Automobile rescue management method and device based on AI

Abstract

The invention discloses an AI-based automobile rescue management method and device, and relates to the technical field of automobile rescue. The method comprises the following steps: receiving a rescue request sent by a target user, determining a target vehicle according to license plate information, and obtaining first operation data corresponding to the target vehicle; inputting the vehicle type and the first operation data into a preset model for processing to obtain a first fault reason; generating a user portrait according to the license plate information and the demand information; matching a target rescue mode conforming to the first fault reason according to the user portrait; determining a first automobile rescue team according to the target rescue mode, and obtaining a first position corresponding to the first automobile rescue team; generating a target rescue route according to the second position and the first position; and sending the target rescue route to a rescue end, so that a first automobile rescue team corresponding to the rescue end goes to a first position according to the target rescue route to rescue the target automobile. By implementing the technical scheme provided by the invention, the rescue efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicle rescue, and particularly to an AI-based vehicle rescue management method and device. Background Art

[0002] With the booming economic development and the significant improvement of people's living standards, cars have become an indispensable means of transportation for many families, leading to a sharp increase in the car ownership. The widespread popularity of cars has been accompanied by frequent vehicle failures and an increase in the traffic accident rate, thus giving rise to a sharp expansion in the demand for vehicle rescue services. In the current situation, when a vehicle owner encounters a vehicle failure, they can seek assistance by calling the rescue service hotline or using relevant online platforms. Once the rescue service platform receives the help request, it will respond quickly and dispatch professional personnel to the scene for fault diagnosis and repair operations.

[0003] However, in the traditional vehicle rescue service mode, after the vehicle owner contacts a neighboring rescue service agency, due to unclear geographical location description, the rescue team cannot quickly locate, which prolongs the vehicle owner's waiting time, makes the entire rescue process time-consuming, and ultimately leads to the problem of low rescue efficiency.

[0004] Therefore, there is an urgent need for an AI-based vehicle rescue management method and device that can solve the above technical problems. Summary of the Invention

[0005] This application provides an AI-based vehicle rescue management method and device, which effectively solves the problem that occurs when the vehicle owner's geographical location description is unclear after contacting the rescue service agency, thereby improving the rescue efficiency and shortening the vehicle owner's waiting time.

[0006] In a first aspect, this application provides an AI-based vehicle rescue management method, which is applied to a vehicle rescue platform. The method includes: receiving a rescue request sent by a target user, processing the rescue request to obtain license plate information, demand information, and vehicle type; determining a target vehicle according to the license plate information, and obtaining first operation data corresponding to the target vehicle; inputting the vehicle type and the first operation data into a preset model for processing to obtain a first fault cause; generating a user profile according to the license plate information and the demand information; matching a target rescue method that conforms to the first fault cause according to the user profile; determining a first vehicle rescue team according to the target rescue method, and obtaining a first location corresponding to the first vehicle rescue team; generating a target rescue route according to a second location and the first location, where the second location is the location currently corresponding to the target vehicle; sending the target rescue route to the rescue end, so that the first vehicle rescue team corresponding to the rescue end can go to the first location according to the target rescue route to perform rescue operations on the target vehicle.

[0007] By adopting the above technical solution, the license plate information is determined according to the rescue request, then the target vehicle is determined according to the license plate information, and then the first operation data corresponding to the target vehicle is obtained. The vehicle type and the first operation data are input into a preset model for processing to obtain the first cause of the fault, avoiding the time for manual judgment or waiting for professionals to arrive at the scene for diagnosis. Then, a user profile is generated according to the license plate information and the demand information, and then a target rescue method that matches the first cause of the fault is matched based on the user profile. The first vehicle rescue team is determined according to the target rescue method, and the second position currently corresponding to the target vehicle is obtained, ensuring that the rescue team obtains accurate vehicle position information and avoiding positioning difficulties caused by unclear descriptions from the vehicle owner. Then, a target rescue route is automatically generated based on the second position of the target vehicle and the first position of the first vehicle rescue team, and the target rescue route is displayed to the first vehicle rescue team, so that the first vehicle rescue team can quickly and efficiently reach the accident scene, effectively solving the problem caused by unclear geographical location descriptions after the vehicle owner contacts the rescue service agency, thereby improving the rescue efficiency and shortening the waiting time of the vehicle owner.

[0008] Optionally, after determining the target vehicle according to the license plate information, the method further includes: determining whether the communication mode of the target vehicle is in a normal state; if the communication mode of the target vehicle is not in a normal state, obtaining second operation data, where the second operation data refers to the historical operation data of the target vehicle before the target time, and the target time refers to the time corresponding to receiving the rescue request sent by the target user; receiving the abnormal description information sent by the target user for the target vehicle; combining the second operation data and the abnormal description information to obtain third operation data; inputting the third operation data and the vehicle type into a preset model for processing to obtain the second cause of the fault.

[0009] By adopting the above technical solution, when the communication mode of the target vehicle is abnormal and data cannot be transmitted in real time, it can automatically switch to the mode of using historical operation data (second operation data); this flexibility ensures that even when the vehicle communication is poor, fault diagnosis can still be carried out. Combining the abnormal description information (such as sounds, odors, and lighting changes when the fault occurs) provided by the target user in the rescue request with the historical operation data of the vehicle forms more comprehensive third operation data, which can reduce unnecessary on-site inspections and multiple round trips, thereby reducing the cost of rescue services.

[0010] Optionally, generating a user profile according to the license plate information and the demand information specifically includes: determining the vehicle owner information according to the license plate information; determining the vehicle insurance information based on the license plate information and the vehicle owner information; analyzing the demand information to obtain rescue preference information; determining user tags according to the license plate information, the vehicle insurance information, and the rescue preference information, and assigning the user tags to the user profile.

