction process, multiple concurrent trips can be effectively avoided, and unnecessary distress and panic of users can also be avoided. It can be understood that if the trip is abnormal due to the vehicle failing to upload the trip end signal in time at the end of the trip, the target vehicle may have been powered off or be charging, while the cloud still displays that the vehicle is still driving. This will cause unnecessary distress and trouble to the user. Through the abnormal trip correction method in the above embodiment, this problem can be better solved.

[0066] In order to reduce the burden of trip end verification, in some embodiments, before the abnormal trip data is verified based on the preset trip end determination rule, the method further comprises:

[0067] I. Determine a plurality of abnormal trip data as an abnormal trip data set.

[0068] II. Update the abnormal trip data in the abnormal trip data set based on the real-time uploaded trip data of the target vehicle, wherein the target vehicle refers to the vehicle corresponding to the abnormal trip data.

[0069] In some examples of the present embodiment, since the above determination of abnormal trip data is a real-time or instantaneous behavior, it is still possible to receive a delayed trip end signal due to network delay and other problems before the trip end verification is performed. Therefore, the present embodiment updates the abnormal trip data before the trip end verification is performed, that is, collects the signals uploaded by the target vehicle corresponding to the abnormal trip data, so as to facilitate determining whether the target vehicle uploads the trip end signal in the time period. If the trip end signal is received, the corresponding trip can be directly ended according to the trip end signal, thereby reducing the pressure and burden of subsequent trip end verification.

[0070] III. Perform trip end signal checking on the updated abnormal trip data, and if the trip end signal cannot be checked, verify the abnormal trip data based on the trip end determination rule.

[0071] In some embodiments, verifying the abnormal trip data based on the preset trip end determination rule comprises:

[0072] I. Perform trip detection and state detection on the target vehicle corresponding to the abnormal trip data, and if the target vehicle has two or more trips, or the state of the target vehicle is charging, determine that the trip corresponding to the current abnormal trip data is an ended trip.

[0073] It can be understood that the same vehicle usually does not have two parallel trips, that is, the same vehicle usually does not have two trips being performed at the same time, which is a clear contradiction and mutual exclusion, indicating that the current trip is an ended trip. Therefore, if the target vehicle has two or more trips, it can be determined that the trip corresponding to the current abnormal trip data is an ended trip and subsequent correction is performed.

[0074] In addition, the same vehicle usually does not have a charging state and a driving state at the same time. Since the trip state corresponding to the abnormal trip data is a trip in progress, if the target vehicle corresponding to the abnormal trip data is in a charging state at this time, the two states are mutually exclusive. In this case, it can be determined that the trip corresponding to the current abnormal trip data is an ended trip and subsequent correction is performed.

[0075] The judgment method of the above-mentioned mutual exclusion has the advantages of clear logic, simple implementation, and high accuracy. In order to better deal with more complex scenarios, such as the vehicle not making a mutual exclusion action after the trip is abnormal, further judgment is made in combination with the historical driving data of the target user and other multiple users.

[0076] II. If the target vehicle has only one trip and the state of the target vehicle is a trip in progress, the last uploaded vehicle position signal of the target vehicle is obtained from the abnormal trip data. If the target vehicle is located in a predetermined target area, a suspected end mark is added to the current abnormal trip data, and the target area includes: an area where a predetermined general parking point is located, an area where a frequently used parking point of the target user is located, and an area where a target parking point is located. The frequently used parking point is obtained based on the historical driving data of the target user, and the target parking point is obtained by statistical analysis of the historical parking points of multiple users.

[0077] In some examples of the present embodiment, the general parking point is a general frequently used parking location such as a company, a charging station, a residential area, a commercial area, etc. The area where the parking point is located is, for example, an area covered by a circle formed by taking the parking point as the center and a predetermined distance (such as 100 meters, etc.) as the radius. The frequently used parking point of the target user can be obtained by counting the number of times of parking at different parking points in the historical driving data of the target user.

