A method and related device for tracing illegal behavior of a shared car

Abstract

The application discloses a kind of method and related equipment of illegal behavior tracing of shared car, including the original record data of car use, time stamp and location stamp when car user uses shared car are synchronously collected, obtain the confirmation information of traffic violation behavior of shared car, according to traffic violation behavior confirmation information and original record data of car use, and the steps such as illegal behavior tracing are carried out.The application accurately traces traffic violation behavior to the determined car user in the case where shared car is used by a large number of different car users, provides sufficient information support for subsequent processing such as handling and imputation of traffic violation behavior;Since shared car records original record data of car use, these data can provide sufficient information support for investigation of traffic violation behavior;Therefore, by executing the illegal behavior tracing method of shared car in the embodiment, it is beneficial to restore the truth and protect the legal interests of each traffic participant.The application is widely used in the field of automobile technology.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a method and related equipment for tracing violations in shared vehicles. Background Technology

[0002] Car sharing is a car rental service model in which car rental companies purchase, own, and operate shared cars. Car users pay the car rental company on demand to obtain the right to use the car for a specific period of time without bearing the car's ownership and long-term maintenance costs. It is suitable for scenarios that require temporary use of a car, such as business trips, tourism, and business activities.

[0003] Driving any car carries the risk of violating regulations, and driving a shared car is no exception. Furthermore, because shared cars are not the property of the car owner, users are often more relaxed when driving them, making them more prone to violations. If a violation occurs, it is necessary to clearly assign responsibility to fully protect the legitimate interests of both the owner and user of the shared car.

[0004] However, car-sharing has a large number of actual users, so once a violation occurs, it can easily lead to a complicated investigation and evidence collection process. This may require the cooperation of car users who have used the car-sharing service, or even require the car-sharing service to suspend operations to cooperate with the investigation and evidence collection process, thus affecting the experience in all aspects. Summary of the Invention

[0005] To address at least one of the aforementioned technical problems, the present invention aims to provide a method for tracing violations in car-sharing.

[0006] On one hand, embodiments of the present invention include a method for tracing violations in shared vehicles, the method comprising: Obtain the identity and authorization information of the car user; the car user is the user who accepts the car-sharing service; Based on the authorization information, when a car user uses the shared car, the original car usage record data, timestamp, and location stamp are collected simultaneously, and the original car usage record data is marked using the timestamp and the location stamp; Establish a binding relationship between the identity information and the original vehicle usage record data; Obtain confirmation information on traffic violations committed by the shared car; The violation can be traced based on the traffic violation confirmation information and the original vehicle usage record data.

[0007] Furthermore, the step of tracing violations based on the traffic violation confirmation information and the original vehicle usage record data includes: Based on the traffic violation confirmation information, the actual time and location of the violation are determined; Based on the actual time of the violation, a matching timestamp is searched. Based on the actual location of the violation, a matching location stamp can be retrieved; When the timestamp and location stamp are collected simultaneously, the identity information bound to the original vehicle usage record data marked by the timestamp and location stamp is retrieved.

[0008] Furthermore, the method for tracing violations in the shared car service also includes: Multimodal behavior recognition is performed on the original vehicle usage record data to obtain the traffic behavior type corresponding to the original vehicle usage record data; Based on the type of traffic behavior, the original vehicle usage record data is determined to be either ordinary record data or suspicious violation record data; The timestamp and location stamp corresponding to the suspected illegal record data are respectively identified as suspicious timestamp and suspicious location stamp.

[0009] Furthermore, the step of tracing violations based on the traffic violation confirmation information and the original vehicle usage record data includes: Based on the traffic violation confirmation information, the actual time and location of the violation are determined; Based on the actual time of the violation, search for matching suspicious timestamps; Based on the actual location of the violation, search for matching suspicious location stamps; When the suspicious timestamp and the suspicious location stamp are collected simultaneously, the identity information bound to the original vehicle usage record data marked by the suspicious timestamp and the suspicious location stamp is retrieved.

[0010] Furthermore, the method for tracing violations in the shared car service also includes: Before obtaining the traffic violation confirmation information, the suspected violation record data is counted to obtain the number of suspected violations, and the account corresponding to the identity information is pre-deducted based on the number of suspected violations; After obtaining confirmation information of the traffic violation or after a preset time limit has been exceeded, the suspected violation record data is confirmed or revoked, and the account corresponding to the identity information is adjusted according to the confirmation or revocation of the suspected violation record data.

[0011] Furthermore, the method for tracing violations in the shared car service also includes: Establish a credit file corresponding to the aforementioned identity information; Credit scores are recorded in the credit profile; The processing results of the traffic violation confirmation information are tracked, and the credit score in the credit file is adjusted according to the processing results.

[0012] Furthermore, the method for tracing violations in the shared car service also includes: Multiple data custodians are identified; the data custodians include some or all of the actual drivers, users, lessors, insurers, law enforcement agencies, and manufacturers of the shared vehicles; Based on the degree of correlation between each data custodian and the traffic liability of the traffic violation confirmation information, the recommended retention period information for each data custodian is determined; the duration indicated by the recommended retention period information is positively correlated with the degree of correlation with the traffic liability. Obtain the hash value corresponding to the original vehicle usage record data; For any of the data custodians, the original vehicle usage record data, the hash value, and the suggested retention period information corresponding to the data custodian are sent to the data custodian; the suggested retention period information is used to instruct the data custodian to retain the hash value and delete the original vehicle usage record data after the recommended retention period information has been reached.

