Vehicle operation management method and system for vehicle rental platform

Abstract

The invention relates to the technical field of vehicle renting, in particular to a vehicle operation management method and system for a vehicle renting platform. The method comprises the following steps: acquiring a vehicle use demand of a user, analyzing the vehicle use demand, and determining whether the user returns a vehicle or not according to a demand analysis result; if it is determined that the vehicle is returned, obtaining an initiating position of the vehicle using demand, determining a vehicle returning operation according to the initiating position, and sending the vehicle returning operation to the equipment of the user; and receiving and analyzing operation feedback of the user, determining whether vehicle returning is allowed or not according to a feedback analysis result, and after vehicle returning is allowed, obtaining a vehicle returning position and sending the vehicle returning position to equipment of a manager so as to perform vehicle scheduling. The method is advantaged in that vehicle scheduling is rapidly responded and planned, waiting time and necessity of manual intervention are reduced, scheduling efficiency is improved, the whole vehicle operation management process is more automatic and intelligent, the user can rapidly complete vehicle returning and using processes without waiting for manual processing, and user satisfaction is greatly improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle rental technology, and in particular to a vehicle operation management method and system for a vehicle rental platform. Background Art

[0002] As vehicle rental platforms have been widely used in recent years, they have provided a convenient way of travel for the majority of users. In vehicle rental services, vehicle operation management methods play a vital role in improving service quality, reducing operating costs and improving user satisfaction.

[0003] However, existing vehicle rental platforms have certain problems in operation and management, such as low vehicle dispatch efficiency and complex vehicle return operations for users. These problems limit the development and service quality of vehicle rental platforms. Summary of the invention

[0004] The present application provides a vehicle operation management method and system for a vehicle rental platform to solve the above-mentioned problems.

[0005] In a first aspect, the present application provides a vehicle operation management method for a vehicle rental platform, the method comprising: Obtaining the user's car use demand, analyzing the car use demand, and determining whether the user should return the car based on the demand analysis result; If the vehicle is determined to be returned, the initiation location of the vehicle use demand is obtained, and the vehicle return operation is determined according to the initiation location and sent to the user's device; Receive and analyze the user's operational feedback, determine whether to allow the vehicle to be returned based on the feedback analysis results, and if the vehicle is allowed to be returned, obtain the vehicle return location and send it to the manager's device for vehicle scheduling.

[0006] Through this solution, by obtaining and analyzing the user's vehicle use needs from the user's device, it is possible to determine in time whether the user needs to return the vehicle, thereby quickly responding to and planning vehicle scheduling, reducing waiting time and the necessity of manual intervention, and improving scheduling efficiency; automatically determining the return operation based on the user's initiating location, and sending the operation instructions to the user's device, so that the user can complete the return of the vehicle according to the instructions, simplifying the user's operation process and improving the user experience; by receiving and analyzing the user's operation feedback, the vehicle status of the rental vehicle can be accurately judged to decide whether to allow the return of the vehicle; after the user allows the return of the vehicle, the actual return location of the vehicle is obtained, and the information is sent to the manager's device, so that the manager can perform vehicle scheduling in real time to ensure the maximum utilization of vehicle resources; ensure that the vehicle can respond to new rental needs in a timely manner and maintain high efficiency and low-cost operation; the entire vehicle operation management process is more automated and intelligent, and users can quickly complete the return and use of the vehicle without waiting for manual processing, greatly improving user satisfaction.

[0007] Optionally, determining the vehicle return operation based on the initiating location includes: obtaining the vehicle handover location; determining a scheduling route based on the vehicle handover location and the initiating location; determining the vehicle return location based on the scheduling route and the initiating location; obtaining road condition information for each scheduling route; determining the scheduling duration and the scheduling cost based on the vehicle return location and the road condition information for each scheduling route; and determining the vehicle return operation based on a preset vehicle return method, the scheduling duration, the scheduling cost, and the vehicle return location.

[0008] Through this solution, the optimal dispatch route can be quickly calculated through the precise vehicle delivery location and initiation location, thereby reducing unnecessary driving distance and time and improving dispatch efficiency. By analyzing road conditions and dispatch costs, vehicle resources can be reasonably allocated to ensure that the vehicle can reach the user's location in a timely manner, while reducing operating costs. Users can easily complete the return process by receiving clear return instructions without complicated operating steps, thereby improving user experience. Dispatch strategies can be adjusted according to real-time road conditions information to avoid dispatch delays caused by traffic congestion or unexpected situations. Through precise dispatch and cost control, the vehicle rental platform can reduce unnecessary fuel consumption and waste of human resources, thereby reducing overall operating costs.

[0009] Optionally, analyzing the user's operation feedback and determining whether to allow the vehicle to be returned based on the feedback analysis results includes: extracting the operation feedback to obtain a vehicle return image; performing image analysis on the vehicle return image to determine whether there is an accident point for the vehicle; if it is determined that there is an accident point, retrieving historical vehicle delivery records to determine historical vehicle delivery videos and historical vehicle delivery pictures; analyzing the historical vehicle delivery videos and historical vehicle delivery pictures to determine whether the accident point is a historical accident; if the accident point is not a historical accident, determining the degree of accident damage based on the vehicle return image, and determining a vehicle damage price based on the degree of accident damage and sending it to the user's device; receiving vehicle damage feedback from the user, and determining whether the user accepts the vehicle damage price and pays it based on the vehicle damage feedback; if the user accepts the vehicle damage price and pays it, determining that the vehicle return is allowed.

[0010] This solution reduces manual review time and improves the speed and efficiency of vehicle return processing through automated image analysis and historical record comparison; provides more accurate accident damage assessment through image analysis and historical record comparison, reduces disputes caused by vehicle damage; automated processing reduces the need for manual intervention, thereby reducing operating costs; users can receive vehicle damage analysis and quotations in a short period of time, speeding up the vehicle return process.

[0011] Optionally, before determining the degree of accident damage based on the returned vehicle image, the method further includes: analyzing the returned vehicle image to determine the maximum brightness and the minimum brightness of the returned vehicle image; determining the image contrast based on the maximum brightness and the minimum brightness; determining whether the returned vehicle image meets the clarity standard based on the image contrast; if the clarity standard is not met, using an image segmentation algorithm to separate the returned vehicle image to determine the accident damage area; and performing histogram equalization on the accident damage area to enhance the display of the accident damage area.

[0012] Through this solution, by analyzing the brightness and contrast of the returned vehicle image, the damaged area in the image can be more accurately identified, thereby improving the accuracy of the assessment of the degree of accident damage; the automated image analysis process reduces the operations that users need to perform when returning the vehicle, simplifies the return process, and improves user satisfaction; relying on algorithms for image analysis and damage assessment reduces the subjectivity and errors of human judgment and improves the objectivity and consistency of the assessment; the automated image processing and damage assessment process speeds up the accident handling speed and reduces the manpower and time costs of the vehicle rental platform; clear image analysis and damage assessment results provide users with transparent services, and users can intuitively understand the damage to the vehicle; fast accident damage assessment results help rental companies make quick decisions, such as whether repairs are needed and how to price; by comparing historical delivery records and return vehicle images, it is possible to effectively identify and prevent users from concealing or exaggerating vehicle damage when returning the vehicle, and avoid rental companies from using accident points in historical accidents to deceive users while ensuring the rights and interests of rental companies.

[0013] Optionally, the analyzing of the demand for vehicle use and determining whether the user returns the vehicle based on the demand analysis results further includes: determining whether to use the vehicle based on the demand analysis results; if it is determined to use the vehicle, determining the vehicle usage budget and vehicle usage time based on the demand analysis results; determining a suitable vehicle based on the vehicle usage budget and the vehicle usage time, and based on the suitable vehicle, retrieving a preset vehicle information database to obtain suitable vehicle information; sending the suitable vehicle information to the user's device and receiving the user's vehicle selection; determining a final vehicle based on the vehicle selection; obtaining and analyzing the vehicle usage situation of the final vehicle, and determining a dispatchable vehicle based on the situation analysis results; obtaining the user's vehicle usage location, and determining a dispatch plan for the dispatchable vehicle based on the vehicle usage time and the vehicle usage location.