[0078] In some examples of the present embodiment, the target parking point can be obtained by statistical analysis of the historical parking point information of multiple users in the cloud. For example, if multiple users have parked at a parking point multiple times, the parking point can be determined as a target parking point. Taking the target parking point as the center and a predetermined distance as the radius, the circular range formed is determined as the area where the target parking point is located.

[0079] By obtaining the area where the target parking point is located, the above-mentioned situation that the target user is a new user or has less historical driving data, etc. can be avoided, and the target parking point can be understood as the target user's less common parking point. It can be understood that even if the target user's common parking point is less, the target parking point can also be used for judgment and marking.

[0080] III. Based on the suspected end marker, the trip end verification of the abnormal trip data is completed.

[0081] In some examples of the present embodiment, the abnormal trip data with the suspected end marker can be directly determined as the trip end data, and the trip end processing is performed on the trip end data.

[0082] In some embodiments, based on the preset trip end determination rule, the trip end verification of the abnormal trip data further includes:

[0083] I. If the target vehicle has only one trip and the state of the target vehicle is in the trip, the time of the last signal reported by the target vehicle is obtained from the abnormal trip data.

[0084] II. If the time of the last signal reported by the target vehicle is located in a preset target time period, the suspected end marker is added to the current abnormal trip data, and the target time period is obtained by statistical analysis of the parking time of multiple users.

[0085] In some examples of the present embodiment, the parking time of multiple users can be obtained and statistically analyzed to obtain the common parking time period of most users, for example: 8-10, 11-13, and 18-21. The common parking time period is determined as the above-mentioned target time period. Through the above-mentioned determination, the accuracy of the trip end verification can be improved.

[0086] In order to further improve the accuracy of the trip end verification, in some embodiments, based on the suspected end marker, the trip end verification of the abnormal trip data includes:

[0087] A. Obtain the electronic parking gear, the time of the last uploaded vehicle position signal, the vehicle speed signal, and the vehicle power mode in the abnormal trip data.

[0088] B. If the electronic parking gear of the target vehicle is in the parking gear and the duration is greater than a preset first threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the difference between the current time and the time of the last uploaded vehicle position signal is greater than a preset second threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip.

[0089] C, if the speed of the target vehicle is less than a preset speed threshold and the duration is greater than a preset third threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power supply mode is an off mode or a hibernation mode, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power supply mode is an engine-off mode and the duration is greater than a preset fourth threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip.

[0090] It can be understood that if any one of the conditions in steps B and C is met, it is determined that the trip corresponding to the abnormal trip data is an ended trip, and subsequent trip correction processing is performed, that is, the trip is ended. Through the above-mentioned manner, the accuracy of abnormal trip correction can be improved.

[0091] In addition, in the embodiment, whether the abnormal trip data carries a suspected end marker or not, the conditions in steps B and C are required to be judged for the abnormal trip data. There are three cases, case one, the abnormal trip data carries a suspected end marker and at least one of the conditions defined in steps B and C is met; case two, the abnormal trip data does not carry a suspected end marker and at least one of the conditions defined in steps B and C is met; case three, at least one of the conditions defined in steps B and C is not met. Among the three cases, the accuracy of case one is the highest, and the accuracy of case two is the second. In order to improve the accuracy of trip correction, if the abnormal trip data does not meet at least one of the conditions defined in steps B and C, whether it carries a suspected end marker or not, the trip corresponding to the abnormal trip data is determined to be an unended trip, that is, the current correction fails.

[0092] In some examples of the embodiment, the first threshold, the second threshold, the third threshold, and the third threshold can be set according to actual conditions, such as 1 hour, 2 hours, etc.

[0093] In some embodiments, if it is determined that the trip corresponding to the abnormal trip data is an ended trip, the current trip corresponding to the abnormal trip data is ended to complete the abnormal trip correction, comprising:

[0094] I. If it is determined that the trip corresponding to the abnormal trip data is an ended trip, a type identifier is added to the current abnormal trip data, the type identifier is used to indicate the determination condition adopted when it is determined that the current trip is an ended trip, or is used to indicate the determination condition adopted when it is determined that the current trip is suspected to be ended, and the determination condition is in the trip end determination rule.

