Reverse processing method and system for online car-hailing platform

Abstract

The invention discloses a reverse processing method and system for an online car-hailing platform. The invention relates to the technical field of online car-hailing platform management. Receiving a data packet from the channel, wherein the data packet comprises order information, complaint content and GPS track data; the received data packet is processed according to a preset responsibility judgment rule, and a responsibility party (a driver or a platform) is automatically judged; the responsibility judgment result comprises a responsibility person identifier, a violation type and a violation degree; through an automatic and intelligent responsibility judgment system, comprehensive data analysis and a preset responsibility judgment rule are combined, illegal behaviors can be accurately recognized, the responsible party can be accurately judged, the possibility of manual misjudgment and prejudgement is greatly reduced, and the responsibility judgment accuracy and fairness are improved. The work order automatic generation and pushing mechanism in the invention ensures the timeliness of work order processing. Meanwhile, due to the standardized work order processing flow and the real-time monitoring mechanism, a work order processing link is smoother, and delay and errors in the processing process are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of online ride-hailing platform management, specifically to the technical direction of processing online ride-hailing work orders, and especially to a method and system for reverse processing of online ride-hailing platforms. Background Art

[0002] With the booming online ride-hailing industry, the traditional "hail and you stop" model has been gradually replaced by a new mode of transportation: online booking. This has greatly improved the convenience and flexibility of public transportation. However, this has led to the complexity of managing order fees. Specifically, drivers frequently take detours, maliciously add additional fees, incur fees without actually riding, and terminate billing early or late. These issues have directly led to the need for adjustments to order amounts, such as full or partial refunds, order amount revisions, and order cancellations. This series of measures aims to balance the interests of drivers and passengers and ensure that the rights and interests of both parties are properly protected.

[0003] Under the current operational framework, processing order refunds, price adjustments, order closures, and assigning responsibility (to the driver or service provider) relies on manual customer service to synchronize order change information with the identification and handling of violations through the accountability work order system. This mechanism is designed to clearly inform the driver or service provider (SP) of their identified violations. If the driver or SP disagrees with the accountability outcome, they must initiate an online appeal process based on the identified violations. However, this system faces a core challenge: manual customer service's accuracy in the accountability process is insufficient. This shortcoming is particularly prominent in cost-related customer complaint scenarios, including but not limited to the aforementioned detours and malicious surcharges.

[0004] Further analysis reveals that the specific problems with the current work order assessment process and management system can be summarized into the following two points:

[0005] (1) Accuracy of judgment: When front-line customer service staff handle customer complaints about fees, their judgment decisions often lack sufficient accuracy, which directly affects the fairness and credibility of the judgment results, and may lead to escalating dissatisfaction among drivers or passengers.

[0006] (2) Inconsistency in the work order processing chain: On the one hand, some work order types cannot find corresponding mapping relationships in the subsequent management and control system after channel selection, so violation records cannot be effectively generated. On the other hand, certain types of work orders are automatically filtered at the channel management level, resulting in the failure to correctly identify and process relevant violation information. The existence of such filtering rules not only causes information omissions, but also exacerbates the negative experience of drivers and service providers.

[0007] Specifically:

[0008] (1) For drivers, if they are wrongly identified as the responsible party, they will face the situation of having their wallet balance deducted, but they will not be able to view the specific violation records on the appeal interface, thus depriving them of their right to appeal.

[0009] (2) For service providers, when they are judged as the responsible party, they not only face the risk of order settlement being rejected, but also can only see the refund and change operations and the responsible person marked as the platform in the order details, but cannot find the corresponding records in the platform's violation record query system to file a complaint. This undoubtedly increases the operational difficulty and dissatisfaction of service providers.

[0010] In summary, current online ride-hailing platforms have significant room for improvement in terms of order fee management and liability determination. There is an urgent need to optimize the liability determination process, improve accuracy, and ensure transparency and consistency in information processing to comprehensively enhance the overall experience for drivers, passengers, and service providers. To this end, this paper proposes a method and system for reverse processing on online ride-hailing platforms. Summary of the Invention

[0011] In view of this, the present invention aims to provide a method and system for reverse processing of online ride-hailing platforms to solve or alleviate the technical problems existing in the prior art, namely, the accuracy of judgment and the inconsistency of the work order processing chain, and to provide at least a beneficial option. The technical solution of the present invention is implemented as follows:

[0012] First, the reverse processing method for online car-hailing platforms:

[0013] (1) Overview:

[0014] The present invention aims to solve the problems of accuracy in accountability and inconsistency in work order processing links in the order refund, change and closure process of online ride-hailing platforms through automated and intelligent technical means. The solution first receives order information, complaint content and GPS trajectory data from the channel, and then automatically determines the responsible party and generates accountability results such as the responsible person identification, violation type, and violation degree based on the preset accountability rules. Based on these results, the system automatically generates a accountability work order and pushes it to the relevant departments for processing. At the same time, the solution automatically determines the party responsible for the cost based on the degree of violation and preset rules, and executes refunds, price changes or order closure operations. Throughout the process, the system is also responsible for financial accounting, updating relevant records, and feeding back the processing results to passengers, drivers and service providers.

[0015] (2) Technical solution:

[0016] To achieve the above technical objectives, the present invention chooses to perform the following operating steps.

[0017] 2.1 Step S1, automatic judgment logic execution:

[0018] Receive data packets from channels, including order information, complaint content, and GPS trajectory data; process the received data packets according to preset judgment rules and automatically determine the responsible party (driver or platform); the judgment results include the identification of the responsible person, the type of violation, and the degree of violation.

[0019] 2.1.1 Step S100, judgment rule matching:

[0020] Based on the judgment rules of the online ride-hailing platform, the data packets are matched with the judgment rules. The order information, complaint content and GPS trajectory data are analyzed and compared through algorithms to identify any violations. The specific solutions include:

[0021] D: Data packet, including order information, complaint content and GPS trajectory data;

[0022] R: A set of judgment rules, where each rule r∈R contains a set of violation types corresponding to the conditional time range and location range;

[0023] V: a set of violation types, where each violation type v∈V corresponds to one or more judgment rules;

[0024] M(D,r): matching function used to determine whether the packet D meets the conditions of rule r;

[0025] The rules for judging liability are:

[0026] S1000, initialize violation type set V matched Is an empty set.

[0027] S1001, for each rule r in the judgment rule set R:

[0028] Call the matching function M(D,r) to determine whether the data packet D meets the conditions of rule r;

[0029] If it is satisfied (ie M(D, r) = true), then the violation type v corresponding to rule r is added to V matched middle.

[0030] S1002, return to V matched as the set of identified violations.

[0031] 2.1.2 Step S101, responsible party determines:

[0032] Based on the matching results of the accountability rules, the driver or the platform is determined to be responsible based on the driver's driving route, the passenger's complaint content, and the accuracy of GPS trajectory data. Specific solutions include:

[0033] R driver: A collection of violation types directly related to drivers, including detours, speeding, impolite behavior, etc.

[0034] R platform : A collection of violation types directly related to the platform, such as system errors, order dispatch errors, improper customer service handling, etc.

[0035] D route : Driver’s driving route data.

[0036] D complain t: Content of the passenger’s complaint.

[0037] D gps : GPS trajectory data and its accuracy evaluation.

[0038] The rules for judging liability are:

[0039] S1010, initialize responsible party party is unknown (UNKNOWN).

[0040] S1011, check V matched Is it empty?

[0041] If it is empty, it means no violation was identified; if it is not empty, continue to execute:

[0042] Traverse V matched For each violation type v in:

[0043] If v belongs to R driver , which is directly related to the driver:

[0044] S1012, Analysis D route 、D complaint and D gps , confirm whether the driver's driving route is consistent with the complaint content, and whether the GPS trajectory data supports this conclusion; if the analysis results show that the driver has indeed violated the regulations, the responsible party Set to DRIVER; break out of the loop because the responsible party has been found.

[0045] S1013, if v belongs to R platform , which is directly related to the platform: analyze relevant data to confirm whether the platform has any violations; if the analysis results show that there are indeed problems with the platform, the responsible party Set to platform (PLATFORM); jump out of the loop;

[0046] S1014, returning responsible_party as the determination result of the responsible party.

[0047] 2.1.3 Step S102, generating the judgment result:

[0048] Based on the determination result of the responsible party, the determination result information is generated, including the responsible person identification (used to uniquely identify the responsible party), the violation type (detour or malicious surcharge) and the violation degree (measurement of the severity of the violation).

[0049] 2.2 Step S2, generate a judgment work order:

[0050] Based on the results of automatic accountability, a work order is generated and pushed to the corresponding responsible party. The work order contains the order number, responsible person, violation details and recommended handling measures.