[0013] Further, obtaining the hash value corresponding to the original vehicle usage record data includes: The original vehicle usage record data is segmented to obtain multiple data segments; Obtain the hash value of each of the data segments respectively; For any of the hash values, the hash value is marked according to the position of the data segment corresponding to the hash value in the original vehicle usage record data.

[0014] On the other hand, embodiments of the present invention also include a computer device, including a memory and a processor, the memory for storing at least one program, and the processor for loading at least one program to execute the shared car violation tracing method of the embodiments.

[0015] On the other hand, embodiments of the present invention also include a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to perform the shared car violation tracing method in the embodiments.

[0016] The beneficial effects of this invention are as follows: the method for tracing traffic violations in shared cars as described in the embodiments can accurately trace traffic violations to specific car users when shared cars are used by a large number of different car users, providing sufficient information support for subsequent processing such as handling and assigning responsibility for traffic violations; moreover, since shared cars record original usage data, this data can provide sufficient information support for investigating traffic violations; therefore, by implementing the method for tracing traffic violations in shared cars as described in the embodiments, it is beneficial to restore the facts and protect the legitimate interests of all traffic participants. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a shared car for which the method for tracing violations of shared car regulations can be applied in this embodiment; Figure 2 This is a schematic diagram illustrating the steps of the method for tracing violations in shared cars as described in this embodiment; Figure 3 This is a schematic diagram illustrating the principle of steps S9-S12 in the embodiment. Detailed Implementation

[0018] In this embodiment, violations include acts that violate road traffic safety laws and regulations or management regulations established by the management of a specific location while driving a car, resulting in legal liabilities such as economic compensation, administrative liability, or even criminal liability. For example, specific violations include failing to change lanes, turn, or make a U-turn according to road markings, failing to stop or pass according to traffic light instructions, causing collisions with other vehicles, and exceeding the time limit for parking in temporary parking spaces.

[0019] In this embodiment, the method for tracing violations in car-sharing can be applied to... Figure 1 In the shared car shown. (Refer to...) Figure 1The shared car includes components such as a control module, a communication module, an accelerator pedal sensor, a brake pedal sensor, a steering wheel sensor, a high-precision timer, a high-precision satellite positioning module, an omnidirectional dashcam, an identity recognition module, a human-machine interaction module, and a large-capacity storage device. The control module is a component with functions such as data acquisition, data processing, data output, and control; for example, an Electronic Control Unit (ECU) can be used as the control module. The communication module can connect and communicate with a cloud server via a wireless communication protocol, where the cloud server can be a server operated by the shared car's operating platform. The accelerator pedal sensor detects the depth of the accelerator pedal; the brake pedal sensor detects the depth of the brake pedal; the steering wheel sensor detects the angle of the steering wheel; the high-precision timer performs timing to generate a timestamp; the high-precision satellite positioning module performs satellite positioning to generate a location stamp; and the omnidirectional dashcam performs 360° omnidirectional imaging and recording of the shared car's external environment to obtain... The system includes omnidirectional driving video and audio; an identity recognition module that obtains user identity information through facial recognition or fingerprint recognition, encrypts the information, and sends it to the cloud server via the communication module. The cloud server verifies the identity information against pre-reserved verification information and returns the result (pass or fail) to the identity recognition module via the communication module, allowing the identity recognition module to confirm whether the user's identity information has passed or failed verification; a human-machine interaction module that provides touchscreen or intelligent voice interaction for user interaction; and a large-capacity storage device with a sufficiently large capacity (e.g., 1TB) to store the large amount of data generated locally by the shared car.

[0020] In this embodiment, Figure 1 The shared car service shown can implement methods for tracing violations related to shared cars. (Refer to...) Figure 2 The method for tracing violations in car-sharing services includes the following steps: S1. Obtain the vehicle user's identity information and authorization information; S2. Based on authorization information, when a car user uses a shared car, the original car usage record data, timestamp, and location stamp are collected simultaneously, and the original car usage record data is marked using the timestamp and location stamp; S3. Establish a binding relationship between identity information and original vehicle usage record data; S4. Obtain confirmation information on traffic violations committed by shared cars; S5. Tracing violations based on traffic violation confirmation information and original vehicle usage record data.

[0021] In this embodiment, the control module within the shared car can execute the various steps of the method for tracing violations in the shared car. When executing some of these steps, the control module can invoke other components within the shared car for further processing.

[0022] In this embodiment, the shared car mentioned is a specific car operated by a car-sharing service provider (lessor) for shared use. Before executing steps S1-S5, the car user and the car-sharing service provider complete procedures such as signing a usage contract, thereby granting the car user the right to use the shared car. Specifically, the car user can include one person (driver) or multiple people (including driver and passengers). When there are multiple car users, one person can sign a usage contract with the car-sharing service provider (lessor) and register personal information such as their driver's license with the car-sharing service provider (lessor). This person is the registered user of the shared car; the registered user or someone else actually drives the shared car, and the person who actually drives the shared car is the actual driver.

