A method for managing online ride-hailing services based on image analysis

Abstract

The present invention discloses an online car-hailing management method based on image analysis, which specifically relates to the technical field of online car-hailing management, and comprises the following steps: collecting car-using needs of car users and searching for all car-supplying user information within a dispatching distance according to a preset dispatching rule, then screening, and displaying the screened results to the car users, the car users selecting target car-supplying users, completing dispatching matching, evaluating the dispatching completion quality based on image analysis and sending the evaluation results to the car-supplying users, the car-supplying users confirming or giving feedback on the given evaluation results, and updating the car-supplying user information according to the confirmation or feedback results; the present invention improves the dispatching efficiency and accuracy of online car-hailing in a parking waiting area, reduces the communication cost between car users and car-supplying users, and realizes supervision and urging of the online car-hailing service quality by calculating the credit value, reputation value and service value of the car-supplying users, thereby establishing a good online car-hailing service platform.

Description

Technical Field

[0001] The present invention relates to the technical field of online car-hailing management, and more specifically, to an online car-hailing management method based on image analysis. Background Art

[0002] Online car-hailing is the abbreviation of online taxi booking service. It refers to the business activities of building a service platform based on Internet technology, connecting qualified vehicles and drivers, and providing non-cruising taxi booking services by integrating supply and demand information. Online car-hailing is convenient: users only need to enter the destination and departure time on the mobile phone application, and the system will automatically match the most suitable vehicle. There is no need to wait for a taxi or go to the station, saving time and energy; flexibility: online car-hailing is not restricted by regular buses, and users can flexibly choose travel time, location and vehicle type according to their own needs to fully meet the personalized needs of users; safety: most online car-hailing companies will take various measures to ensure the safety of passengers and drivers, such as establishing a safety monitoring mechanism and a real-name authentication system. In people's daily travel scenarios, some scenarios will set up separate parking waiting areas. In view of the difficulty of finding a parking location for online car-hailing, the car user even needs to contact the online car-hailing user, the car supplier, several times to determine the parking location when arriving at the pick-up place, and find the vehicle or find the car supplier first and then find the vehicle under his guidance. Therefore, a online car-hailing management method based on image analysis is proposed here.

[0003] Invention Project

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for managing online car-hailing services based on image analysis, comprising the following steps:

[0006] Step 1: Collect car users' car needs;

[0007] Step 2: Find all vehicle supply user information within the dispatch distance according to the vehicle user's vehicle demand and pre-set dispatch rules;

[0008] Step 3: Filter all the car supply user information, and then display the filtered results to the car users;

[0009] Step 4: The car user selects the target car supplier to complete the order matching;

[0010] Step 5: Based on image analysis, evaluate the order completion quality and send the evaluation results to the vehicle supplier;

[0011] Step 6. The vehicle supplier confirms or provides feedback on the evaluation results. If the vehicle supplier confirms the evaluation results, the evaluation results will be updated in the vehicle supplier information. If the vehicle supplier provides feedback on the evaluation results, the evaluation results will be manually reviewed and the review results will be updated in the vehicle supplier information.

[0012] In a preferred embodiment, the online car-hailing management method based on image analysis also includes collecting vehicle supplier user information, and updating the vehicle supplier user information based on the evaluation results given by the vehicle supplier in step six or the feedback results.

[0013] In a preferred embodiment, in step one, collecting the vehicle usage needs of vehicle users refers to collecting the vehicle usage time interval, boarding place, destination, and time of issuing the vehicle usage needs of vehicle users.

[0014] In a preferred embodiment, step 2, searching for all vehicle supply user information within the dispatching distance according to the vehicle user's vehicle demand and the pre-set dispatching rules, refers to:

[0015] The car user's car use time interval is recorded as [y1, y2], and the time of issuing the car demand is recorded as y3, then the time difference one is calculated, SJ1=y3-y1, SJ1 is the time difference one, if the time difference one SJ1 is less than or equal to the preset first time threshold, then according to the preset dispatching rule, a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is searched for all car supply user information, if a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is drawn with a total number of not less than n car supply users, then the first dispatching distance r1 is expanded by m times each time until a total number of not less than n car supply user information is found;

[0016] If the time difference SJ1 is greater than the preset first time threshold, then the time difference SJ2 is calculated, SJ2=y3-y2, SJ2 is the time difference 2, and then according to the preset dispatching rules, search for all vehicle supply user information within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle. If no vehicle supply users with a total number of not less than n are found within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle, then the second dispatching distance r2 will be expanded m times each time until vehicle supply user information with a total number of not less than n is found, r2=r1*h, h is the ratio of the time difference SJ2 to the preset first time threshold.