[0011] By adopting the above technical solution, the introduction of license plate information, vehicle owner information, vehicle insurance information, and rescue preference information provides multi-dimensional data support for user profiling. The integration of these information makes the user profile more comprehensive and can more accurately reflect the actual situation and needs of vehicle owners, thereby improving the personalization of rescue services.

[0012] Optionally, match the target rescue method that conforms to the first failure reason according to the user profile, which specifically includes: determining whether there is a rescue service in the vehicle insurance information; when there is no rescue service in the vehicle insurance information, obtaining the first rescue method corresponding to the first failure reason; if the first rescue method is consistent with the user label, confirm that the first rescue method is used as the target rescue method for output.

[0013] By adopting the above technical solution, determining whether the vehicle insurance information contains a rescue service can intelligently identify whether the vehicle owner enjoys the rescue service rights and interests provided by the insurance company. If not, the most suitable rescue method is selected according to the first failure reason and the user label to ensure the pertinence and effectiveness of the service and avoid unnecessary waste of rescue resources.

[0014] Optionally, after determining whether there is a rescue service in the vehicle insurance information, the method further includes: when there is a rescue service in the vehicle insurance information, determining a second rescue team according to the rescue service.

[0015] By adopting the above technical solution, in the case where the vehicle insurance information includes a rescue service, the rescue service agency can allocate rescue resources more reasonably, directly determine the rescue team according to the rescue service in the vehicle insurance information, which can simplify the rescue process and reduce the communication and coordination costs between the vehicle owner and the rescue service agency.

[0016] Optionally, determining a first vehicle rescue team according to the target rescue method specifically includes: obtaining target location information from the rescue request, where the target location information is the location information corresponding to the target vehicle; determining multiple vehicle rescue teams according to the vehicle type; obtaining a third vehicle rescue team from the multiple rescue teams; determining whether the third vehicle rescue team is in a rescue state; if the third vehicle rescue team is not in a rescue state, adding the third vehicle rescue team to the set of rescue teams to be dispatched.

[0017] By adopting the above technical solution, the target location information can be obtained from the rescue request, and the specific location of the target vehicle can be quickly determined, which helps the rescue team to respond quickly, reduces the time for searching for the faulty vehicle, and improves the rescue efficiency. Determining multiple vehicle rescue teams according to the vehicle type can ensure that the selected rescue team has the professional ability and experience to handle the faults of the corresponding type of vehicle. Judging the status of the third vehicle rescue team can understand whether it is currently in a rescue state. The entire process quickly screens and determines the available rescue teams in an automated manner, reduces human intervention and waiting time, and improves the reliability and efficiency of the rescue service.

[0018] Optionally, after confirming that the third vehicle rescue team is added to the set of rescue teams to be retrieved if the third vehicle rescue team is not in a rescue state, the method further includes: obtaining multiple rescue distances, where the rescue distance is the distance between the vehicle rescue team in the set of rescue teams to be retrieved and the target location information, and one rescue distance corresponds to one vehicle rescue team; obtaining a first rescue distance and a second rescue distance from the multiple rescue distances; judging whether the first rescue distance is less than the second rescue distance; when the first rescue distance is less than the second rescue distance, outputting the vehicle rescue team corresponding to the first rescue distance as the first vehicle rescue team.

[0019] By adopting the above technical solution, by calculating the distance between each rescue team and the target vehicle, the rescue resources can be more reasonably allocated, and then the rescue team closest to the target vehicle (the first vehicle rescue team) can be selected for rescue, which can significantly reduce the rescue response time.

[0020] In the second aspect of the present application, an AI-based vehicle rescue management device is provided. The device is a vehicle rescue platform, and the vehicle rescue platform includes a receiving unit, a processing unit, and a sending unit; the receiving unit receives the rescue request sent by the target user, processes the rescue request, and obtains the license plate information, demand information, and vehicle type; the processing unit determines the target vehicle according to the license plate information, obtains the first operation data corresponding to the target vehicle; inputs the vehicle type and the first operation data into a preset model for processing to obtain the first fault cause; generates a user profile according to the license plate information and the demand information; matches the target rescue method that conforms to the first fault cause according to the user profile; determines the first vehicle rescue team according to the target rescue method, and obtains the first location corresponding to the first vehicle rescue team; generates a target rescue route according to the second location and the first location, where the second location is the current location corresponding to the target vehicle; the sending unit sends the target rescue route to the rescue end, so that the first vehicle rescue team corresponding to the rescue end can go to the first location according to the target rescue route to perform rescue operations on the target vehicle.

[0021] Optionally, the processing unit is used to determine whether the communication mode of the target vehicle is in a normal state; the receiving unit is used to obtain second operation data if the communication mode of the target vehicle is not in a normal state, where the second operation data refers to the historical operation data of the target vehicle before the target time, and the target time refers to the time corresponding to receiving the rescue request sent by the target user; receive the abnormal description information sent by the target user for the target vehicle; the processing unit is used to combine the second operation data and the abnormal description information to obtain third operation data; input the third operation data and the vehicle type into a preset model for processing to obtain the second fault cause.

[0022] Optionally, the processing unit is used to determine the vehicle owner information according to the license plate information; determine the vehicle insurance information based on the license plate information and the vehicle owner information; analyze the demand information to obtain the rescue preference information; determine the user label according to the license plate information, the vehicle insurance information and the rescue preference information, and assign the user label to the user portrait.