[0023] After completing preliminary procedures such as signing a usage contract and collecting and reserving the car user's identity information, the car-sharing service provider allocates a specific shared car to the car user and instructs the car user to pick up the shared car at a specific location. After the car user picks up the shared car, steps S1-S5 are triggered.

[0024] In step S1, the control module calls the identity recognition module to obtain the identity information of at least one of the vehicle users. The identity recognition module encrypts the collected identity information and sends it to the cloud server via the communication module for verification against pre-registered identity information. If the cloud server returns a successful verification result, the control module confirms the vehicle user is a legitimate user and updates the system with the identity information collected on-site. identity 1. Data (including facial features and fingerprints) is stored in a large-capacity memory. The control module requests authorization information from the car user. Specifically, the control module can call the human-machine interface module to display a text or voice message to the car user stating, "To protect your legal interests, we need your authorization. If you authorize, we will collect information generated by your use of the shared car during your driving. Have a pleasant journey." This allows the car user to know that information such as accelerator pedal depth, brake pedal depth, and driving trajectory will be collected while driving the shared car. The car user can indicate their awareness and confirmation by operating the touchscreen or speaking, thereby inputting authorization information into the human-machine interface module. The human-machine interface module then sends the received authorization information to the control module.

[0025] Upon receiving the authorization information, the control module executes steps S2-S5.

[0026] In step S2, the control module synchronously collects the original usage record data, timestamp, and location stamp when the car user uses the shared car, for example, while the car user is driving the shared car.

[0027] Specifically, the control module calls a high-precision timer to perform real-time timing, thereby generating... t 1. t 2. t 3…… t n The timestamps, which can be Beijing time accurate to the second, are used. The control module calls the high-precision satellite positioning module to synchronously perform satellite positioning on the shared car, thereby generating... p 1. p 2. p 3…… p n Location stamps, these timestamps can be latitude and longitude coordinates, where the location stamp... p i (i=1, 2, 3...n) represents the shared car in t i The position of the moment is p i The control module uses the accelerator pedal sensor to detect the depth of the accelerator pedal, thereby obtaining... depth acceleration_1 , depth acceleration_2 , depth acceleration_3 ... depth acceleration_n The accelerator pedal depth time series, where depth acceleration_i The accelerator pedal of the shared car is in t i The control module uses the brake pedal sensor to detect the depth of the brake pedal, thereby obtaining the depth at any given moment. depth braking_1 , depth braking_2 , depth braking_3 ... depth braking_n The time series of brake pedal depth, where depth braking_i Indicates the brake pedal of the shared car. t i The depth of time. The control module calls the steering wheel sensor to detect the steering wheel's rotation angle, thereby obtaining... θ 1. θ 2. θ 3…… θ nThe time series of steering wheel rotation angles, where θ i The steering wheel of the shared car is in t i The rotation angle at any given moment. The control module calls the omnidirectional car recorder to capture omnidirectional footage of the shared car's surroundings, thereby obtaining... multimedia 1. multimedia 2. multimedia 3…… multimedia n Multimedia data streams, of which multimedia i Indicates in t i Multimedia data consisting of image frames from real-time captured driving videos and audio recordings.

[0028] In step S2, the accelerator pedal depth time series depth acceleration_1 , depth acceleration_2 , depth acceleration_3 ... depth acceleration_n Brake pedal depth time series depth braking_1 , depth braking_2 , depth braking_3 ... depth braking_n Steering wheel rotation angle time series θ 1. θ 2. θ 3…… θ n and multimedia data streams multimedia 1. multimedia 2. multimedia 3…… multimedia n This constitutes the original vehicle usage record data. This original vehicle usage record data, along with timestamps... t 1. t 2. t 3…… t n With location stamp p 1. p 2. p 3…… p n There is a one-to-one correspondence between them, thus enabling the timestamp and location stamp to mark the original vehicle usage record data.

[0029] In step S3, the processing module stores the original vehicle usage record data marked with timestamps and location stamps into a large-capacity storage device, and establishes the original vehicle usage record data and identity information. identity 1. Binding relationship.

[0030] While using shared cars, users may or may not commit traffic violations. If a user commits a traffic violation, the traffic management department (law enforcement) will detect and take corrective or disciplinary action. The traffic management department (law enforcement) will record the shared car's identification information (such as license plate number and vehicle identification number), the time and location of the traffic violation, and generate a traffic violation confirmation based on the actual time and location. This record documents the event of the user's traffic violation and the action taken against the user.

[0031] The processing module can execute step S4 during the car user's use of the shared car, or after the car user has finished using the shared car and returned it to the car-sharing service provider (renter). Specifically, when executing step S4, the processing module actively queries information sources such as the information disclosure platform of the traffic management department (law enforcement agency) to obtain confirmation information of traffic violations, or receives confirmation information of traffic violations sent by the traffic management department (law enforcement agency).

