A method and system for generating vehicle lease renewal information based on vehicle positioning

Abstract

An embodiment of the present application discloses a method and system for generating vehicle renewal information based on vehicle positioning, including: when the return time of the current rental vehicle is less than a set time threshold, obtaining the return time, return location and positioning information of the rental vehicle during the rental period; determining the stop location point of the rental vehicle during the rental period and the current real-time location point based on the positioning information, and predicting the rental vehicle's usage time interval based on the building information within a preset range of the stop location point; determining the vehicle renewal strategy based on the correlation between the return time and the usage time interval, and the positional relationship between the real-time location point and the return location, and generating vehicle renewal information based on the vehicle renewal strategy and the vehicle information of the rental vehicle, thereby improving the accuracy and rationality of the vehicle renewal information.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing, and in particular to a method and system for generating vehicle lease renewal information based on vehicle positioning. Background Art

[0002] In recent years, the car rental industry has shown a booming development trend. Whether it is travel, business activities, or urban commuting, the demand for car rentals is growing. As the market scale continues to expand, the number of car rental companies has increased, and industry competition has become increasingly fierce. In such an environment, how to retain old users and increase users' enthusiasm for car rental renewal has become a key factor for car rental companies to maintain competitiveness and achieve sustainable development.

[0003] In related technologies, a user's car rental needs are usually determined based on factors such as the user's historical car rental frequency and total rental duration, and corresponding renewal rewards or renewal discounts are generated based on the car rental needs and sent to the client of the renewing user. When determining the car rental needs, only the impact of the car usage demand within the historical rental period on the vehicle renewal is considered, which makes the generated car rental information less accurate and reasonable, and cannot truly meet the actual car rental needs. Summary of the Invention

[0004] The present invention provides a method and system for generating vehicle renewal information based on vehicle positioning, addressing the problem of poor accuracy and rationality in the generated vehicle rental information, which in turn fails to meet actual vehicle rental needs. By comprehensively analyzing a user's actual vehicle usage based on the actual return location and time, as well as vehicle positioning information, vehicle renewal information containing corresponding vehicle renewal policies is generated based on different vehicle usage situations, thereby improving the accuracy and rationality of vehicle renewal information.

[0005] In a first aspect, an embodiment of the present application provides a method for generating vehicle lease renewal information based on vehicle positioning, comprising:

[0006] When the return time of the current rental vehicle is less than a set time threshold, obtaining the return time, return location and positioning information of the rental vehicle during the rental period;

[0007] Determine the location of the rental vehicle during the rental period and its current real-time location based on the positioning information, and predict the use time interval of the rental vehicle based on the building information within a preset range of the location;

[0008] A vehicle renewal strategy is determined based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, and vehicle renewal information is generated based on the vehicle renewal strategy and the vehicle information of the rental vehicle.

[0009] Optionally, determining the stopping location of the rental vehicle during the rental period based on the positioning information includes:

[0010] collecting a plurality of vehicle mark points of the rental vehicle during the rental period according to a preset time interval, identifying whether there is a traffic light mark in the area to which each vehicle mark point belongs, and determining the vehicle mark point corresponding to the area without the traffic light mark as the target vehicle mark point;

[0011] Aggregation processing is performed on the target vehicle mark points according to the coordinates of the target vehicle mark points, and the stop location of the rental vehicle during the rental period is determined based on the aggregation processing result.

[0012] Optionally, performing aggregation processing on the target vehicle mark points according to the coordinates of the target vehicle mark points, and determining the stop location of the rental vehicle during the rental period based on the aggregation processing result, includes:

[0013] The target vehicle mark points are aggregated according to their coordinates to obtain overlapping mark points with overlapping positions, and the number of overlaps of the overlapping mark points is determined. The overlapping mark points with a number of overlaps greater than a preset overlap number threshold are determined as the stopping points of the taxi during the rental period.

[0014] Optionally, the step of predicting the use time interval of the rental vehicle based on building information within a preset range of the stop location includes:

[0015] The number of building identifications is counted according to the building information within the preset range of the stop location, the building identification with the largest number is determined as the target building identification, and the time interval associated with the target building identification is determined as the use time interval of the rental vehicle.

[0016] Optionally, determining the vehicle lease renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, includes:

[0017] A first renewal probability is determined based on the correlation between the return time and the vehicle usage time interval, a second renewal probability is determined based on the positional relationship between the real-time location point and the return location, a target renewal probability is calculated based on the first renewal probability and the second renewal probability and a preset weight ratio, and a vehicle renewal strategy corresponding to the target renewal probability is determined.

[0018] Optionally, determining the first renewal probability according to the correlation between the vehicle return time and the vehicle usage time interval includes:

[0019] When the vehicle usage time interval includes the vehicle return time, and the vehicle return time includes a continuous period after the vehicle return time, determining the first renewal probability to be a first preset value;

[0020] When the vehicle usage time interval does not include the vehicle return time or the vehicle usage time interval does not include a continuous period after the vehicle return time, the first renewal probability is determined to be a second preset value, and the first preset value is greater than the second preset value.