[0014] Through this solution, by analyzing user needs, the rental platform can provide more personalized vehicle recommendations and services, improve user satisfaction, and intelligently dispatch vehicles according to the user's vehicle usage time and location, reduce vehicle vacancy and waiting time, and improve vehicle utilization; users can easily complete demand analysis, vehicle selection and vehicle return operations through the rental platform's application or website, which simplifies the user's operation process; through intelligent scheduling and optimization of vehicle usage, the vehicle operation and maintenance costs can be reduced and the platform's profitability can be improved; fast-response user demand analysis and vehicle scheduling, as well as convenient vehicle return operations, can enhance the user's overall experience; efficient demand analysis and vehicle scheduling processes provide innovation space for the rental platform, and can develop more intelligent services.

[0015] Optionally, determining whether to allow the return of the vehicle based on the feedback analysis results includes: determining the vehicle status reported by the user based on the feedback analysis results; acquiring and analyzing vehicle detection data from a preset sensor device, and determining the actual vehicle status based on the data analysis results; comparing the vehicle status reported by the user with the actual vehicle status to determine whether there is a difference; if there is a difference, determining the type of difference based on the data analysis results, and determining the possibility of damage to the vehicle based on the type of difference; based on the possibility of damage to the vehicle, sending an image acquisition signal to the user, and receiving an image of a suspicious location uploaded by the user based on the image acquisition signal; analyzing the suspicious location image to determine whether there is a possibility of damage; if not, determining that the return of the vehicle is allowed.

[0016] Through this solution, by combining user feedback and sensor equipment detection data, the actual status of the vehicle can be evaluated more accurately, thereby reducing misjudgments and missed judgments; simplifying the user's vehicle return process, quickly determining whether the vehicle is damaged through data analysis, reducing user waiting time and unnecessary vehicle return operations; through timely feedback analysis and vehicle status monitoring, unnecessary vehicle maintenance and inspection costs can be reduced, while avoiding operational interruptions caused by vehicle problems; quickly responding to user feedback and accurately handling vehicle status issues can improve users' overall satisfaction with rental services; using data analysis results to guide whether the vehicle is allowed to be returned, making decisions more objective and scientific; through image verification and data analysis, disputes caused by user misreporting or misunderstanding can be reduced; through a strict vehicle status inspection process, possible fraud by users can be prevented, such as deliberately concealing vehicle damage.

[0017] Optionally, before determining that the vehicle is allowed to be returned if it does not exist, the method further includes: if it does not exist, obtaining the user's driving record to determine the user's driving behavior; obtaining the driving specifications in the driving record; determining whether the user has abnormal driving behavior based on the driving behavior and the driving specifications; if so, determining compensation information based on the driving specifications and the type of abnormal driving behavior and sending it to the user's device; after receiving the compensation data corresponding to the compensation information, determining that the vehicle is allowed to be returned.

[0018] Through this solution, by analyzing the user's driving records, the user's driving behavior can be monitored and evaluated more accurately, thereby providing more effective feedback and incentives; users know that their driving behavior will be recorded and analyzed, which may prompt them to pay more attention to driving safety and reduce violations; by monitoring driving behavior, the rental platform can provide more personalized services, such as additional training and guidance for high-risk driving behaviors; by reducing high-risk driving behaviors and vehicle damage, the rental platform can reduce repair costs and insurance premiums; providing transparent feedback and incentives can increase user satisfaction with the rental service.

[0019] Optionally, determining the extent of the accident damage based on the returned vehicle image includes: analyzing the returned vehicle image to determine a shooting angle and shooting light; after enhanced display of the accident damage area, filtering the accident damage area according to the shooting angle and the shooting light to obtain an image of an area without light spots; analyzing the image of the area without light spots to determine a damage type; and determining the extent of the accident damage based on the damage type.

[0020] Through this solution, through image analysis and light and shadow filtering, vehicle damage can be more accurately identified and assessed, reducing human errors; users can complete part of the vehicle return process by uploading the vehicle return image, without the need for on-site inspection, simplifying the operation; reducing the need for manual inspection, reducing labor costs and vehicle inspection time; rapid damage assessment and feedback can speed up the process of putting the vehicle back into service and improve vehicle utilization; a transparent and efficient damage assessment process can enhance users' trust in the rental service; through image analysis and light and shadow filtering, it can reduce possible fraud by users, such as vehicle damage cannot be hidden.

[0021] Optionally, before obtaining the driving record of the user and determining the driving behavior of the user, the method further includes: obtaining the driving location of the user; retrieving historical driving records based on the driving location; analyzing the historical driving records to determine common abnormal behaviors; and, based on the common abnormal behaviors, setting an alarm device to give a reminder at the location where the common abnormal behaviors occur.

[0022] Through this solution, by analyzing the user's driving location and historical driving records, common abnormal driving behaviors occurring at specific locations can be identified, so that alarm devices can be set at these locations to remind users to pay attention to driving safety; providing personalized driving safety reminders can enhance users' sense of security and satisfaction when using rental vehicles; through early warning of abnormal driving behaviors, it helps to reduce the occurrence of traffic accidents and improve road safety; analyzing users' driving records can help rental platforms dispatch vehicles more effectively and improve vehicle utilization efficiency and operational management; by preventing traffic accidents and reducing vehicle damage, rental platforms can reduce maintenance costs and insurance costs, thereby reducing operating costs.

[0023] In a second aspect, the present application provides a vehicle operation management system for a vehicle rental platform, including: A car return analysis module is used to obtain the user's car use demand, analyze the car use demand, and determine whether the user returns the car according to the demand analysis result; An operation sending module, for obtaining the initiation location of the vehicle use demand if the vehicle return is determined, and determining the vehicle return operation according to the initiation location and sending the operation to the user's device; The feedback analysis module is used to receive and analyze the user's operational feedback, determine whether to allow the vehicle to be returned based on the feedback analysis results, and if the vehicle is allowed to be returned, obtain the vehicle return location and send it to the manager's device for vehicle scheduling.

[0024] Optionally, when the operation sending module determines the vehicle return operation based on the initiating location, it is specifically used to: obtain the vehicle handover location; determine the scheduling route based on the vehicle handover location and the initiating location; determine the vehicle return location based on the scheduling route and the initiating location; obtain the road condition information of each scheduling route; determine the scheduling duration and the scheduling cost based on the vehicle return location and the road condition information of each scheduling route; determine the vehicle return operation based on the preset vehicle return method, the scheduling duration, the scheduling cost and the vehicle return location.

[0025] Optionally, the feedback analysis module analyzes the user's operational feedback, and determines whether to allow the vehicle to be returned based on the feedback analysis results, and is used to: extract the operational feedback to obtain a vehicle return image; perform image analysis on the vehicle return image to determine whether there is an accident point for the vehicle; if it is determined that there is an accident point, retrieve historical vehicle delivery records to determine historical vehicle delivery videos and historical vehicle delivery pictures; analyze the historical vehicle delivery videos and historical vehicle delivery pictures to determine whether the accident point is a historical accident; if the accident point is not a historical accident, determine the degree of accident damage based on the vehicle return image, and determine the vehicle damage price based on the accident damage degree and send it to the user's device; receive the user's vehicle damage feedback, and determine whether the user accepts the vehicle damage price and pays it based on the vehicle damage feedback; if the user accepts the vehicle damage price and pays it, determine that the vehicle return is allowed.