[0023] Optionally, the processing unit is used to determine whether there is a rescue service in the vehicle insurance information; the receiving unit is used to obtain the first rescue method corresponding to the first fault cause when there is no rescue service in the vehicle insurance information; the processing unit is used to confirm and output the first rescue method as the target rescue method if the first rescue method is consistent with the user label.

[0024] Optionally, when there is a rescue service in the vehicle insurance information, the processing unit is used to determine the second rescue team according to the rescue service.

[0025] Optionally, the receiving unit is used to obtain the target location information from the rescue request, where the target location information is the location information corresponding to the target vehicle; the processing unit is used to determine multiple vehicle rescue teams according to the vehicle type; the receiving unit is used to obtain the third vehicle rescue team from the multiple rescue teams; the processing unit is used to determine whether the third vehicle rescue team is in a rescue state; if the third vehicle rescue team is not in a rescue state, add the third vehicle rescue team to the set of rescue teams to be retrieved.

[0026] Optionally, the receiving unit is used to obtain multiple rescue distances, where the rescue distance is the distance between the vehicle rescue team in the set of rescue teams to be retrieved and the target location information, and one rescue distance corresponds to one vehicle rescue team; obtain the first rescue distance and the second rescue distance from the multiple rescue distances; the processing unit is used to determine whether the first rescue distance is less than the second rescue distance; when the first rescue distance is less than the second rescue distance, output the vehicle rescue team corresponding to the first rescue distance as the first vehicle rescue team.

[0027] In a third aspect of the present application, an electronic device is provided. The electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions. The user interface and the network interface are used to communicate with other devices. The processor is used to execute the instructions stored in the memory, so that an electronic device executes the method of any one of the above in the present application.

[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions, and when the instructions are executed, the method of any one of the above in the present application is executed.

[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Determine the license plate information according to the rescue request, then determine the target vehicle according to the license plate information, then obtain the first operation data corresponding to the target vehicle, input the vehicle type and the first operation data into a preset model for processing to obtain the first fault cause, avoiding the time of manual judgment or waiting for professionals to arrive at the scene for diagnosis. Then generate a user portrait according to the license plate information and the demand information, and then match the target rescue method that matches the first fault cause based on the user portrait. Determine the first vehicle rescue team according to the target rescue method, obtain the current second position corresponding to the target vehicle, ensure that the rescue team obtains accurate vehicle position information, avoid positioning difficulties caused by unclear descriptions of the vehicle owner, and then automatically generate a target rescue route based on the second position of the target vehicle and the first position of the first vehicle rescue team, and display the target rescue route to the first vehicle rescue team, so that the first vehicle rescue team can quickly and efficiently reach the accident scene, effectively solving the problem caused by unclear geographical location description after the vehicle owner contacts the rescue service agency, thereby improving the rescue efficiency and shortening the waiting time of the vehicle owner.

[0030] 2. Judge whether the vehicle insurance information includes rescue services, and can intelligently identify whether the vehicle owner enjoys the rescue service rights and interests provided by the insurance company. If not, select the most appropriate rescue method according to the first fault cause and user tags to ensure the pertinence and effectiveness of the service, and avoid unnecessary waste of rescue resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a flowchart of a method for AI-based vehicle rescue management provided by an embodiment of the present application; Figure 2 is a structural diagram of an AI-based vehicle rescue management device provided by an embodiment of the present application; Figure 3 is a structural diagram of an electronic device disclosed in an embodiment of the present application.

[0032] Explanation of reference numerals: 201, receiving unit; 202, processing unit; 203, sending unit; 300, electronic device; 301, processor; 302, memory; 303, user interface; 304, network interface; 305, communication bus. DETAILED DESCRIPTION

[0033] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0034] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0035] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0036] With the booming economy and the significant improvement in people's quality of life, cars have become an indispensable means of transportation for many families, prompting a sharp increase in the number of cars. The widespread popularity of cars has led to frequent car failures and an increase in traffic accident rates, which has led to a sharp increase in the demand for car rescue services. In the current situation, when car owners encounter car failures, they can seek help by calling the rescue service hotline or using relevant online platforms. Once the rescue service platform receives a request for help, it will respond quickly and dispatch professionals to the scene to perform fault diagnosis and repair operations.

[0037] However, under the traditional automobile rescue service model, after the car owner contacts the nearby rescue service agency, the rescue team is unable to locate the location quickly due to unclear geographical description, which in turn prolongs the car owner's waiting time, making the entire rescue process time-consuming and ultimately causing the problem of low rescue efficiency.

[0038] Therefore, how to solve the problem caused by the unclear geographical location description after the vehicle owner contacts the rescue service agency. An AI-based vehicle rescue management method provided by an embodiment of the present application is applied to a vehicle rescue platform. The vehicle rescue platform of the present application can be a platform that provides rescue for vehicle rescue agencies. Figure 1 It is a schematic flowchart of an AI-based vehicle rescue management method provided by an embodiment of the present application. Refer to Figure 1 , this method includes the following steps S101-S108.

[0039] S101: Receive a rescue request sent by a target user, process the rescue request, and obtain license plate information, demand information, and vehicle type.

[0040] In the above S101, when the vehicle owner is driving the vehicle normally and the vehicle breaks down or cannot move, the user asks the rescue agency for help, so that the rescue agency dispatches relevant personnel to the vehicle location for repair. The target user refers to the vehicle owner with rescue needs. The user sends a rescue request to the vehicle rescue platform through a mobile application, a web page, etc. After receiving the rescue request, the vehicle rescue platform parses the rescue request and extracts key information, such as user contact information and vehicle information. Extract the license plate number, the needs described by the user (such as "the vehicle cannot start", "the tire is flat", etc.), and the vehicle type information that the user may provide (such as sedan, SUV, truck, and new energy vehicle, etc.) from the parsed request. Then verify and clean the extracted data to ensure the accuracy and integrity of the information.