[0021] Optionally, determining the second renewal probability based on the positional relationship between the real-time location point and the vehicle return location includes:

[0022] generating vehicle navigation information based on the real-time location point and the location of the vehicle return location, and determining an estimated arrival time based on the navigation information;

[0023] Whether the rental vehicle meets the return conditions is determined based on the estimated arrival time and the return time. If the rental vehicle meets the return conditions, the second renewal probability is determined to be a second preset value. If the rental vehicle does not meet the return conditions, the second renewal probability is determined to be a first preset value, and the first preset value is greater than the second preset value.

[0024] In a second aspect, an embodiment of the present application provides a vehicle renewal information generation system based on vehicle positioning, comprising:

[0025] An information acquisition module is used to obtain the return time, return location and positioning information of the rental vehicle during the rental period when the return time of the current rental vehicle is less than a set time threshold;

[0026] A location point determination module is used to determine the location point where the rental vehicle stayed during the rental period and the current real-time location point based on the positioning information;

[0027] A vehicle usage time interval determination module is used to predict the usage time interval of the rental vehicle based on the building information within a preset range of the stop location point;

[0028] A vehicle lease renewal strategy determination module, configured to determine a vehicle lease renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location and the vehicle return location;

[0029] The vehicle lease renewal information generation module is used to generate vehicle lease renewal information according to the vehicle lease renewal strategy and the vehicle information of the rental vehicle.

[0030] In a third aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for generating vehicle renewal information based on vehicle positioning as described in the first aspect.

[0031] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer-executable instructions, which, when executed by a computer processor, are used to execute the method for generating vehicle renewal information based on vehicle positioning as described in the first aspect.

[0032] In an embodiment of the present application, when the return time of the current rental vehicle is less than a set time threshold, the return time, return location and positioning information of the rental vehicle during the rental period are obtained; based on the positioning information, the stop location of the rental vehicle during the rental period and the current real-time location are determined, and the use time interval of the rental vehicle is predicted based on the building information within a preset range of the stop location; the vehicle renewal strategy is determined based on the correlation between the return time and the use time interval, and the positional relationship between the real-time location and the return location, and the vehicle renewal information is generated based on the vehicle renewal strategy and the vehicle information of the rental vehicle. In the above scheme, by determining the vehicle's parking location and identifying the building information around the parking location, the rental vehicle's usage time period is determined based on the building information. The rental vehicle's purpose and the corresponding usage time period can be analyzed based on the activity data of the rental vehicle during the rental period, thereby improving the accuracy of determining the rental vehicle's usage time period. The vehicle renewal strategy is determined based on the correlation between the return time and the usage time period and the positional relationship between the real-time location point and the return location. The influence of the vehicle usage time and the positional relationship between the real-time location point and the return location on the generation of the renewal strategy can be comprehensively considered, thereby improving the rationality of the vehicle renewal strategy and, correspondingly, improving the accuracy and rationality of the vehicle renewal information. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of a method for generating vehicle lease renewal information based on vehicle positioning provided in an embodiment of the present application;

[0034] Figure 2 This is a schematic diagram of a preset range of a stop location point provided in an embodiment of the present application;

[0035] Figure 3 This is a flow chart of a method for determining a stop location point provided by an embodiment of the present application;

[0036] Figure 4 This is a flowchart of a method for determining a first renewal probability provided by an embodiment of the present application;

[0037] Figure 5 This is a flow chart of a method for determining a second renewal probability provided by an embodiment of the present application;

[0038] Figure 6 This is a structural diagram of a vehicle lease renewal information generation system based on vehicle positioning provided in an embodiment of the present application;

[0039] Figure 7 This is a structural diagram of a vehicle lease renewal information generation device based on vehicle positioning provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] To further clarify the objectives, technical solutions, and advantages of this application, specific embodiments of the present application are described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are intended only to illustrate this application and are not intended to limit it. It should also be noted that, for ease of description, the drawings only illustrate portions relevant to this application, not all of them. Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts depict the various operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process may terminate upon completion of its operations, but may also include additional steps not shown in the accompanying drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, or the like.

[0041] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0042] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0043] In the following, in conjunction with the accompanying drawings, a method and system for generating vehicle renewal information based on vehicle positioning provided by an embodiment of the present application are described in detail through specific embodiments and their application scenarios.

[0044] The vehicle renewal information generation method based on vehicle positioning provided in the embodiment of the present application is used in the scenario of monitoring and managing rented vehicles. Based on the above application scenario, it can be understood that the executor of this solution can be a server.

[0045] Figure 1 This is a flow chart of a method for generating vehicle lease renewal information based on vehicle positioning provided by an embodiment of the present application, such as Figure 1 As shown, including:

[0046] Step S101: When the return time of the current rental vehicle is less than a set time threshold, obtain the return time, return location and positioning information of the rental vehicle during the rental period.