[0032] The traffic violation confirmation information indicates the traffic management department's (law enforcement agency's) confirmation of traffic violations committed by the shared car. If the shared car was not in motion when inspected by law enforcement (e.g., the shared car was detected speeding by speed cameras, or the shared car was illegally parked), the traffic management department (law enforcement agency) cannot confirm which person committed the traffic violation. Therefore, the traffic violation confirmation information obtained in step S4 will not contain the identity information of the specific violator. In this case, the processing module can proceed to step S5.

[0033] In this embodiment, when the processing module executes step S5, which is the step of tracing violations based on traffic violation confirmation information and original vehicle usage record data, it can specifically perform the following steps: S501A. Based on the traffic violation confirmation information, determine the actual time and location of the violation; S502A. Based on the actual time of the violation, search for the matching timestamp; S503A. Based on the actual location of the violation, search for the matching location stamp; S504A. When the searched timestamp and location stamp are collected simultaneously, retrieve the identity information bound to the original vehicle usage record data marked by the timestamp and location stamp.

[0034] Steps S501A-S504A are the first execution method of step S5.

[0035] In step S501A, the processing module extracts the actual violation time and actual violation location from the traffic violation confirmation information.

[0036] In step S502A, the processing module retrieves the timestamp stored in the large-capacity memory based on the actual violation time extracted in step S501A. t 1. t 2. t 3…… t n The search engine retrieves timestamps that match the original. Assuming the search finds a timestamp... t i The same as the actual time of the violation.

[0037] In step S503A, the processing module retrieves the location stamp from the large-capacity storage based on the actual violation location extracted in step S501A. p 1. p 2. p 3…… p n In the search, find the location stamp that matches it. Assume the location stamp is found... p j Same as the actual location of the violation.

[0038] In step S504A, the processing module retrieves the timestamps found in step S502A. t i The location stamp found in step S503A p j By comparison, if i=j, the searched timestamp can be determined. t i and location stamp p j They were collected simultaneously; retrieve the timestamp. t i and location stamp p j The identity information linked to the marked original vehicle usage record data identity 1.

[0039] In this embodiment, the principle of executing steps S1-S4 and S501A-S504A is as follows: By collecting original usage record data, timestamps, and location stamps during the use of the car by the shared car user, it is possible to save original data such as driving video, driving audio, and the user's operation records of the shared car. Upon receiving traffic violation confirmation information, confirming that the shared car has indeed committed a traffic violation, it can search for matching timestamps and location stamps based on the actual violation time and location recorded by the traffic management department (law enforcement) in the traffic violation confirmation information. The searched timestamp represents a specific moment in a user's use of the shared car, and the searched location stamps represent... This method involves tracking a car user's journey to a specific point while using a shared car. If the timestamp and location stamp are collected simultaneously, the user information linked to the original usage record data can be accurately identified. This information corresponds to the user information of the car user whose traffic violation was confirmed by the shared car's traffic violation confirmation information. This allows for accurate tracing of traffic violations back to a specific car user even when shared cars are used by numerous different users, providing sufficient information for subsequent processing such as handling and assigning responsibility for traffic violations. Furthermore, since shared cars record original usage data, this data can provide ample information for investigating traffic violations. Therefore, implementing the shared car violation tracing method in this embodiment helps to reconstruct the facts and protect the legitimate interests of all traffic participants.

[0040] In this embodiment, after executing step S2 and before executing step S5, the processing module may also execute the following steps: P1. Perform multimodal behavior recognition on the original vehicle usage record data to obtain the traffic behavior type corresponding to the original vehicle usage record data; P2. Based on the type of traffic behavior, the original vehicle usage record data will be classified as either ordinary record data or suspected violation record data; P3. The timestamps and location stamps corresponding to the suspected illegal records are identified as suspicious timestamps and suspicious location stamps, respectively.

[0041] In step P1, the processing module processes the original vehicle usage data, namely the accelerator pedal depth time series. depth acceleration_1 , depth acceleration_2 , depth acceleration_3 ... depth acceleration_n Brake pedal depth time series depth braking_1 , depthbraking_2 , depth braking_3 ... depth braking_n Steering wheel rotation angle time series θ 1. θ 2. θ 3…… θ n and multimedia data streams multimedia 1. multimedia 2. multimedia 3…… multimedia n Multimodal behavior recognition is performed to obtain the traffic behavior type corresponding to the original vehicle usage record data. Specifically, the processing module can determine the type based on the timestamp. t 1. t 2. t 3…… t n In the corresponding order, read the data with the same timestamp from each time series in the original vehicle usage record data, and perform multimodal behavior recognition.