[0041] S102: Determine the target vehicle according to the license plate information, and obtain the first operation data corresponding to the target vehicle.

[0042] In the above S102, after extracting the license plate information of the vehicle to be rescued from the rescue request, the license plate number can be used as a query condition to query the current operation data of the vehicle corresponding to the license plate information. Sensors have been installed in the vehicle in advance, and then the corresponding relationship between the sensor and the license plate information is constructed, so that the corresponding sensor can be queried according to the license plate information in the future, and then the data of the vehicle monitored by the sensor in real time can be obtained, and the real-time obtained data is integrated into the first operation data.

[0043] In addition, before obtaining the first operation data corresponding to the target vehicle, it is necessary to judge the communication method of the target vehicle. Since after the sensor monitors various data of the vehicle, it needs to transmit the data to the vehicle rescue platform through the communication method. Therefore, judging the communication method of the vehicle and determining that the communication method is in a normal state are the prerequisite conditions for ensuring the acquisition of the first operation data, which specifically includes: judging whether the communication mode of the target vehicle is in a normal state; if the communication mode of the target vehicle is not in a normal state, then obtain the second operation data, where the second operation data refers to the historical operation data of the target vehicle before the target moment, and the target moment refers to the moment corresponding to receiving the rescue request sent by the target user; then receive the abnormal description information sent by the target user for the target vehicle; combine the second operation data and the abnormal description information to obtain the third operation data; input the third operation data and the vehicle type into a preset model for processing to obtain the second fault cause. Specifically, the vehicle rescue platform can attempt to establish a communication connection with the target vehicle, which may involve using on-board diagnostic systems (OBD), telematics technology, or similar vehicle-to-cloud communication methods. If the platform can successfully establish a connection with the target vehicle and can receive real-time data updates of the vehicle (such as speed, position, engine status, etc.), then it is considered that the communication mode of the vehicle is in a normal state. If the connection cannot be established, or the connection is unstable, the data update is delayed or interrupted, then it is determined that the communication mode of the target vehicle is not in a normal state. Once it is determined that the communication mode is abnormal, the platform needs to obtain other available vehicle operation data. These data are usually stored in the vehicle's own storage system or historical data that has been uploaded to the cloud server. The platform retrieves the historical operation data before the target moment in the database according to the license plate number, VIN code or other unique identifiers of the target vehicle. These data may include vehicle performance records, maintenance history, fault codes, etc. in the past few days or weeks. The data that is closest to and most relevant to the target moment is selected from the retrieved historical data as the second operation data. The platform prompts the target user to input a detailed description of the vehicle anomaly through a user interface (such as a mobile application, a web page, or a telephone customer service). The information input by the user, such as the specific manifestation of the fault, the time of occurrence, and whether any repair measures have been attempted, is received and recorded by the platform. Combine the second operation data and the abnormal description information provided by the user to form a more comprehensive data set. This data set may include the vehicle's historical performance data, fault codes, fault phenomena and descriptions observed by the user, etc. Input the preprocessed third operation data and the vehicle type information into a preset diagnostic model. This model may be a machine learning-based classifier or regressor that has been trained to identify different types of vehicle faults. The model performs feature extraction, pattern matching, and inference on the input data to predict the most likely fault cause.The model outputs the second fault cause, which may be one or more specific fault types, as well as the confidence or probability of each fault type.

[0044] Furthermore, when the communication module of the target vehicle is in a normal state, the data real-time monitored by each sensor installed in the target vehicle can be obtained, and the monitored data can be integrated to obtain the first operation data.

[0045] S103: Input the vehicle type and the first operation data into a preset model for processing to obtain the first fault cause.

[0046] In the above S103, after obtaining the first operation data corresponding to the target vehicle, before inputting the vehicle type and the first operation data into the preset model for processing, it is necessary to construct the preset model. The vehicle type in this application refers to whether the power system of the vehicle uses gasoline or a battery, that is, whether it is a gasoline vehicle or a new energy vehicle. Since there are significant differences between gasoline vehicles and new energy vehicles in terms of structure, power system, fault modes, etc., when encountering the same situation, the possible fault causes of the two may also be different. Therefore, when constructing the preset model, it is necessary to fully consider this key factor of vehicle type. First, collect a large amount of data on fault types, fault causes, rescue requirements, etc. of gasoline vehicles and new energy vehicles. Clean and organize the data to ensure the accuracy and integrity of the data. Extract the features related to fault types and fault causes according to the vehicle type (gasoline vehicle, new energy vehicle). Select the features that have an important impact on the selection of the rescue team, such as vehicle location, fault type, rescue requirements, etc. Then select a suitable algorithm to further process and optimize the features, so that in fault prediction, it is possible to predict the possible fault causes based on the vehicle type and operation data. Then use historical data to train the model, and adjust the model parameters to make it better adapt to the actual situation. During the training process, it is necessary to monitor the performance of the model, such as indicators such as accuracy and recall rate. Optimize the model according to the training results and performance evaluation indicators. Deploy the trained preset model to the vehicle rescue platform so that it can perform feature extraction and pattern matching based on the vehicle type and the first operation data. When outputting the fault cause that matches the vehicle type and the first operation data, AI can also be used for intelligent analysis to ensure that the output fault cause matches the vehicle type, that is, the preset model outputs the most likely fault cause, that is, the first fault cause. Make the output fault cause match the vehicle type to avoid the situation of misjudgment caused by the output fault cause not matching the vehicle type.

[0047] S104: Generate a user profile according to the license plate information and demand information.