[0047] Among them, the current rental vehicle refers to all vehicles that the vehicle operator has currently rented out, and the return time of the current rental vehicle refers to the return time pre-agreed by the vehicle operator and the rental user before the vehicle is rented. Correspondingly, the return location is also the return location pre-agreed by the vehicle operator and the rental user before the vehicle is rented. The positioning information during the rental period is the vehicle position information collected through the satellite positioning technology of the Beidou satellite navigation system. In one embodiment, the return time of all current rental vehicles is obtained, and the time difference between the return time of each current rental vehicle and the current time is determined, and rental vehicles with a time difference less than a preset time threshold are screened out, and the return time, return location and positioning information during the rental period corresponding to the vehicle identification are queried based on the vehicle identification of the rental vehicle, where the vehicle identification can be a license plate number or a frame number, etc.

[0048] Step S102: determining the stop location and current real-time location of the taxi during the rental period based on the positioning information, and predicting the use time interval of the taxi based on the building information within a preset range of the stop location.

[0049] Among them, the stop location point during the rental period can be a parking point where the taxi vehicle stays for more than a preset time threshold during the rental period. The real-time location point refers to the current location of the vehicle. The preset range is used to represent the area size of the building information recognition area, and the stop location point preset range can be the building information recognition range centered on the stop location point and determined according to the area size of the preset recognition area. Building information is used to represent relevant data and related introductions of the building, and may include the style of the building, the building's logo, and the purpose of the building. The taxi vehicle usage time range refers to the predicted time range with a high frequency of taxi vehicle usage, such as holidays or weekdays.

[0050] In one embodiment, the parking location of the rental vehicle during the rental period and the current location of the rental vehicle are determined based on the positioning information. Figure 2 This is a schematic diagram of a preset range of a stop location provided in an embodiment of the present application, such as Figure 2 As shown, the target detection range, i.e., the preset range of the parking location, is determined based on the area of ​​the preset detection range, with the parking location as the center. All building uses within the preset range of the parking location are identified, and the building use with the highest frequency is determined as the vehicle use. The rental vehicle's usage time interval associated with this vehicle use is then determined. For example, if a factory used for industrial production is repeatedly identified within the target detection range, it can be determined that the rental vehicle is likely used to transport goods within the factory or for commuting by factory employees. Therefore, the pre-acquired factory working hours can be determined as the rental vehicle's usage time, i.e., the rental vehicle's usage time interval.

[0051] Optionally, the step of predicting the use time interval of the rental vehicle based on building information within a preset range of the stop location includes:

[0052] The number of building identifications is counted according to the building information within the preset range of the stop location, the building identification with the largest number is determined as the target building identification, and the time interval associated with the target building identification is determined as the use time interval of the rental vehicle.

[0053] Among them, a building identifier can refer to a name or symbol used to identify, indicate, and explain building-related information in a building and its surrounding environment, and may include XX scenic spot, XX school, and XX office building, etc. In one embodiment, based on the building information within the preset range of the stop location, the number of building identifiers within the preset range of each stop location and the total number of building identifiers are counted, and the building identifier with the largest total number is determined, and the time interval associated with the building identifier is determined as the taxi usage time interval. For example, if there is a scenic spot identifier within the preset range of each stop location, the scenic spot identifier is determined as the target building identifier, and the time interval associated with the scenic spot identifier is determined as the taxi usage time interval, such as the holiday interval.

[0054] This embodiment of the present application counts the number of building identifiers within a preset range of the stop location, identifies the building identifier with the largest number of identifiers as the target building identifier, and determines the time interval associated with the target building identifier as the taxi's use time interval. This approach improves the accuracy of determining the use time interval by counting the frequency of building identifiers within the preset range of the stop location and determining the corresponding use time interval based on the statistical results.

[0055] Step S103: Determine a vehicle renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, and generate vehicle renewal information based on the vehicle renewal strategy and the vehicle information of the rental vehicle.

[0056] Among them, the association between the return time and the vehicle usage time interval is used to indicate the relationship between the return time and the vehicle usage time interval, which can be an inclusion relationship between the vehicle usage time interval and the return time, or an adjacent relationship between the return time and the vehicle usage time interval. The vehicle renewal policy is used to indicate the preferential policy provided by the vehicle operator when renewing the vehicle, which can include discount information or coupons, etc., to attract the rental user to renew the vehicle. The vehicle information of the rental vehicle refers to the basic information of the vehicle, such as the vehicle type, license plate number, vehicle color, and the number of passengers allowed. The vehicle renewal information is a prompt information used to prompt the rental user to renew the vehicle or return the vehicle, which can include the vehicle information of the rental vehicle and the vehicle renewal policy.

[0057] In one embodiment, the probability of renewal is determined based on the correlation between the return time and the vehicle usage time interval. If the correlation is that the return time and the vehicle usage time interval do not overlap at all, the user will most likely not renew the lease after returning the vehicle. If the correlation is that the return time and the vehicle usage time interval overlap, the user will most likely continue to rent the vehicle, and the return distance between the real-time location point and the return location is determined based on the coordinates of the real-time location point and the coordinates of the return location, and the return distance is compared with a preset distance threshold. If the return distance is greater than the preset distance threshold, the user will most likely continue to rent the vehicle. If the return distance is less than or equal to the preset distance threshold, the user is about to return the vehicle and will most likely not continue to rent the vehicle. The overall renewal probability is evaluated based on the above judgment result of the vehicle rental probability, and a corresponding vehicle renewal strategy is generated based on the evaluation result. For example, if the association is that the return time and the vehicle usage time interval do not overlap at all, the corresponding renewal probability is 0; if the association is that the return time and the vehicle usage time interval overlap, the corresponding renewal probability is 50%; if the return distance is greater than the preset distance threshold, the corresponding renewal probability is 50%; if the return distance is less than or equal to the preset distance threshold, the corresponding renewal probability is 0; the overall renewal probability is determined based on the association between the return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the return location; and the corresponding vehicle renewal strategy is determined based on the association between the preset renewal probability and the vehicle renewal strategy; the vehicle renewal strategy is bound to the vehicle information of the rental vehicle to generate vehicle renewal information.

