New energy commercial vehicle insurance cost reduction and operation management and control system and method

Abstract

This invention relates to the field of vehicle intelligent management and insurance data technology, and discloses a system and method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles. The system includes a vehicle terminal unit, a communication transmission unit, a cloud management platform, an insurance data interaction unit, and an operation and maintenance management unit. The vehicle terminal unit collects vehicle operation, environmental, and driver status data, which is then uploaded to the cloud via the communication transmission unit. The cloud management platform performs fusion analysis on the multi-source data, generates driving behavior scores, and establishes a dynamic insurance pricing model, enabling data interaction between vehicle manufacturers and insurance companies. The operation and maintenance management unit executes vehicle maintenance scheduling and risk intervention based on the analysis results. This method achieves risk identification and insurance cost control throughout the entire lifecycle of commercial vehicles through vehicle status monitoring, behavior recognition, and closed-loop management of insurance data.

Description

Technical Field

[0001] This invention belongs to the field of automotive technology. Specifically, this invention relates to a system and method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles. Background Technology

[0002] With the rapid development of the new energy commercial vehicle industry, vehicle operation safety, controllable maintenance costs, and scientific insurance pricing have become core pain points of concern in the industry. As the core carrier of logistics transportation, the overall stability of commercial vehicles, the standardization of driver operation, and the rationality of cargo load directly affect driving safety, and are also related to maintenance losses and the efficiency of insurance risk assessment.

[0003] In existing technologies, various related technical solutions have emerged to improve driving safety and risk management. Automatic Emergency Braking (AEB) technology avoids collision risks by issuing warnings or triggering emergency braking when the vehicle approaches an object. Its operating speed range is 10kph~135kph. It is enabled by default upon power-on and can be manually disabled by the driver after secondary confirmation. It can identify pedestrians, two-wheeled vehicles, three-wheeled vehicles, and various motor vehicles. Technical acceptance references national standards GB / T 38186, JT / T 1242, and some CNCAP scenarios to optimize for false triggering issues. The Driver Fatigue Detection System (DMS), as an ASIL-B level safety function module, uses a hardware combination of an infrared camera, a TOF sensor, and an MCU processor to monitor driver fatigue and distraction in real time. Based on the risk level, it implements a graded intervention strategy, including instrument warnings, speed reduction warnings, or emergency braking combined with contact calls. The dynamic premium pricing model (UBI) replaces the traditional static assessment method by collecting real-time data such as vehicle mileage and driving behavior. This allows users with good driving habits to enjoy lower rates and reduces the risk pricing error from ±30% to ±8%.

[0004] However, the aforementioned existing technologies still have significant defects and shortcomings: First, the lower limit of the working speed of AEB technology is 10 kph, which cannot be triggered in low-speed driving scenarios such as logistics parks and farmers' markets, making it difficult to cope with the collision risks in such scenarios; Second, DMS technology relies on biometric recognition and sensor data, and when the driver's eyes are too small or their face is passively obscured, inaccurate information collection is likely to occur, causing the system to malfunction; Third, the optimization and iteration of the UBI model depends on the support of a large amount of vehicle operation data, but the number of vehicles currently equipped with this system is insufficient, and the data volume is difficult to meet the algorithm's needs for model improvement, thus limiting the accuracy of insurance pricing.

[0005] This paper provides a method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles, specifically on how to achieve risk identification and insurance cost control throughout the entire life cycle of commercial vehicles through vehicle status monitoring, behavior recognition, and closed-loop management of insurance data. Summary of the Invention

[0006] This invention aims to address at least one of the technical problems existing in the prior art. To this end, this invention provides a method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles. The purpose is to achieve risk identification and insurance cost control throughout the entire lifecycle of commercial vehicles through vehicle status monitoring, behavior recognition, and closed-loop management of insurance data.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by this invention is: a cost reduction and operation and maintenance management system for new energy commercial vehicle insurance, comprising: The vehicle terminal unit is used to collect vehicle operation data, environmental data, and driver status data. A communication transmission unit is used to upload the vehicle operation data, environmental data, and driver status data to the cloud. The cloud management platform is used to integrate and analyze data uploaded to the cloud, generate vehicle risk scores, and establish dynamic insurance pricing models. The insurance data interaction unit is used to enable data sharing and feedback between the cloud management platform and the insurance company; and The operation and maintenance control unit is used to perform vehicle maintenance scheduling, driving behavior analysis and risk intervention control based on the vehicle risk information output by the cloud management platform; The vehicle terminal unit includes an automatic emergency braking module (AEB) and a driver monitoring module (DMS). The cloud management platform identifies driving behavior types and accident scenarios based on the operating data uploaded by the automatic emergency braking module and the driver monitoring module, and dynamically adjusts the risk coefficient in the insurance pricing model.

