Public inspection method and system for carrying out passenger voting based on behaviors of designated drivers

Abstract

The invention discloses a public verification method and system for passenger voting based on behaviors of designated drivers. The invention relates to the field of mobile internet travel management and control. When the supervised driver is online for the first time, a public verification prompt message is sent to the supervised driver to inform the supervised driver that the service condition is to be continuously observed; and when the driver matches the passenger and starts the order travel, checking whether the passenger participates in the public check voting of the driver in the latest period of time (such as the latest five orders). If the passenger does not participate in voting, a voting problem message pops up to the bottom of an order travel detail page map of a mobile phone terminal of the passenger, the problem content is information about recent violation of a driver, and a voting selection button is provided; through a public inspection supervision mechanism, the system can continuously supervise the driver, and ensures that the driver still keeps a standard service behavior after being punished and educated. The wide participation of passengers enables the supervision to be more comprehensive and objective, and effectively reduces the leakage of illegal behaviors of drivers.

Description

Technical Field

[0001] The present invention relates to the field of mobile Internet travel control, and specifically to a scenario of designated driver service. When a driver violates a rule, the driver's service behavior for a period of time is supervised and observed to regulate the driver's subsequent service behavior, and in particular, to a crowd-verification method and system for passenger voting based on the designated driver's behavior. Background Art

[0002] In online ride-hailing services, after a driver is punished and educated for a violation, if there is no effective mechanism for continuous observation of the driver's recent service performance, it may easily lead to the driver continuing to commit similar violations in subsequent services.

[0003] That is, within a period of time after the driver is punished and educated, there is a lack of clear judgment standards and enforcement mechanisms in the existing technology as to whether the driver commits the same type of violation again, and whether such repeated violations should be punished more severely. This not only affects the fairness and effectiveness of the punishment, but also weakens the authority of the platform management rules. Moreover, drivers’ dissatisfaction with the results of customer complaints is largely due to the lack of objective basis in the penalty decision-making process. This deficiency causes drivers to question the fairness of the platform’s punishment, which in turn weakens drivers’ trust in the platform. Therefore, how to establish an objective and transparent penalty decision-making mechanism to provide sufficient and verifiable basis for the punishment of drivers’ violations has become the key to improving driver trust and platform management efficiency.

[0004] To this end, the present invention proposes a crowd-verification method and system for passenger voting based on the behavior of designated drivers. Summary of the invention

[0005] In view of this, the present invention hopes to provide a crowd-verification method and system for passenger voting based on the behavior of designated drivers to solve or alleviate the technical problems existing in the prior art, namely:

[0006] First: How to solve the problem of lack of follow-up supervision measures after the driver is punished and educated;

[0007] Second: How to solve the problem of whether the penalty for repeated violations should be increased after the driver has been punished and educated for a period of time;

[0008] Third: How to solve the problem of drivers’ lack of trust in the platform due to the lack of objective basis for the aggravated violations;

[0009] The technical solution of the present invention is achieved in this way:

[0010] First, a crowd-testing method for passenger voting based on designated driver behavior:

[0011] 1. Overview:

[0012] The present invention aims to improve the quality of online car-hailing services through a public inspection supervision mechanism. Specifically, the system selects a part of drivers as the objects of supervision, and sends a public inspection reminder message when they go online, informing them that their service situation will be continuously observed by passengers. When the driver matches a passenger and starts the order trip, the system will push public inspection voting questions to passengers who have not participated in the voting, and passengers can evaluate the driver's service through the voting selection button. The system accumulates the voting results, and when the total number of votes reaches the threshold, the voting ratio is calculated and compared with the preset ratio threshold. If the voting ratio is lower than the threshold, the driver is deemed to have qualified service and the supervision is lifted; if the ratio reaches or exceeds the threshold, the aggravated penalty process is triggered and the driver is punished accordingly. This scheme realizes effective supervision of driver services through extensive participation and anonymous voting by passengers, motivates drivers to improve service quality, and ensures the objectivity and fairness of the evaluation.

[0013] (II) Technical solution:

[0014] In order to achieve the above technical objectives, the present invention selects to execute the following operation steps.

