Accounting notice delivery method and system for online car-hailing driver

Abstract

The invention discloses a liability judgment notification delivery method and system for online car-hailing drivers. The invention relates to the technical field of online car hailing. After complaint information submitted by a passenger is received, a real-time notification mechanism is triggered, that is, a complaint notification including complaint time, place and complaint content summary is sent to a related driver through two modes of message and short message in the application. Performing preliminary analysis on the complaint information according to a preset responsibility judgment standard, and determining whether violation is formed or not; if the violation is formed, generating violation behavior evidences including automobile data recorder video clips and GPS positioning data; the real-time notification mechanism ensures that the complaint of the passenger can be quickly known and processed by the driver, the waiting response time of the passenger is reduced, and the service experience of the passenger is enhanced. Transparent processing of the responsibility judgment process enables passengers to better understand the complaint processing flow and standard, the credibility of processing results is increased, and therefore the satisfaction degree is improved.

Description

Technical Field

[0001] The present invention relates to the field of online car-hailing technology, specifically to the management of online car-hailing drivers, and more particularly to a method and system for delivering notices of liability to online car-hailing drivers. Background Art

[0002] Amidst increasingly fierce competition in the ride-hailing market, platforms face the significant challenge of ensuring driver behavior and service standards are adhered to, aiming to comprehensively enhance the quality of the user experience. When violations such as passenger refusal, lateness, and poor service attitude occur, existing technologies immediately initiate a responsibility determination process upon detection, determining appropriate action based on established rules. These actions may include issuing warnings to drivers, imposing fines, deducting points, or even suspending their service eligibility, ensuring timely correction and prevention of misconduct.

[0003] Warning information is pushed to the relevant drivers through the platform system, clearly indicating the specific details of the violation and the penalties suffered. After receiving the warning information, the driver has the right to provide feedback and appeal. This two-way communication mechanism not only enhances the driver's understanding and recognition of the platform rules, but also ensures that the driver has reasonable explanation and defense channels. During the appeal verification and processing stage, the platform will carefully review the appeal materials submitted by the driver, update the information status in a timely manner, and record the entire processing process in detail for regulatory purposes and future decision-making reference. However, the current solution still has several flaws:

[0004] (1) Lack of notification of passenger complaints and the accountability process: Drivers lack a clear understanding of the accountability process, which weakens the deterrent effect of regulatory measures and reduces drivers’ trust in the platform’s accountability process. Penalties are not easily explained, resulting in a limited warning effect on potential problem drivers, and drivers are prone to ignoring rectification requirements.

[0005] (2) The conversion rate from customer complaints to driver liability is relatively low: Among all types of complaints, the proportion of drivers being deemed responsible is relatively low. This leads drivers to lack sufficient awareness of complaints that are not determined to be responsible, and they mistakenly believe that the platform only focuses on the responsible party, which in turn leads to bias in the platform's liability judgment and reduces their trust in the platform. Drivers generally perceive that the platform's judgment of liability is biased, which can easily lead to resentment and resistance.

[0006] To this end, the present invention proposes a method and system for delivering a notice of culpability to online car-hailing drivers. Summary of the Invention

[0007] In view of this, the present invention aims to provide a method and system for delivering liability notices to online ride-hailing drivers to solve or alleviate the technical problems existing in the prior art, namely, the lack of passenger subjective complaint notifications and liability determination processes and the low conversion rate from customer complaints to driver liability determinations, and to at least provide a beneficial alternative. The technical solution of the present invention is achieved as follows:

[0008] First, the method of delivering the notice of judgment to online car-hailing drivers:

[0009] (1) Overview:

[0010] The present invention aims to build an efficient, transparent and continuously improving customer complaint handling system. Through a real-time notification mechanism, it ensures that drivers can promptly understand the passenger's complaint information, thereby enhancing the timeliness of processing. At the same time, based on the preset judgment and accountability standards, the complaints are objectively and impartially analyzed, detailed evidence of violations is generated, and the judgment and accountability results and explanations are transparently communicated to the driver, thereby improving the transparency of the judgment and accountability process. The solution also establishes multiple review queues, and auditors at different levels review the judgment and accountability results to ensure accuracy. In addition, through follow-up tasks, feedback from drivers is promptly understood, suggestions for improvement are collected, and in-depth analysis is conducted based on data such as judgment and accountability accuracy and driver feedback rates, so as to continuously optimize the judgment and accountability standards and processes. Ultimately, the solution aims to improve the service quality of drivers through incentive and training mechanisms, and to achieve a virtuous cycle and continuous improvement in the customer complaint handling process.