[0026] Optionally, the vehicle operation management system for the vehicle rental platform also includes an image adjustment module, which is used to: analyze the vehicle return image to determine the maximum brightness and the minimum brightness of the vehicle return image; determine the image contrast based on the maximum brightness and the minimum brightness; determine whether the vehicle return image meets the clarity standard based on the image contrast; if the clarity standard is not met, use an image segmentation algorithm to separate the vehicle return image and determine the accident damage area; and perform histogram equalization on the accident damage area to enhance the display of the accident damage area.

[0027] Optionally, the vehicle operation management system for the vehicle rental platform also includes a vehicle use analysis module, which is used to: determine whether to use a vehicle based on the results of demand analysis; if it is determined to use a vehicle, determine the vehicle use budget and vehicle use time based on the results of demand analysis; determine a suitable vehicle based on the vehicle use budget and the vehicle use time, and based on the suitable vehicle, retrieve a preset vehicle information database to obtain suitable vehicle information; send the suitable vehicle information to the user's device and receive the user's vehicle selection; determine a final vehicle based on the vehicle selection; obtain and analyze the vehicle usage of the final vehicle, and determine a dispatchable vehicle based on the situation analysis results; obtain the user's vehicle use location, and determine a dispatch plan for the dispatchable vehicle based on the vehicle use time and the vehicle use location.

[0028] Optionally, when the feedback analysis module determines whether to allow the return of the vehicle based on the feedback analysis results, it is specifically used to: determine the vehicle status reported by the user based on the feedback analysis results; obtain and analyze vehicle detection data from a preset sensor device, and determine the actual vehicle status based on the data analysis results; compare the vehicle status reported by the user with the actual vehicle status to determine whether there is a difference; if there is a difference, determine the type of difference based on the data analysis results, and determine the possibility of damage to the vehicle based on the type of difference; based on the possibility of damage to the vehicle, send an image acquisition signal to the user, and receive an image of a suspicious location uploaded by the user based on the image acquisition signal; analyze the suspicious location image to determine whether there is a possibility of damage; if not, determine that the return of the vehicle is allowed.

[0029] Optionally, the vehicle operation management system for the vehicle rental platform also includes a compensation analysis module, which is used to: if it does not exist, obtain the user's driving record to determine the user's driving behavior; obtain the driving specifications in the driving record; determine whether the user has abnormal driving behavior based on the driving behavior and the driving specifications; if so, determine the compensation information based on the driving specifications and the type of abnormal driving behavior and send it to the user's device; after receiving the compensation data corresponding to the compensation information, determine whether the vehicle return is allowed.

[0030] Optionally, when the feedback analysis module determines the extent of the accident damage based on the returned vehicle image, it is used to: analyze the returned vehicle image to determine the shooting angle and the shooting light; after the enhanced display of the accident damage area, filter the light and shadow of the accident damage area according to the shooting angle and the shooting light to obtain an image of the area without light spots; analyze the image of the area without light spots to determine the type of damage; and determine the extent of the accident damage based on the damage type.

[0031] Optionally, the vehicle operation management system for the vehicle rental platform also includes an alarm reminder module, which is used to: obtain the driving location of the user; retrieve historical driving records based on the driving location; analyze the historical driving records to determine common abnormal behaviors; and based on the common abnormal behaviors, set an alarm device to remind at the location where the common abnormal behaviors belong. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flow chart of a vehicle operation management method for a vehicle rental platform provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a vehicle operation management system for a vehicle rental platform provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments 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 without creative work are within the scope of protection of this application.

[0035] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0036] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0037] With the widespread use of vehicle rental platforms in recent years, it has provided a convenient way of travel for the majority of users. In vehicle rental services, vehicle operation management methods play a vital role in improving service quality, reducing operating costs and improving user satisfaction. However, existing vehicle rental platforms have certain problems in operation and management, such as low vehicle dispatching efficiency and complex user return operations. These problems limit the development and service quality of vehicle rental platforms.

[0038] Based on this, the present application provides a vehicle operation management method and system for a vehicle rental platform, which obtains the user's vehicle demand, analyzes the vehicle demand, and determines whether the user returns the vehicle based on the demand analysis results; if the vehicle is determined to be returned, the initiation location of the vehicle demand is obtained, and the return operation is determined based on the initiation location and sent to the user's device; the user's operation feedback is received and analyzed, and based on the feedback analysis results, it is determined whether the return of the vehicle is allowed, and after the return of the vehicle is allowed, the vehicle return location is obtained and sent to the manager's device for vehicle scheduling. By obtaining and analyzing the user's car use needs, it is possible to determine in a timely manner whether the user needs to return the car, so as to quickly respond and plan vehicle scheduling, reduce waiting time and the necessity of manual intervention, and improve scheduling efficiency; automatically determine the return operation based on the user's initiation location, and send the operation instructions to the user's device, so that the user can complete the return of the car according to the instructions, simplifying the user's operation process and improving the user experience; by receiving and analyzing the user's operation feedback, the vehicle status can be accurately judged to decide whether to allow the return of the car; after the user allows the return of the car, the actual return location of the vehicle is obtained, and the information is sent to the manager's device, so that the manager can perform vehicle scheduling in real time to ensure the maximum utilization of vehicle resources; the entire vehicle operation management process is more automated and intelligent, and users can quickly complete the return and use of the car without waiting for manual processing, which greatly improves user satisfaction.

[0039] Figure 1 A schematic diagram of an application scenario provided by the present application is provided. When a user returns a rented car, the method provided by the present application is applied. Specifically, the method provided by the present application is applied to any server, and the server interacts with the rented vehicle and the user's device. By obtaining the user's car use needs from the user's device and analyzing them, it can be determined in time whether the user needs to return the car, thereby quickly responding and planning vehicle scheduling, reducing waiting time and the necessity of manual intervention, and improving scheduling efficiency; automatically determining the return operation according to the user's initiation location, and sending the operation instructions to the user's device, so that the user can complete the return according to the instructions, simplifying the user's operation process and improving the user experience; by receiving and analyzing the user's operation feedback, the vehicle status of the rented vehicle can be accurately judged to determine whether to allow the return; after the user allows the return, the actual return location of the vehicle is obtained, and the information is sent to the management personnel's device, so that the management personnel can perform vehicle scheduling in real time to ensure the maximum utilization of vehicle resources; the entire vehicle operation management process is more automated and intelligent, and the user can quickly complete the return and use of the vehicle without waiting for manual processing, greatly improving user satisfaction. The specific implementation method can refer to the following embodiments.

[0040] Figure 2This is a flow chart of a vehicle operation management method for a vehicle rental platform provided in an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Obtain the user's car use demand, analyze the car use demand, and determine whether the user returns the car based on the demand analysis result.

[0041] The vehicle demand may be the specific requirements of the user who wishes to rent a vehicle through the vehicle rental platform, including but not limited to the rental time period, rental vehicle model, rental destination, expected driving route, etc.

[0042] Specifically, users submit car rental needs through the application of the car rental platform, including information such as the time of use and destination. After receiving the user's needs, the platform server records and analyzes the user's car usage pattern, such as frequency, time period, and commonly used car models. According to the user's historical data and real-time needs, the needs are analyzed using data mining and machine learning algorithms. The analysis results are used to determine whether the user is ready to return the car. If it is determined to be a return, the next step will be taken. If not, a renewal option may be provided or the user may be reminded of the rental time. For example, if the user submits a demand when the rental time is about to end, it may be predicted that the user is about to return the car. S202: If the vehicle is determined to be returned, the initiation location of the vehicle use demand is obtained, and the vehicle return operation is determined according to the initiation location and sent to the user's device.

[0043] The initiating location may be the location where the user is when submitting the car request, which is usually obtained through the built-in GPS or other positioning services of the user's device (such as a smartphone).