[0058] In an embodiment of the present application, when the return time of the current rental vehicle is less than a set time threshold, the return time, return location and positioning information of the rental vehicle during the rental period are obtained; based on the positioning information, the stop location of the rental vehicle during the rental period and the current real-time location are determined, and the use time interval of the rental vehicle is predicted based on the building information within a preset range of the stop location; the vehicle renewal strategy is determined based on the correlation between the return time and the use time interval, and the positional relationship between the real-time location and the return location, and the vehicle renewal information is generated based on the vehicle renewal strategy and the vehicle information of the rental vehicle. In the above scheme, by determining the vehicle's parking location and identifying the building information around the parking location, the rental vehicle's usage time period is determined based on the building information. The rental vehicle's purpose and the corresponding usage time period can be analyzed based on the activity data of the rental vehicle during the rental period, thereby improving the accuracy of determining the rental vehicle's usage time period. The vehicle renewal strategy is determined based on the correlation between the return time and the usage time period and the positional relationship between the real-time location point and the return location. The influence of the vehicle usage time and the positional relationship between the real-time location point and the return location on the generation of the renewal strategy can be comprehensively considered, thereby improving the rationality of the vehicle renewal strategy and, correspondingly, improving the accuracy and rationality of the vehicle renewal information.

[0059] Optionally, determining the vehicle lease renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, includes:

[0060] A first renewal probability is determined based on the correlation between the return time and the vehicle usage time interval, a second renewal probability is determined based on the positional relationship between the real-time location point and the return location, a target renewal probability is calculated based on the first renewal probability and the second renewal probability and a preset weight ratio, and a vehicle renewal strategy corresponding to the target renewal probability is determined.

[0061] The first renewal probability represents the degree to which the relationship between the return time and the usage period affects a user's vehicle renewal decision. The second renewal probability represents the degree to which the relationship between the real-time location and the return location affects a user's vehicle renewal decision. The target renewal probability represents the overall degree to which the current status of the rental vehicle affects a user's vehicle renewal decision.

[0062] For example, if the vehicle usage time interval includes the return time, the first renewal probability is determined to be 60%. If the vehicle usage time interval does not include the return time, the first renewal probability is determined to be 40%. If the real-time location point does not overlap with the return location, and the distance between the two points is greater than a preset distance threshold, the second renewal probability is determined to be 80%. If the real-time location point does not overlap with the return location, the second renewal probability is determined to be 20%. If the current status of the rental vehicle is that the vehicle usage time interval includes the return time, the real-time location point does not overlap with the return location, and the distance between the two points is greater than a preset distance threshold, the first renewal probability is determined to be 50%, and the second renewal probability is determined to be 80%. The preset weight ratio is 4:6. Based on the first and second renewal probabilities and the preset weight ratio, the target renewal probability is calculated as: (60% * 40% + 80% * 60%) 100% = 72%. The target renewal probability is then assigned a tier according to the preset target renewal probability tier table, and the vehicle renewal strategy associated with that tier is determined.

[0063] The embodiment of the present application determines a first renewal probability based on the correlation between the return time and the vehicle usage time interval, determines a second renewal probability based on the positional relationship between the real-time location point and the vehicle return location, calculates a target renewal probability based on the first renewal probability and the second renewal probability and a preset weight ratio, and determines a vehicle renewal strategy corresponding to the target renewal probability. In the above scheme, the vehicle renewal strategy is determined based on the degree of influence of the correlation between the return time and the vehicle usage time interval and the positional relationship between the real-time location point and the vehicle return location on the target renewal probability, respectively, thereby improving the accuracy of the target renewal probability and the accuracy of the vehicle renewal strategy.

[0064] Figure 3This is a flow chart of a method for determining a stop location point provided by an embodiment of the present application. Figure 3 As shown, including:

[0065] Step S1021: Collect multiple vehicle mark points of the rental vehicle during the rental period according to a preset time interval, identify whether there is a traffic light mark in the area to which each vehicle mark point belongs, and determine the vehicle mark point corresponding to the area without the traffic light mark as the target vehicle mark point.