[0017] In a preferred embodiment, in step 3, filtering all vehicle supply user information and then displaying the filtered results to the vehicle user refers to:

[0018] Step A1, obtaining the trustworthy information, dishonest information, and law-abiding information in the vehicle supply user information within a preset time window, and then marking the trustworthy item data in the trustworthy information as SX1i, marking the dishonest item data in the dishonest information as SX2i, marking the law-abiding item data in the law-abiding information as SF i, and then obtaining the credit value of the vehicle supply user by calculation, XY1=Σ(SX1i*fi)-Σ(SX2i*ki)-Σ(SFi*ji), XY1 is the credit value of the vehicle supply user, fi is the preset trustworthy coefficient corresponding to the trustworthy item SX1i, ki is the preset dishonest coefficient corresponding to the dishonest item SX2i, and ji is the preset law-abiding coefficient corresponding to the law-abiding item SFi;

[0019] Step A2, obtaining the evaluation information in the vehicle supply user information in the preset time window, marking the evaluation item data of the evaluation information as PJi, and then calculating to obtain the reputation value of the vehicle supply user, XY2 = Σ(PJi*pi), XY2 is the reputation value of the vehicle supply user, pi is the preset evaluation coefficient corresponding to the evaluation item;

[0020] Step A3, the service value of the vehicle supplier is obtained by the credit value XY1 and the reputation value XY2 of the vehicle supplier, FW=a1*XY1+a2*XY2, FW is the service value of the vehicle supplier, a1 and a2 correspond to the preset proportional coefficients of the credit value XY1 and the reputation value XY2 of the vehicle supplier respectively;

[0021] Step A4: compare the service value FW with a preset screening threshold, screen out the car supply users corresponding to the service value FW below the preset screening threshold, and then sort the remaining car supply users in descending order according to the size of the service value FW and display them to the car user.

[0022] In a preferred embodiment, in step 4, the vehicle user selects a target vehicle supplier, and completing the order matching means:

[0023] The car user selects the car supplier, and then matching reminders are sent to the car user and the selected target car supplier respectively. The nearest vacant parking space is matched according to the car user's boarding location and the coordinates of the vacant parking space are sent to the target car supplier to complete the order matching.

[0024] In a preferred embodiment, in step 5, evaluating the order completion quality based on image analysis and sending the evaluation result to the vehicle supply user refers to:

[0025] Perform image analysis on the image items in the items of order completion quality, obtain image analysis data and record it as TXi, and at the same time obtain non-image item data in the items of order completion quality and record it as FTi. When the image analysis data TXi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. When the non-image item data FTi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. A data set consisting of numbers 1 and 0, i.e., the evaluation result, is obtained and sent to the vehicle supply user.

[0026] Technical effects and advantages of the present invention:

[0027] The present invention collects the needs of car users and information of car suppliers, performs intelligent screening and matching, and uses image analysis technology to evaluate the quality of dispatch completion, thereby achieving effective supervision and supervision of the quality of online car-hailing services. In addition, the method also provides a feedback mechanism, so that car suppliers can identify or feedback the evaluation results, further improving the fairness and transparency of the service. The method can effectively solve the problems of difficulty in finding parking spaces for online car-hailing and difficulty for car users to find vehicles, and improve the efficiency and quality of online car-hailing services.

[0028] The present invention improves the efficiency and accuracy of dispatching online-hailing vehicles in parking waiting areas, reduces the communication costs between vehicle users and vehicle suppliers, improves user experience, and realizes supervision and urging of the service quality of online-hailing vehicles by calculating the credit value, reputation value and service value of vehicle suppliers, establishes a good online-hailing vehicle service platform, and provides objective and fair service quality feedback to vehicle suppliers based on the quality evaluation results of image analysis, which helps to improve the service level of vehicle suppliers. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0030] Figure 1 This is a schematic diagram of a method for managing online ride-hailing vehicles based on image analysis in the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Example 1

[0033] A method for managing online car-hailing based on image analysis comprises the following steps: step 1, collecting car needs of car users; step 2, searching for all car supply user information within the dispatch distance according to the car needs of car users and pre-set dispatch rules; step 3, screening all car supply user information, and then displaying the screened results to the car users; step 4, the car users select target car supply users to complete dispatch matching; step 5, based on image analysis, evaluating the dispatch completion quality and sending the evaluation results to the car supply users; step 6, the car supply users confirm or feedback the given evaluation results. If the car supply users confirm the given evaluation results, the evaluation results will be updated in the car supply user information. If the car supply users feedback the given evaluation results, the evaluation results will be manually reviewed, and then the review results will be updated in the car supply user information.