[0015] 2.1 Step S1, driver online prompt:

[0016] When the supervised driver comes online for the first time, a public verification reminder message is sent to him to inform him that his service situation will be continuously observed; when the driver is matched with a passenger and starts an order trip, it is checked whether the passenger has participated in the public verification vote on the driver in the recent period (such as the last 5 orders).

[0017] 2.1.1 Step S100, sending a public verification prompt message:

[0018] The system sends a public reminder message to the supervised driver, including the purpose, method, duration of supervision, and the rules and precautions that the driver should follow.

[0019] 2.1.2 Step S101, order itinerary starts detection:

[0020] When the supervised driver matches a passenger and starts an order trip, the system activates the detection mechanism to record the start time of the order trip, driver information, and passenger information.

[0021] 2.1.3 Step S102, passenger voting history check:

[0022] Check whether the current passenger has participated in the public voting for the driver in the last 5 orders;

[0023] If the passenger has not participated in the vote, the system will push the public voting questions to the passenger;

[0024] If a passenger has already participated in the vote, the system will no longer push voting questions to the passenger to avoid duplicate voting.

[0025] 2.2 Step S2, voting question push:

[0026] If the passenger has not participated in the vote, a voting question message will pop up at the bottom of the map on the order trip details page on the passenger's mobile phone. The question content will be information about the driver's recent violations, and a voting selection button will be provided;

[0027] Receive the passenger's voting choice and record the voting results, and keep the voting anonymous and not disclose it to the driver.

[0028] 2.2.1 Step S200, passenger voting status confirmation:

[0029] Check the current passenger's voting record for the supervised driver to confirm whether the passenger has participated in the voting; if the passenger has not participated in the voting, proceed to the next step; if the passenger has participated, the voting question will not be pushed.

[0030] 2.2.2 Step S201, voting question preparation:

[0031] Specific voting question content is generated based on the recent service status and violation record of the supervised driver.

[0032] For example, "Has the driver committed XX violation recently?"

[0033] 2.2.3 Step S202, voting question push:

[0034] When the order trip reaches an appropriate stage (before or after the end of the trip), push voting question messages to the passenger's mobile phone.

[0035] 2.2.4 Step S203, voting selection record:

[0036] After receiving the voting questions, the passenger selects the corresponding voting option and submits it; the passenger's voting choice is recorded, including the voting time, passenger information, driver information and voting results.

[0037] 2.4 Step S3, voting results accumulation:

[0038] Repeat S1 to S2 for each order of the driver, and accumulate the voting results until the configured total vote threshold is reached; when the number of votes reaches the threshold, calculate the voting ratio.

[0039] 2.5 Step S4, penalty decision:

[0040] The calculated voting ratio is compared with the configured ratio threshold; if the ratio is less than the ratio threshold, the public supervision of the driver is lifted and the driver's status is marked as normal; otherwise, the aggravated penalty process is triggered.

[0041] According to the preset penalty level rules, corresponding aggravated penalty measures (online course examination or ban) will be implemented on the driver, and the driver will be notified of the violation and penalty results through driver-side messages.

[0042] 2.4.1 Step S400, voting ratio calculation and comparison:

[0043] Based on the collected passenger voting data, the ratio of the number of illegal votes to the total number of votes is calculated; and the calculated voting ratio is compared with a pre-configured ratio threshold.

[0044] If the voting ratio is less than the ratio threshold, it means that the driver's service performance meets or exceeds the platform standards;

[0045] Remove the public supervision of the driver and mark his status as "normal";

[0046] If the voting ratio is greater than or equal to the ratio threshold, the aggravated penalty process is triggered and the next step is entered;

[0047] 2.4.2 Step S401, triggering of the aggravated penalty process:

[0048] According to the preset penalty level rules, online course examinations, temporary account bans or permanent account bans are implemented.

[0049] 2.4.3 Step S402, implementation of aggravated penalty measures:

[0050] If it is an online course exam, the exam link and requirements will be sent to the driver, and the driver must complete the exam within the specified time.

[0051] If the account is banned, the driver's account status will be updated to prohibit him from logging in and accepting orders.

[0052] Record the time and results of penalty execution for subsequent inquiries and audits.

[0053] 2.6 Step S5, re-verification:

[0054] For drivers who need heavier penalties, determine whether public inspection and supervision are needed again; if necessary, return to S1; otherwise, end the public inspection and supervision process.