[0066] Among them, the vehicle identification point is used to indicate the position of the vehicle at a certain point in time, and can be represented by position coordinates. The area to which the vehicle identification point belongs refers to the signal light recognition range determined with the vehicle identification point as the center, and the size of the range can be pre-set according to demand. The target vehicle identification point is a vehicle identification point with no signal lights around it. In one embodiment, multiple vehicle identification points of the taxi during the rental period are collected according to preset time intervals. For example, one vehicle identification point is collected every hour to obtain multiple vehicle identification points, and the area to which each vehicle identification point belongs is determined based on the size of the preset signal light recognition range with each vehicle identification point as the center, and it is identified whether there is a signal light mark in the area to which each vehicle identification point belongs. If there is a signal light mark, it can be determined that the taxi stopped due to waiting for the traffic light, and the parking point has no effect on the judgment of the vehicle use time interval. The vehicle identification point corresponding to the area containing the signal light mark can be ignored, and the vehicle identification point corresponding to the area not containing the signal light mark is determined as the target vehicle identification point.

[0067] Step S1022: performing aggregation processing on the target vehicle mark points according to the coordinates of the target vehicle mark points, and determining the stop location of the rental vehicle during the rental period based on the aggregation processing result.

[0068] Aggregating the target vehicle mark points refers to the process of summarizing, counting, or grouping the target vehicle mark points. In one embodiment, the target vehicle mark points are aggregated according to their coordinates to obtain overlapping target vehicle mark points, and the overlapping target vehicle mark points are determined as the parking locations of the rental vehicle during the rental period.

[0069] The embodiment of the present application collects multiple vehicle marking points of a taxi during the rental period according to a preset time interval, identifies whether there is a traffic light mark in the area to which each vehicle marking point belongs, and determines the vehicle marking point corresponding to the area without a traffic light mark as the target vehicle marking point; aggregates the target vehicle marking points according to their coordinates, and determines the location point where the taxi stayed during the rental period based on the aggregation processing result. In the above scheme, by identifying the traffic light marks in the area to which multiple vehicle marking points belong and determining the target vehicle marking point, the influence of irrelevant vehicle marking points on the determination of the vehicle use time interval can be reduced, and the efficiency of the aggregation processing and the accuracy of the determination of the vehicle use time interval can be improved.

[0070] Optionally, performing aggregation processing on the target vehicle mark points according to the coordinates of the target vehicle mark points, and determining the stop location of the rental vehicle during the rental period based on the aggregation processing result, includes:

[0071] The target vehicle mark points are aggregated according to their coordinates to obtain overlapping mark points with overlapping positions, and the number of overlaps of the overlapping mark points is determined. The overlapping mark points with a number of overlaps greater than a preset overlap number threshold are determined as the stopping points of the taxi during the rental period.

[0072] In one embodiment, the target vehicle mark points are aggregated according to their coordinates to determine the overlapped locations where the target vehicle mark points exist, and the number of target vehicle mark points at the overlapped locations is determined, i.e., the overlapped times of the overlapped mark points. A greater overlapped time indicates that the taxi has stayed at the target vehicle mark point for a longer time, and conversely, a smaller overlapped time indicates that the taxi has stayed at the target vehicle mark point for a shorter time. The overlapped mark points with an overlapped time greater than a preset overlapped time threshold are determined as the taxi's stay location during the rental period. In another possible embodiment, a range of overlapped times of the overlapped mark points is pre-set, and the overlapped mark points with an overlapped time within the range are determined as the taxi's stay location during the rental period.

[0073] The embodiment of the present application aggregates the target vehicle's marked points based on their coordinates to obtain overlapping marked points with overlapping positions. The overlap count of the overlapping marked points is then determined, and the overlapping marked points with an overlap count greater than a preset overlap count threshold are determined as the taxi's resting locations during the rental period. By aggregating the target vehicle's marked points, overlapping marked points with a high overlap count are determined as resting locations, thereby improving the accuracy of resting location determination.

[0074] Figure 4 This is a flow chart of a method for determining a first renewal probability provided by an embodiment of the present application. Figure 4As shown, including:

[0075] Step S201: When the vehicle usage time interval includes the vehicle return time, and the vehicle return time includes a continuous period after the vehicle return time, determining a first renewal probability to be a first preset value.

[0076] For example, if the return time is Wednesday, and the usage time interval is Monday to Friday, where the usage time interval includes the return time, and also includes Thursday and Friday after the return time Wednesday, where Thursday and Friday are consecutive time periods after the return time, in this case it can be considered that the rental user has a higher frequency of car usage from Monday to Friday. Although Wednesday is the return time, the user is more likely to continue renting the vehicle on Thursday and Friday. At this time, the first renewal probability can be determined to be 1.

[0077] Step S202: When the vehicle usage time interval does not include the vehicle return time or the vehicle usage time interval does not include a continuous period after the vehicle return time, determine that the first renewal probability is a second preset value, and the first preset value is greater than the second preset value.

[0078] For example, if the return time is Wednesday and the usage time interval is Saturday and Sunday, or the return time is Wednesday and the usage time interval is Monday to Wednesday, and the usage time interval does not include a continuous period after the return time on Wednesday, in this case it can be considered that the rental user has a higher frequency of car usage from Monday to Wednesday. Although Wednesday is the return time, it meets the rental user's vehicle usage needs, and the user is unlikely to renew the lease. At this time, the first renewal probability can be determined to be 0.