[0034] In step one, collecting the car user's car demand refers to collecting the car user's car use time range, boarding place, destination, and time of issuing the car demand.

[0035] Step 2: Find all vehicle supply user information within the dispatch distance according to the vehicle user's vehicle demand and the pre-set dispatch rules:

[0036] The car user's car use time interval is recorded as [y1, y2], and the time of issuing the car demand is recorded as y3, then the time difference one is calculated, SJ1=y3-y1, SJ1 is the time difference one, if the time difference one SJ1 is less than or equal to the preset first time threshold, then according to the preset dispatching rule, a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is searched for all car supply user information, if a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is drawn with a total number of not less than n car supply users, then the first dispatching distance r1 is expanded by m times each time until a total number of not less than n car supply user information is found;

[0037] If the time difference SJ1 is greater than the preset first time threshold, then the time difference SJ2 is calculated, SJ2=y3-y2, SJ2 is the time difference 2, and then according to the preset dispatching rules, search for all vehicle supply user information within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle. If no vehicle supply users with a total number of not less than n are found within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle, then the second dispatching distance r2 will be expanded m times each time until vehicle supply user information with a total number of not less than n is found, r2=r1*h, h is the ratio of the time difference SJ2 to the preset first time threshold.

[0038] Step 3: Filtering all car supply user information and then displaying the filtered results to the car user means:

[0039] Step A1, obtaining the trustworthy information, dishonest information, and law-abiding information in the vehicle supply user information within a preset time window, and then marking the trustworthy item data in the trustworthy information as SX1i, marking the dishonest item data in the dishonest information as SX2i, marking the law-abiding item data in the law-abiding information as SF i, and then obtaining the credit value of the vehicle supply user by calculation, XY1=Σ(SX1i*fi)-Σ(SX2i*ki)-Σ(SFi*ji), XY1 is the credit value of the vehicle supply user, fi is the preset trustworthy coefficient corresponding to the trustworthy item SX1i, ki is the preset dishonest coefficient corresponding to the dishonest item SX2i, and ji is the preset law-abiding coefficient corresponding to the law-abiding item SFi;

[0040] Step A2, obtaining the evaluation information in the vehicle supply user information in the preset time window, marking the evaluation item data of the evaluation information as PJi, and then calculating to obtain the reputation value of the vehicle supply user, XY2 = ∑ (PJi * pi), XY2 is the reputation value of the vehicle supply user, pi is the preset evaluation coefficient corresponding to the evaluation item;

[0041] Step A3, the service value of the vehicle supplier is obtained by the credit value XY1 and the reputation value XY2 of the vehicle supplier, FW=a1*XY1+a2*XY2, FW is the service value of the vehicle supplier, a1 and a2 correspond to the preset proportional coefficients of the credit value XY1 and the reputation value XY2 of the vehicle supplier respectively;

[0042] Step A4: compare the service value FW with a preset screening threshold, screen out the car supply users corresponding to the service value FW below the preset screening threshold, and then sort the remaining car supply users in descending order according to the size of the service value FW and display them to the car user.

[0043] In step 4, the car user selects the target car supplier, and completing the order matching means:

[0044] The car user selects the car supplier, and then matching reminders are sent to the car user and the selected target car supplier respectively. The nearest vacant parking space is matched according to the car user's boarding location and the coordinates of the vacant parking space are sent to the target car supplier to complete the order matching.

[0045] In step 5, based on image analysis, the order completion quality is evaluated and the evaluation results are sent to the vehicle supplier.

[0046] Perform image analysis on the image items in the items of order completion quality, obtain image analysis data and record it as TXi, and at the same time obtain non-image item data in the items of order completion quality and record it as FTi. When the image analysis data TXi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. When the non-image item data FTi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. A data set consisting of numbers 1 and 0, i.e., the evaluation result, is obtained and sent to the vehicle supply user.

[0047] Example 2

[0048] In people's daily travel scenarios, some scenarios will set up separate parking waiting areas. Aiming at the situation that it is difficult to find a parking location for online car-hailing, and the car user needs to contact the online car-hailing user, that is, the car supplier, for many times after arriving at the pick-up location to determine the parking location, find the vehicle, or find the car supplier first and then find the vehicle under the guidance of the car supplier, the present invention proposes an online car-hailing management method based on image analysis, including the following steps:

[0049] Step 1: Collect the car-using needs of car users; specifically: collect the car-using time range, boarding place, destination, and time of issuing the car-using needs of car users.