[0044] The vehicle return operation can be a series of instructions or actions for the user to return the vehicle to the designated location according to the platform's instructions after the rental is completed; including the designated return point, return time, and vehicle inspection process when returning the vehicle.

[0045] Specifically, if it is determined to be a vehicle return, the location information of the user when submitting the vehicle request is obtained through the GPS or similar positioning technology installed on the rental vehicle; based on the user's initiating location, the optimal vehicle return operation is planned, such as specifying the nearest vehicle return point; and the detailed information of the vehicle return operation is sent to the user's device to guide the user to complete the vehicle return.

[0046] S203, receiving and analyzing the user's operational feedback, determining whether to allow the vehicle to be returned based on the feedback analysis result, and after allowing the vehicle to be returned, obtaining the vehicle return location and sending it to the manager's device for vehicle scheduling.

[0047] The operation feedback may be information about the vehicle return process submitted by the user through the rental platform on the user's device after the user completes the vehicle return operation.

[0048] Vehicle dispatching can be the process of rationally allocating and arranging vehicles based on factors such as vehicle usage, user demand, and vehicle location.

[0049] Specifically, after the user completes the vehicle return operation, the user submits feedback through the user's device, and the received feedback is automatically analyzed to evaluate the vehicle's condition; based on the feedback analysis results, it is determined whether the vehicle is damaged or has other problems. If the vehicle is in normal condition, the vehicle will be allowed to be returned; if there is a problem, the user will be notified and guided on the subsequent operations.

[0050] After the vehicle return is allowed, the actual return location of the vehicle will be obtained; the return location information will be sent to the manager's device so that the manager can dispatch the vehicle in time; the manager will formulate a dispatch plan based on the information received, combined with the current vehicle distribution and user needs.

[0051] Through this solution, by obtaining and analyzing the user's vehicle use needs from the user's device, it is possible to determine in time whether the user needs to return the vehicle, thereby quickly responding to and planning vehicle scheduling, reducing waiting time and the necessity of manual intervention, and improving scheduling efficiency; automatically determining the return operation based on the user's initiating location, and sending the operation instructions to the user's device, so that the user can complete the return of the vehicle according to the instructions, simplifying the user's operation process and improving the user experience; by receiving and analyzing the user's operation feedback, the vehicle status of the rental vehicle can be accurately judged to decide whether to allow the return of the vehicle; after the user allows the return of the vehicle, the actual return location of the vehicle is obtained, and the information is sent to the manager's device, so that the manager can perform vehicle scheduling in real time to ensure the maximum utilization of vehicle resources; ensure that the vehicle can respond to new rental needs in a timely manner and maintain high efficiency and low-cost operation; the entire vehicle operation management process is more automated and intelligent, and users can quickly complete the return and use of the vehicle without waiting for manual processing, greatly improving user satisfaction.

[0052] In some embodiments, the vehicle delivery position is obtained; the dispatch route is determined based on the vehicle delivery position and the initiation position; the return position is determined based on the dispatch route and the initiation position; the road condition information of each dispatch route is obtained; the dispatch duration and the dispatch cost are determined based on the return position and the road condition information of each dispatch route; based on the preset return method, the return operation is determined according to the dispatch duration, the dispatch cost and the return position.

[0053] The vehicle delivery location may be the location where the vehicle is picked up by the lessee, usually at a delivery point provided by the leasing company or a location designated by the lessee.

[0054] The dispatch route can be a driving path from the location of the rental company to the user's designated return location.

[0055] The return location can be the place where the user returns the leased vehicle, which is usually a return point designated by the rental company, or it can be any legal location selected by the user according to the platform's instructions.

[0056] Traffic information can be real-time data about road conditions, including traffic flow, accident reports, road construction, weather conditions, speed limit information, etc.

[0057] The dispatch time can be the total time required from the vehicle delivery location to the vehicle return location, including driving time, parking waiting time, traffic congestion time, etc.

[0058] The dispatch cost may be the cost incurred in performing the dispatch task, which includes but is not limited to fuel cost, vehicle depreciation, driver wages, vehicle maintenance costs, etc.

[0059] The preset return method can be the return process pre-set by the vehicle rental platform, including self-service return, scheduled return, and out-of-town return.

[0060] Specifically, a car is needed during some business trips and self-driving travels. For example, when a business trip arrives at the West Station of a city, the business tripper needs to drop off multiple customers and leave from the East Station at noon on the third day; or when driving a car, for example, the business tripper starts from a certain place, enjoys the scenery along the way, and returns the car to the destination after arriving at the destination and leaves by train; therefore, it is necessary to obtain the vehicle delivery position at the beginning of the user's rental through GPS positioning or user input, and use the map service API to plan a dispatch route from the delivery position to the initiation position in combination with the vehicle delivery position and the position where the user initiates the return request. According to the dispatch route and the initiation position, the best position for the user to return the car is determined, which may be the nearest return point, or may be based on the results of vehicle demand distribution and cost-benefit analysis, or may be the user's vehicle delivery position. By cooperating with a traffic information provider or using a public transportation data API to obtain real-time road condition information of the dispatch route, based on the road condition information, the estimated dispatch time and cost from the location of the rental company to the return location are calculated, and the final return operation is determined according to the preset return method (such as self-service return, scheduled return, off-site vehicle exchange, etc.), combined with the dispatch time, dispatch cost and return location.

[0061] Through this solution, the optimal dispatch route can be quickly calculated through the precise vehicle delivery location and initiation location, thereby reducing unnecessary driving distance and time and improving dispatch efficiency. By analyzing road conditions and dispatch costs, vehicle resources can be reasonably allocated to ensure that the vehicle can reach the user's location in a timely manner, while reducing operating costs. Users can easily complete the return process by receiving clear return instructions without complicated operating steps, thereby improving user experience. Dispatch strategies can be adjusted according to real-time road conditions information to avoid dispatch delays caused by traffic congestion or unexpected situations. Through precise dispatch and cost control, the vehicle rental platform can reduce unnecessary fuel consumption and waste of human resources, thereby reducing overall operating costs.

[0062] In some embodiments, operation feedback is extracted to obtain a vehicle return image; image analysis is performed on the vehicle return image to determine whether there is an accident point for the vehicle; if it is determined that there is an accident point, historical vehicle delivery records are retrieved to determine historical vehicle delivery videos and historical vehicle delivery pictures; historical vehicle delivery videos and historical vehicle delivery pictures are analyzed to determine whether the accident point is a historical accident; if the accident point is not a historical accident, the degree of accident damage is determined based on the vehicle return image, and based on the degree of accident damage, the vehicle damage price is determined and sent to the user's device; the user's vehicle damage feedback is received, and based on the vehicle damage feedback, it is determined whether the user accepts the vehicle damage price and pays; if the user accepts the vehicle damage price and pays, it is determined that the vehicle return is allowed.

[0063] Operation feedback can be the user's evaluation and opinions on the vehicle condition, service quality, etc. during the vehicle rental process. The return image can be a photo or video taken by the user when returning the vehicle, which is used to record the condition of the vehicle when it is returned, so as to facilitate the vehicle rental platform to conduct vehicle inspection and damage assessment. The accident point can be the specific location of the collision, scratch or other forms of damage to the vehicle during the rental process. The historical delivery record can be the relevant record of each delivery of the vehicle during the rental process, including the vehicle condition, damage record, user signature, etc. The historical delivery video can be a video recorded when the vehicle is delivered, which is used to record the condition of the vehicle at the time of delivery, including the appearance, interior, etc. The historical delivery picture can be a photo taken when the vehicle is delivered, which is used to record the condition of the vehicle at the time of delivery, including the appearance, interior, etc. The degree of accident damage can be the degree of damage suffered by the vehicle in the accident, which can be divided into different levels such as slight, moderate, and severe. The vehicle damage price can be the repair cost calculated based on the degree of damage to the vehicle.