[0042] For example, the processing module first obtains the timestamp. t 1 corresponds to the accelerator pedal depth depth acceleration_1 Brake pedal depth depth braking_1 Steering wheel rotation angle θ 1 and multimedia data multimedia 1. Perform multimodal behavior recognition on this data to obtain timestamps. t 1 corresponds to the traffic behavior type; then obtain the timestamp. t 2 corresponds to the accelerator pedal depth depth acceleration_2 Brake pedal depth depth braking_2 Steering wheel rotation angle θ 2 and multimedia data multimedia 2. Perform multimodal behavior recognition on this data to obtain timestamps. t 2 corresponds to the type of traffic behavior... Multimodal behavior recognition identifies the types of traffic behaviors exhibited by car users while driving shared vehicles based on various data types. The results of multimodal behavior recognition include categories such as "compliant" and "suspected violation." Specifically, step P1 is used to timestamp... t Taking the original vehicle usage record data as an example for multimodal behavior recognition, the result of multimodal behavior recognition is "compliant," indicating that the processing module uses timestamps... t 1. Corresponding to the original vehicle usage record data, determine the car user's usage at the timestamp. tIf the driving actions of the shared car at the corresponding time point (e.g., forward, backward, turning, honking) are compliant, the result of the multimodal behavior identification is "suspected violation type," indicating that the processing module, based on the timestamp... t 1. Corresponding to the original vehicle usage record data, determine the car user's usage at the timestamp. t The traffic behavior of driving a shared car at the corresponding time is suspected of being illegal.

[0043] In this embodiment, the traffic behavior type obtained by the processing module in step P1 is only used for local processing. It can also be provided to the traffic management department (law enforcement agency) for processing if it is legally retrieved by the traffic management department (law enforcement agency). However, the traffic behavior type itself has no legal effect and is not used as the final basis for attributing responsibility for traffic violations.

[0044] In this embodiment, step P1 is performed based on the timestamp. t Taking the traffic behavior type determined by the original vehicle usage record data corresponding to step 1 as an example, when executing step P2, if the identified traffic behavior type is "compliant", then the processing module will timestamp... t The original vehicle usage record data corresponding to 1 is determined to be ordinary record data; if the identified traffic behavior type is "suspected violation type", then the processing module will timestamp t The original vehicle usage record data corresponding to 1 was identified as suspicious violation record data, and the timestamp was set. t 1. Identify the timestamp as suspicious and update the corresponding location stamp. p 1. Identified as a suspicious location stamp.

[0045] In this embodiment, by executing steps P1-P3, the shared car can process the original vehicle usage record data locally. The identified suspicious timestamps and suspicious location stamps indicate the specific time and location at which the car user is suspected of committing a traffic violation, as identified locally by the shared car. The suspicious violation record data is the original data recorded for the suspected traffic violation committed by the car user.

[0046] In this embodiment, after executing steps P1-P3, when the processing module executes step S5, which is the step of tracing violations based on traffic violation confirmation information and original vehicle usage record data, the following steps can be specifically performed: S501B. Based on the traffic violation confirmation information, determine the actual time and location of the violation; S502B. Based on the actual time of the violation, search for matching suspicious timestamps; S503B. Based on the actual location of the violation, search for matching suspicious location stamps; S504B. When suspicious timestamps and suspicious location stamps are collected simultaneously, retrieve the identity information bound to the original vehicle usage record data marked by the suspicious timestamps and suspicious location stamps.

[0047] Steps S501B-S504B are the second execution method of step S5.

[0048] The principle of steps S501B-S504B is similar to that of steps S501A-S504A. The difference lies in that while steps S502A-S503A search for all timestamps and location stamps stored in the large-capacity memory, steps S502B-S503B search for only suspicious timestamps and location stamps—that is, a subset of all timestamps and location stamps. Therefore, compared to executing steps S501A-S504A, executing steps S501B-S504B requires a smaller data search space, resulting in higher search efficiency and thus more efficient vehicle user tracing.

[0049] In this embodiment, the processing module may also perform the following steps: P4. Before obtaining confirmation information of traffic violations, count the number of suspected violations to obtain the number of suspected violations, and pre-deduct funds from the accounts corresponding to the identity information based on the number of suspected violations. P5. After obtaining confirmation information of traffic violations or after the preset time limit has expired, confirm or cancel the suspected violation record data, and adjust the account corresponding to the identity information according to the confirmation or cancellation of the suspected violation record data.

[0050] Step P4 is executed by the processing module before obtaining traffic violation confirmation information in step S4. In step P4, the processing module counts the number of suspicious violation records obtained in step P2 to determine the number of suspected violations. This number is then sent to the cloud server, requesting the car-sharing service provider (renter) to pre-deduct payment from the account corresponding to the user's identity information. This account can be the deposit account opened by the car user with the car-sharing service provider (renter). Specifically, the car-sharing service provider (renter) can set a per-trip price and pre-deduct payment from the account based on the price and the number of suspected violations. After pre-deducting payment, the car-sharing service provider (renter) can also generate a pre-deduction notification and send it to the shared car via the cloud server. The shared car then displays the notification to the user through the human-machine interaction module, informing the user that they have committed a suspected violation and have been pre-deducted payment.

[0051] Step P5 is executed by the processing module after obtaining traffic violation confirmation information in step S4. In step P5, the processing module determines the actual number of traffic violations committed by the car user while driving the shared car based on the traffic violation confirmation information. If the processing module does not receive traffic violation confirmation information within a preset time limit (e.g., 1 month), the actual number is determined to be 0. The processing module compares the actual number with the suspected number of violations. If the actual number equals the suspected number of violations, there is no need to adjust the account corresponding to the identity information that has been pre-deducted. If the actual number is less than the suspected number of violations, the pre-deduction for the account corresponding to the identity information is cancelled.