[0011] (2) Technical solution:

[0012] To achieve the above technical objectives, the present invention chooses to perform the following operating steps.

[0013] 2.1 Step S1, data reception and processing:

[0014] After receiving the complaint information submitted by the passenger, the real-time notification mechanism is triggered, that is, the complaint notification is sent to the relevant driver through in-app messages and text messages, including the time, location and summary of the complaint content.

[0015] 2.1.1 Step S100: Receive complaint information:

[0016] Receive complaint information submitted by passengers through designated interfaces or channels, including complaint time, complaint location, complaint content and passenger contact information; store complaint information in the database as basic data for subsequent processing.

[0017] 2.1.2 Step S101, triggering the real-time notification mechanism:

[0018] Based on the relevant driver identification (driver ID and license plate number) in the complaint information, determine the driver who needs to be notified; assemble the content of the complaint notification; the notification content includes the time, location and an overview of the complaint content to ensure that the driver can quickly understand the basic circumstances of the complaint.

[0019] 2.1.3 Step S102: Send complaint notification:

[0020] Complaint notifications are sent to relevant drivers via in-app messages and SMS messages; in-app messages are pushed through the platform's mobile application, while SMS messages are sent through the SMS gateway.

[0021] 2.1.4 Step S103, record notification sending status:

[0022] Record the sending of complaint notices, including the sending time, sending method and whether they were successfully delivered.

[0023] 2.2 Step S2: Transparency of the accountability process:

[0024] Complaint information is preliminarily analyzed based on preset judgment standards to determine whether it constitutes a violation. If so, evidence of the violation is generated, including dashcam video footage and GPS positioning data. The judgment results and detailed explanation are pushed to the driver via in-app messages or text messages, and the judgment standards are made public for drivers to query and understand.

[0025] 2.2.1 Step S200: Preliminary analysis of complaint information:

[0026] Receive complaint information from the passenger complaint module and conduct preliminary sorting and analysis of the complaint content; based on the preset judgment standards, determine whether the complaint behavior constitutes a violation, and determine the type and extent of the violation.

[0027] 2.2.2 Step S201: Generate evidence of violation:

[0028] If the complaint constitutes a violation, relevant evidence of the violation will be collected and generated, including dashcam video footage and GPS positioning data. The final judgment will be determined based on the preliminary analysis and generated evidence of the violation. The judgment will include the driver's violation, the degree of violation, and the corresponding handling measures.

[0029] 2.2.3 Step S202, detailed explanation of the judgment result:

[0030] To ensure transparency in the accountability process, provide a detailed explanation of the accountability outcome, including the basis for the accountability, the specific manifestations of the violation, and the rationale for the action taken;

[0031] Push the judgment result and detailed explanation to the relevant driver through in-app message or SMS;

[0032] 2.2.4 Step S203: Publicly disclose the criteria for accountability:

[0033] The standards for judging responsibility are made public, and drivers can check the standards at any time to understand whether their behavior complies with the regulations, as well as possible violations and corresponding handling measures.

[0034] 2.3 Step S3, Optimize the customer complaint handling process:

[0035] Submit the accountability results to multiple review queues for review by auditors at different levels; auditors can confirm or adjust the accountability results based on detailed evidence and accountability criteria.

[0036] A follow-up task is automatically arranged for each complaint, so that customer service personnel or the automated follow-up system can explain the basis and process of the judgment to the driver; the follow-up results are recorded in the system database.

[0037] 2.3.1 Step S300: Submit the judgment result to the multiple review queue:

[0038] Submit the preliminary determination results to a multi-level review queue; arrange for junior auditors, senior auditors, supervisors, etc. to review the determination results; auditors at each level should review the determination results based on the evidence and the preset determination criteria;

[0039] 2.3.2 Step S301: Confirm or adjust the judgment result:

[0040] After the auditor confirms or adjusts the judgment result based on the review, if the judgment result is accurate, it will be confirmed; if it is found to be incorrect or controversial, it will be adjusted;

[0041] 2.3.3 Step S302: Automatically arrange return visit tasks:

[0042] For each complaint, a follow-up task will be arranged; during the follow-up process, the customer service staff or the automated follow-up system should explain to the driver the basis for the judgment, including the standards for judgment, the specific manifestations of the violation and the reasons for the handling measures.