[0055] (III) Mechanism for solving technical problems:

[0056] 3.1 Solve the problem of lack of follow-up supervision measures:

[0057] The present invention adopts a public inspection supervision mode to continuously observe a specific driver. When the driver comes online, the system sends a public inspection prompt message and checks whether the passenger has participated in the public inspection vote for the driver in each order trip.

[0058] Through public supervision, the system can continuously collect passengers' feedback on the driver's service and ensure that the driver is still supervised after punishment and education. This mechanism not only covers the driver's working hours, but also enhances the universality and effectiveness of supervision through the extensive participation of passengers.

[0059] 3.2 Solve the problem of increased penalties for repeated violations:

[0060] The present invention sets a total vote threshold and a ratio threshold. When the number of votes reaches the threshold, the system calculates the "yes" vote ratio and compares it with the preset ratio threshold. If the ratio reaches or exceeds the threshold, the aggravated penalty process is triggered.

[0061] By setting thresholds and calculating ratios, the system can objectively assess the extent of a driver's violations. When a driver continues to violate the rules frequently after being punished and educated, the voting ratio will increase, triggering more severe penalties. This mechanism ensures that the penalty matches the severity of the violation, effectively curbing repeated violations.

[0062] 3.3 Solve the problem of lack of trust caused by lack of objective basis for heavier punishment:

[0063] The public voting and proportion calculation in the present invention are completely based on the feedback and objective data of passengers, avoiding human intervention and subjective judgment. The decision to increase the penalty is also based on clear thresholds and proportion calculation results.

[0064] Through public voting and proportional calculation, the system can provide a fair and transparent evaluation process. Drivers can clearly understand why they are subject to heavier penalties and the basis for the penalties. This mechanism enhances the objectivity and persuasiveness of the penalties and helps rebuild drivers' trust in the platform.

[0065] Secondly, a crowd-verification system for passengers to vote based on the behavior of designated drivers:

[0066] like Figure 4 As shown, the system is used to implement the above-mentioned crowd-verification method for passenger voting based on the behavior of the designated driver, which includes:

[0067] (1) Driver management module: responsible for driver information entry, status management (such as normal, supervised, etc.) and penalty records.

[0068] Ensure that the supervised driver information is accurate and be able to track the driver's status changes in real time.

[0069] (2) Order matching and voting check module: When a driver matches a passenger and starts an order trip, it checks whether the passenger has participated in the public voting for the driver.

[0070] Prevent the same passenger from voting for the same driver repeatedly in a short period of time, and ensure the fairness and effectiveness of the voting.

[0071] (3) Public verification prompt and voting push module: Send public verification prompt messages to the supervised drivers and push public verification voting questions to passengers when necessary.

[0072] Ensure that drivers and passengers are aware of the existence of public supervision and encourage passengers to actively participate in voting.

[0073] (4) Voting processing and result accumulation module: receives passengers’ voting choices, records voting results, and accumulates the total number of votes.

[0074] Collect and analyze passenger feedback data to provide objective basis for subsequent penalty decisions.

[0075] (5) Penalty decision and execution module: Make penalty decisions based on voting results and preset thresholds, and execute corresponding penalty measures (such as online course exams, bans, etc.).

[0076] Imposing timely and fair punishment on drivers who violate the rules to maintain the order of the platform and the rights and interests of passengers.

[0077] (6) Data statistics and analysis module: Statistics and analysis of various data in the public supervision process, such as the total number of votes, voting ratio, driver violation rate, etc.

[0078] Provide decision-making support for the platform and help it understand the effectiveness and existing problems of public supervision so as to continuously optimize and improve the plan.

[0079] Compared with the prior art, the present invention has the following beneficial effects:

[0080] 1. Enhance the continuity and effectiveness of supervision: Through the public inspection supervision mechanism, the present invention can continuously supervise the drivers to ensure that the drivers still maintain standardized service behaviors after punishment and education. The extensive participation of passengers makes the supervision more comprehensive and objective, effectively reducing the number of drivers who slip through the net for illegal behaviors.

[0081] 2. Improve the accuracy and fairness of punishment: The total vote threshold and proportion threshold settings in the present invention provide a clear and objective basis for punishment, avoiding the unfairness caused by human intervention and subjective judgment. The decision to increase the punishment is based on passenger feedback and objective data, ensuring that the punishment matches the severity of the violation and improving the accuracy of the punishment.