[0048] In the above S104, a user portrait is constructed by combining license plate information (such as implicit information like vehicle value, brand preference, etc.), demand information (such as urgency, user habits, etc.), and other available data (such as the user's historical rescue records). That is, a user portrait is generated based on license plate information and demand information, specifically including: determining vehicle owner information according to license plate information; determining vehicle insurance information based on license plate information and vehicle owner information; analyzing demand information to obtain rescue preference information; determining user tags according to license plate information, vehicle insurance information, and rescue preference information, and assigning the user tags to the user portrait. Specifically, receive and parse the input data containing license plate information to ensure the accuracy and integrity of the license plate information. The license plate information can be queried online to determine the vehicle owner information corresponding to the current license plate information. Before obtaining the vehicle owner information based on the license plate information, it is necessary to ensure that the platform has obtained the relevant privacy permissions, and then the vehicle owner information can be queried. Then verify the queried vehicle owner information to ensure its accuracy. Obtain the vehicle owner information, including the vehicle owner's name, contact information, etc. A third-party platform can be used. Enter the vehicle owner's name, license plate information, and identity information on the third-party platform to query the vehicle insurance company name and insurance expiration date information. Manage and integrate the queried vehicle insurance information with the license plate information and vehicle owner information. Then perform text analysis on the vehicle owner's demand information to extract key information, such as the type of breakdown, urgency, expected rescue time, etc. Combine the user's historical rescue records to analyze the user's rescue preferences, such as which rescue method is preferred (on-site repair, towing service, etc.), the sensitivity to rescue time, etc. Generate rescue preference information according to the analysis results. Integrate the license plate information, vehicle insurance information, and rescue preference information. Determine user tags according to the integrated information. These tags may include vehicle value tags (such as high-end cars, economy cars, etc.), vehicle owner type tags (such as individual vehicle owners, corporate vehicle owners, etc.), insurance status tags (such as comprehensive insurance, compulsory insurance, etc.), rescue preference tags (such as fast rescue preference, low-cost rescue preference, etc.). Assign the determined user tags to the user portrait. Ensure the accuracy and comprehensiveness of the user portrait for subsequent precise rescue matching and personalized service provision. Subsequently, as the user's rescue history increases and rescue preferences change, update the tags and information in the user portrait in a timely manner.

[0049] S105: Match the target rescue method that matches the first failure cause according to the user portrait.

[0050] In the above S105, matching the target rescue method that conforms to the first fault cause according to the user portrait specifically includes: judging whether there is a rescue service in the vehicle insurance information; when there is no rescue service in the vehicle insurance information, obtaining the first rescue method corresponding to the first fault cause; if the first rescue method is consistent with the user label, then confirm that the first rescue method is used as the target rescue method for output. Specifically, after determining the vehicle insurance information corresponding to the target vehicle, keyword fields can be extracted from the received vehicle insurance information, such as insurance type, insurance terms, additional services, etc. According to the extracted insurance information, identify whether there are terms or descriptions related to rescue services. Rescue services may include roadside assistance, towing service, emergency repair, etc. If the vehicle insurance information clearly contains terms or descriptions of rescue services, it is judged that there is a rescue service. If the rescue service is not mentioned in the vehicle insurance information, or the relevant terms are unclear, it is judged that there is no rescue service. After determining the first fault cause of the target vehicle, the fault cause involves mechanical failure, electrical failure, accident damage, etc. According to the first fault cause, match the corresponding first rescue method from the preset rescue method library. The rescue method library may contain various rescue methods, such as on-site repair, towing service, emergency fuel delivery, etc. From the matched rescue methods, select the rescue method that is most suitable for the current fault situation and vehicle status. Also extract label information related to the user from the user portrait. User labels may include vehicle owner type, vehicle value, rescue preference, etc. Compare the first rescue method with the user label to judge whether they are consistent. If the first rescue method is consistent with the user label, then confirm that the first rescue method is the target rescue method. If they are inconsistent, it may be necessary to reconsider the choice of rescue method, or communicate with the user to understand their preferences and needs. Output the target rescue method to the user or the relevant rescue agency.

[0051] In addition, when there is a rescue service in the vehicle insurance information, determine the second rescue team according to the rescue service. Carefully read and extract the terms and details related to the rescue service from the vehicle insurance information. Clearly define the specific content covered by the rescue service, such as towing service, on-site repair, emergency fuel delivery, battery charging, etc. According to the information in the insurance terms, identify the specific team or company providing the rescue service. It may be the in-house rescue team of the insurance company, or a third-party rescue service provider cooperating with the insurance company. Then, according to the specific content of the rescue service and the vehicle fault situation, evaluate the capabilities and adaptabilities of different rescue teams. If it is determined that the team providing the rescue service can handle this rescue request, then determine the second rescue team according to the rescue service terms in the vehicle insurance information.

[0052] S106: Determine the first vehicle rescue team according to the target rescue method, and obtain the first location corresponding to the first vehicle rescue team.