[0043] 2.3.4 Step S303: Record the results of the follow-up visit:

[0044] The results of the follow-up visit (drivers' feedback, opinions and suggestions) should be accurately recorded in the system database; the follow-up visit results should serve as the basis for subsequent processing and improvement, which will help to improve the customer complaint handling process and enhance service quality.

[0045] 2.4 Step S4, data analysis and statistics:

[0046] Regularly collect and analyze the accuracy rate of judgment and driver feedback rate during the judgment process, and monitor the driver's driving trajectory and speed in real time through GPS positioning and driving recorders; compare real-time monitoring data with the system's preset service standards to promptly detect and deal with violations.

[0047] 2.4.1 Step S400: Regularly collect accountability data:

[0048] Set regular time intervals (such as daily, weekly, monthly, etc.) to automatically collect the accuracy rate of the accountability process and the driver feedback rate, as well as detailed records of the accountability process, including the accountability time, the person who made the judgment, and the accountability results.

[0049] 2.4.2 Step S401: Analyze the accuracy of judgment:

[0050] The collected accountability data were analyzed and the accountability accuracy rate was calculated; the accountability accuracy rate was defined as the ratio of the number of complaints that were correctly accounted for to the total number of complaints.

[0051] 2.4.3 Step S402: Analyze driver feedback rate:

[0052] The driver feedback data is collected and analyzed to calculate the driver feedback rate, which is defined as the ratio of the number of complaints in which drivers provide feedback on the judgment results to the total number of complaints.

[0053] 2.4.4 Step S403: Real-time monitoring of driver's driving data:

[0054] Use GPS positioning and driving recorders to monitor the driver's driving trajectory and speed in real time;

[0055] Compare real-time monitoring data with the system's preset service standards to determine whether the driver's driving behavior complies with regulations, including speed limits, the rationality of driving trajectories, and service attitude requirements. By comparing real-time monitoring data with service standards, drivers' violations can be discovered in a timely manner and appropriate measures can be taken.

[0056] 2.4.5 Step S404: Handle violations promptly:

[0057] For any violations discovered, the processing mechanism is automatically triggered, including warnings, fines, training or suspension of services.

[0058] 2.5 Step S5, incentive and training mechanism:

[0059] Automatically calculate reward amounts or points based on the driver's service quality and performance; push reward information to the driver and update the driver's account balance or points; regularly arrange seminars or online meetings and notify drivers to participate.

[0060] (3) Mechanisms for resolving technical issues:

[0061] 3.1 Deficiencies in passenger complaint notification and accountability processes:

[0062] Upon receiving a passenger complaint, the system triggers a real-time notification mechanism via in-app and SMS messages, ensuring that the relevant driver receives prompt notification. This notification includes the time, location, and summary of the complaint, allowing drivers to promptly understand and prepare for a response. The system then conducts a preliminary analysis of the complaint based on pre-set criteria to determine whether it constitutes a violation. If so, detailed evidence of the violation, such as dashcam footage and GPS location data, is generated. The system then sends the driver a notification of the verdict and a detailed explanation via in-app or SMS messages. The criteria are also publicly available for drivers to review and understand. This process not only ensures fairness but also enhances transparency in the process.

[0063] Using technology to instantly transmit complaint information ensures drivers can respond quickly to passenger complaints. Publicizing accountability criteria and detailed explanations enhances the transparency and credibility of the accountability process, reducing misunderstandings and conflicts between passengers and drivers.

[0064] 3.2 The conversion rate from customer complaints to driver liability determinations is relatively low:

[0065] The judgment results are submitted to multiple review queues and reviewed by reviewers or algorithms at different levels. This helps ensure the accuracy and fairness of the judgment results and reduces misjudgments and missed cases. For each complaint, the system automatically schedules a follow-up visit. Customer service personnel or the automated follow-up system will explain the basis and process of the judgment to the driver and understand the driver's feedback and opinions. This helps strengthen the driver's recognition and acceptance of the judgment results. Data from the judgment process, such as judgment accuracy and driver feedback rates, is regularly collected and analyzed. This data can be used to promptly identify problems and deficiencies in the judgment process and implement appropriate measures for optimization and improvement.