[0051] 2.2.1 Step S200, obtaining the judgment result:

[0052] Obtain the judgment results from the automatic judgment module, including the order number, responsible person (driver or platform), violation type and violation severity.

[0053] The content of the judgment work order is automatically assembled based on the judgment results, including the order number, which is used to uniquely identify the order; the responsible party, which clearly indicates which party (driver or platform) bears the responsibility; the violation details, which describe the specific circumstances and evidence of the violation in detail; and the recommended handling measures, which are given according to the type and severity of the violation, including refunding the passenger and / or punishing the driver.

[0054] 2.2.2 Step S201, responsible party pushes:

[0055] Based on the responsible person information in the judgment result, the work order will be pushed to the corresponding responsible party; if the driver is responsible, the work order will be pushed to the driver's application or platform for the driver to review and handle; if the platform is responsible, the work order will be pushed to the department or system within the platform for subsequent processing.

[0056] 2.2.3 Step S202: Work Order Tracking and Feedback:

[0057] Record the push time and push status of the work order. After processing the work order, the responsible party receives and records the processing results and feedback information.

[0058] 2.3 Step S3: Determine the party responsible for the expenses:

[0059] Automatically execute refunds, price changes, or order closures based on the responsible person information in the judgment work order;

[0060] The refund amount is calculated based on the severity of the violation and the preset rules for the refund amount;

[0061] The price change operation adjusts the order amount according to actual needs;

[0062] The order closing operation is used to cancel invalid or illegal orders.

[0063] 2.3.1 Step S300, work order analysis:

[0064] For orders that require a refund, the system automatically calculates the refund amount based on the degree of violation and the preset rules for the refund amount;

[0065] If the order amount needs to be adjusted, the price will be adjusted based on the actual needs of the passenger. This includes increasing or decreasing the order amount.

[0066] Order closing operations include updating, deleting or modifying order status.

[0067] 2.3.2 Step S301, Financial Accounting and Notification:

[0068] Financial accounting is carried out for refunds, price changes and order closure operations to ensure that the accounts are clear and accurate; at the same time, notifications are sent to passengers, drivers and the platform's financial department to inform the cost bearer of the judgment results, refund amount, price change or order closure operation.

[0069] 2.4 Step S4, Financial Accounting and Record Update:

[0070] Financial accounting is performed for refund, price change and order closing operations, and databases and records are updated, including order status, driver credit records and passenger complaint handling records.

[0071] 2.4.1 Step S400, financial accounting preparation:

[0072] Collect and organize financial information on refunds, price changes, and order closures, including the type, amount, and time of the operation;

[0073] For refund operations, record the refund expenditure in the financial system based on the refund amount and the preset accounting account;

[0074] For price changes, record the income or expense adjustment based on the difference between the order amount after the price change and the original order amount;

[0075] For order closure operations, the system records the corresponding income reduction or expense expenditure based on the order amount and the incurred expenses (such as the partial amount paid and platform fees);

[0076] 2.4.2 Step S401, database record update:

[0077] Based on the results of refund, price change, and order closure operations, the order status information in the database is updated, including the order status and processing time; for any illegal operations involving the driver, the corresponding record is added to the driver's credit record; for passenger complaints, the processing results are added to the passenger complaint handling record.

[0078] 2.5 Step S5, Result Feedback and Notification:

[0079] The processing results will be fed back to the channels and relevant parties, including passengers, drivers and service providers; the notification content will include the processing results, refund amount and order status update information.

[0080] (3) Mechanisms for resolving technical issues:

[0081] 3.1 Mechanism and Principles for Solving the Problem of Accuracy in Judgment:

[0082] This invention receives order information, complaint content, and GPS trajectory data from channels, providing a comprehensive basis for accountability. The system's built-in, pre-set accountability rules accurately identify violations and determine who is responsible. The system comprehensively analyzes received data packets, applying algorithms to process and match the data, automatically generating accountability results that include the identification of the responsible party, the type of violation, and the severity of the violation.

[0083] Compared to traditional manual judgment, this invention uses an automated and intelligent judgment method, avoiding misjudgments and biases caused by human factors. The system can continuously learn and optimize judgment rules, improving the accuracy and efficiency of judgment.