[0008] The vehicle terminal unit includes vehicle radar, camera, reversing image system, and instrument display module, which are used to realize forward collision avoidance, reversing assistance and panoramic monitoring functions.

[0009] The cloud management platform includes a data access module, a driving behavior analysis module, an accident record module, a trajectory query module, and an alarm query module. The driving behavior analysis module is used to calculate driving behavior characteristic indicators based on the vehicle operation data and output the risk level; The data access module is configured to support the access of insurance company data collectors, and extracts vehicle TBOX data, automatic emergency braking module and driver monitoring module video data through reserved interfaces to achieve multi-source data fusion.

[0010] The system is configured sequentially according to the implementation phases as follows: The first phase is the economic version, the second phase is the upgraded version, and the third phase is the full-featured version; Each stage is equipped with basic AEB+DMS monitoring, intelligent navigation and cargo management, short-term automatic takeover and third-party ecosystem connectivity functions; The second phase adds a cargo hold management module that includes a cargo hold camera, radar, and temperature and humidity sensors to monitor cargo hold environmental parameters and cargo status. The short-term automatic takeover module configured in the third stage is used to autonomously decelerate or brake the vehicle to a stop in dangerous situations.

[0011] The cloud management platform's dynamic insurance pricing model is based on driving behavior scores, accident records, and runtime parameters to dynamically adjust premiums.

[0012] The calculation of the driving behavior score includes the identification of at least one of the following driving behaviors: rear-end collision risk behavior, blind spot reversing behavior, fatigued driving behavior, dangerous driving behavior, or aggressive driving behavior.

[0013] The system supports two operating modes: one where the insurance company has not intervened and the other where it has. In non-intervention mode, vehicle alarm data is transmitted from the cloud to the vehicle manufacturer's after-sales department for investigation; In the intervened mode, vehicle alarm data and insurance claim data are analyzed together and fed back to the vehicle manufacturer and insurance company. The vehicle manufacturer prepares spare parts in advance based on the accident attribution report and notifies the vehicle owner or operator to arrange for the vehicle to be brought in for repair, thus achieving a rapid response.

[0014] The insurance data interaction unit is used to receive accident data from insurance companies, compare and analyze the accident data with vehicle operation data, and generate an accident attribution report. The accident attribution report is transmitted to the vehicle manufacturer's after-sales service module via a cloud management platform for vehicle maintenance scheduling and parts preparation. The operation and maintenance management unit includes a data screening module, a problem investigation module, and a driving behavior optimization module; it is used to dynamically adjust and hierarchically manage driving behavior based on cloud feedback data.

[0015] This invention also provides a method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles based on the system, comprising the following steps: 1) The vehicle terminal unit collects vehicle operation data and driver status data; 2) Uploaded to the cloud management platform via the communication transmission unit; 3) The cloud management platform integrates and analyzes the data to generate driving behavior scores and accident reports; 4) Update the dynamic insurance pricing model based on driving behavior scores; 5) Feedback the analysis results to vehicle manufacturers and insurance companies for vehicle operation and maintenance scheduling and risk intervention.

[0016] The fusion analysis in step 3) includes joint analysis of vehicle AEB trigger records, DMS detection results and positioning data to identify driving behavior characteristics; The feedback in step 5) includes pushing accident reports and driving behavior reports to the driver's terminal and classifying and managing driver behavior.