[0052] In this embodiment, by executing steps P4-P5, the shared car can identify suspected traffic violations by the user during the use of the shared car, pre-deduct funds from the user's deposit account, and notify the user. This allows the user to receive real-time feedback on suspected traffic violations, making the user more cautious when using the shared car, reducing the likelihood of traffic violations, and ensuring the safety of using the shared car.

[0053] In this embodiment, the processing module may also perform the following steps: S6. Establish credit files corresponding to identity information; S7. Record credit scores in credit files; S8. Track the processing results of traffic violation confirmation information and adjust the credit score in the credit file according to the processing results.

[0054] In this embodiment, the credit profile and recorded credit score established in steps S6-S7 are data processed internally by the car-sharing service provider (renter) and kept confidential externally. By recording the credit score, the severity of traffic violation confirmation information for a specific car user can be quantified, and appropriate actions can be taken against the car user based on their credit score. For example, car-sharing order requests initiated by car users with credit scores below a threshold can be rejected, thereby helping to protect the legitimate interests of the car-sharing service provider (renter).

[0055] In this embodiment, the processing module may also perform the following steps: S9. Identify multiple data custodians; S10. Based on the degree of correlation between each data custodian and the traffic liability confirmation information, determine the recommended retention period for each data custodian; the recommended retention period is positively correlated with the degree of correlation with traffic liability. S11. Obtain the hash value corresponding to the original vehicle usage record data; S12. For any data custodian, send the original vehicle usage record data, hash value, and the suggested retention period information corresponding to the data custodian to the data custodian; the suggested retention period information is used to instruct the data custodian to retain the hash value and delete the original vehicle usage record data after the suggested retention period information is reached.

[0056] The principle of steps S9-S12 is as follows: Figure 3 As shown.

[0057] Reference Figure 3 In step S9, multiple data custodians are determined. A data custodian refers to an entity or individual with a legal interest in traffic liability related to traffic violations committed or potentially committed by the shared vehicle. This includes entities or individuals who are legally responsible for traffic violations committed by the shared vehicle or who determine the allocation of legal liability. For example, in this embodiment, the data custodians specifically include the actual driver of the shared vehicle, the user registration party, the lessor, the insurer (providing insurance for the shared vehicle), the law enforcement agency, and the manufacturer (the car manufacturer that produces the shared vehicle and assumes warranty responsibility). Some or all of these entities can be selected as data custodians.

[0058] In this embodiment, for traffic violations confirmed by traffic violation information received by shared cars, the degree of traffic liability relevance of different data custodians varies, such as the severity of the legal responsibility they need to bear. This degree of relevance can be quantified by factors such as the economic losses resulting from the legal liability caused by the traffic violation. For example, generally, the data custodians are arranged in descending order of traffic liability relevance as follows: actual driver, registered user, insurer, lessor, manufacturer, and law enforcement.

[0059] In step S10, the recommended retention period is determined based on the degree of traffic responsibility of each data custodian. Specifically, the greater the degree of traffic responsibility a data custodian has, the longer the recommended retention period is assigned to that data custodian.

[0060] For example, refer to Figure 3In this embodiment, suggested retention period information 1 is generated for the actual driver (data custodian), with the largest value (e.g., 1 year); suggested retention period information 2 is generated for the user registration (data custodian), with the second largest value (e.g., 6 months); suggested retention period information 6 is generated for the insurer (data custodian), with the third largest value (e.g., 3 months); suggested retention period information 3 is generated for the lessor (data custodian), with the fourth largest value (e.g., 2 months); suggested retention period information 5 is generated for the manufacturer (data custodian), with the fifth largest value (e.g., 1 month); and suggested retention period information 4 is generated for the law enforcement (data custodian), with the smallest value (e.g., 1 week).

[0061] In step S11, the processing module performs hash processing on the original vehicle usage record data stored in the large-capacity storage device to obtain the hash value corresponding to the original vehicle usage record data. Specifically, the processing module can use hash functions such as SHA-256 to process the original vehicle usage record data to obtain the hash value.

[0062] The hash value obtained in step S11 can serve as a data fingerprint of the original vehicle usage record data. Even a very minor modification to the original vehicle usage record data can cause a significant change in the hash value. Therefore, if the hash value obtained by hashing the original vehicle usage record data again at any later time is the same as the hash value obtained in step S11, it can be determined that the original vehicle usage record data has not been modified and is completely identical to the original vehicle usage record data stored in the shared car's large-capacity storage at the time step S11 was executed.

[0063] In step S12, the processing module sends the original vehicle usage record data, hash value, and suggested retention period information corresponding to the data custodian to the data custodian. Specifically, each data custodian receives the same original vehicle usage record data and the same hash value, but each data custodian generally receives different suggested retention period information, for example, referring to... Figure 3 The actual driver receives suggested storage duration information 1, and the user registration party receives suggested storage duration information 2.

[0064] In this embodiment, each data custodian can retain the received original vehicle usage record data for a corresponding duration based on the received suggested retention period information, while storing the received hash value for an extended period. For example, the actual driver, based on the received suggested retention period information 1 (value is 1 year), retains the received original vehicle usage record data for 1 year, and can choose to delete the original vehicle usage record data after 1 year; the law enforcement agency, based on the received suggested retention period information 4 (value is 1 week), retains the received original vehicle usage record data for 1 week, and can choose to delete the original vehicle usage record data after 1 week. Each data custodian also stores the received hash value for an extended period, such as more than 1 year.