[0066] Through multiple audits and follow-up visits, we improve the accuracy and fairness of accountability decisions and strengthen drivers' recognition of these decisions. Through data analysis and statistics, we promptly identify and resolve issues in the accountability process, continuously optimize and improve the accountability process, and increase the conversion rate from customer complaints to driver accountability decisions.

[0067] Secondly, the system for delivering notices of judgment to online ride-hailing drivers:

[0068] like Figure 2 As shown, the system is used to implement the above-mentioned method for delivering a notice of judgment to a ride-hailing driver, which includes:

[0069] (1) Passenger complaint module: responsible for receiving complaint information submitted by passengers, including the time, location and content of the complaint.

[0070] Accurately store complaint information in the database as a basis for subsequent processing. At the same time, push complaint information to the driver notification module in real time to ensure that drivers can quickly understand and handle it.

[0071] (2) Driver Notification Module: Receives complaint information from the passenger complaint module and pushes it to relevant drivers in real time through mobile applications and text messages.

[0072] Record the notification sending status, including the sending time and method, and store the driver's feedback information in the database to provide a basis for subsequent processing.

[0073] (3) Judgment module: Receives complaint information and conducts review and judgment based on preset judgment standards.

[0074] The judgment results are sent to the driver notification module, informing the driver of the handling results and recording them in the database. Multiple audit mechanisms and third-party supervision are supported to ensure the fairness and transparency of the judgment process.

[0075] (4) Driver feedback module: Receives feedback and appeals from drivers regarding the judgment results, including the driver’s objection and explanation or additional evidence.

[0076] Driver feedback is passed to the accountability module for review to ensure the accuracy and fairness of the accountability results. Feedback and processing results are recorded and stored in the database to provide a basis for subsequent analysis and improvement.

[0077] (5) Service quality management module: Through GPS positioning and driving recorder, the driver's driving trajectory and speed are monitored in real time.

[0078] Collect and analyze driver service data to generate a service quality evaluation report. Feedback the evaluation results to the driver notification module, allowing drivers to understand their service performance. At the same time, an incentive mechanism rewards outstanding drivers to stimulate their enthusiasm and motivation for service.

[0079] (6) Data analysis and statistics module: Comprehensive analysis of the data from each module, including the number of complaints, accuracy of judgment and driver feedback rate.

[0080] Identify common issues and optimization directions to support platform management decisions. Generate statistical reports to visually display the overall status of customer complaint handling and service quality management.

[0081] (7) Communication and training module: responsible for organizing regular training for drivers to improve their service awareness and skills.

[0082] Improve drivers' service levels through training and reduce complaints. Learn about drivers' needs and demands in a timely manner through communication mechanisms, providing first-hand information for platform management.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] 1. Improved passenger satisfaction and optimized the customer complaint handling process: The real-time notification mechanism of the present invention ensures that passenger complaints can be quickly known and handled by drivers, reducing the time passengers have to wait for responses and enhancing the passenger service experience. The transparent handling of the accountability process allows passengers to better understand the process and standards for complaint handling, increasing their trust in the handling results, thereby improving satisfaction. The arrangement of follow-up tasks allows customer service personnel to promptly understand the driver's feedback and opinions, providing a valuable reference for improving the accountability process. The application of data analysis and statistics makes the customer complaint handling process more scientific and refined, enabling timely identification and resolution of problems in the process, thereby improving processing efficiency.

[0085] Second, it enhances drivers' sense of responsibility and acceptance: By receiving real-time complaint notifications, drivers can promptly understand any issues with their service, enabling them to proactively improve their service attitude and quality. Detailed explanations of judgments and public disclosure of judgment criteria allow drivers to better understand the basis for judgments, enhancing their acceptance and acceptance of judgments and, in turn, fostering a stronger sense of responsibility.

[0086] Improved accuracy and fairness of accountability: The present invention's multiple review queues ensure that accountability results undergo multiple levels of review, reducing misjudgments and omissions, and improving accuracy. The participation of reviewers at different levels ensures the fairness of the accountability process and enhances the credibility of the results.

[0087] Fourth, it promotes the continuous improvement of driver service quality: The establishment of the incentive and training mechanism of this invention gives drivers more motivation to improve their service quality and strive to obtain more rewards and points. Regular discussion mechanisms or online conferences provide a platform for drivers to communicate and learn, which helps drivers learn from each other and make progress together. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] 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.

[0089] Figure 1 Schematic diagram of the method flow of the present invention;

[0090] Figure 2 Schematic diagram of the system composition of the present invention. DETAILED DESCRIPTION

[0091] 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.