[0053] In the above S106, the most suitable rescue method is determined according to the user profile and the first failure cause. The rescue methods include on-site repair, towing service, replacement parts, etc. Then, according to the target rescue method, the first automobile rescue team is determined, which specifically includes: obtaining the target location information from the rescue request, where the target location information is the location information corresponding to the target vehicle; determining multiple automobile rescue teams according to the vehicle type; obtaining the third automobile rescue team from the multiple rescue teams; judging whether the third automobile rescue team is in a rescue state; if the third automobile rescue team is not in a rescue state, then confirm to add the third automobile rescue team to the set of rescue teams to be retrieved. Specifically, the target location information is extracted from the rescue request, which usually includes the precise location of the target vehicle (such as latitude and longitude coordinates), the road where it is located, intersections, nearby landmarks, etc. If the user does not directly provide the location information, it can be obtained through other means, such as asking the user, using the mobile phone positioning function, etc. Then, according to the vehicle information provided in the rescue request, key parameters such as the model, brand, and vehicle series of the target vehicle are determined. According to the vehicle type, multiple automobile rescue teams that can handle the faults of this type of vehicle are selected from the pre-established rescue team database. The rescue teams in the database may be classified according to vehicle models, brands, regions, etc. for quick matching. Then, the most suitable automobile rescue team is selected from the multiple selected rescue teams as the third automobile rescue team. Query the current rescue state of the third automobile rescue team. In order to quickly confirm the rescue state of each automobile rescue team, when an automobile rescue team undertakes a rescue task, the rescue state of the automobile rescue team can be adjusted from idle to in-rescue, so as to screen the automobile rescue teams in the idle state in a timely manner. If the third automobile rescue team is in an idle state or can respond immediately, it is judged that it meets the rescue conditions. The third automobile rescue team that meets the conditions is added to the set of rescue teams to be retrieved. This set may contain multiple rescue teams, and the platform will sort them according to factors such as priority and response time for quick retrieval when needed. Once it is confirmed that the third automobile rescue team (or other teams in the set) can perform the rescue task, the platform can be prepared for scheduling, including sending task notifications to the rescue team, providing the location and fault information of the target vehicle, etc.

[0054] In addition, after confirming that the automobile rescue teams in the idle state are added to the set of rescue teams to be retrieved, the locations of the automobile rescue teams in the set of rescue teams to be retrieved are obtained, and then the distances between each automobile rescue team and the target vehicle are calculated in turn to ensure that the team closest to the target vehicle is selected from the multiple automobile rescue teams for rescue, improving the rescue efficiency and accuracy. Specifically, Obtain multiple rescue distances. The rescue distance is the distance between the vehicle rescue team in the to-be-invoked set of teams and the target location information. One rescue distance corresponds to one vehicle rescue team. Obtain the first rescue distance and the second rescue distance from the multiple rescue distances. Determine whether the first rescue distance is less than the second rescue distance. When the first rescue distance is less than the second rescue distance, confirm that the vehicle rescue team corresponding to the first rescue distance is output as the first vehicle rescue team. Specifically, obtain multiple vehicle rescue teams from the to-be-invoked set of vehicle rescue teams, and then use a Geographic Information System (GIS) or related positioning technology to calculate the distance between the current location of each rescue team and the location of the target vehicle. Usually, it involves inputting the coordinates of the rescue team and the coordinates of the target vehicle into a calculation model, and obtaining the rescue distance of each rescue team by calculating the straight-line distance between two points or the driving distance calculated according to the actual road conditions. Record the calculated rescue distance of each rescue team and associate it with its corresponding rescue team. Obtain any two rescue distances from the multiple rescue distances, namely the first rescue distance and the second rescue distance, and then determine whether the first rescue distance is less than the second rescue distance. This step is to confirm which rescue team is the closest team. When the first rescue distance is less than the second rescue distance, compare the first rescue distance with other rescue distances. If the first rescue distance is less than all other rescue distances, at this time, it can be defaulted that the vehicle rescue team corresponding to the first rescue distance in the multiple rescue distances is the closest, so the vehicle rescue team corresponding to the first rescue distance is output as the first vehicle rescue team. In addition to using the pairwise comparison mentioned above, all rescue distances can be sorted in ascending order for subsequent comparison and selection. From the sorted rescue distances, select the smallest as the first rescue distance and the second smallest as the second rescue distance. Output the information of the first vehicle rescue team (such as team name, contact information, estimated arrival time, etc.) so that the relevant personnel of the target vehicle can contact and obtain rescue services in a timely manner. Then query the current location of the first vehicle rescue team, that is, the first location, usually obtained through GPS positioning or team reports.

[0055] S107: Generate a target rescue route based on the second location and the first location. The second location is the location currently corresponding to the target vehicle.

[0056] In the above S107, obtain the location currently corresponding to the target vehicle, that is, the second location. The second location can be obtained through the GPS coordinates provided by the user or automatic detection based on the vehicle location. Then use a map service API (such as Baidu Map, etc.) to calculate the optimal route from the first location to the second location, that is, the target rescue route.

[0057] S108: Send the target rescue route to the rescue end so that the first vehicle rescue team corresponding to the rescue end can go to the first location according to the target rescue route to perform rescue operations on the target vehicle.

[0058] In the above S108, the target rescue route and other necessary information (such as user contact information, vehicle information, fault description, etc.) are sent to the first vehicle rescue team via text message, mobile application notification or internal communication system. After the rescue team confirms receipt of the information, it starts to go to the target location. At the same time, the platform can track the mobile status and arrival time of the rescue team in real time to provide updates to the user. After the first vehicle rescue team arrives at the first location, it repairs the target vehicle. After finishing the repair of the target vehicle, the first vehicle rescue team generates a repair bill and sends the repair bill to the target user so that the target user can pay the repair bill after verification. After the user completes the payment of the repair bill, the user evaluates the rescue service of the first vehicle rescue team so that the subsequent ranking of each vehicle rescue team can be carried out according to the user evaluation. For the convenience of subsequent traceability, the initiator and participants of this rescue order can also be obtained, and then the information of the rescue order is uploaded to the blockchain for storage. If there is a rescue dispute later, the corresponding rescue order can be queried from the blockchain and the relevant personnel participating in the rescue order can be investigated to ensure that the rescue situation can be traced.