[0050] Step 2: Find all the car supply user information within the dispatch distance according to the car user's car demand and the pre-set dispatch rules; specifically include the following contents: record the car user's car use time interval as [y1, y2], where y1 can be the car use time selected by the car user, y2 is the reserved time provided to the car supply user in order to meet the current parking waiting area size, y2 = y1 + t, the size of t is determined according to the current parking waiting area area size s, and is specifically set by the corresponding personnel in this field, the time when the car demand is issued is recorded as y3, and the time difference is calculated as one, SJ1 = y3 -y1, SJ1 is the time difference value 1. If the time difference value SJ1 is less than or equal to the preset first time threshold, then according to the preset dispatching rules, search for all the vehicle supply user information within the first dispatching distance r1 with a circle drawn with the boarding place as the center and a radius of the circle. If no vehicle supply users with a total number of not less than n are found within the first dispatching distance r1 with a circle drawn with the boarding place as the center and a radius of the circle, then the first dispatching distance r1 is expanded m times each time until the vehicle supply user information with a total number of not less than n is found; m and n are both positive integers greater than zero. Generally, m is set to 1.5 and n is set to 10. They can also be adjusted according to actual conditions.

[0051] If the time difference SJ1 is greater than the preset first time threshold, then the time difference SJ2 is calculated, SJ2=y3-y2, SJ2 is the time difference 2, and then according to the preset dispatching rules, search for all vehicle supply user information within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle. If no vehicle supply users with a total number of not less than n are found within the second dispatching distance r2 with a circle drawn with the boarding place as the center and a radius of the circle, then the second dispatching distance r2 will be expanded m times each time until vehicle supply user information with a total number of not less than n is found, r2=r1*h, h is the ratio of the time difference SJ2 to the preset first time threshold.

[0052] Step 3: Filter all the information of car suppliers, and then display the filtered results to the car users; specifically, step A1: obtain the trustworthy information, untrustworthy information, and law-abiding information in the car supplier information within a preset time window, and then mark the trustworthy item data in the trustworthy information as SX1i, mark the untrustworthy item data in the untrustworthy information as SX2i, mark the law-abiding item data in the law-abiding information as SFi, and then calculate the credit value of the car supplier, XY1=∑(SX1i*fi)-∑(SX2i*ki)-∑(SFi*ji), X Y1 is the credit value of the car supplier. The higher the credit value XY1 of the car supplier, the more the car supplier, i.e. the corresponding online car-hailing vehicle, abides by the laws and regulations and the set system and the relevant online car-hailing regulations. fi is the preset trustworthiness coefficient corresponding to the trustworthy item SX1i, ki is the preset dishonesty coefficient corresponding to the dishonest item SX2i, and ji is the preset law-abiding coefficient corresponding to the law-abiding item SFi. It should be noted that: the law-abiding information is obtained through the traffic control 12123 information of the vehicle, and the law-abiding item is the item category of traffic violations. Since a separate parking waiting area will be set up in the scenario specified in the present invention, it means There will be a record of vehicles entering and exiting the vehicle, and there will be video or image recording information on whether the vehicle is parked in the reserved parking space. In the subsequent step four, the nearest vacant parking space is matched according to the car user's boarding location and the coordinates of the vacant parking space are sent to the target car supplier to complete the dispatch matching. The nearest vacant parking space will be matched for reservation, and a matching system for each online car-hailing vehicle and parking space will be implemented. For example, when the online car-hailing vehicle is matched in the dispatch, the estimated arrival time u1 will be displayed on the navigation used, and g minutes of time will be set before and after the estimated arrival time. If g is greater than 0, then To the time interval [u1-g, u1+g], if within the time interval [u1-g, u1+g], the online car-hailing vehicle has an entry record in the parking waiting area, it is a trustworthy behavior, otherwise it is a dishonest behavior; if after the online car-hailing vehicle user gets on the vehicle, the navigation used will show that the estimated time of arrival at the destination is u2, if the vehicle user gets off the vehicle and arrives at the destination before time u2+g, it is considered a trustworthy behavior, otherwise it is considered a dishonest behavior. The items considered as trustworthy behavior and the items considered as dishonest behavior are set in opposition, and can be selectively added or adjusted according to the actual usage of the user;