[0017] The new energy commercial vehicle insurance cost reduction and operation and maintenance management system of the present invention has the following beneficial effects: 1. Achieve integrated management of insurance and operation and maintenance data, and realize accurate premium assessment through vehicle status monitoring; 2. Implement risk prediction and dynamic rate strategies to effectively reduce the claim rate and premium expenditure for high-risk vehicles; 3. Reduce operation and maintenance costs and minimize losses from unexpected failures and downtime by using health prediction models; 4. By building a collaborative system linking the vehicle, cloud, and insurers, a data-driven closed loop for insurance cost reduction and operation and maintenance optimization has been formed. This has enabled an integrated design for cost reduction and risk management in new energy commercial vehicle insurance, improving vehicle operation safety and insurance pricing accuracy, and providing the commercial vehicle industry with a systematic safety and cost management solution. Attached Figure Description

[0018] Figure 1 This is a schematic diagram illustrating the principle of the new energy commercial vehicle insurance cost reduction and operation and maintenance management system of the present invention; Figure 2 This is a schematic diagram of the driving safety system solution of the present invention; Figure 3 This is a schematic diagram of the overall architecture of the new energy commercial vehicle insurance reduction control and maintenance technology of the present invention; Figure 4 This is a flowchart of the data transmission and processing process for the new energy commercial vehicle insurance control and maintenance technology. Figure 5 This invention provides a flowchart for the technical service processing of reducing insurance costs and maintaining operations for new energy commercial vehicles. Detailed Implementation

[0019] To facilitate understanding of the present invention, a more comprehensive description of the present invention will be given below with reference to the accompanying drawings, which illustrate several embodiments of the present invention. However, the present invention can be implemented in different forms and is not limited to the embodiments described in the text. Rather, these embodiments are provided to make the disclosure of the present invention more thorough and complete.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly associated with those skilled in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments and is not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] In a first aspect, embodiments of the present invention provide a cost reduction and operation and maintenance management system for new energy commercial vehicle insurance, comprising: The vehicle terminal unit is used to collect vehicle operation data, environmental data, and driver status data. A communication transmission unit is used to upload the vehicle operation data, environmental data, and driver status data to the cloud. The cloud management platform is used to integrate and analyze data uploaded to the cloud, generate vehicle risk scores, and establish dynamic insurance pricing models. The insurance data interaction unit is used to enable data sharing and feedback between the cloud management platform and the insurance company; and The operation and maintenance control unit is used to perform vehicle maintenance scheduling, driving behavior analysis, and risk intervention control based on the vehicle risk information output by the cloud management platform.

[0022] The vehicle terminal unit includes an automatic emergency braking module (AEB) and a driver monitoring module (DMS). The cloud management platform identifies driving behavior types and accident scenarios based on the operational data uploaded by the automatic emergency braking module and the driver monitoring module, and dynamically adjusts the risk coefficients in the insurance pricing model.

[0023] Specifically, an analysis of statistics from a certain insurance company's operations in a city over a year, involving 77,000 vehicles, revealed that rear-end collisions accounted for 29.66% of all accidents, while reversing accidents and various minor scrapes accounted for 19%. The frequency of these accidents can generally be attributed to two main factors: equipment-related and driver-related. Blind spots and insufficient safe following distance are significant contributing factors to the high incidence of traffic accidents, especially in densely populated urban areas and on ordinary roads. Automatic Emergency Braking (AEB) provides warnings to the driver to brake or evade when the vehicle approaches an object; as the distance closes further and the risk of collision increases, it triggers emergency braking.

[0024] According to statistics from the China Federation of Logistics and Purchasing on 50 million commercial vehicles, the payouts for accidents occurring in the early morning hours are significantly higher than those during peak accident periods. Furthermore, drivers typically work more than 10 hours a day, highlighting the serious dangers of prolonged driving. Vehicles equipped with Driver Monitoring Systems (DMS) can monitor driver fatigue, distraction, and driving habits. Through real-time feedback and warnings, they can correct poor driving behaviors, reduce accident rates, and ultimately decrease insurance claims.

[0025] The commercial vehicle market suffers from numerous safety hazards, including a large fleet, fragmented industry players, chaotic management, and long working hours, leading to high insurance premiums and difficulties in obtaining insurance. Against this backdrop, eliminating these safety hazards and reducing claims and premiums in the commercial vehicle industry has become urgent. By collaborating with OEMs and insurance companies, sharing vehicle data, and utilizing a usage-based insurance (UBI) model, the following can be achieved: users with good driving habits can enjoy lower rates, and the risk pricing error will be reduced from ±30% in the traditional model to ±8%.

[0026] This invention proposes for the first time a vehicle management system oriented towards reducing insurance costs. It establishes a data chain connecting vehicle manufacturers, insurance companies, and vehicle owners or operators, enabling closed-loop collaboration in vehicle safety management, risk assessment, and insurance pricing. The previously independent vehicle network monitoring, driving behavior recognition, and insurance pricing systems are integrated at the system level to form a dynamic premium and maintenance linkage mechanism based on vehicle status prediction.