[0092] 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.

[0093] Explanation of relevant terms:

[0094] (1) Real-time notification mechanism: a notification system that sends complaint information to drivers immediately.

[0095] (2) Summary of complaint content: A brief description of the passenger’s complaint content.

[0096] (3) Pre-set standards for judgment: standards set in advance to determine whether a driver has violated the law.

[0097] (4) Multiple audit queue: A queue consisting of multiple audit links, used to review the judgment results.

[0098] (5) Auditors at different levels: Auditors with different authority and responsibilities participate in the review of the judgment results.

[0099] (6) Follow-up task: Arrange customer service staff to explain the judgment results to the driver.

[0100] (7) Accuracy of judgment: the degree of consistency between the judgment result and the actual violation situation.

[0101] (8) Driver feedback rate: the proportion of drivers’ feedback on the judgment results or service quality improvement suggestions.

[0102] (9) Confirmation or adjustment: The process by which auditors confirm the judgment results or make adjustments as needed.

[0103] (10) Notice of Judgment: A written notice issued to the driver in an online car-hailing service to inform him of any possible violations.

[0104] (11) Violation: The driver violates the platform regulations, laws or service agreement during the provision of services.

[0105] (12) Appeal: If the driver believes that the notice is incorrect or there are special circumstances, he or she may file an appeal through designated channels.

[0106] (13) Disposal: usually refers to the handling and management of driver violations or improper service.

[0107] Example 1: Figure 1 As shown, this embodiment discloses an application example of the method for delivering a notice of judgment to an online car-hailing driver in an online car-hailing driver operation and maintenance management system.

[0108] In this embodiment, regarding step S1: data reception and processing

[0109] Step S100: Receive complaint information: A passenger submits a complaint through the ride-hailing app, including the time of complaint (e.g., 2:30 PM, May 1, 2023), location (e.g., No. XX, Road XX), content (e.g., "The driver had a bad attitude and refused to pick me up"), and the passenger's contact information. The system receives this information through the API and stores it in the database as basic data for subsequent processing.

[0110] Step S101: Triggering the real-time notification mechanism: The system determines the driver to be notified based on the driver ID and license plate number in the complaint information. The complaint notification content is assembled: "You were complained by a passenger about your bad attitude and refusal to pick up passengers at No. XX, XX Road, at 2:30 PM on May 1, 2023. Please review and handle the matter as soon as possible."

[0111] Step S102: Send complaint notification: Push an in-app message to the driver via the platform's mobile app. Simultaneously, send a text message notification to the driver via the SMS gateway.

[0112] Step S103: Record notification sending status: The system records the sending time of the complaint notification (such as XX:XX, XX, XX, XX), the sending method (in-app message and SMS) and whether it was successfully delivered (successful / failed).

[0113] The real-time notification mechanism ensures that drivers are aware of passenger complaints in a timely manner and can respond quickly. This solves the problem of delayed notification of passenger complaints and improves the timeliness of complaint handling.

[0114] In this embodiment, regarding step S2: transparent processing of the accountability process:

[0115] Step S200: Preliminary analysis of complaint information: After receiving the complaint information, the system performs a preliminary analysis based on preset judgment standards (such as poor service attitude, refusal to carry passengers, etc., which are violations).

[0116] Determine whether the complaint constitutes a violation and determine the type (e.g., poor service attitude) and degree (e.g., serious) of the violation.

[0117] Step S201: Generate Violation Evidence: If the complaint constitutes a violation, the system collects dashcam video footage and GPS location data as evidence. Based on this evidence and preliminary analysis, the final judgment is made: the driver has committed a serious violation, characterized by poor service attitude.

[0118] Step S202: Detailed explanation of the judgment result: For example, the system provides a detailed explanation of the judgment result: "Based on the dashcam video and GPS positioning data, you violated the rules of poor service attitude at No. XX, XX Road at 2:30 PM on May 1, 2023. The violation was serious. According to the platform regulations, you will be dealt with accordingly."

[0119] The judgment result and detailed explanation will be pushed to the driver via in-app message or SMS.

[0120] Step S203: Publicly publish the judgment standards: The system publishes the judgment standards on the platform, and drivers can check them at any time to understand whether their behavior complies with the regulations.