[0082] 3. Improve the service quality and awareness of drivers: The existence of public supervision makes drivers pay more attention to their service behaviors, fearing that they will be punished for violations, thus improving the service quality. After understanding the objective basis for punishment, drivers will be more accepting of the platform's punishment decision, and thus enhance their awareness of compliance with platform rules. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or technical descriptions will be briefly introduced below. 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 creative work.

[0084] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0085] Figure 2 Configuring public verification for administrators, and a diagram of the public verification process triggered by driver violations;

[0086] Figure 3 A diagram showing the impact of passengers' participation in a public vote on the driver.

[0087] Figure 4 It is a schematic diagram of the system composition of the present invention. DETAILED DESCRIPTION

[0088] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below;

[0089] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0090] Explanation of relevant terms:

[0091] (1) Supervised driver: refers to the driver selected by the system for public supervision.

[0092] (2) Public verification reminder message: It is a notification sent by the system to the driver to inform him that his service will be continuously monitored.

[0093] (3) Public voting: This is an anonymous vote by passengers on the driver’s service performance.

[0094] (4) Voting selection button: a button used by passengers to select options such as "yes" or "no" when voting.

[0095] (5) Voting results: the voting data recorded by the system after the passenger votes.

[0096] (6) Total vote threshold: This is the minimum number of votes required by the system.

[0097] (7) Voting ratio: the ratio of “yes” votes to the total number of votes.

[0098] (8) Ratio threshold: It is the ratio standard set by the system to determine whether the driver has violated the rules.

[0099] Embodiment 1: Figures 1 to 3 As shown, this embodiment discloses the application of a crowd-verification method for passenger voting based on the behavior of designated drivers in the operation and maintenance of online ride-hailing services. The purpose is to continuously supervise the drivers through the voting of passengers on the behavior of designated drivers, and to make corresponding penalties or educational measures based on the voting results to solve the problem of driver behavior norms. The process includes key steps such as driver online reminder, voting question push, voting result accumulation, penalty decision and re-crowd-verification judgment.

[0100] In the technical solution provided in this embodiment, step S1: driver online prompt:

[0101] S100: Send a public verification reminder message: When the supervised driver logs in to the online car-hailing platform for the first time, the system automatically sends a public verification reminder message to the driver's mobile phone.

[0102] The message content includes the purpose of supervision (improving service quality), method (passenger voting), duration (such as one month), and rules and precautions that drivers should follow.

[0103] S101: Order trip start detection: When the driver matches the passenger and starts the order trip, the system starts the detection mechanism to record the start time of the order trip, driver information (such as ID, name, score) and passenger information (such as ID, historical voting records).

[0104] S102: Passenger voting history check: The system checks whether the current passenger has participated in the public voting for the driver in the last five orders. If the passenger has not participated in the voting, the system will prepare to push the public voting questions to the passenger; if the passenger has participated, it will not be pushed to avoid repeated voting.

[0105] In the technical solution provided in this embodiment, step S2: voting question push:

[0106] S200: Passenger voting status confirmation: The system reconfirms the passenger's voting status to ensure that the passenger has not participated in voting for the driver.

[0107] S201: Preparation of voting questions: Based on the driver's recent service status and violation record, the system generates specific voting questions, such as "Has the driver been speeding recently?".

[0108] S202: Voting question push: Before or after the end of the order trip, the system pushes a voting question message to the passenger's mobile phone, and the message is displayed at the bottom of the map on the order trip details page.

[0109] S203: Voting selection record: The passenger selects the corresponding voting option (such as "yes", "no" or "uncertain") and submits it. The system records the passenger's voting selection, including voting time, passenger information, driver information and voting results, and maintains the anonymity of the voting.

[0110] In the technical solution provided in this embodiment, step S3: cumulative voting results: repeat steps S1 to S2 for each order of the driver to accumulate voting results. When the number of votes reaches the configured total threshold (such as 100 votes), the system calculates the ratio of the number of illegal votes to the total number of votes.