[0095] The type identifier is exemplarily shown in Table 1 as follows:

[0096] Table 1 Type identifier example

[0097]

[0098] The advantages and disadvantages of the above four types of identification are exemplarily illustrated in the following Table 2:

[0099] Advantages and disadvantages of type identification

[0100]

[0101] II. In the case of completing the type identification addition, ending the trip corresponding to the current abnormal trip data to complete the abnormal trip correction.

[0102] It can be understood that, by performing the above type identification addition, the determination condition used to end the trip can be facilitated for subsequent relevant personnel to identify, and subsequent tracing and condition correction can be facilitated.

[0103] Figure 2 For the flowchart of abnormal trip judgment and correction in the abnormal trip correction method provided in an embodiment of the present application, please refer to Figure 2 S210: Obtain a trip data set.

[0104] S220: Determine whether it is abnormal trip data, i.e., determine whether the trip data in the trip data set is abnormal trip data.

[0105] S230: Obtain an abnormal trip data set. Specifically, the abnormal trip data in the current trip data set and the abnormal trip data that failed to be corrected in the last correction process (the abnormal trip data that was not placed in the end in the last correction process, i.e., the abnormal trip data whose trip was not ended) are combined into the abnormal trip data set.

[0106] S240: Check whether there is a trip end signal. If yes, execute step S280; if no, execute step S250.

[0107] S250: Mutual exclusion condition judgment. If the mutual exclusion condition is met, execute step S280; if the mutual exclusion condition is not met, execute step S260.

[0108] S260: Fusion condition judgment. Specifically, determine whether the following fusion conditions are met: the target vehicle is located in a preset target area, or the time of the last signal reported by the target vehicle is located in a preset target time period. If yes, add a suspected end mark and execute step S270; if no, directly execute step S270.

[0109] S270: Time and signal judgment, i.e., judgment is made based on the judgment conditions in steps B and C. If the judgment conditions in steps B and C are met, step S280 is performed; if the judgment conditions in steps B and C are not met, step S230 is performed.

[0110] S280: Adding type identification.

[0111] S290: End of trip. Specifically, the trip corresponding to the current abnormal trip data is ended.

[0112] Figure 3 For the abnormal trip correction method provided in an embodiment of the present application, a flowchart of the fusion condition judgment is shown in Figure 3 S310: General parking point condition judgment, i.e., whether the target vehicle is in the area where the general parking point is located is judged. If the condition is met, step S350 is performed; if not, step S320 is performed.

[0113] S320: Single-user analysis judgment. Specifically, based on the historical driving data of the target user, the frequently used parking point of the target user is obtained, and it is judged whether the target vehicle is in the area where the frequently used parking point is located. If the condition is met, step S350 is performed; if not, step S330 is performed.

[0114] S330: Multi-user analysis judgment. Specifically, based on the historical driving data of multiple users, the target parking point is obtained. It is judged whether the target vehicle is in the area where the target parking point is located. If the condition is met, step S350 is performed; if not, step S340 is performed.

[0115] S340: Time feature judgment. Specifically, it is judged whether the time when the target vehicle last reported the signal is in the preset target time period. If the condition is met, step S350 is performed; if not, the time and signal judgment in step S270 is performed.

[0116] S350: Adding a suspected end marker.

[0117] In some embodiments, the multiple abnormal trip data are determined as an abnormal trip data set, comprising:

[0118] I. If a new trip data set is received, trip anomaly analysis is performed on the trip data in the new trip data set to obtain abnormal trip data in the new trip data set.

[0119] II. The abnormal trip data in the new trip data set and the abnormal trip data that are not corrected in the last abnormal trip correction process are determined as the abnormal trip data set.

[0120] It can be understood that through the above steps, the need for judgment and correction of all travel data each time of correction can be avoided, and the difficulty and complexity of data processing are reduced.