[0027] In this embodiment of the invention, the vehicle terminal unit includes an onboard radar, a camera, a reversing camera system, and an instrument display module, used to realize forward collision avoidance, reversing assistance, and panoramic monitoring functions. It collects vehicle operation and driving behavior data through various hardware such as AEB, DMS, radar, cameras, and TBOX to achieve effective monitoring of the vehicle's status. Furthermore, it utilizes a cloud platform for fusion analysis to achieve accident risk prediction, dynamic rate adjustment, and proactive maintenance decisions.

[0028] In this embodiment of the invention, the cloud management platform includes a data access module, a driving behavior analysis module, an accident record module, a trajectory query module, and an alarm query module; The driving behavior analysis module is used to calculate driving behavior characteristic indicators based on vehicle operation data and output the risk level; The data access module is configured to support the access of insurance company data collectors, and extracts vehicle TBOX data, automatic emergency braking module and driver monitoring module video data through reserved interfaces to achieve multi-source data fusion and form a multi-source sensor fusion control mechanism.

[0029] In this embodiment of the invention, the system is configured sequentially according to the implementation stages as follows: The first phase is the economic version, the second phase is the upgraded version, and the third phase is the full-featured version; Each stage is equipped with basic AEB+DMS monitoring, intelligent navigation and cargo management, short-term automatic takeover and third-party ecosystem connectivity functions; The second phase of the newly added cargo hold management module includes cargo hold cameras, radar, and temperature and humidity sensors, which are used to monitor cargo hold environmental parameters and cargo status. The short-term automatic takeover module configured in the third stage is used to autonomously decelerate or brake the vehicle to a stop in dangerous situations.

[0030] In this embodiment of the invention, a hierarchical implementation architecture of economy version → upgraded version → full-featured version is proposed, which enables the system to have scalability from basic safety control to advanced intelligent driving and ecological interconnection; each stage corresponds to different insurance data interfaces and risk identification capabilities, realizing the synchronous evolution of hardware and insurance models.

[0031] like Figure 3 As shown, a complete overall architecture for reducing insurance costs in new energy commercial vehicles is constructed from four directions: hardware service layer, data service layer, scenario service layer, and operation service layer. Based on the current situation, this is divided into three stages: The first phase, the economic version, aims for rapid implementation and seizing market opportunities. Based on the "AEB+DMS+intelligent cloud" system, it monitors the safety status of vehicles and passengers in real time, and intervenes in a combination of system and human intervention when necessary, to achieve comprehensive management of driving safety and the initial goal of reducing insurance premiums. The second phase involves upgrading the version with an iterative upgrade plan to optimize the customer experience. Compared to the economy version, the intelligent driving system is optimized: the intelligent navigation function (ACC+LKA) is expanded to free the driver's hands and feet and reduce driving fatigue; a new cargo hold management system is added to realize cargo hold data visualization and improve operational efficiency when combined with the capacity scheduling platform. The third phase, the full-fledged version, features a fully integrated system solution that enhances brand image and allows for customization. It includes different safety scenario packages, improving the intelligent driving experience compared to the upgraded version. It also develops a short-term autonomous driving function that can be forcibly taken over in dangerous situations to bring the vehicle to a safe stop. Furthermore, it integrates with the third-party ecosystem to comprehensively protect the safety of passengers and vehicles throughout their entire lifecycle, thereby reducing TCO (Total Cost of Ownership).

[0032] In this embodiment of the invention, the vehicle installation plan is also implemented in three stages, taking into account the overall architecture: Phase 1: Optimize TBOX and install DMS on the A-pillar of the cab of the new energy commercial vehicle, and install radar and camera at the front of the vehicle body to realize basic AEB (Autonomous Emergency Braking) function. The whole vehicle is reserved in advance for the interface channel for insurance company data collection. Phase Two: Building on Phase One, a large instrument panel is installed in the cab to display scene video data of the cargo compartment and the cab. The intelligent navigation function (ACC+LKA) is further expanded, and a cargo compartment camera and radar are installed in the cargo compartment of the new energy commercial vehicle to achieve comprehensive monitoring of the cargo compartment, enabling cargo monitoring and capacity scheduling. Phase 3: Building on Phase 2, multiple new cameras will be added to achieve a 360-degree panoramic view, eliminating blind spots for drivers. Sensors for controlling temperature and humidity will also be added to the cargo compartment to enhance intelligent driving and develop short-term autonomous driving functions, thus achieving more comprehensive protection for the safety of people and goods.