[0059] Through the above method, the license plate information is determined according to the rescue request, then the target vehicle is determined according to the license plate information, and then the first operation data corresponding to the target vehicle is obtained. The vehicle type and the first operation data are input into the preset model for processing to obtain the first fault cause, avoiding the time of manual judgment or waiting for professionals to arrive at the scene for diagnosis. Then, a user portrait is generated according to the license plate information and the demand information, and then a target rescue method that matches the first fault cause is matched based on the user portrait. The first vehicle rescue team is determined according to the target rescue method, and the current second location corresponding to the target vehicle is obtained to ensure that the rescue team obtains accurate vehicle location information, avoiding positioning difficulties caused by unclear descriptions from the vehicle owner. Then, based on the second location of the target vehicle and the first location of the first vehicle rescue team, a target rescue route is automatically generated, and the target rescue route is displayed to the first vehicle rescue team so that the first vehicle rescue team can quickly and efficiently reach the accident scene, effectively solving the problem caused by unclear geographical location description after the vehicle owner contacts the rescue service agency, thereby improving the rescue efficiency and shortening the waiting time of the vehicle owner.

[0060] The embodiment of the present application also provides an AI-based vehicle rescue management device. Figure 2 It is a schematic structural diagram of an AI-based vehicle rescue management device provided by the embodiment of the present application. Refer to Figure 2, the device is an automobile rescue platform, and the automobile rescue platform includes a receiving unit 201, a processing unit 202, and a sending unit 203.

[0061] The receiving unit 201 receives the rescue request sent by the target user, processes the rescue request, and obtains the license plate information, demand information, and vehicle type.

[0062] The processing unit 202 determines the target vehicle according to the license plate information, and obtains the first operation data corresponding to the target vehicle; inputs the vehicle type and the first operation data into a preset model for processing to obtain the first failure cause; generates a user portrait according to the license plate information and the demand information; matches the target rescue method that matches the first failure cause according to the user portrait; determines the first automobile rescue team according to the target rescue method, and obtains the first position corresponding to the first automobile rescue team; generates a target rescue route according to the second position and the first position, where the second position is the position currently corresponding to the target vehicle.

[0063] The sending unit 203 sends the target rescue route to the rescue end, so that the first automobile rescue team corresponding to the rescue end can go to the first position according to the target rescue route to perform rescue operations on the target vehicle.

[0064] In a possible implementation manner, the processing unit 202 is used to determine whether the communication mode of the target vehicle is in a normal state; the receiving unit 201 is used to obtain the second operation data if the communication mode of the target vehicle is not in a normal state, where the second operation data refers to the historical operation data of the target vehicle before the target time, and the target time refers to the time corresponding to receiving the rescue request sent by the target user; receive the abnormal description information sent by the target user for the target vehicle; the processing unit 202 is used to combine the second operation data and the abnormal description information to obtain the third operation data; input the third operation data and the vehicle type into a preset model for processing to obtain the second failure cause.

[0065] In a possible implementation manner, the processing unit 202 is used to determine the owner information according to the license plate information; determine the vehicle insurance information based on the license plate information and the owner information; analyze the demand information to obtain the rescue preference information; determine the user label according to the license plate information, the vehicle insurance information, and the rescue preference information, and assign the user label to the user portrait.

[0066] In a possible implementation manner, the processing unit 202 is used to determine whether there is a rescue service in the vehicle insurance information; the receiving unit 201 is used to obtain the first rescue method corresponding to the first failure cause when there is no rescue service in the vehicle insurance information; the processing unit 202 is used to confirm that the first rescue method is used as the target rescue method for output if the first rescue method is consistent with the user label.

[0067] In a possible implementation, the processing unit 202 is configured to determine a second rescue team according to the rescue service when there is a rescue service in the vehicle insurance information.

[0068] In a possible implementation, the receiving unit 201 is configured to obtain target location information from a rescue request, where the target location information is the location information corresponding to the target vehicle; the processing unit 202 is configured to determine a plurality of vehicle rescue teams according to the vehicle type; the receiving unit 201 is configured to obtain a third vehicle rescue team from the plurality of rescue teams; the processing unit 202 is configured to determine whether the third vehicle rescue team is in a rescue state; if the third vehicle rescue team is not in a rescue state, add the third vehicle rescue team to the set of rescue teams to be retrieved.

[0069] In a possible implementation, the receiving unit 201 is configured to obtain a plurality of rescue distances, where the rescue distance is the distance between the vehicle rescue team in the set of rescue teams to be retrieved and the target location information, and one rescue distance corresponds to one vehicle rescue team; obtain a first rescue distance and a second rescue distance from the plurality of rescue distances; the processing unit 202 is configured to determine whether the first rescue distance is less than the second rescue distance; when the first rescue distance is less than the second rescue distance, output the vehicle rescue team corresponding to the first rescue distance as the first vehicle rescue team.

[0070] It should be noted that: when the device provided in the above embodiments implements its functions, only the division of the above function modules is used for illustration. In actual applications, the above functions can be allocated to different function modules according to needs, that is, the internal structure of the device is divided into different function modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments, which will not be repeated here.

[0071] This application also discloses an electronic device. Refer to Figure 3 , Figure 3 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 302, and at least one communication bus 305.

[0072] Among them, the communication bus 305 is used to realize the connection and communication between these components.

[0073] Among them, the user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0074] Among them, the network interface 304 may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface).

[0075] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server through various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 302, and by calling the data stored in the memory 302, it executes various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application requests, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately through a single chip.

[0076] Among them, the memory 302 may include random access memory (RAM) and may also include read-only memory. Optionally, the memory 302 includes a non-transitory computer-readable storage medium. The memory 302 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 302 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store the data involved in the above-mentioned various method embodiments. Optionally, the memory 302 may also be at least one storage device located far from the aforementioned processor 301.