[0121] Transparency in the accountability process strengthens drivers' sense of identity and acceptance. Public accountability criteria allow drivers to clearly understand their own code of conduct, thereby reducing violations. This improves the conversion rate from customer complaints to driver accountability determinations.

[0122] In this embodiment, regarding step S3: optimizing the customer complaint handling process:

[0123] Step S300: Submit the judgment result to the multi-audit queue: The system submits the preliminary judgment result to the multi-audit queue and arranges junior auditors, senior auditors, supervisors, etc. to review the judgment result.

[0124] Step S301: Confirm or adjust the judgment result: The auditor reviews the judgment result based on the evidence and the preset judgment criteria. If the judgment result is accurate, it is confirmed; if it is found to be incorrect or controversial, it is adjusted.

[0125] Step S302: Automatically arrange a follow-up visit: The system arranges a follow-up visit for each complaint. Customer service personnel or the automated follow-up system explains the basis for the judgment to the driver, including the judgment criteria, the specific manifestations of the violation, and the reasons for the handling measures.

[0126] Step S303: Record the return visit results: The system accurately records the return visit results (driver's feedback, opinions and suggestions) in the system database.

[0127] Optimizing the customer complaint handling process ensures the accuracy and fairness of complaint decisions. Automated follow-up visits allow drivers to fully understand the circumstances of complaints, improving driver satisfaction and engagement.

[0128] In this embodiment, regarding step S4: data analysis and statistics:

[0129] Step S400: Regularly collect accountability data: The system sets a daily time interval to automatically collect the accountability accuracy rate and driver feedback rate during the accountability process, as well as detailed records of the accountability process.

[0130] Step S401: Analyze the accuracy of accountability: The system analyzes the collected accountability data and calculates the accuracy of accountability (eg, 95%).

[0131] Step S402: Analyze the driver feedback rate: The system collects and analyzes the driver's feedback data and calculates the driver feedback rate (eg, 80%).

[0132] Step S403: Real-time monitoring of driver's driving data: The system uses GPS positioning and a driving recorder to monitor the driver's driving trajectory and speed in real time. The real-time monitoring data is compared with the system's preset service standards to determine whether the driver's driving behavior meets the standards.

[0133] Step S404: Timely handling of violations: For any violations discovered, the system automatically triggers a handling mechanism, such as sending a warning notification to the driver, deducting points, or suspending service.

[0134] Data analysis and statistics enable the platform to promptly understand the accuracy of the accountability process and driver feedback. Real-time monitoring of driver driving data ensures that driver behavior complies with regulations, thereby improving service quality. This helps reduce violations and enhances passenger satisfaction.

[0135] In this embodiment, regarding step S5: Incentive and Training Mechanism: the system automatically calculates reward amounts or points based on the driver's service quality and performance. Reward information is pushed to the driver, and the driver's account balance or points are updated. Regular seminars or online meetings are scheduled, with drivers notified to participate, to share experiences and improve their skills.

[0136] The incentive and training system stimulates drivers' enthusiasm and passion for service. Through rewards and training, drivers can continuously improve their service quality, providing passengers with a better and safer travel experience. This also helps reduce complaints and violations, and enhances the platform's overall image and competitiveness.

[0137] Example 2: Based on Example 1, this example further provides a Python execution program for the solution described in Example 1 as follows:

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[0146] 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.

[0147] 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.

[0148] 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. 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 various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

Claims

1. The method for delivering a notice of judgment to a ride-hailing driver is characterized by: The following steps are included: S1, after receiving the complaint information submitted by the passenger, triggers the real-time notification mechanism; S2: Conducts a preliminary analysis of the complaint information based on pre-set judgment criteria to determine whether it constitutes a violation. If so, generates evidence of the violation, the judgment result, and a detailed explanation, and sends them to the driver. S3: Submit the judgment results to the multi-level review queue for review by reviewers at different levels; Enable auditors to confirm or adjust the accountability results based on evidence and accountability standards; S4 collects and analyzes the accuracy of the judgment and the driver feedback rate during the judgment process, compares the real-time monitoring data with the system's preset service standards, and discovers and handles violations.

2. The method for delivering a judgment notice according to claim 1, characterized in that: In S1, the real-time notification mechanism sends complaint notifications to relevant drivers via in-app messages and SMS messages, including the time, location and summary of the complaint content.