[0121] Figure 4 An iteration correction schematic diagram of full data and incremental data in the abnormal travel correction method provided by an embodiment of the present application is shown. The full data refers to a data set that has not been subjected to abnormal travel correction. For example, a travel data set collected in a first travel collection period has not been subjected to abnormal travel correction. It is assumed that the first travel collection period is T-3, and it is assumed that the travel data set collected in the T-3 period is travel data from January 1, 2024 to November 30, 2024. Through the abnormal travel identification in step S120, abnormal travel data in the travel data set can be obtained. The multiple abnormal travel data obtained herein form an abnormal travel data set.

[0122] The incremental data refers to travel data collected in a next or future travel collection period. It is assumed that the next period of the T-3 period is T-2, and it is assumed that a batch of new travel data is collected in the T-2 period. Then, multiple abnormal travel data can be obtained by screening the batch of new travel data. The multiple abnormal travel data screened and the abnormal travel data in the abnormal travel data set corresponding to the T-3 period that cannot be corrected are combined to obtain a new abnormal travel data set.

[0123] For example, it is assumed that the travel data collected in the T-2 period is travel data on December 1, 2024, and abnormal travel data in the batch of travel data is obtained after abnormal travel data screening. On this basis, the batch of abnormal travel data and the abnormal travel data in the abnormal travel data set corresponding to the T-3 period that cannot be corrected are combined to obtain a new abnormal travel data set.

[0124] It is assumed that the next period of the T-2 period is T-1, and it is assumed that a batch of new travel data is collected in the T-1 period. Then, multiple abnormal travel data can be obtained by screening the batch of new travel data. The multiple abnormal travel data screened and the abnormal travel data in the abnormal travel data set corresponding to the T-2 period that cannot be corrected are combined to obtain a new abnormal travel data set.

[0125] Similarly, it is assumed that the next period of the T-1 period is T, and it is assumed that a batch of new travel data is collected in the T period. Then, multiple abnormal travel data can be obtained by screening the batch of new travel data. The multiple abnormal travel data screened and the abnormal travel data in the abnormal travel data set corresponding to the T-1 period that cannot be corrected are combined to obtain a new abnormal travel data set.

[0126] For example, it is assumed that the next period of the T-1 period is T, and it is assumed that a batch of new travel data is collected in the T period. Then, multiple abnormal travel data can be obtained by screening the batch of new travel data. The multiple abnormal travel data screened and the abnormal travel data in the abnormal travel data set corresponding to the T-1 period that cannot be corrected are combined to obtain a new abnormal travel data set. Figure 4As shown, the T-3 period collects the trip data set as full data. Based on the trip data set, abnormal trip data screening, trip end verification and correction are performed. If the correction is successful, it is determined that the abnormal trip data has been corrected. If the correction fails, i.e., the abnormal trip data does not meet the multiple determination conditions set in the above embodiments, the abnormal trip data is combined with the new abnormal trip data in the T-2 period, and the next trip end verification and correction are performed together. The new abnormal trip data in the T-2 period is obtained by screening the abnormal trip data from the new trip data set collected in the T-2 period, and the T-1 period and the T period are the same. If the correction is successful, it is determined that the abnormal trip data has been corrected. If the correction fails, the abnormal trip data that fails to be corrected is combined with the new abnormal trip data in the T-1 period, and the next trip end verification and correction are performed together. In this way, iteration is continued until there is no new abnormal trip data and no abnormal trip data that has not been successfully corrected.

[0127] The conventional trip anomaly correction method needs to recalculate the full data + incremental data each time the trip is corrected. This method greatly increases the calculation difficulty and reduces the calculation efficiency. Therefore, through the iteration method in the above embodiments, the calculation amount is greatly reduced, and the calculation efficiency and correction efficiency are improved.