[0053] Step A2, obtaining the evaluation information in the vehicle supply user information in the preset time window, marking the evaluation item data of the evaluation information as PJi, and then calculating the reputation value of the vehicle supply user, XY2 = ∑ (PJi * pi), XY2 is the reputation value of the vehicle supply user, pi is the preset evaluation coefficient corresponding to the evaluation item; the preset evaluation coefficient pi, the preset dishonesty coefficient ki, the preset law-abiding coefficient ji, and the preset trustworthiness coefficient fi are all non-zero; the larger the reputation value XY2 of the vehicle supply user, the higher the evaluation received by the vehicle supply user, i.e., the corresponding online car-hailing vehicle;

[0054] Step A3, the service value of the car supplier is obtained through the credit value XY1 and the reputation value XY2 of the car supplier, FW=a1*XY1+a2*XY2, FW is the service value of the car supplier, a1 and a2 correspond to the preset proportional coefficients of the credit value XY1 and the reputation value XY2 of the car supplier respectively, and a1 and a2 are not zero; the larger the service value FW of the car supplier is, the higher the overall service quality of the corresponding online car-hailing vehicle is;

[0055] Step A4: Compare the service value FW with a preset screening threshold, screen out the car supply users corresponding to the service value FW lower than the preset screening threshold, and then sort the retained car supply users in descending order according to the size of the service value FW and display them to the car user. When displaying, the corresponding vehicle model, license plate number and other information will also be displayed. The online car-hailing vehicles that do not meet the preset service standards are screened out. By setting up this screening system, the quality of online car-hailing services can be supervised and urged, and a good online car-hailing service platform can be established.

[0056] Step 4. The car user selects the target car supplier to complete the dispatch matching; specifically: the car user selects the car supplier, and then sends matching reminders to the car user and the selected target car supplier respectively, and matches the nearest vacant parking space according to the car user's boarding location and sends the coordinates of the vacant parking space to the target car supplier to complete the dispatch matching.

[0057] Step 5. Based on image analysis, evaluate the quality of order completion and send the evaluation results to the car supply user; specifically: perform image analysis on the image items in the order completion quality items, obtain image analysis data and record it as TXi, and simultaneously obtain non-image item data in the order completion quality items and record it as FT i. When the image analysis data TXi meets the preset standard, the quality evaluation result is recorded as 1, otherwise it is recorded as 0. When the non-image item data FTi meets the preset standard, the quality evaluation result is recorded as 1, otherwise it is recorded as 0. A data set consisting of the numbers 1 and 0, i.e., the evaluation result, is obtained and sent to the car supply user. The items mentioned in the previous article that will be recorded in video or image are image items. For example, the time on the image is obtained during image analysis. When the time when the online car-hailing vehicle has a record of entering the parking waiting area is within the time interval [u1-g, u1+g], the quality evaluation result is recorded as 1.

[0058] Step 6. The vehicle supplier confirms or provides feedback on the given evaluation results. If the vehicle supplier confirms the given evaluation results, the evaluation results will be updated in the vehicle supplier information. If the vehicle supplier provides feedback on the given evaluation results, the evaluation results will be manually reviewed and the review results will be updated in the vehicle supplier information. If the vehicle supplier confirms the given evaluation results, the evaluation results will be updated in the vehicle supplier information. If the vehicle supplier provides feedback on the given evaluation results, such as if the vehicle supplier has questions about the time of entering and exiting the parking area, the data in the image and the preset standards will be manually reviewed to determine whether the evaluation results are accurate, and then the review results will be updated in the vehicle supplier information.

[0059] The online car-hailing management method based on image analysis also includes collecting vehicle supplier user information, and updating the vehicle supplier user information based on the evaluation results or feedback results given by the vehicle supplier in step six.