[0077] As Figure 3 shown, the memory 302, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for AI-based vehicle rescue management.

[0078] In Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 301 can be used to call the application program stored in the memory 302 for AI-based vehicle rescue management. When executed by one or more processors, the electronic device is caused to execute one or more of the methods as described in the above embodiments.

[0079] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0080] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0081] In several embodiments provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0082] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] In addition, in each embodiment of this application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0084] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes various media that can store program codes, such as USB flash drives, mobile hard disks, magnetic disks, or optical discs.

[0085] The foregoing are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will readily think of other implementation manners of the present disclosure after considering the specification and practicing the disclosure herein. This application aims to cover any variations, uses, or adaptive changes of the present disclosure, and these variations, uses, or adaptive changes follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not described in the present disclosure.

Claims

1. An AI-based automobile rescue management method, characterized in that: Applied in a car rescue platform, the method comprises: Receive a rescue request sent by a target user, process the rescue request, and obtain license plate information, demand information, and vehicle type; Determine a target vehicle according to the license plate information, and obtain first operating data corresponding to the target vehicle; Inputting the vehicle type and the first operating data into a preset model for processing to obtain a first fault cause; Generate a user portrait according to the license plate information and the demand information; Matching a target rescue method that matches the first fault cause according to the user profile; Determining a first automobile rescue team according to the target rescue method, and obtaining a first position corresponding to the first automobile rescue team; Generate a target rescue route according to a second position and the first position, wherein the second position is a current position corresponding to the target vehicle; The target rescue route is sent to a rescue end, so that the first vehicle rescue team corresponding to the rescue end goes to the first position according to the target rescue route to perform a rescue operation on the target vehicle.

2. The method according to claim 1, characterized in that After determining the target vehicle according to the license plate information, the method further includes: Determining whether the communication mode of the target vehicle is in a normal state; If the communication mode of the target vehicle is not in the normal state, obtaining second operation data, where the second operation data refers to historical operation data of the target vehicle before a target time, where the target time refers to a time corresponding to receiving the rescue request sent by the target user; Receiving abnormal description information for the target vehicle sent by the target user; Combining the second operation data and the abnormal description information to obtain third operation data; The third operating data and the vehicle type are input into the preset model for processing to obtain a second fault cause.

3. The method according to claim 1, characterized in that: The generating of the user portrait according to the license plate information and the demand information specifically includes: Determine the vehicle owner information according to the license plate information; Determining vehicle insurance information based on the license plate information and the vehicle owner information; Analyzing the demand information to obtain rescue preference information; A user tag is determined according to the license plate information, the vehicle insurance information and the rescue preference information, and the user tag is assigned to the user portrait.

4. The method according to claim 3, characterized in that: The matching of the target rescue method consistent with the first fault cause according to the user profile specifically includes: Determining whether there is a rescue service in the vehicle insurance information; When the rescue service does not exist in the vehicle insurance information, obtaining a first rescue method corresponding to the first fault cause; If the first rescue method is consistent with the user tag, it is confirmed to output the first rescue method as the target rescue method.

5. The method according to claim 4, characterized in that After determining whether there is a rescue service in the vehicle insurance information, the method further includes: When the rescue service exists in the vehicle insurance information, a second rescue team is determined according to the rescue service.

6. The method according to claim 1, characterized in that The determining of the first automobile rescue team according to the target rescue method specifically includes: Acquire target positioning information from the rescue request, where the target positioning information is location information corresponding to the target vehicle; determining a plurality of automobile rescue teams based on the type of vehicle; obtaining a third vehicle rescue team from the plurality of said rescue teams; Determining whether the third automobile rescue team is in a rescue state; If the third automobile rescue team is not in the rescue state, the third automobile rescue team is added to the rescue team set to be retrieved.

7. The method according to claim 6, characterized in that After confirming that the third automobile rescue team is added to the set of rescue teams to be retrieved if the third automobile rescue team is not in the rescue state, the method further includes: Acquire multiple rescue distances, where the rescue distance is the distance between the vehicle rescue team in the to-be-retrieved collection team set and the target positioning information, and one rescue distance corresponds to one vehicle rescue team; Acquire a first rescue distance and a second rescue distance from the plurality of rescue distances; determining whether the first rescue distance is less than the second rescue distance; When the first rescue distance is smaller than the second rescue distance, the vehicle rescue team corresponding to the first rescue distance is output as the first vehicle rescue team.

8. An AI-based automobile rescue management device, characterized in that: The device is a car rescue platform, comprising a receiving unit (201), a processing unit (202) and a sending unit (203); The receiving unit (201) receives a rescue request sent by a target user, processes the rescue request, and obtains license plate information, demand information, and vehicle type; The processing unit (202) determines a target vehicle according to the license plate information, obtains first operating data corresponding to the target vehicle; inputs the vehicle type and the first operating data into a preset model for processing, and obtains a first fault cause; and generates a user portrait according to the license plate information and the demand information; Matching a target rescue method that matches the first fault cause according to the user portrait; determining a first automobile rescue team according to the target rescue method, and obtaining a first position corresponding to the first automobile rescue team; generating a target rescue route according to a second position and the first position, the second position being the current position corresponding to the target vehicle; The sending unit (203) sends the target rescue route to the rescue end, so that the first vehicle rescue team corresponding to the rescue end goes to the first position according to the target rescue route to perform a rescue operation on the target vehicle.

9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (302), a user interface (303) and a network interface (304), wherein the memory (302) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (302) so that the electronic device (300) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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