[0111] In the technical solution provided in this embodiment, step S4: penalty decision:

[0112] S400: Calculation and comparison of voting ratio: The system calculates the proportion of illegal voting based on the collected passenger voting data. The calculated voting ratio is compared with the pre-configured ratio threshold (such as 20%). If the voting ratio is less than the ratio threshold, it means that the driver's service performance meets or exceeds the platform standard, and the public supervision of the driver is lifted and his status is marked as "normal". If the voting ratio is greater than or equal to the ratio threshold, the aggravated penalty process is triggered.

[0113] By continuously collecting passenger votes, the system is able to monitor drivers' behavior in real time, ensuring that their behavior continues to improve even after they have been punished and educated.

[0114] S401: Triggering of the aggravated penalty process: Based on the preset penalty level rules, the system decides to implement penalty measures such as online course examinations, temporary account bans, or permanent account bans.

[0115] S402: Execution of aggravated penalty measures: For example, in the case of online course exams, the system sends the driver an exam link and requirements, and the driver must complete the exam within the specified time. If the account is banned, the system updates the driver's account status, prohibiting him from logging in and accepting orders, and records the time and results of the penalty execution.

[0116] Through continuous voting and proportional calculation, the system can promptly detect repeated violations by drivers and increase penalties according to preset rules to ensure that driver behavior is effectively restrained.

[0117] Throughout the entire process, the system's penalty decisions are based on passenger voting data, which is objective, anonymous, and can reflect the driver's service performance in real time. The system notifies the driver of the violation and penalty results through driver-side messages, providing clear and objective evidence to enhance the driver's trust in the platform.

[0118] In the technical solution provided in this embodiment, step S5: Re-public inspection judgment: For drivers who need to be punished more severely, the system determines whether public inspection supervision needs to be re-performed. If the driver's behavior has not improved significantly or there are serious violations, the system decides to re-perform public inspection supervision and returns to step S1. If the driver's behavior has improved significantly, the system ends this public inspection supervision process.

[0119] In the technical solution provided in this embodiment, through passenger voting and continuous supervision, drivers are encouraged to improve their service behavior and improve the overall service quality. Objective punishment basis is provided to enhance drivers' trust in the platform and reduce disputes and complaints. Automated processes reduce manual intervention, improve management efficiency, and reduce operating costs. Through a fair and transparent supervision mechanism, all drivers are ensured to compete under the same conditions, promoting the healthy development of the market.

[0120] Embodiment 2: Based on Embodiment 1, this embodiment further provides a Python execution program of the solution involved in Embodiment 1 as follows:

[0121]

[0122]

[0123]

[0124] #Order itinerary starts detection

[0125] # Check passenger voting history

[0126] if not check_passenger_vote_history(passenger,driver.driver_id):

[0127] #Push voting questions

[0128] push_vote_question(passenger,driver)

[0129] #Record passenger votes

[0130] record_vote(driver,passenger.passenger_id,"yes")

[0131] #Penalty Decision

[0132] decide_penalty(driver)

[0133] #Re-test the judgment

[0134] if reevaluate_supervision(driver):

[0135] #If re-supervision is required, return to the driver online prompt step

[0136] send_supervision_notice(driver)

[0137] The principle of the above procedure is:

[0138] Driver online reminder: When the driver logs in for the first time, the system sends a public reminder message through the send_supervision_notice function.

[0139] Voting question push: At the beginning of the order trip, the system checks the passenger's voting history (check_passenger_vote_history function). If the passenger has not participated in the vote for the driver, the voting question is pushed through the push_vote_question function.

[0140] Voting result accumulation: Passengers' votes are recorded into the driver's voting list through the record_vote function. The system can accumulate voting results of multiple orders.

[0141] Penalty decision: When the number of votes reaches the threshold, the system calculates the proportion of illegal votes through the decide_penalty function and compares it with the preset threshold. Based on the comparison results, it decides whether to lift supervision or trigger the heavier penalty process.

[0142] Re-evaluation: Use the reevaluate_supervision function to determine whether re-supervision is needed. If the driver's behavior has not improved significantly, the supervision process will be restarted.

[0143] All the above embodiments only express the implementation methods of the relevant practical applications of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

[0144] 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 the above description according to function. 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.