[0064] Vehicle damage feedback can be the user's opinions and feedback on the vehicle damage assessment and quotation proposed by the vehicle rental platform.

[0065] Specifically, the user uploads photos or videos of the vehicle return through the mobile application of the rental platform, and fills in relevant text feedback. Image analysis is performed on the vehicle return images or videos uploaded by the user, and computer vision technology is used to detect whether there are new accident points in the vehicle. If the image analysis detects an accident point, the location and characteristics of these accident points are recorded, and the historical delivery records of the vehicle are retrieved and retrieved, including videos and pictures of historical deliveries. By comparing the historical delivery records with the current vehicle return images, it is analyzed whether the accident point is a historical accident. If the accident point is not a historical accident, the degree of damage at the accident point will be evaluated based on the image analysis results, and the corresponding vehicle damage price will be calculated based on the degree of accident damage. The calculated vehicle damage price will be sent to the user's device for confirmation. The user will provide feedback on whether to accept this price based on the received vehicle damage price and decide whether to pay. If the user accepts the vehicle damage price and completes the payment, the user is allowed to return the vehicle. If the user does not accept the vehicle damage price or refuses to pay, the user will be notified of further operation steps, which may include vehicle repairs, insurance claims, etc.

[0066] This solution reduces manual review time and improves the speed and efficiency of vehicle return processing through automated image analysis and historical record comparison; provides more accurate accident damage assessment through image analysis and historical record comparison, reduces disputes caused by vehicle damage; automated processing reduces the need for manual intervention, thereby reducing operating costs; users can receive vehicle damage analysis and quotations in a short period of time, speeding up the vehicle return process.

[0067] In some embodiments, the vehicle return image is analyzed to determine the maximum brightness and the minimum brightness of the vehicle return image; the image contrast is determined based on the maximum brightness and the minimum brightness; based on the image contrast, it is determined whether the vehicle return image meets the clarity standard; if the clarity standard is not met, the image segmentation algorithm is used to separate the vehicle return image to determine the accident damage area; the accident damage area is histogram equalized to enhance the display of the accident damage area.

[0068] The clarity standard can be a set of preset requirements for image clarity, including parameters such as contrast, resolution, and noise level, which are stored in a preset database. Image segmentation algorithms can be a set of techniques and methods for segmenting an image into multiple meaningful parts. Image separation can be the separation of different parts in an image (such as foreground and background, different objects, etc.). The accident damage area can be the damaged part of the vehicle shown in the image after the vehicle has an accident. Including scratches, dents, cracks and other damage. Histogram equalization can be an image enhancement technology that makes the brightness distribution of the image more uniform by redistributing the pixel values ​​of the image, thereby enhancing the contrast and details of the image. Enhanced display can be through image processing technology to make certain parts of the image (such as accident damage areas) more prominent and obvious for easy observation and analysis.

[0069] Specifically, the return image is preprocessed, including denoising, adjusting resolution, standardizing brightness, etc., to ensure image quality. The brightness value of the return image is calculated by analyzing the grayscale value of each pixel in the image, and the maximum and minimum brightness values ​​in the image are determined. These two values ​​can reflect the overall brightness and contrast of the image; the image contrast is calculated based on the maximum and minimum brightness values; based on the calculated contrast, it is evaluated whether the return image meets the preset clarity standard. In the case of some small scratches or changing cars at night, if the image contrast is lower than a certain threshold, the damage point may not be clearly displayed; if the return image does not meet the clarity standard, an image segmentation algorithm is used to separate the image, separate the vehicle from the background, or separate the damaged area from other areas; after image segmentation, the separated area is further analyzed to determine the accident damage area; the histogram equalization technology is applied to the determined accident damage area to improve the contrast of the area and make the damage point more obvious; according to the enhanced image and the characteristics of the accident damage area, the degree of damage is analyzed and evaluated.

[0070] Through this solution, by analyzing the brightness and contrast of the returned vehicle image, the damaged area in the image can be more accurately identified, thereby improving the accuracy of the assessment of the degree of accident damage; the automated image analysis process reduces the operations that users need to perform when returning the vehicle, simplifies the return process, and improves user satisfaction; relying on algorithms for image analysis and damage assessment reduces the subjectivity and errors of human judgment and improves the objectivity and consistency of the assessment; the automated image processing and damage assessment process speeds up the accident handling speed and reduces the manpower and time costs of the vehicle rental platform; clear image analysis and damage assessment results provide users with transparent services, and users can intuitively understand the damage to the vehicle; fast accident damage assessment results help rental companies make quick decisions, such as whether repairs are needed and how to price; by comparing historical delivery records and return vehicle images, it is possible to effectively identify and prevent users from concealing or exaggerating vehicle damage when returning the vehicle, and avoid rental companies from using accident points in historical accidents to deceive users while ensuring the rights and interests of rental companies.

[0071] In some embodiments, based on the results of demand analysis, it is determined whether to use a vehicle; if it is determined to use a vehicle, the vehicle usage budget and vehicle usage time are determined based on the results of demand analysis; based on the vehicle usage budget and vehicle usage time, a suitable vehicle is determined, and based on the suitable vehicle, a preset vehicle information library is retrieved to obtain suitable vehicle information; the applicable vehicle information is sent to the user's device, and the user's vehicle selection is received; based on the vehicle selection, a final vehicle is determined; the vehicle usage situation of the final vehicle is obtained and analyzed, and a dispatchable vehicle is determined based on the situation analysis results; the user's vehicle usage location is obtained, and a dispatch plan for the dispatchable vehicle is determined based on the vehicle usage time and vehicle usage location.

[0072] The preset vehicle information database can be an information database pre-established by the vehicle rental platform that contains a variety of vehicle information, including the vehicle model, license plate number, maintenance record, current location, rental price, vehicle status (such as available, waiting for repair or under repair), etc. stored in the preset database.

[0073] Applicable vehicle information may be qualified vehicle information screened out from a preset vehicle information database based on the user's vehicle needs, including vehicle model, rental, vehicle photos, vehicle performance parameters, etc.

[0074] The vehicle usage status may be the actual usage status of the vehicle during the rental process, including the vehicle's mileage, usage frequency, damage record, refueling record, cleaning status, etc.

[0075] A dispatchable vehicle can be a vehicle available for rent that the rental platform determines meets the rental standards based on vehicle usage and user needs, and is able to provide services within the time required by the user.

[0076] Specifically, users input their car use needs, including the purpose of using the car, the time of using the car, the location of using the car, etc. through the application of the rental platform, and the needs input by the user are analyzed to determine whether the user needs to use the car, as well as the time period and location of the car use; according to the user's needs, the user is helped to determine the budget and specific time schedule for using the car; according to the user's budget, the time and location of the car use, a suitable vehicle type is selected from the preset vehicle information library; the screened applicable vehicle information is sent to the user's device for the user's reference and selection; after viewing the vehicle information, the user selects the most suitable vehicle according to personal preferences and needs; based on the user's vehicle selection, the final vehicle to be provided is determined and reserved for the user's use; during peak periods of car rental such as holidays, when many vehicles are in a tight idle time situation, the current usage of the selected vehicle is obtained and analyzed, including the availability, maintenance status, location, etc. of the vehicle; according to the usage of the vehicle and the user's time and location of the vehicle, a vehicle scheduling plan is formulated to ensure that the vehicle can arrive at the user's designated location at the appropriate time.