[0084] 3.2 Mechanism and principle for resolving inconsistencies in the work order processing link:

[0085] Based on the results of the automated accountability assessment, the present invention immediately generates an accountability work order and automatically pushes it to the appropriate handling department or system. This approach ensures timely work order processing and avoids delays and errors caused by manual intervention. Furthermore, the work order contains detailed order information, responsible individuals, violation details, and recommended action measures, providing clear guidance to the handling department.

[0086] Second, the reverse processing system for online ride-hailing platforms:

[0087] like Figure 2-3 As shown, the system is used to implement the above-mentioned reverse processing method for the online car-hailing platform, which includes:

[0088] (1) Data collection module: responsible for receiving data packets from different channels, including order information, complaint content and GPS trajectory data.

[0089] The data collection module ensures that the system can obtain comprehensive and accurate information, providing data support for subsequent judgment and processing.

[0090] (2) Automatic accountability module: It has built-in preset accountability rules, conducts comprehensive analysis on the collected data, uses algorithms to process and match the data, automatically determines the responsible party (driver or platform), and generates accountability results, including the identification of the responsible person, the type of violation, and the degree of violation.

[0091] The automatic judgment module improves the accuracy and efficiency of judgment and avoids misjudgment and bias caused by human factors.

[0092] (3) Work order generation and push module: Based on the results of automatic accountability, a work order is automatically generated; the work order contains detailed order information, responsible person, violation details, and recommended handling measures;

[0093] Automatically push work orders to the corresponding processing department or system to ensure timely processing of work orders.

[0094] (4) Cost processing module: automatically determines the party responsible for the cost based on the degree of violation and preset rules; performs refund, price change or order closure operations, and the refund amount is calculated based on the degree of violation and preset rules;

[0095] The fee processing module ensures fair and reasonable handling of fees and protects the rights and interests of passengers and the platform.

[0096] (5) Financial accounting and record update module: Financial accounting of refunds, price changes and order closing operations; update relevant databases and records, including order status, driver credit records and passenger complaint handling records.

[0097] (6) Result Feedback and Notification Module: Feedback the processing results to the channel and relevant parties, including passengers, drivers, and service providers. The notification content includes the processing results, refund amount, and order status update information. The result feedback and notification module enhances the transparency and credibility of the platform and improves the satisfaction of passengers and drivers.

[0098] Compared with the prior art, the present invention has the following beneficial effects:

[0099] 1. Improved accountability accuracy: Through an automated and intelligent accountability system, combined with comprehensive data analysis and pre-set accountability rules, the present invention can accurately identify violations and determine the responsible party, significantly reducing the possibility of human misjudgment and bias, and improving the accuracy and fairness of accountability. The present invention's automatic work order generation and push mechanism ensures timely work order processing. Furthermore, the standardized work order processing process and real-time monitoring mechanism make the work order processing chain smoother, reducing delays and errors during the processing process and improving overall processing efficiency.

[0100] Second, enhanced passenger satisfaction: Accurate accountability and efficient ticket processing ensure timely and fair resolution of passenger complaints and issues. This not only improves the passenger experience but also strengthens their trust and loyalty to the platform. Through clear accountability and a reasonable cost-sharing mechanism, this invention effectively avoids disputes between drivers and the platform. Furthermore, accurate identification and punishment of violations maintains the platform's operational order and a fair competitive environment.

[0101] 3. Optimizing resource allocation: Automated accountability and work order processing reduces manual intervention and operations, thereby optimizing platform resource allocation. This allows the platform to focus more on improving service quality and expanding business, further driving platform development. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or technical descriptions. Obviously, the drawings described below are only 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 work.

[0103] Figure 1 Schematic diagram of the method flow of the present invention;

[0104] Figure 2 It is a schematic diagram of the system composition of the present invention;

[0105] Figure 3 Schematic diagram of the system execution flow of the present invention. DETAILED DESCRIPTION

[0106] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. The following description sets forth many specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0107] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0108] Explanation of relevant terms:

[0109] (1) Order information: Contains all relevant information generated when a passenger makes a taxi reservation, such as the starting and ending points, time, and cost.

[0110] (2) Complaint content: The specific complaint description submitted to the platform by the passenger when the passenger is dissatisfied with the driver's service or discovers a violation.

[0111] (3) GPS trajectory data: records the geographic location information of the vehicle during driving, which is used to verify the driving route and distance.

[0112] (4) Responsibility judgment rules: The standards and logic preset by the platform to determine whether the driver or the platform has violated the rules and to determine the responsibility.

[0113] (5) Responsible person identification: The unique identification mark of the responsible party (driver or platform) determined according to the liability judgment rules.