[0128] For example, assume that there are 1 million trip data from January 1, 2024 to November 30, 2024, 10,000 new trip data on December 1, 2024, and 10,000 new trip data on December 2, 2024. The traditional method is to calculate 1 million data once, then calculate 101 million trip data when the first new trip data is added, and calculate 102 million data when the second new trip data is added. The method in the above embodiments is to perform abnormal trip data screening, trip end verification and correction on the trip data from January 1, 2024 to November 30, 2024. When the first new trip data is added, 10,000 new trip data on December 1, 2024 is screened for abnormal trip data, the abnormal trip data obtained by screening is combined with the abnormal trip data that has not been successfully corrected last time to obtain a new abnormal trip data set, and the trip end verification and correction are performed on the new abnormal trip data set. In this way, iteration is performed in turn.

[0129] A single trip can be a cross-day trip or a non-cross-day trip. A cross-day trip refers to a trip that starts from the current day and does not end on the current day. A non-cross-day trip refers to a trip that starts from the current day and ends on the current day. If the trip corresponding to the abnormal trip data is a cross-day trip or a cross-period (trip collection period) trip, trip data splicing is required. The trip data splicing method is explained below. In some embodiments, it also includes:

[0130] I. In the case of obtaining the current journey data set, if there is a journey data set collected in the last journey collection period, the journey data in the current journey data set is matched with the journey data in the journey data set collected in the last journey collection period.

[0131] II. If the matching is successful, the journey data splicing is performed to obtain spliced journey data, and the matching success refers to that the two journey data belong to the same journey.

[0132] III. The spliced journey data is stored in the current journey data set for calling when a new journey data set is collected in the next journey collection period.

[0133] In some examples of the embodiment, when the journey data collected in each journey collection period is stored, the journey data in the period is spliced with the journey data in all previous periods, so that when the journey data is collected in the new journey collection period, the journey data stored in the last period can be directly accessed or queried, and the journey data splicing can be completed without accessing and querying the journey data stored in each journey collection period one by one.

[0134] Figure 5 For an example of the traditional journey splicing provided by an embodiment of the present application, please refer to Figure 5 The traditional journey splicing method assumes that the current journey collection period is T-1, and the journey data of journey F is included in the journey data collected in the T-1 period. Therefore, before the abnormal journey data screening, it is necessary to determine that the journey data of journey F collected in the T-1 period is complete journey data. Therefore, the traditional method needs to query the journey data collected in the T-2 period, and if there is journey data of journey F in the T-2 period, the journey data of journey F collected in the T-1 period needs to be spliced with the journey data of journey F in the T-2 period. After the splicing is completed, the journey data collected in the T-3 period is queried until there is no journey data of journey F in the journey data in a certain period. This method needs to be iterated multiple times, that is, it needs to access the previous period multiple times to complete the journey splicing. When the amount of journey data is large, such as having ten million journeys, it will result in a decrease in splicing efficiency, and the amount of data accessed and queried is huge. T-N represents the Nth journey collection period.

[0135] Figure 6 For an example of the journey splicing in the abnormal journey correction method provided by an embodiment of the present application, please refer to Figure 6The storage manner of the travel data collected in each travel collection period in the embodiment includes: splicing the travel data collected in the current travel collection period with the travel data stored in the last travel collection period, and storing the spliced travel data. Figure 6 As shown in FIG. 6, it is assumed that there is a current travel F, and it is assumed that T-5 is the first travel collection period, then the travel data stored in the T-5 period is the entire travel data collected in the period. T-4 is the next travel collection period of T-5, then the travel data stored in the T-4 period is the spliced travel data of T-4 and T-5. T-3 is the next travel collection period of T-4, then the travel data stored in the T-3 period is the spliced travel data of T-3, T-4 and T-5. T-2 is the next travel collection period of T-3, then the travel data stored in the T-2 period is the spliced travel data of T-2, T-3, T-4 and T-5. T-1 is the next travel collection period of T-2, then the travel data stored in the T-1 period is the spliced travel data of T-1, T-2, T-3, T-4 and T-5. By using this manner, the travel data splicing efficiency can be effectively improved. It can be understood that, it is assumed that the current travel collection period is T-1, and it is assumed that the travel data collected in T-1 includes the travel data of travel F, then the travel data splicing of travel F can be completed by accessing only the travel data stored in the T-2 period, without accessing the travel data stored in each period one by one.