3. The method for delivering a judgment notice according to claim 2, characterized in that: The execution process of S1 includes: S100, receiving complaint information submitted by passengers through a designated interface or channel, including complaint time, complaint location, complaint content, and passenger contact information; and storing the complaint information in a database; S101, based on the relevant driver identifiers in the complaint information, determine the driver to be notified; assemble the content of the complaint notification; the notification content includes the time, location, and summary of the complaint content; S102, sending complaint notifications to relevant drivers via in-app messages and SMS messages; in-app messages are pushed via the platform's mobile application, and SMS messages are sent via the SMS gateway.

4. The method for delivering a notice of judgment according to claim 1, wherein: In S2, the evidence of the violation includes dashcam video clips and GPS positioning data; the judgment result and detailed explanation are pushed to the driver via in-app message or SMS, and the judgment criteria are made public for the driver to query and understand.

5. The method for delivering a notice of judgment according to claim 4, characterized in that: The execution process of S2 includes: S200, receiving complaint information from the passenger complaint module, and conducting preliminary sorting and analysis of the complaint content; judging whether the complaint constitutes a violation based on the preset judgment criteria, and determining the type and degree of the violation; S201: If the complaint constitutes a violation, collect and generate relevant evidence of the violation, including dashcam video footage and GPS location data; determine the final penalty based on the preliminary analysis and generated evidence of the violation; the penalty will include the driver's violation, the severity of the violation, and the corresponding handling measures; S202: To ensure the transparency of the accountability process, provide a detailed explanation of the accountability results, including the basis for the accountability, the specific manifestations of the violation, and the reasons for the handling measures; push the accountability results and detailed explanations to the relevant drivers via in-app messages or text messages.

6. The method for delivering a notice of judgment according to claim 1, characterized in that: The execution process of S3 includes: S300: Submit the preliminary judgment result to a queue with multiple review levels; arrange junior auditors, senior auditors, supervisors, etc. to review the judgment result; S301: After the auditor confirms or adjusts the judgment result based on the review, if the judgment result is accurate, it will be confirmed; if it is found to be incorrect or controversial, it will be adjusted; S302: Arrange a follow-up visit for each complaint. During the follow-up visit, customer service personnel or the automated follow-up system should explain to the driver the basis for the judgment, including the judgment criteria, the specific manifestations of the violation, and the reasons for the handling measures. S303, recording the feedback, opinions and suggestions of the return-visited drivers in the system database.

7. The method for delivering a notice of judgment according to claim 6, characterized in that: The execution process of S4 includes: S400, set a regular time interval to automatically collect the accuracy rate of the judgment and the driver feedback rate during the judgment process, as well as detailed records of the judgment process, including the judgment time, the judgment person and the judgment result; S401, analyzing the collected accountability data and calculating the accountability accuracy rate; the accountability accuracy rate is defined as the ratio of the number of complaints correctly accounted for to the total number of complaints; S402: Count and analyze the driver feedback data to calculate the driver feedback rate, which is defined as the ratio of the number of complaints in which drivers provide feedback on the judgment results to the total number of complaints; S403, using GPS positioning and a driving recorder to monitor the driver's driving trajectory and speed in real time; comparing the real-time monitoring data with the system's preset service standards to determine whether the driver's driving behavior complies with the standards, including speed limits, reasonableness of driving trajectory, and service attitude requirements; S404, for any violations discovered, automatically triggers the processing mechanism, including warnings, fines, training or suspension of services.

8. The method for delivering a judgment notice according to claim 1, characterized in that: It also includes S5, which automatically calculates reward amounts or points based on the driver's service quality and performance; pushes reward information to the driver and updates the driver's account balance or points; and regularly arranges seminars or online meetings and notifies drivers to participate.

9. A system for implementing the method for delivering a judgment notice according to any one of claims 1 to 8, characterized in that: The system comprises: Passenger complaint module: responsible for receiving complaint information submitted by passengers, including complaint time, location and content; Driver Notification Module: Receives complaint information from the passenger complaint module and pushes it to relevant drivers in real time via mobile applications and SMS; Judgment module: Receives complaint information, reviews and judges according to preset judgment standards; Driver feedback module: Receive feedback and appeals from drivers regarding the judgment results, including the driver's objection, explanation, or additional evidence; Service quality management module: Real-time monitoring of the driver's driving trajectory and speed through GPS positioning and driving recorder.

10. The system according to claim 9, characterized in that: It also includes a data analysis and statistics module: comprehensive analysis of the data from each module, including the number of complaints, accuracy of judgment and driver feedback rate.

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