[0077] Through this solution, by analyzing user needs, the rental platform can provide more personalized vehicle recommendations and services, improve user satisfaction, and can intelligently dispatch vehicles according to the user's vehicle usage time and location, reduce vehicle vacancy and waiting time, and improve vehicle utilization; users can easily complete demand analysis, vehicle selection and vehicle return operations through the rental platform's application or website, which simplifies the user's operation process; through intelligent scheduling and optimization of vehicle usage, the vehicle operation and maintenance costs can be reduced and the platform's profitability can be improved; fast-response user demand analysis and vehicle scheduling, as well as convenient vehicle return operations, can enhance the user's overall experience; efficient demand analysis and vehicle scheduling processes provide innovation space for the rental platform, and can develop more intelligent services, such as real-time vehicle tracking, automatic vehicle return, etc.; through detailed analysis of vehicle usage, it can effectively identify and prevent user fraud during vehicle use, such as overtime vehicle return, false damage report, etc.

[0078] In some embodiments, based on the feedback analysis results, the vehicle status reported by the user is determined; the vehicle detection data of the preset sensor equipment is obtained and analyzed, and the actual vehicle status is determined based on the data analysis results; the vehicle status reported by the user and the actual vehicle status are compared to determine whether there is a difference; if there is a difference, the type of difference is determined based on the data analysis results, and the possibility of damage to the vehicle is determined based on the type of difference; based on the possibility of damage to the vehicle, an image acquisition signal is sent to the user, and an image of a suspicious location uploaded by the user based on the image acquisition signal is received; the suspicious location image is analyzed to determine whether there is a possibility of damage; if not, it is determined that the vehicle is allowed to be returned.

[0079] The vehicle status may be the current condition of the vehicle, including the physical condition of the vehicle (such as whether there is any damage, cleanliness), technical condition (such as whether various functions are normal), location information, etc.

[0080] The preset sensing equipment can be various sensors and monitoring equipment pre-installed on the vehicle by the vehicle rental platform, such as GPS locator, driving recorder, accelerometer, vibration sensor, etc.

[0081] Vehicle detection data can be information about the vehicle status collected by preset sensing equipment, such as the vehicle's location, speed, mileage, collision record, abnormal vibration, etc.

[0082] The actual state of the vehicle may be the actual situation of the vehicle, such as whether the vehicle has been in a collision, whether there is damage, whether maintenance is required, etc.

[0083] The discrepancy type can be an inconsistency between the vehicle status reported by the user and the actual vehicle status, including minor errors (such as the user's inaccurate description of the extent of damage) or major inconsistencies (such as the user did not report serious damage).

[0084] The vehicle damage may be the degree and probability of possible damage to the vehicle obtained based on user feedback and sensor equipment data analysis.

[0085] Suspicious location images can be pictures of specific parts of the vehicle uploaded by users according to the requirements of the rental platform, which are used to help the platform evaluate whether the vehicle is actually damaged.

[0086] Damage may be determined by analyzing images uploaded by users and sensor device data to determine whether the vehicle is actually damaged.

[0087] Specifically, users submit feedback about the vehicle status through the rental platform's application or website, such as vehicle damage, cleanliness, functional failures, etc. The feedback submitted by users is analyzed to determine the vehicle status reported by users, such as the specific location, degree and possible causes of damage; vehicle detection data is obtained from preset sensor equipment, such as GPS, accelerometer, and driving recorder to monitor the location and movement status of the vehicle; the collected vehicle detection data is analyzed in detail to determine the actual status of the vehicle, such as whether the vehicle has moved abnormally or whether there is new damage; the vehicle status reported by users is compared with the actual status detected by the sensor equipment to determine whether there is a difference; if there is a difference, determine the type of difference based on the data analysis results, such as whether it is a false alarm by the user, minor damage or serious damage; based on the type of difference, assess the possibility of damage to the vehicle and determine whether further investigation is needed; if necessary, send an image acquisition signal to the user to request the user to upload images of suspicious locations; after the user uploads images of suspicious locations, analyze the received images to determine whether there is damage; if the analysis results show that the vehicle is not damaged or the damage is within an acceptable range, determine to allow the user to return the vehicle; if there is serious damage or it cannot be determined, require the user to wait for further inspection or refuse to return the vehicle online.

[0088] Through this solution, by combining user feedback and sensor equipment detection data, the actual status of the vehicle can be evaluated more accurately, thereby reducing misjudgments and missed judgments; simplifying the user's vehicle return process, quickly determining whether the vehicle is damaged through data analysis, reducing user waiting time and unnecessary vehicle return operations; through timely feedback analysis and vehicle status monitoring, unnecessary vehicle maintenance and inspection costs can be reduced, while avoiding operational interruptions caused by vehicle problems; quickly responding to user feedback and accurately handling vehicle status issues can improve users' overall satisfaction with rental services; using data analysis results to guide whether the vehicle is allowed to be returned, making decisions more objective and scientific; through image verification and data analysis, disputes caused by user misreporting or misunderstanding can be reduced; through a strict vehicle status inspection process, possible fraud by users can be prevented, such as deliberately concealing vehicle damage.

[0089] In some embodiments, if it does not exist, the user's driving record is obtained to determine the user's driving behavior; the driving regulations in the driving record are obtained; based on the driving behavior and the driving regulations, it is determined whether the user has abnormal driving behavior; if so, the compensation information is determined based on the driving regulations and the type of abnormal driving behavior and sent to the user's device; after receiving the compensation data corresponding to the compensation information, it is determined that the return of the vehicle is allowed.

[0090] Driving records can be detailed data about the vehicle's driving process recorded by built-in or external devices in the vehicle. Driving behavior can be the actions and operations taken by the driver during driving, including but not limited to acceleration, deceleration, turning, parking, etc. Driving regulations can be the basic rules and standards for safe driving set by the vehicle rental platform or relevant institutions. Abnormal driving behavior can be driving behavior that does not meet driving regulations or safe driving standards. Including but not limited to speeding, sudden braking, sharp turns, and fatigue driving.

[0091] Compensation information can be a reward or compensation measure provided by the rental platform to the user in response to the user's abnormal driving behavior or vehicle problems, which may include rental discounts, points, coupons, repair cost reimbursement, etc. Compensation data can be specific values ​​or information related to compensation information, such as discount amount, number of points, coupon code, etc.

[0092] Specifically, through the previous analysis, confirm that the vehicle status reported by the user is consistent with the actual status and there is no damage; obtain the user's driving record from the background of the rental platform or the device connected to the vehicle within the scope permitted by law and authorized by the user, including data such as driving route, speed, sudden braking, sharp turns, etc.; use data analysis tools to analyze key parameters in the driving record, such as average speed, maximum speed, number of sudden braking, etc., to determine whether the user's driving behavior complies with driving regulations; in order to control driving risks caused by unsafe driving behaviors such as racing and chasing, or the situation where the user's normal use is affected by vehicle problems during driving, it is necessary to obtain the driving regulations set by the platform, including basic principles and standards for safe driving; compare the user's driving behavior with the driving regulations to check whether there is any abnormal behavior; if it is found that the user's driving behavior does not comply with the driving regulations, identify the specific type of abnormal behavior, such as speeding, sudden braking, sharp turns, etc.; determine the corresponding compensation information according to the driving regulations and the type of abnormal driving behavior; send the determined compensation information to the user's device to notify the user; after receiving the compensation information, the user makes a payment operation and determines to allow the user to return the vehicle.

[0093] Through this solution, by analyzing the user's driving records, the user's driving behavior can be monitored and evaluated more accurately, thereby providing more effective feedback and incentives; users know that their driving behavior will be recorded and analyzed, which may prompt them to pay more attention to driving safety and reduce violations; by monitoring driving behavior, the rental platform can provide more personalized services, such as additional training and guidance for high-risk driving behaviors; by reducing high-risk driving behaviors and vehicle damage, the rental platform can reduce repair costs and insurance premiums; providing transparent feedback and incentives can increase user satisfaction with the rental service.

[0094] In some embodiments, the vehicle return image is analyzed to determine the shooting angle and shooting light; after the accident damage area is enhanced and displayed, the accident damage area is filtered for light and shadow according to the shooting angle and shooting light to obtain an image of the area without light spots; the image of the area without light spots is analyzed to determine the type of damage; and the degree of accident damage is determined according to the type of damage.