[0079] In this embodiment of the present application, if the vehicle usage time interval includes the return time and the return time includes a continuous period after the return time, the first renewal probability is determined to be a first preset value. If the vehicle usage time interval does not include the return time or the vehicle usage time interval does not include a continuous period after the return time, the first renewal probability is determined to be a second preset value. The first renewal probability can be determined by determining whether the vehicle usage time interval includes the return time and whether the return time includes a continuous period after the return time, thereby improving the accuracy of the first renewal probability.

[0080] Figure 5 This is a flow chart of a method for determining a second renewal probability provided by an embodiment of the present application. Figure 5 As shown, including:

[0081] Step S301: Generate vehicle navigation information based on the real-time location point and the location of the vehicle return location, and determine an estimated arrival time based on the navigation information.

[0082] Step S302: determine whether the rental vehicle meets the return conditions based on the estimated arrival time and the return time; if the rental vehicle meets the return conditions, determine the second renewal probability to be a second preset value; if the rental vehicle does not meet the return conditions, determine the second renewal probability to be a first preset value, and the first preset value is greater than the second preset value.

[0083] Among them, vehicle navigation information refers to providing the vehicle with relevant information such as location, driving route, traffic conditions, etc. through technologies such as satellite positioning systems and geographic information systems, so as to help the driver reach the destination accurately and efficiently. Optionally, the navigation information may also include information such as the estimated time of arrival at the destination and the average driving speed of the vehicle. In one embodiment, the estimated time of arrival at the return location is determined based on the vehicle navigation information, and it is determined whether the estimated time of arrival is before the agreed return time. If the estimated time of arrival is before the agreed return time, it is determined that the car rental user is willing to return the car. At this time, the second renewal probability can be determined to be 0. If the estimated time of arrival is after the agreed return time, it can be understood that the car rental user cannot return the car at the agreed return time and may be willing to renew the lease. At this time, the second renewal probability can be determined to be 1.

[0084] The embodiment of the present application generates vehicle navigation information based on the real-time location and the location of the return location, determines an estimated arrival time based on the navigation information, and determines whether the rental vehicle meets the return conditions based on the estimated arrival time and the return time. If the rental vehicle meets the return conditions, the second renewal probability is determined to be a second preset value; if the rental vehicle does not meet the return conditions, the second renewal probability is determined to be a first preset value. The second renewal probability can be determined by determining whether the rental user can return the vehicle within the agreed return time, thereby improving the accuracy of the second renewal probability.

[0085] Figure 6 This is a structural diagram of a vehicle renewal information generation system based on vehicle positioning provided by an embodiment of the present application, such as Figure 6 As shown, including:

[0086] An information acquisition module 41 is configured to acquire the return time, return location, and location information of the rental vehicle during the rental period when the return time of the current rental vehicle is less than a set time threshold;

[0087] A location determination module 42 is configured to determine the location of the rental vehicle during the rental period and the current real-time location of the rental vehicle based on the positioning information;

[0088] A vehicle usage time interval determination module 43 is configured to predict the usage time interval of the rental vehicle based on building information within a preset range of the stop location;

[0089] A vehicle lease renewal strategy determination module 44 is configured to determine a vehicle lease renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location and the vehicle return location;

[0090] The vehicle lease renewal information generating module 45 is configured to generate vehicle lease renewal information according to the vehicle lease renewal policy and the vehicle information of the rental vehicle.

[0091] In an embodiment of the present application, when the return time of the current rental vehicle is less than a set time threshold, the return time, return location and positioning information of the rental vehicle during the rental period are obtained; based on the positioning information, the stop location of the rental vehicle during the rental period and the current real-time location are determined, and the use time interval of the rental vehicle is predicted based on the building information within a preset range of the stop location; the vehicle renewal strategy is determined based on the correlation between the return time and the use time interval, and the positional relationship between the real-time location and the return location, and the vehicle renewal information is generated based on the vehicle renewal strategy and the vehicle information of the rental vehicle. In the above scheme, by determining the vehicle's parking location and identifying the building information around the parking location, the rental vehicle's usage time period is determined based on the building information. The rental vehicle's purpose and the corresponding usage time period can be analyzed based on the activity data of the rental vehicle during the rental period, thereby improving the accuracy of determining the rental vehicle's usage time period. The vehicle renewal strategy is determined based on the correlation between the return time and the usage time period and the positional relationship between the real-time location point and the return location. The influence of the vehicle usage time and the positional relationship between the real-time location point and the return location on the generation of the renewal strategy can be comprehensively considered, thereby improving the rationality of the vehicle renewal strategy and, correspondingly, improving the accuracy and rationality of the vehicle renewal information.

[0092] In a possible embodiment, the location point determination module 42 is specifically configured to:

[0093] collecting a plurality of vehicle mark points of the rental vehicle during the rental period according to a preset time interval, identifying whether there is a traffic light mark in the area to which each vehicle mark point belongs, and determining the vehicle mark point corresponding to the area without the traffic light mark as the target vehicle mark point;

[0094] Aggregation processing is performed on the target vehicle mark points according to the coordinates of the target vehicle mark points, and the stop location of the rental vehicle during the rental period is determined based on the aggregation processing result.