[0060] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0061] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0062] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0063] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0064] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0065] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for managing online car-hailing services based on image analysis, characterized in that: The following steps are involved: Step 1: Collect car users' car needs; Step 2: Find all vehicle supply user information within the dispatch distance according to the vehicle user's vehicle demand and pre-set dispatch rules; Step 3: Filter all the car supply user information, and then display the filtered results to the car users; Step 4: The car user selects the target car supplier to complete the order matching; Step 5: Based on image analysis, evaluate the order completion quality and send the evaluation results to the vehicle supplier; Step 6: The vehicle supplier confirms or provides feedback on the evaluation result. If the vehicle supplier confirms the evaluation result, the evaluation result will be updated in the vehicle supplier information. If the vehicle supplier provides feedback on the evaluation result, the evaluation result will be manually reviewed, and the review result will be updated in the vehicle supplier information. Step 2: Find all vehicle supply user information within the dispatch distance according to the vehicle user's vehicle demand and the pre-set dispatch rules: The car user's car use time interval is recorded as [y1, y2], and the time of issuing the car demand is recorded as y3, then the time difference one is calculated, SJ1=y3-y1, SJ1 is the time difference one, if the time difference one SJ1 is less than or equal to the preset first time threshold, then according to the preset dispatching rule, a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is searched for all car supply user information, if a circle with the boarding place as the center and the circle radius as the first dispatching distance r1 is drawn with a total number of not less than n car supply users, then the first dispatching distance r1 is expanded by m times each time until a total number of not less than n car supply user information is found; If the time difference SJ1 is greater than the preset first time threshold, then calculate the time difference SJ2 = y3-y2, SJ2 is the time difference SJ2, and then search for all the vehicle supply user information within the second dispatch distance r2 with a circle drawn with the boarding place as the center and a radius of the circle according to the preset dispatch rule. If no vehicle supply user with a total number of not less than n is found within the second dispatch distance r2 with a circle drawn with the boarding place as the center and a radius of the circle, then expand the second dispatch distance r2 by m times each time until the vehicle supply user information with a total number of not less than n is found, r2 = r1*h, h is the ratio of the time difference SJ2 to the preset first time threshold; Step 3: Filtering all car supply user information and then displaying the filtered results to the car user means: Step A1, obtain the trustworthy information, dishonest information, and law-abiding information in the vehicle supply user information within a preset time window, then mark the trustworthy item data in the trustworthy information as SX1i, mark the dishonest item data in the dishonest information as SX2i, mark the law-abiding item data in the law-abiding information as SFi, and then obtain the credit value of the vehicle supply user by calculation, XY1=∑(SX1i*fi)-∑(SX2i*ki)-∑(SFi*ji), XY1 is the credit value of the vehicle supply user, fi is the preset trustworthy coefficient corresponding to the trustworthy item SX1i, ki is the preset dishonest coefficient corresponding to the dishonest item SX2i, and ji is the preset law-abiding coefficient corresponding to the law-abiding item SFi; Step A2, obtaining the evaluation information in the vehicle supply user information in the preset time window, marking the evaluation item data of the evaluation information as PJi, and then calculating to obtain the reputation value of the vehicle supply user, XY2 = ∑ (PJi * pi), XY2 is the reputation value of the vehicle supply user, pi is the preset evaluation coefficient corresponding to the evaluation item; Step A3, the service value of the vehicle supplier is obtained by the credit value XY1 and the reputation value XY2 of the vehicle supplier, FW=a1*XY1+a2*XY2, FW is the service value of the vehicle supplier, a1 and a2 correspond to the preset proportional coefficients of the credit value XY1 and the reputation value XY2 of the vehicle supplier respectively; Step A4: compare the service value FW with a preset screening threshold, screen out the car supply users whose service value FW is lower than the preset screening threshold, and then sort the remaining car supply users in descending order according to the size of the service value FW and display them to the car user; In step 4, the car user selects the target car supplier, and completing the order matching means: The car user selects a car supplier, and then sends matching reminders to the car user and the selected target car supplier respectively, and matches the nearest vacant parking space according to the car user's boarding location and sends the coordinates of the vacant parking space to the target car supplier to complete the dispatch matching; In step 5, based on image analysis, the order completion quality is evaluated and the evaluation results are sent to the vehicle supplier. Perform image analysis on the image items in the items of order completion quality, obtain image analysis data and record it as TXi, and at the same time obtain non-image item data in the items of order completion quality and record it as FTi. When the image analysis data TXi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. When the non-image item data FTi meets the preset standard, the quality assessment result is recorded as 1, otherwise it is recorded as 0. A data set consisting of numbers 1 and 0, i.e., the evaluation result, is obtained and sent to the vehicle supply user.

2. According to the image analysis-based online car-hailing management method of claim 1, it is characterized in that: The online car-hailing management method based on image analysis also includes collecting vehicle supplier user information, and updating the vehicle supplier user information based on the evaluation results or feedback results given by the vehicle supplier in step six.

3. The method for managing online car-hailing services based on image analysis according to claim 2, characterized in that: In step one, collecting the car user's car demand refers to collecting the car user's car use time range, boarding place, destination, and time of issuing the car demand.

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