[0114] (6) Violation type: classification of driver or platform violations, such as detours, malicious surcharges, etc.

[0115] (7) Violation severity: This measures the severity of the violation and may affect the refund amount and handling measures.

[0116] (8) Violation details: A detailed description of the specific circumstances of the violation, including time, location, behavior, etc.

[0117] (9) Recommended treatment measures: Based on the type and severity of the violation, the system provides treatment suggestions, such as refund, price change, order closure, etc.

[0118] (10) Preset rules for violation degree and refund amount: rules preset by the platform for calculating the refund amount based on the violation degree.

[0119] (11) Order status: information reflecting the current stage or status of the order, such as pending payment, in progress, completed, canceled, etc.

[0120] (12) Driver credit record: a file that records the driver’s service performance, violations and penalties on the platform.

[0121] (13) Passenger complaint handling records: files that record the details of passenger complaints and the platform’s handling results.

[0122] (14) Order status update information: When the order status changes, the platform sends an update notification to the relevant parties, including the new status and the reason for the change.

[0123] Example 1: Figure 1As shown, this embodiment discloses an application example of the reverse processing method of an online ride-hailing platform in an online ride-hailing operation and maintenance system. Assume that on a certain online ride-hailing platform, passenger A complains to driver B about taking a detour and provides order information, complaint description, and GPS trajectory data. Based on this data, the platform needs to determine the responsible party through an automatic accountability system, generate an accountability work order based on this data, ultimately determine the cost bearer, complete financial accounting and record updates, and feedback the results to the relevant parties. The solution process includes:

[0124] In this embodiment, regarding step S1: automatic judgment logic execution:

[0125] Receiving data packets: The system receives a complaint data packet from passenger A, including order information (order number, passenger ID, driver ID, starting location, destination, order time, etc.), complaint content (text description of the detour) and GPS trajectory data (driving trajectory of the passenger and driver sides).

[0126] Violation rule processing: The system processes data packets based on pre-set violation rules. These rules include mappings between time ranges, location ranges, and violation types. For example, if a driver's route deviates by more than 20% from the pre-set route, it will be considered a detour.

[0127] Judgment result: The system determines that driver B has taken a detour, the violation type is "detour", the violation level is "moderate", and a responsible person identification (driver B's ID) is generated.

[0128] Specifically, step S100: matching of judgment rules:

[0129] Initialization: The system initializes the violation type set Vmatched to an empty set.

[0130] Rule matching: The system traverses the set of judgment rules R. For each rule r, it calls the matching function M(D, r) to determine whether the packet D meets the conditions. For example, if the rule "If the driver's driving time exceeds the estimated time by 30% and the driving distance exceeds the estimated distance by 20%, it is considered a detour" is met by comparing the GPS trajectory data with the time information.

[0131] Result generation: Add the violation type "detour" corresponding to the rule that meets the conditions to V matched middle.

[0132] Specifically, step S101: the responsible party determines:

[0133] Initialization: responsible party for system initialization party is unknown (UNKNOWN).

[0134] Decision logic: System checks V matchedIs not empty, traverse the violation types. It is found that "detour" belongs to the violation type set R that is directly related to the driver driver .

[0135] Detailed analysis: The system analyzes the driver's driving route D route 、Content of passenger's complaint D complaint and GPS trajectory data D gps , confirming that the driver did take a detour.

[0136] Result judgment: Set the responsible party to driver (DRIVER).

[0137] Specifically, step S102: generating the judgment result: the system generates the judgment result information according to the judgment result of the responsible party, including the identification of the responsible person (the ID of driver B), the violation type (detour) and the degree of violation (moderate).

[0138] In this embodiment, regarding step S2: generating a judgment work order:

[0139] S200, obtaining the judgment result: the system obtains the judgment result from the automatic judgment module.

[0140] S201, Work Order Assembly: Automatically assemble a work order for accountability, including the order number, responsible person (Driver B), violation details (specific circumstances and evidence of the detour), and recommended handling measures (refund the passenger and warn the driver).

[0141] S202, responsible party push: push the work order to driver B's application end so that the driver can view and process it.

[0142] In this embodiment, regarding step S3: determining the party responsible for the expenses:

[0143] S300, work order analysis: The system analyzes the work order content and automatically calculates the refund amount based on the preset rules of the violation level and refund amount.