[0095] The shooting angle may be the position and viewing angle of the photographer relative to the subject when taking the photo or video. The shooting light may be the light source conditions used when shooting, including natural light and artificial light. Light and shadow filtering may be a technology for processing light and shadow in an image to improve the quality and visual effect of the image. A light spot-free area image may be an image that uses light and shadow filtering technology to remove or reduce light spots, reflections or highlights in the image during image processing to highlight other details. The damage type may be different types of damage suffered by the vehicle during an accident or use.

[0096] Specifically, when returning a vehicle, the user uploads a return image of the vehicle through the rental platform's application or designated return process; performs preliminary processing on the uploaded return image, including cropping, resizing, contrast enhancement, etc., to ensure that the image quality meets the analysis requirements; analyzes the shooting angle and lighting conditions of the image to determine how to adjust subsequent light and shadow processing; uses image processing techniques, such as edge detection and area selection, to identify and enhance accident damage areas in the image; applies light and shadow filtering technology based on the shooting angle and lighting conditions to reduce or eliminate light spots, reflections, and shadows in the damaged area, thereby obtaining a clearer image of the damaged area; analyzes the image of the light spot-free area after light and shadow filtering to determine the type and distribution of damage; identifies the type of damage, such as scratches, dents, tears, wear, etc., based on the image analysis results; assesses the extent of the damage based on the type of damage, combined with the area, depth, and distribution of the damage; generates a report based on the analysis results and the extent of the damage.

[0097] Through this solution, through image analysis and light and shadow filtering, vehicle damage can be more accurately identified and assessed, reducing human errors; users can complete part of the vehicle return process by uploading the vehicle return image, without the need for on-site inspection, simplifying the operation; reducing the need for manual inspection, reducing labor costs and vehicle inspection time; rapid damage assessment and feedback can speed up the process of putting the vehicle back into service and improve vehicle utilization; a transparent and efficient damage assessment process can enhance users' trust in the rental service; through image analysis and light and shadow filtering, it can reduce possible fraud by users, such as vehicle damage cannot be hidden.

[0098] In some embodiments, the driving location of the user is obtained; historical driving records are retrieved based on the driving location; historical driving records are analyzed to determine common abnormal behaviors; and based on the common abnormal behaviors, an alarm device is set to provide reminders at the locations where the common abnormal behaviors occur.

[0099] The driving location can be the geographical location of the vehicle during driving. The historical driving record can be the detailed data about the vehicle's past driving stored on the server, including driving time, speed, route, location and other information. Common abnormal behavior can be abnormal driving behavior that often occurs during vehicle driving. Alarm device can be a device used to remind or warn the driver of certain situations. The location can be a geographical location related to a specific behavior or event.

[0100] Specifically, the user's driving location is obtained in real time through the vehicle's GPS or the location service of the user's mobile phone; based on the user's real-time driving location, the historical driving records of the location are retrieved from the database. Data analysis tools are used to analyze historical driving records to identify common abnormal behaviors that occur at the location, such as speeding, sudden braking, illegal lane changes, etc.; based on the analysis results, alarm devices are set at the locations of common abnormal behaviors, such as vehicle-mounted reminder devices, mobile application notifications, etc.; when the user approaches or is at the location of common abnormal behaviors, the alarm device triggers a reminder to inform the user to drive safely.

[0101] Through this solution, by analyzing the user's driving location and historical driving records, common abnormal driving behaviors occurring at specific locations can be identified, so that alarm devices can be set at these locations to remind users to pay attention to driving safety; providing personalized driving safety reminders can enhance users' sense of security and satisfaction when using rental vehicles; through early warning of abnormal driving behaviors, it helps to reduce the occurrence of traffic accidents and improve road safety; analyzing users' driving records can help rental platforms dispatch vehicles more effectively and improve vehicle utilization efficiency and operational management; by preventing traffic accidents and reducing vehicle damage, rental platforms can reduce maintenance costs and insurance costs, thereby reducing operating costs.

[0102] Figure 3A schematic diagram of a vehicle operation management system for a vehicle rental platform provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, the vehicle operation management system 300 for the vehicle rental platform of this embodiment includes: a vehicle return analysis module 301 , an operation sending module 302 , and a feedback analysis module 303 .

[0103] The car return analysis module 301 is used to obtain the user's car use demand, analyze the car use demand, and determine whether the user returns the car according to the demand analysis result; The operation sending module 302 is used to obtain the initiation location of the vehicle demand if the vehicle return is determined, determine the vehicle return operation according to the initiation location, and send it to the user's device; The feedback analysis module 303 is used to receive and analyze the user's operational feedback, determine whether to allow the vehicle to be returned based on the feedback analysis results, and if the vehicle is allowed to be returned, obtain the vehicle return location and send it to the manager's device for vehicle scheduling.

[0104] Optionally, when the operation sending module 302 determines the vehicle return operation according to the initiating position, it is specifically used to: obtain the vehicle handover position; determine the scheduling route according to the vehicle handover position and the initiating position; determine the vehicle return position according to the scheduling route and the initiating position; obtain the road condition information of each scheduling route; determine the scheduling duration and the scheduling cost according to the vehicle return position and the road condition information of each scheduling route; based on the preset vehicle return method, determine the vehicle return operation according to the scheduling duration, the scheduling cost and the vehicle return position.

[0105] Optionally, the feedback analysis module 303 analyzes the user's operational feedback, and determines whether to allow the vehicle to be returned based on the feedback analysis results. It is used to: extract the operational feedback to obtain a vehicle return image; perform image analysis on the vehicle return image to determine whether there is an accident point for the vehicle; if it is determined that there is an accident point, retrieve historical vehicle delivery records to determine historical vehicle delivery videos and historical vehicle delivery pictures; analyze the historical vehicle delivery videos and historical vehicle delivery pictures to determine whether the accident point is a historical accident; if the accident point is not a historical accident, determine the degree of accident damage based on the vehicle return image, and determine the vehicle damage price based on the accident damage degree and send it to the user's device; receive the user's vehicle damage feedback, and determine whether the user accepts the vehicle damage price and pays it based on the vehicle damage feedback; if the user accepts the vehicle damage price and pays it, determine that the vehicle return is allowed.

[0106] Optionally, the vehicle operation management system 300 for the vehicle rental platform also includes an image adjustment module 304, which is used to: analyze the vehicle return image to determine the maximum brightness and the minimum brightness of the vehicle return image; determine the image contrast based on the maximum brightness and the minimum brightness; determine whether the vehicle return image meets the clarity standard based on the image contrast; if the clarity standard is not met, use an image segmentation algorithm to separate the vehicle return image and determine the accident damage area; and perform histogram equalization on the accident damage area to enhance the display of the accident damage area.

[0107] Optionally, the vehicle operation management system 300 of the vehicle rental platform also includes a vehicle use analysis module 305, which is used to: determine whether to use a vehicle based on the demand analysis results; if it is determined to use a vehicle, determine the vehicle use budget and vehicle use time based on the demand analysis results; determine a suitable vehicle based on the vehicle use budget and the vehicle use time, and based on the suitable vehicle, retrieve a preset vehicle information library to obtain suitable vehicle information; send the suitable vehicle information to the user's device and receive the user's vehicle selection; determine the final vehicle based on the vehicle selection; obtain and analyze the vehicle usage of the final vehicle, and determine a dispatchable vehicle based on the situation analysis results; obtain the user's vehicle use location, and determine the dispatch plan of the dispatchable vehicle based on the vehicle use time and the vehicle use location.