[0065] In this embodiment, the principle behind steps S9-S12 is as follows: By sending the original vehicle usage record data to various data custodians, multiple parties responsible for traffic violations related to shared cars can obtain the original vehicle usage record data. This allows for analysis based on the original vehicle usage record data, providing information support for attributing responsibility for traffic violations. Furthermore, by sending the hash value of the original vehicle usage record data to each data custodian, even after deleting the original vehicle usage record data, each data custodian can still use its stored hash value to analyze the original vehicle usage records provided by other data custodians. The recorded data can be verified. For example, suppose the insurer obtains the original vehicle usage record data, deletes it after 3 months, and the actual driver objects to the insurer's confirmation of traffic violations, requests a redistribution of responsibility, and provides the original vehicle usage record data as evidence. The insurer can calculate the hash value of the original vehicle usage record data provided by the actual driver and compare it with the hash value that the insurer still keeps. If the two hash values ​​match, the insurer can be certain that the original vehicle usage record data provided by the actual driver has not been modified, and can then conduct an investigation and analysis based on the original vehicle usage record data.

[0066] As can be seen from the above embodiments, by executing steps S9-S12, each data custodian can delete the original vehicle usage record data they have received after the suggested retention period, thereby reducing data space occupation and helping to reduce their equipment operating costs or equipment usage costs. The hash value data volume is very small, and even long-term storage will not lead to a significant increase in costs. Data custodians with a higher degree of traffic liability may retain the original vehicle usage record data for a longer period. Even if some data custodians have deleted the original vehicle usage record data, the still-retained original vehicle usage record data can still be verified, and after successful verification, investigations can be conducted based on the original vehicle usage record data. Therefore, by executing steps S9-S12, information support for clarifying the facts can be provided, and the overall data storage cost can be reduced, which is beneficial for energy conservation and emission reduction.

[0067] Figure 3 This example illustrates the process of calculating the hash value of the entire original vehicle usage record data. In this embodiment, the original vehicle usage record data is processed to obtain a hash value. In step S11, the original vehicle usage record data can be divided into multiple data segments, and each data segment can be hashed to obtain its own hash value. The position of each hash value within the original vehicle usage record data is then marked. This way, when the original vehicle usage record data needs to be verified based on the hash value, only the hash value corresponding to the data segment that needs to be processed can be verified, thereby reducing the amount of data that needs to be processed.

[0068] A computer program for executing the shared car violation tracing method in this embodiment can be written into a computer device or storage medium. When the computer program is read and run, the shared car violation tracing method in this embodiment is executed, thereby achieving the same technical effect as the shared car violation tracing method in the embodiment.

[0069] It should be noted that, unless otherwise specified, when a feature is referred to as "fixed" or "connected" to another feature, it can be directly fixed or connected to the other feature, or indirectly fixed or connected to the other feature. Furthermore, the descriptions of "upper," "lower," "left," and "right" used in this disclosure are only relative to the relative positional relationships of the components of this disclosure in the accompanying drawings. The singular forms "a," "an," and "the" used in this disclosure are also intended to include the plural forms, unless the context clearly indicates otherwise. Moreover, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this embodiment specification is only for describing particular embodiments and is not intended to limit the invention. The term "and / or" as used in this embodiment includes any combination of one or more of the associated listed items.

[0070] It should be understood that although the terms first, second, third, etc., may be used to describe various elements in this disclosure, these elements should not be limited to these terms. These terms are only used to distinguish elements of the same type from each other. For example, a first element may also be referred to as a second element without departing from the scope of this disclosure, and similarly, a second element may also be referred to as a first element. The use of any and all instances or exemplary language (“e.g.,” “such as,” etc.) provided in this embodiment is intended only to better illustrate embodiments of the invention and, unless otherwise required, does not impose a limitation on the scope of the invention.

[0071] It should be recognized that embodiments of the present invention can be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium. The method can be implemented using standard programming techniques—including a non-transitory computer-readable storage medium configured with a computer program, wherein such a storage medium causes the computer to operate in a specific and predefined manner—according to the methods and drawings described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Furthermore, for this purpose, the program can run on a programmed application-specific integrated circuit (ASIC).

[0072] Furthermore, the procedures described in this embodiment can be performed in any suitable order unless otherwise indicated by this embodiment or clearly contradicted by the context. The procedures (or variations and / or combinations thereof) described in this embodiment can be executed under the control of one or more computer systems configured with executable instructions, and can be implemented by hardware or a combination thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that commonly executes on one or more processors. A computer program includes multiple instructions executable by one or more processors.

[0073] Furthermore, the method can be implemented in any suitable type of computing platform, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, standalone or integrated computer platforms, or in communication with charged particle tools or other imaging devices, etc. Aspects of the invention can be implemented as machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it is readable by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the processes described herein. Furthermore, the machine-readable code, or portions thereof, can be transmitted via wired or wireless networks. The invention of this embodiment includes these and other different types of non-transitory computer-readable storage media when such media comprises instructions or programs that implement the steps above in conjunction with a microprocessor or other data processor. When programmed according to the methods and techniques of the invention, the invention also includes the computer itself.