[0095] In a possible embodiment, the location point determination module 42 is further configured to:

[0096] The target vehicle mark points are aggregated according to their coordinates to obtain overlapping mark points with overlapping positions, and the number of overlaps of the overlapping mark points is determined. The overlapping mark points with a number of overlaps greater than a preset overlap number threshold are determined as the stopping points of the taxi during the rental period.

[0097] In a possible embodiment, the vehicle usage time interval determination module 43 is specifically configured to:

[0098] The number of building identifications is counted according to the building information within the preset range of the stop location, the building identification with the largest number is determined as the target building identification, and the time interval associated with the target building identification is determined as the use time interval of the rental vehicle.

[0099] In one possible embodiment, the vehicle lease renewal strategy determination module 44 is specifically configured to:

[0100] A first renewal probability is determined based on the correlation between the return time and the vehicle usage time interval, a second renewal probability is determined based on the positional relationship between the real-time location point and the return location, a target renewal probability is calculated based on the first renewal probability and the second renewal probability and a preset weight ratio, and a vehicle renewal strategy corresponding to the target renewal probability is determined.

[0101] In one possible embodiment, the vehicle lease renewal strategy determination module 44 is further configured to:

[0102] When the vehicle usage time interval includes the vehicle return time, and the vehicle return time includes a continuous period after the vehicle return time, determining the first renewal probability to be a first preset value;

[0103] When the vehicle usage time interval does not include the vehicle return time or the vehicle usage time interval does not include a continuous period after the vehicle return time, the first renewal probability is determined to be a second preset value, and the first preset value is greater than the second preset value.

[0104] In one possible embodiment, the vehicle lease renewal strategy determination module 44 is further configured to:

[0105] generating vehicle navigation information based on the real-time location point and the location of the vehicle return location, and determining an estimated arrival time based on the navigation information;

[0106] Whether the rental vehicle meets the return conditions is determined based on the estimated arrival time and the return time. If the rental vehicle meets the return conditions, the second renewal probability is determined to be a second preset value. If the rental vehicle does not meet the return conditions, the second renewal probability is determined to be a first preset value, and the first preset value is greater than the second preset value.

[0107] An embodiment of the present application also provides a vehicle renewal information generation device based on vehicle positioning. The vehicle renewal information generation device based on vehicle positioning can be integrated with a vehicle renewal information generation system based on vehicle positioning provided in an embodiment of the present application. Figure 7 This is a schematic diagram of the structure of a vehicle renewal information generation device based on vehicle positioning provided by an embodiment of the present application, with reference to Figure 7 The vehicle renewal information generation device based on vehicle positioning includes: an input device 53, an output device 54, a memory 52, and one or more processors 51; the memory 52 is used to store one or more programs; when the one or more programs are executed by the one or more processors 51, the one or more processors 51 implement the vehicle renewal information generation method based on vehicle positioning as provided in the above embodiment. The input device 53, the output device 54, the memory 52, and the processor 51 can be connected via a bus or other means. Figure 7 The bus connection is taken as an example.

[0108] Memory 52, as a computing device-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the vehicle location-based vehicle renewal information generation method provided in any embodiment of the present application. Memory 52 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on device usage, etc. Furthermore, memory 52 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some instances, memory 52 may further include memory remotely located relative to processor 51, and such remote memory may be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0109] The input device 53 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 54 may include a display device such as a display screen.

[0110] The processor 51 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 52, that is, realizes the above-mentioned method for generating vehicle renewal information based on vehicle positioning.

[0111] The vehicle renewal information generation system, device and computer based on vehicle positioning provided above can be used to execute the vehicle renewal information generation method based on vehicle positioning provided in any of the above embodiments, and have corresponding functions and beneficial effects.

[0112] The present application also provides a storage medium storing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to execute the vehicle renewal information generation method based on vehicle positioning as provided in the above embodiment. The vehicle renewal information generation method based on vehicle positioning includes:

[0113] When the return time of the current rental vehicle is less than a set time threshold, obtaining the return time, return location and positioning information of the rental vehicle during the rental period;

[0114] Determine the location of the rental vehicle during the rental period and its current real-time location based on the positioning information, and predict the use time interval of the rental vehicle based on the building information within a preset range of the location;

[0115] A vehicle renewal strategy is determined based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, and vehicle renewal information is generated based on the vehicle renewal strategy and the vehicle information of the rental vehicle.

[0116] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROMs, floppy disks, or tape drives; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disks or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or it may be located in a different second computer system that is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., embodied as a computer program) that can be executed by one or more processors.

[0117] Of course, the storage medium containing computer-executable instructions provided in an embodiment of the present application, whose computer-executable instructions are not limited to the vehicle renewal information generation method based on vehicle positioning as described above, can also execute related operations in the vehicle renewal information generation method based on vehicle positioning provided in any embodiment of the present application.

[0118] The vehicle renewal information generation system, device and storage medium based on vehicle positioning provided in the above embodiments can execute the vehicle renewal information generation method based on vehicle positioning provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the vehicle renewal information generation method based on vehicle positioning provided in any embodiment of the present application.