[0136] In some embodiments, the method further comprises: obtaining the real-time state of the target vehicle, if the real-time state of the target vehicle is a parking state, determining that the judgment result of the current abnormal travel data is correct; if the real-time state of the target vehicle is a driving state, determining that the judgment result of the current abnormal travel data is incorrect and feeding back to adjust the travel end determination rule.

[0137] In some embodiments, the method further comprises: receiving the vehicle state information of the target vehicle fed back by the user, determining that the judgment result of the current abnormal travel data is correct or incorrect based on the vehicle state information, if the judgment result is incorrect, feeding back the error to adjust the travel end determination rule. It can be understood that, by the above manner, the accuracy of the abnormal travel correction can be further improved.

[0138] In the following, an exemplary embodiment is used to explain the abnormal travel correction method in the above embodiments.

[0139] Please refer to Figure 7 S710: determining whether the current travel data set is full data or incremental data. If it is full data, step S730 is executed, if it is incremental data, step S720 is executed.

[0140] S720: determining whether the incremental data is cross-day. If cross-day, cross-day incremental data is obtained, and if not cross-day, non-cross-day incremental data is obtained. It can be understood that by determining the type of the trip data set, subsequent recording can be facilitated.

[0141] S730: performing abnormal trip data screening, trip end verification and correction.

[0142] S740: correction result accuracy verification. Specifically, based on the real-time state of the target vehicle or the vehicle state information of the target vehicle fed back by the user, it is determined whether the correction result is wrong. If it is wrong, the rules used in the trip end verification process are optimized; if it is not wrong, the correction is ended.

[0143] The abnormal trip correction system provided in the present application is described below, and the abnormal trip correction system described below can be referred to each other corresponding to the abnormal trip correction method described above.

[0144] Please refer to Figure 8 The abnormal trip correction system provided in the present embodiment comprises:

[0145] The data acquisition module 810 is configured to obtain a trip data set, the trip data set comprising trip data uploaded by at least one vehicle, the trip state in the trip data being in progress, and the trip data comprising a trip duration.

[0146] The abnormal trip marking module 820 is configured to mark the trip data corresponding to the current trip duration as abnormal trip data if the trip duration is greater than a preset duration threshold.

[0147] The trip end verification module 830 is configured to verify the end of the trip based on a preset trip end determination rule, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data.

[0148] The abnormal trip correction module 840 is configured to end the trip corresponding to the abnormal trip data if it is determined that the trip corresponding to the abnormal trip data has ended, so as to complete the abnormal trip correction. The data acquisition module 810, the abnormal trip marking module 820, the trip end verification module 830, and the abnormal trip correction module 840 are connected. The abnormal trip correction system in the present embodiment can accurately identify and correct abnormal trips, avoid a series of problems caused by the vehicle failing to upload the trip end signal in time when the trip ends, has high flexibility, and has strong implementability.

[0149] It should be noted that the abnormal trip correction method provided in the above embodiments and the abnormal trip correction system belong to the same concept, wherein the specific manner in which each module performs operations has been described in detail in the method embodiments, which will not be repeated here. The abnormal trip correction system provided in the above embodiments can allocate the above functions to different functional modules to complete in actual application, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0150] In some embodiments, an electronic device is also provided, which can be a server, and a block diagram of an internal structure thereof is shown in Figure 9 The electronic device includes a processor, a memory, a network interface and a database connected through a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes non-volatile and / or volatile storage media, internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the electronic device is used to communicate with the external client through the network connection. The computer program is executed by the processor to implement the functions or steps of the server side of the above method.