[0074] A computer program can be applied to input data to perform the functions of this embodiment, thereby transforming the input data to generate output data stored in non-volatile memory. The output information can also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including specific visual depictions of physical and tangible objects generated on the display.

[0075] The above are merely preferred embodiments of the present invention. The present invention is not limited to the above-described embodiments. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention, as long as they achieve the technical effects of the present invention by the same means, should be included within the scope of protection of the present invention. Within the scope of protection of the present invention, the technical solutions and / or implementation methods can have various modifications and variations.

Claims

1. A method for tracing violations in car-sharing services, characterized in that, The methods for tracing violations related to the shared car service include: Obtain the identity and authorization information of the car user; the car user is the user who accepts the car-sharing service; Based on the authorization information, when a car user uses the shared car, the original car usage record data, timestamp, and location stamp are collected simultaneously, and the original car usage record data is marked using the timestamp and the location stamp; Establish a binding relationship between the identity information and the original vehicle usage record data; Obtain confirmation information on traffic violations committed by the shared car; The violation can be traced based on the traffic violation confirmation information and the original vehicle usage record data.

2. The method for tracing violations in shared cars according to claim 1, characterized in that, The step of tracing violations based on the traffic violation confirmation information and the original vehicle usage record data includes: Based on the traffic violation confirmation information, the actual time and location of the violation are determined; Based on the actual time of the violation, a matching timestamp is searched. Based on the actual location of the violation, a matching location stamp can be retrieved; When the timestamp and location stamp are collected simultaneously, the identity information bound to the original vehicle usage record data marked by the timestamp and location stamp is retrieved.

3. The method for tracing violations in shared cars according to claim 1, characterized in that, The method for tracing violations related to car-sharing also includes: Multimodal behavior recognition is performed on the original vehicle usage record data to obtain the traffic behavior type corresponding to the original vehicle usage record data; Based on the type of traffic behavior, the original vehicle usage record data is determined to be either ordinary record data or suspicious violation record data; The timestamp and location stamp corresponding to the suspected illegal record data are respectively identified as suspicious timestamp and suspicious location stamp.

4. The method for tracing violations in shared cars according to claim 3, characterized in that, The step of tracing violations based on the traffic violation confirmation information and the original vehicle usage record data includes: Based on the traffic violation confirmation information, the actual time and location of the violation are determined; Based on the actual time of the violation, search for matching suspicious timestamps; Based on the actual location of the violation, search for matching suspicious location stamps; When the suspicious timestamp and the suspicious location stamp are collected simultaneously, the identity information bound to the original vehicle usage record data marked by the suspicious timestamp and the suspicious location stamp is retrieved.

5. The method for tracing violations in shared cars according to claim 3, characterized in that, The method for tracing violations related to car-sharing also includes: Before obtaining the traffic violation confirmation information, the suspected violation record data is counted to obtain the number of suspected violations, and the account corresponding to the identity information is pre-deducted based on the number of suspected violations; After obtaining confirmation information of the traffic violation or after a preset time limit has been exceeded, the suspected violation record data is confirmed or revoked, and the account corresponding to the identity information is adjusted according to the confirmation or revocation of the suspected violation record data.

6. The method for tracing violations in shared cars according to claim 1, characterized in that, The method for tracing violations related to car-sharing also includes: Establish a credit file corresponding to the aforementioned identity information; Credit scores are recorded in the credit profile. The processing results of the traffic violation confirmation information are tracked, and the credit score in the credit file is adjusted according to the processing results.

7. The method for tracing violations of shared car regulations according to any one of claims 1-6, characterized in that, The method for tracing violations related to car-sharing also includes: Multiple data custodians are identified; the data custodians include some or all of the actual drivers, users, lessors, insurers, law enforcement agencies, and manufacturers of the shared vehicles; Based on the degree of correlation between each data custodian and the traffic liability of the traffic violation confirmation information, the recommended retention period information for each data custodian is determined; the duration indicated by the recommended retention period information is positively correlated with the degree of correlation with the traffic liability. Obtain the hash value corresponding to the original vehicle usage record data; For any of the data custodians, the original vehicle usage record data, the hash value, and the suggested retention period information corresponding to the data custodian are sent to the data custodian; the suggested retention period information is used to instruct the data custodian to retain the hash value and delete the original vehicle usage record data after the recommended retention period information has been reached.

8. The method for tracing violations in shared cars according to claim 7, characterized in that, The step of obtaining the hash value corresponding to the original vehicle usage record data includes: The original vehicle usage record data is segmented to obtain multiple data segments; Obtain the hash value of each of the data segments respectively; For any of the hash values, the hash value is marked according to the position of the data segment corresponding to the hash value in the original vehicle usage record data.

9. A computer device, characterized in that, It includes a memory and a processor, the memory being used to store at least one program, and the processor being used to load at least one program to execute the shared car violation tracing method according to any one of claims 1-8.

10. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to perform the method for tracing violations of shared vehicles as described in any one of claims 1-8.

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