[0144] S301, Financial Accounting and Notification: Financial accounting of the refund operation is performed, and a notification is sent to passenger A, driver B, and the platform's financial department to inform them of the refund amount and judgment result.

[0145] In this embodiment, regarding step S4: financial accounting and record updating:

[0146] S400, Financial Accounting Preparation: Collect and organize the financial information of the refund operation.

[0147] S401, Financial Accounting: Record refund expenditure in the financial system.

[0148] S402, database record update: update the order status to "refunded", add the detour violation record to driver B's credit record, and update passenger A's complaint handling record to "handled".

[0149] In this embodiment, regarding step S5: Result Feedback and Notification: the system will feedback the processing results (including refund amount and order status update information) to passenger A, driver B, and the service provider (if necessary). The notification content is sent via in-app message, SMS, or email.

[0150] The technical solution provided in this embodiment utilizes an automated accountability system that combines GPS trajectory data, order information, and complaint content to objectively and accurately determine the responsible party, reducing the subjectivity and errors inherent in human judgment. From complaint receipt to work order generation, cost-bearing determination, financial accounting and record updates, and finally feedback and notification, the entire process is automated and standardized, ensuring consistency and efficiency throughout the work order processing chain. This improves accountability efficiency and reduces manual intervention costs; enhances trust between passengers and drivers, improves the platform's service quality, and provides data support for subsequent optimization and improvement.

[0151] Example 2: Based on Example 1, this example further provides a Python execution program for the solution described in Example 1 as follows:

[0152]

[0153]

[0154]

[0155]

[0156]

[0157] The principle of the above procedure is:

[0158] (1) Data reception: The program first receives a data packet containing order information, complaint content, and GPS trajectory data.

[0159] (2) Rule Matching: The program iterates through the pre-set rule set and applies a conditional function to each rule to determine whether the packet meets the rule's conditions. In this example, we assume an is_route_deviation_exceed function to determine whether the driver's route deviates from the pre-set route by more than a threshold. If the condition is met, the corresponding violation type is added to the Vmatched set.

[0160] (3) Determination of responsible party: The program checks the Vmatched set. If it finds that the violation type "detour" is included, the responsible party is determined to be the driver.

[0161] (4) Generation of accountability results: Based on the accountability results, an accountability result is generated that includes the identification of the responsible party, the type of violation, and the degree of violation.

[0162] (5) Work order generation and push: Based on the judgment result, a judgment work order is generated and pushed to the application end of driver B.

[0163] (6) Determination of the party responsible for the cost: Based on the work order content, the calculate_refund_amount function calculates and returns a fixed refund amount.

[0164] (7) Perform financial accounting and database record updates.

[0165] (8) Result feedback and notification: Send a notification to passenger A, driver B and the platform’s financial department to inform them of the refund amount and judgment result.

[0166] All of the above embodiments merely represent implementation methods of the present invention in practical applications. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the scope of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the appended claims.

[0167] For those skilled in the art, it can be further appreciated that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. 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 the present invention.

[0168] At the same time, those skilled in the art will understand that all or part of the processes in all the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

Claims

1. A method for reverse processing of a ride-hailing platform, characterized in that: The following steps are included: S1 receives data packets from the channel, including order information, complaint content, and GPS trajectory data; processes the received data packets according to the preset judgment rules and automatically determines the responsible party; S2, based on the results of automatic accountability, generates an accountability work order and pushes it to the corresponding responsible party; S3, automatically executes refunds, price changes, or order closures based on the responsible person information in the judgment work order; S4, conduct financial accounting for the refund, price change and order closing operations, and update the database and records, including order status, driver credit record and passenger complaint handling record.