[0119] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that are possible for those skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include more other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A method for generating vehicle lease renewal information based on vehicle positioning, characterized in that: include: When the return time of the current rental vehicle is less than a set time threshold, obtaining the return time, return location and positioning information of the rental vehicle during the rental period; Collect multiple vehicle mark points of the taxi during the rental period according to preset time intervals, identify whether there is a traffic light logo in the area to which each vehicle mark point belongs, determine the vehicle mark point corresponding to the area without the traffic light logo as the target vehicle mark point, aggregate the target vehicle mark points according to the coordinates of the target vehicle mark points to obtain overlapping mark points with overlapping positions, and determine the number of overlaps of the overlapping mark points, determine the overlapping mark points with the number of overlaps greater than a preset overlap number threshold as the stop location point of the taxi during the rental period and the current real-time location point, count the number of building logos according to the building information within the preset range of the stop location point, determine the building logo with the largest number as the target building logo, and determine the time interval associated with the target building logo as the taxi usage time interval; Determine whether the return time completely coincides with the vehicle usage time interval, determine the return distance between the real-time location point and the return location based on the coordinates of the real-time location point and the coordinates of the return location, and compare the return distance with a preset distance threshold, determine the vehicle renewal strategy based on the coincidence judgment result and the threshold comparison result, and generate vehicle renewal information based on the vehicle renewal strategy and the vehicle information of the rental vehicle, wherein the vehicle renewal strategy is used to indicate the preferential strategy provided by the vehicle operator when renewing the vehicle.

2. The method for generating vehicle lease renewal information based on vehicle positioning according to claim 1, characterized in that: The determining of the vehicle renewal strategy based on the correlation between the vehicle return time and the vehicle usage time interval, and the positional relationship between the real-time location point and the vehicle return location, includes: A first renewal probability is determined based on the correlation between the return time and the vehicle usage time interval, a second renewal probability is determined based on the positional relationship between the real-time location point and the return location, a target renewal probability is calculated based on the first renewal probability and the second renewal probability and a preset weight ratio, and a vehicle renewal strategy corresponding to the target renewal probability is determined.

3. The method for generating vehicle lease renewal information based on vehicle positioning according to claim 2, characterized in that: The determining of the first renewal probability according to the correlation between the vehicle return time and the vehicle usage time interval includes: When the vehicle usage time interval includes the vehicle return time, and the vehicle return time includes a continuous period after the vehicle return time, determining the first renewal probability to be a first preset value; When the vehicle usage time interval does not include the vehicle return time or the vehicle usage time interval does not include a continuous period after the vehicle return time, the first renewal probability is determined to be a second preset value, and the first preset value is greater than the second preset value.

4. The method for generating vehicle lease renewal information based on vehicle positioning according to claim 2, characterized in that: The determining the second renewal probability according to the positional relationship between the real-time location point and the vehicle return location includes: generating vehicle navigation information based on the real-time location point and the location of the vehicle return location, and determining an estimated arrival time based on the navigation information; Whether the rental vehicle meets the return conditions is determined based on the estimated arrival time and the return time. If the rental vehicle meets the return conditions, the second renewal probability is determined to be a second preset value. If the rental vehicle does not meet the return conditions, the second renewal probability is determined to be a first preset value, and the first preset value is greater than the second preset value.

5. A vehicle renewal information generation system based on vehicle positioning, characterized in that: include: An information acquisition module is used to obtain the return time, return location and positioning information of the rental vehicle during the rental period when the return time of the current rental vehicle is less than a set time threshold; a location point determination module for collecting a plurality of vehicle mark points of the taxi during the rental period according to a preset time interval, identifying whether there is a traffic light mark in the area to which each vehicle mark point belongs, determining the vehicle mark point corresponding to the area without the traffic light mark as the target vehicle mark point, performing aggregation processing on the target vehicle mark points according to the coordinates of the target vehicle mark points to obtain overlapping mark points with overlapping positions, determining the number of overlaps of the overlapping mark points, and determining the overlapping mark points with the number of overlaps greater than a preset overlap number threshold as the stop position point of the taxi during the rental period and the current real-time position point; A vehicle usage time interval determination module is configured to count the number of building identifiers according to the building information within a preset range of the stop location, determine the building identifier with the largest number as the target building identifier, and determine the time interval associated with the target building identifier as the rental vehicle usage time interval; a vehicle lease renewal strategy determination module, configured to determine whether the vehicle return time completely overlaps with the vehicle usage time interval, determine a return distance between the real-time location point and the return location based on the coordinates of the real-time location point and the coordinates of the return location, compare the return distance with a preset distance threshold, and determine a vehicle lease renewal strategy based on the overlap determination result and the threshold comparison result; The vehicle renewal information generation module is used to generate vehicle renewal information based on the vehicle renewal policy and the vehicle information of the rental vehicle. The vehicle renewal policy is used to represent the preferential policy provided by the vehicle operator when renewing the vehicle.

6. An electronic device, comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle renewal information generation method based on vehicle positioning as described in any one of claims 1 to 4.

7. A storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, are used to execute the method for generating vehicle lease renewal information based on vehicle positioning according to any one of claims 1 to 4.

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