[0108] Optionally, when the feedback analysis module 303 determines whether to allow the return of the vehicle based on the feedback analysis results, it is specifically used to: determine the vehicle status reported by the user based on the feedback analysis results; obtain and analyze the vehicle detection data of the preset sensor equipment, and determine the actual vehicle status based on the data analysis results; compare the vehicle status reported by the user with the actual vehicle status to determine whether there is a difference; if there is a difference, determine the type of difference based on the data analysis results, and determine the possibility of damage to the vehicle based on the type of difference; based on the possibility of damage to the vehicle, send an image acquisition signal to the user, and receive the suspicious location image uploaded by the user based on the image acquisition signal; analyze the suspicious location image to determine whether there is a possibility of damage; if not, determine that the return of the vehicle is allowed.

[0109] Optionally, the vehicle operation management system 300 for the vehicle rental platform also includes a compensation analysis module 306, which is used to: if it does not exist, obtain the user's driving record to determine the user's driving behavior; obtain the driving specifications in the driving record; determine whether the user has abnormal driving behavior based on the driving behavior and the driving specifications; if so, determine the compensation information based on the driving specifications and the type of abnormal driving behavior and send it to the user's device; after receiving the compensation data corresponding to the compensation information, determine whether the vehicle return is allowed.

[0110] Optionally, when the feedback analysis module 303 determines the degree of accident damage based on the returned vehicle image, it is used to: analyze the returned vehicle image to determine the shooting angle and the shooting light; after the enhanced display of the accident damage area, filter the light and shadow of the accident damage area according to the shooting angle and the shooting light to obtain an image of the area without light spots; analyze the image of the area without light spots to determine the type of damage; and determine the degree of accident damage based on the damage type.

[0111] Optionally, the vehicle operation management system 300 for the vehicle rental platform also includes an alarm reminder module 307, which is used to: obtain the driving position of the user; retrieve historical driving records based on the driving position; analyze the historical driving records to determine common abnormal behaviors; and according to the common abnormal behaviors, set an alarm device to remind at the location where the common abnormal behaviors belong.

[0112] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A vehicle operation management method for a vehicle rental platform, characterized in that: include: Obtaining the user's car use demand, analyzing the car use demand, and determining whether the user should return the car based on the demand analysis result; If the vehicle is determined to be returned, the initiation location of the vehicle use demand is obtained, and the vehicle return operation is determined according to the initiation location and sent to the user's device; Receive and analyze the user's operational feedback, determine whether to allow the vehicle to be returned based on the feedback analysis results, and if the vehicle is allowed to be returned, obtain the vehicle return location and send it to the manager's device for vehicle scheduling.

2. The method according to claim 1, characterized in that: The step of determining the vehicle return operation according to the initiating location includes: Get the vehicle delivery location; Determine a dispatch route according to the vehicle delivery position and the initiation position; Determine a return location according to the dispatch route and the initiation location; Obtain traffic information for each dispatch route; Determine the dispatching time and dispatching cost according to the return location and the traffic information of each dispatching route; Based on the preset vehicle return method, the vehicle return operation is determined according to the scheduling duration, the scheduling cost and the vehicle return location.

3. The method according to claim 2, characterized in that The analyzing the user's operation feedback and determining whether to allow the vehicle to be returned according to the feedback analysis result includes: Extracting the operation feedback to obtain a vehicle return image; Performing image analysis on the vehicle return image to determine whether there is an accident point on the vehicle; If an accident point is determined, retrieve the historical vehicle delivery records, and determine the historical vehicle delivery videos and historical vehicle delivery pictures; Analyze the historical vehicle delivery video and the historical vehicle delivery picture to determine whether the accident point is a historical accident; If the accident point is not a historical accident, determining the degree of accident damage based on the vehicle return image, and determining the vehicle damage price based on the degree of accident damage and sending it to the user's device; receiving vehicle damage feedback from the user, and determining whether the user accepts the vehicle damage price and pays it according to the vehicle damage feedback; If the vehicle damage price is accepted and paid, the vehicle return is allowed.

4. The method according to claim 3, characterized in that Before determining the extent of the accident damage according to the vehicle return image, the method further includes: Analyze the vehicle return image to determine the maximum brightness and the minimum brightness of the vehicle return image; Determining image contrast according to the maximum brightness value and the minimum brightness value; Determining whether the vehicle return image meets a clarity standard according to the image contrast; If the clarity standard is not met, the image segmentation algorithm is used to separate the vehicle return image to determine the accident damage area; The accident damage area is subjected to histogram equalization to enhance the display of the accident damage area.

5. The method according to claim 1, characterized in that Before analyzing the vehicle demand and determining whether the user returns the vehicle based on the demand analysis result, the method further includes: Determine whether to use the car based on the demand analysis results; If the car is confirmed, the car budget and car use time are determined according to the demand analysis results; Determine a suitable vehicle according to the vehicle usage budget and the vehicle usage time, and retrieve a preset vehicle information database based on the suitable vehicle to obtain suitable vehicle information; sending the applicable vehicle information to the user's device and receiving the user's vehicle selection; Determining a final vehicle based on the vehicle selection; Obtaining and analyzing the vehicle usage of the final vehicle, and determining a dispatchable vehicle based on the situation analysis result; The user's vehicle usage location is obtained, and a dispatch plan for the dispatchable vehicle is determined according to the vehicle usage time and the vehicle usage location.

6. The method according to claim 1, characterized in that Determining whether to allow the return of the vehicle based on the feedback analysis results includes: Determining the vehicle status fed back by the user according to the feedback analysis result; Obtain and analyze vehicle detection data from preset sensor devices, and determine the actual status of the vehicle based on the data analysis results; Comparing the vehicle status reported by the user with the actual vehicle status to determine whether there is a difference; If there is a difference, determining the type of difference based on the data analysis result, and determining the possibility of damage to the vehicle based on the type of difference; sending an image acquisition signal to the user according to the possibility of damage to the vehicle, and receiving an image of a suspicious location uploaded by the user according to the image acquisition signal; Analyze the image of the suspicious location to determine whether there is a possibility of damage; If it does not exist, then the return of the vehicle is allowed.

7. The method according to claim 6, characterized in that If the above does not exist, before determining that the vehicle return is allowed, the following is also included: If not, obtaining the driving record of the user to determine the driving behavior of the user; Obtaining driving specifications in the driving record; Determining whether the user has abnormal driving behavior according to the driving behavior and the driving regulations; If so, determining compensation information according to the driving regulations and the type of the abnormal driving behavior and sending the compensation information to the device of the user; After receiving the compensation data corresponding to the compensation information, it is determined that the vehicle return is allowed.

8. The method according to claim 4, characterized in that Determining the degree of accident damage according to the vehicle return image includes: Analyze the vehicle return image to determine the shooting angle and shooting light; After the accident damage area is enhanced and displayed, the accident damage area is subjected to light and shadow filtering according to the shooting angle and the shooting light to obtain an image of the area without light spots; Analyzing the image of the area without light spots to determine the damage type; Determine the extent of the accident damage based on the damage type.

9. The method according to claim 7, characterized in that: Before obtaining the driving record of the user and determining the driving behavior of the user, the method further includes: Obtaining the driving position of the user; Retrieving historical driving records according to the driving position; Analyze the historical driving records to identify common abnormal behaviors; According to the common abnormal behavior, an alarm device is set to give a reminder at the location where the common abnormal behavior belongs.

10. A vehicle operation management system for a vehicle rental platform, characterized in that: include: A car return analysis module is used to obtain the user's car use demand, analyze the car use demand, and determine whether the user returns the car according to the demand analysis result; An operation sending module, for obtaining the initiation location of the vehicle use demand if the vehicle return is determined, and determining the vehicle return operation according to the initiation location and sending the operation to the user's device; The feedback analysis module is used to receive and analyze the user's operational feedback, determine whether to allow the vehicle to be returned based on the feedback analysis results, and if the vehicle is allowed to be returned, obtain the vehicle return location and send it to the manager's device for vehicle scheduling.

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