2. The reverse processing method according to claim 1, characterized in that: The execution method of S1 includes: S100, Execution of Judgment Rules: S1000, initialize violation type set V matched is an empty set; S1001, for each rule r in the judgment rule set R: Call the matching function M(D,r) to determine whether the data packet D meets the conditions of rule r; If M(D, r) = true, then add the violation type v corresponding to rule r to V matched middle; S1002, return to V matched as a collection of identified violations; Where D is a data packet containing order information, complaint content, and GPS trajectory data; R is a set of judgment rules, where each rule r∈R contains a set of violation types corresponding to a set of conditional time ranges and location ranges; V is a set of violation types, where each violation type v∈V corresponds to one or more judgment rules; M(D,r) is a matching function used to determine whether data packet D meets the conditions of rule r. S101: Determine whether the driver or the platform is responsible based on the driver's route, the passenger's complaint, and the accuracy of GPS trajectory data: S1010, initialize responsible party party is unknown; S1011, check V matched Is it empty? If it is empty, it means no violation has been identified. If it is not empty, continue to execute: Traverse V matched For each violation type v in: If v belongs to R driver , that is, directly related to the driver; S1012, Analysis D route 、D complaint and D gps , confirm whether the driver's driving route is consistent with the complaint content, and whether the GPS trajectory data supports this conclusion; if the analysis results show that the driver has indeed violated the regulations, the responsible party Set to driver; Break out of loop; S1013, if v belongs to R platform , which is directly related to the platform: Analyze relevant data to confirm whether there is any violation on the platform, and party Set to platform; break out of loop; S1014, returning responsible_party as the determination result of the responsible party; S102: Generate information on the responsible party's judgment result, including the responsible party's identification, violation type, and violation severity.

3. The reverse processing method according to claim 1, characterized in that: In S2, the work order includes the order number, responsible person, violation details and recommended handling measures.

4. The reverse processing method according to claim 3, characterized in that: The execution method of S2 includes: S200 automatically assembles the content of the accountability work order based on the accountability result, including the order number, which uniquely identifies the order; the responsible party, which indicates which party bears the responsibility; and the violation details, which describe the violation and evidence. S201: If the driver is responsible, the work order is pushed to the driver's application or platform. If the platform is responsible, the work order is pushed to the platform's internal department or system. S202, recording the push time and push status of the work order. After processing the work order, the responsible party receives and records the processing results and feedback information.

5. The reverse processing method according to claim 1, characterized in that: In said S3, the refund amount is calculated based on the violation degree and the preset refund amount rules; the price change operation adjusts the order amount according to actual needs; The order closing operation is used to cancel invalid or illegal orders.

6. The reverse processing method according to claim 4, characterized in that: The execution method of S3 includes: S300: For orders requiring a refund, the system automatically calculates the refund amount based on the violation severity and preset refund amount rules. If the order amount needs to be adjusted, the system performs a price adjustment based on the actual passenger's needs. This includes increasing or decreasing the order amount, and adjusting the price based on the actual passenger's needs. Order closing operations include updating, deleting, or modifying the order status. S301: Financial accounting of refunds, price changes, and order closures to ensure clarity and accuracy; at the same time, notifications are sent to passengers, drivers, and the platform's financial department to inform the cost-bearing party of the judgment result, refund amount, price change, or order closure operation.

7. The reverse processing method according to claim 4, characterized in that: The execution method of S4 includes: S400 collects and organizes financial information for refund, price change, and order closure operations, including operation type, amount, and time. For refund operations, the refund expense is recorded in the financial system based on the refund amount and the preset accounting account. For price change operations, the revenue or expense adjustment is recorded based on the difference between the order amount after the price change and the original order amount. For order closure operations, the system records the corresponding revenue reduction or expense expenditure based on the order amount and incurred expenses. S401, based on the results of the refund, price change, and order closing operations, update the order status information in the database, including the order status and processing time.

8. The reverse processing method according to any one of claims 1 to 7, characterized in that: It also includes S5: Feedback of processing results to channels and relevant parties, including passengers, drivers and service providers; notification content includes processing results, refund amount and order status update information.

9. A system for implementing the reverse processing method according to any one of claims 1 to 8, characterized in that: The system comprises: Data collection module: responsible for receiving data packets from different channels, including order information, complaint content and GPS trajectory data; Automatic accountability module: This module has built-in preset accountability rules, conducts comprehensive analysis of collected data, uses algorithms to process and match data, automatically determines the responsible party, and generates accountability results, including the responsible party identification, violation type, and violation severity; Digital work order generation and push module: Based on the results of automatic accountability, it automatically generates accountability work orders; the work orders contain detailed order information, responsible persons, violation details, and recommended handling measures; Cost processing module: automatically determines the party responsible for the cost based on the degree of violation and preset rules; performs refunds, price changes, or order closures, with the refund amount calculated based on the degree of violation and preset rules; Financial accounting and record update module: Financial accounting for refunds, price changes and order closures; updates databases and records, including order status, driver credit records and passenger complaint handling records.

10. The system according to claim 9, characterized in that: The system also includes a result feedback and notification module: the processing results are fed back to the channels and relevant parties, including passengers, drivers and service providers.

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