[0151] In some embodiments, an electronic device is provided, including a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the following steps when executing the computer program: obtaining a trip data set, the trip data set including trip data uploaded by at least one vehicle, the trip state in the trip data being in progress, and the trip data including a trip duration; if the trip duration is greater than a preset duration threshold, marking the trip data corresponding to the current trip duration as abnormal trip data; based on a preset trip end determination rule, performing trip end verification on the abnormal trip data, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data; if it is determined that the trip corresponding to the abnormal trip data is an ended trip, ending the trip corresponding to the current abnormal trip data to complete the abnormal trip correction.

[0152] In some embodiments, a computer readable storage medium is provided, and the computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to implement the following steps: obtaining a trip data set, the trip data set including trip data uploaded by at least one vehicle, a trip state in the trip data being in a trip in progress, the trip data including a trip duration; if the trip duration is greater than a preset duration threshold, marking the trip data corresponding to the current trip duration as abnormal trip data; performing trip end verification on the abnormal trip data based on a preset trip end determination rule, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data; and if it is determined that the trip corresponding to the abnormal trip data is an ended trip, ending the trip corresponding to the current abnormal trip data, to complete abnormal trip correction.

[0153] It should be noted that the functions or steps described above with respect to the computer readable storage medium or the electronic device can correspond to the related descriptions of the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0154] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment, or a part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders than those noted in the drawings. For example, two blocks represented in succession can actually be executed in parallel, and they can also be executed in reverse order depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0155] The above embodiments are only illustrative of the principles and effects of the present application, and are not intended to limit the present application. Any person skilled in the art can modify or change the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical idea disclosed in the present application should be covered by the claims of the present application.

Claims

1. An abnormal course correction method characterized by, The method comprises the following steps: acquiring a trip data set, the trip data set comprising trip data uploaded by at least one vehicle, a trip state in the trip data being in progress, and the trip data comprising a trip duration; if the trip duration is greater than a preset duration threshold, marking the trip data corresponding to the current trip duration as abnormal trip data; based on a preset trip end determination rule, performing trip end verification on the abnormal trip data, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data; based on the preset trip end determination rule, performing trip end verification on the abnormal trip data comprises: performing trip detection and state detection on a target vehicle corresponding to the abnormal trip data; if the target vehicle has only one trip and the state of the target vehicle is in progress, obtaining a vehicle location signal uploaded by the target vehicle for the last time from the abnormal trip data; if the target vehicle is located in a preset target area, adding a suspected end mark to the current abnormal trip data, the target area comprising an area where a target parking point is located and an area where a commonly used parking point of a target user is located, the commonly used parking point being obtained based on historical driving data of the target user; based on the suspected end mark, completing trip end verification on the abnormal trip data; if the target vehicle has two or more trips, or the state of the target vehicle is a charging state, determining that a trip corresponding to the current abnormal trip data is an ended trip; if it is determined that the trip corresponding to the abnormal trip data is an ended trip, ending the trip corresponding to the current abnormal trip data to complete abnormal trip correction.

2. The abnormal travel correction method according to claim 1, characterized by, Before performing trip end verification on the abnormal trip data based on the preset trip end determination rule, the method further comprises the following steps: determining a plurality of abnormal trip data as an abnormal trip data set; based on real-time trip data uploaded by a target vehicle, updating abnormal trip data in the abnormal trip data set, the target vehicle referring to a vehicle corresponding to the abnormal trip data; performing trip end signal checking on the updated abnormal trip data, and if no trip end signal can be checked, performing trip end verification on the abnormal trip data based on the trip end determination rule.

3. The abnormal travel correction method according to claim 1 or 2, characterized by, The target area further comprises an area where a preset general parking point is located, and the target parking point is obtained by statistical analysis of historical parking points of a plurality of users.

4. The abnormal travel correction method according to claim 3, characterized by, Based on the preset trip end determination rule, performing trip end verification on the abnormal trip data further comprises the following steps: if the target vehicle has only one trip and the state of the target vehicle is in progress, obtaining a time of a last reported signal of the target vehicle from the abnormal trip data; if the time of the last reported signal of the target vehicle is located in a preset target time period, adding the suspected end mark to the current abnormal trip data, and the target time period is obtained by statistical analysis of parking times of a plurality of users.