[0145] At the same time, those skilled in the art can understand that all or part of the processes in all the above-mentioned embodiments can be completed 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 can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an 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 (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

Claims

1. A crowd-testing method for passenger voting based on the behavior of designated drivers, characterized in that: The following steps are included: S1, when the supervised driver comes online for the first time, a public verification prompt message is sent to him; when the driver matches a passenger and starts the order trip; S2, sending a voting question message to the passenger's mobile phone, the question content is the driver's recent violation information, and provides a voting selection button; receiving the passenger's voting selection and recording the voting result; S3, repeat S1 to S2 for each order of the driver, accumulate voting results until the configured total vote threshold is reached; when the number of votes reaches the threshold, calculate the voting ratio; S4, compares the calculated voting ratio with the configured ratio threshold; If the ratio is less than the ratio threshold, the public supervision of the driver is lifted and the driver's status is marked as normal; Otherwise, the process of aggravated punishment will be triggered.

2. The crowd-testing method according to claim 1, characterized in that: In the S1, it is also included to check whether the passenger has participated in the public voting for the driver in the recent period; if so, the passenger will not participate in the voting.

3. The crowd testing method according to claim 2, characterized in that: The execution process of S1 includes: S100, sending a public verification reminder message to the supervised driver, including the purpose, method, duration of supervision, and rules and precautions that the driver should comply with; S101, when the supervised driver matches a passenger and starts an order trip, a detection mechanism is started to record the start time of the order trip, the driver information and the passenger information; S102, checking whether the current passenger has participated in the public voting on the driver in the last five orders; if the passenger has not participated in the voting, the system prepares to push the public voting questions to the passenger; if the passenger has participated in the voting, the system will no longer push the voting questions to the passenger to avoid repeated voting.

4. The crowd testing method according to claim 1, characterized in that: In S2, the vote anonymity is maintained and is not disclosed to the driver.

5. The crowd testing method according to claim 4, characterized in that: The execution process of S2 includes: S200, checking the voting record of the current passenger for the supervised driver to confirm whether the passenger has participated in the voting; if the passenger has not participated in the voting, proceed to the next step; if the passenger has participated, the voting question is not pushed; S201, generating specific voting questions based on the recent service status and violation records of the supervised driver; S202, pushing a voting question message to the passenger's mobile phone before or after the trip ends; S203, recording the passenger's voting choice, including voting time, passenger information, driver information and voting results.

6. The crowd testing method according to claim 1, characterized in that: In S4, according to the preset penalty level rules, corresponding aggravated penalty measures are implemented on the driver, including online course examination or ban, and the driver is notified of the violation and penalty results through driver-side messages.

7. The method according to claim 6, characterized in that: The execution process of S4 includes: S400, calculating the ratio of the number of illegal votes to the total number of votes based on the collected passenger voting data; comparing the calculated voting ratio with a pre-configured ratio threshold; If the voting ratio is less than the ratio threshold, the public supervision of the driver is lifted and his status is marked as "normal". If the voting ratio is greater than or equal to the ratio threshold, the aggravated penalty process is triggered and the next step is entered. S401, implementing online course examinations, temporarily banning accounts, or permanently banning accounts according to preset penalty level rules; S402, if it is an online course exam, the exam link and requirements will be sent to the driver, and the driver must complete the exam within the specified time; if the account is banned, the driver's account status will be updated to prohibit him from logging in and accepting orders; the time and results of the penalty execution will be recorded for subsequent inquiries and audits.

8. The method according to any one of claims 1 to 7, characterized in that: It also includes S5, re-public inspection judgment: for drivers who need to be punished more severely, it is determined whether public inspection supervision needs to be re-performed; if necessary, it returns to S1; Otherwise, the public inspection and supervision process ends.

9. A system for implementing the crowd-testing method according to any one of claims 1 to 8, characterized in that: The system comprises: Driver management module: responsible for driver information entry, status management and penalty records; Order matching and voting check module: When a driver matches a passenger and starts an order trip, it checks whether the passenger has participated in the public voting for the driver; Public verification prompt and voting push module: send public verification prompt messages to the supervised drivers; Voting processing and result accumulation module: receiving passengers' voting choices, recording voting results, and accumulating the total number of votes; Penalty decision and execution module: Make penalty decisions based on voting results and preset thresholds, and execute corresponding penalty measures.

10. The system according to claim 9, characterized in that: The system also includes a data statistics and analysis module: statistics are collected on various data in the process of public inspection and supervision.

Images