5. The abnormal travel correction method according to claim 3, characterized by, Based on the suspected end marker, the trip end verification of the abnormal trip data is completed, including: Obtaining the electronic parking gear, the time of the last uploaded vehicle position signal, the vehicle speed signal, and the vehicle power mode in the abnormal trip data; If the electronic parking gear of the target vehicle is in the parking gear and the duration is greater than a preset first threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the difference between the current time and the time of the last uploaded vehicle position signal is greater than a preset second threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; If the speed of the target vehicle is less than a preset speed threshold and the duration is greater than a preset third threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power mode is in the off mode or the hibernation mode, it is determined that the trip corresponding to the abnormal trip data is an ended trip; if the vehicle power mode is in the engine off mode and the duration is greater than a preset fourth threshold, it is determined that the trip corresponding to the abnormal trip data is an ended trip.

6. The abnormal travel correction method according to claim 1, characterized by, If it is determined that the trip corresponding to the abnormal trip data is an ended trip, the current trip corresponding to the abnormal trip data is ended to complete the abnormal trip correction, including: If it is determined that the trip corresponding to the abnormal trip data is an ended trip, a type identifier is added to the current abnormal trip data, the type identifier being used to indicate the determination condition adopted when it is determined that the current trip is an ended trip, or being used to indicate the determination condition adopted when it is determined that the current trip is suspected to be ended, the determination condition being in the trip end determination rule; After the type identifier is added, the current trip corresponding to the abnormal trip data is ended to complete the abnormal trip correction.

7. The abnormal travel correction method according to claim 2, characterized by, The plurality of abnormal trip data is determined as an abnormal trip data set, including: If a new trip data set is received, trip anomaly analysis is performed on the trip data in the new trip data set to obtain abnormal trip data in the new trip data set; The abnormal trip data in the new trip data set and the abnormal trip data not corrected in the last abnormal trip correction process are determined as the abnormal trip data set.

8. The abnormal travel correction method according to claim 1, characterized by, Further comprising: After obtaining the current trip data set, if there is a trip data set collected in the last trip collection period, the trip data in the current trip data set is matched with the trip data in the trip data set collected in the last trip collection period; If the matching is successful, trip data splicing is performed to obtain spliced trip data, the matching success indicating that the two trip data belong to the same trip; The spliced trip data is stored in the current trip data set for calling when a new trip data set is collected in the next trip collection period.

9. An abnormal flight correction system characterized by, Comprise: A data collection module is configured to collect a trip data set, the trip data set including trip data uploaded by at least one vehicle, a trip state in the trip data being in progress, the trip data including trip duration; an abnormal trip marking module, configured to mark the trip data corresponding to the current trip duration as abnormal trip data if the trip duration is greater than a preset duration threshold; a trip end verification module, configured to perform trip end verification on the abnormal trip data based on a preset trip end determination rule, the trip end determination rule being determined based on historical driving data of a target user corresponding to the abnormal trip data; an abnormal trip correction module, configured to end the trip corresponding to the abnormal trip data if it is determined that the abnormal trip data corresponds to an ended trip, so as to complete abnormal trip correction; the trip end verification module is specifically configured to perform trip detection and state detection on a target vehicle corresponding to the abnormal trip data, to obtain a vehicle position signal uploaded by the target vehicle for the last time from the abnormal trip data if the target vehicle has only one trip and a state of the target vehicle is in a trip, and to add a suspected end label to the current abnormal trip data if the target vehicle is located in a preset target area, the target area including an area where a target parking point is located and an area where a commonly used parking point of a target user is located, the commonly used parking point being obtained based on historical driving data of the target user, and to complete trip end verification on the abnormal trip data based on the suspected end label; and the abnormal trip correction module is specifically configured to determine that the trip corresponding to the abnormal trip data is an ended trip if the target vehicle has two or more trips or the state of the target vehicle is a charging state.

10. An electronic device, comprising: a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to implement the abnormal trip correction method according to any one of claims 1 to 8.

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