[0033] In this embodiment of the invention, the dynamic insurance pricing model of the cloud management platform is based on driving behavior scores, accident records, and runtime parameters to achieve dynamic adjustment of premiums.

[0034] The accident reporting module of the cloud management platform is used to generate accident data reports based on specified vehicles and accident times, and supports report export and manual annotation.

[0035] The cloud management platform is further equipped with a total vehicle count display module, a warning information comparison module, and an effective alarm statistics module for displaying vehicle operation status and querying data.

[0036] The cloud management platform connects with the car owner's mobile terminal application to push weekly and monthly reports and driving behavior optimization suggestions.

[0037] In this embodiment of the invention, the calculation of the driving behavior score includes the identification of at least one of the following driving behaviors: rear-end collision risk behavior, blind spot behavior when reversing, fatigued driving behavior, dangerous driving behavior, or aggressive driving behavior.

[0038] like Figure 2 As shown, for rear-end collision scenarios: the hardware solution adopts AEB; the vehicle software strategy is to actively brake and reduce speed when an obstacle or collision hazard is detected ahead, and to perform intelligent takeover when necessary; the platform strategy includes safety education and training, vehicle data backtracking, alarm notification when a vehicle accident occurs, and regular output of operation reports; the achieved effect is to reduce major rear-end collision accidents by 80%.

[0039] like Figure 2As shown, for reversing scenarios: the hardware solution is a reversing camera + instrument panel + reversing radar; the vehicle software strategy is to provide rear visibility when reversing to reduce blind spots; the platform strategy covers safety education and training, vehicle data backtracking, alarm notifications when vehicle accidents occur, and regular output of operation reports; the achieved effect is to reduce reversing accidents by 80%.

[0040] like Figure 2 As shown, for fatigue driving scenarios: the hardware solution adopts DMS + voice prompt system + AEB + automatic air conditioning; the vehicle software strategy is to detect fatigue, distraction and other scenarios in a graded manner, and take over the vehicle by actively reducing speed when necessary; the platform strategy includes safety education and training, real-time monitoring of the vehicle and data backtracking, risk warning reminders and manual intervention, alarm notification when a vehicle accident occurs, and regular output of operation reports; the achieved effect is to reduce major fatigue driving accidents by 80%.

[0041] like Figure 2 As shown, for dangerous and aggressive driving scenarios: the hardware solution is DMS + voice prompt system + AEB; the vehicle software strategy is to detect dangerous or aggressive behaviors, provide voice reminders, and take over the vehicle proactively when necessary; the platform strategy includes safety education and training, real-time vehicle monitoring and data backtracking, risk warning reminders and manual intervention, alarm notifications when vehicle accidents occur, and regular output of operation reports; the goal is to reduce major dangerous and aggressive driving accidents by 80%.

[0042] Through proactive risk intervention at both the vehicle and cloud levels, AEB (Autonomous Emergency Braking) enables automatic braking when approaching obstacles; DMS (Distraction Management System) monitors driver fatigue and distracted driving, issuing warnings or taking over; it automatically alerts drivers to dangerous driving behaviors and proactively intervenes to slow down when necessary, thereby reducing vehicle accident rates and claims amounts, ultimately lowering insurance costs. Furthermore, insurance company claim data is shared with OEM cloud platforms, with claim information fed back to the cloud in real time, facilitating adjustments to dynamic premium models and enabling advance maintenance scheduling to reduce vehicle failure rates, further decreasing claims. Premiums are closely linked to vehicle operating status, achieving a closed-loop effect of reduced premiums, reduced risks, and reduced losses. By using data-driven and intelligent intervention, accident rates are reduced at the source, while precise premium strategies optimize costs, ultimately lowering insurance expenses.

[0043] like Figure 4As shown, the data transmission and processing logic of the cloud management platform is as follows: The insurance company adds a data collector connected to a pre-reserved data interface to extract vehicle data from the TBOX, as well as video data such as AEB and DMS, and uploads it to the cloud. The cloud uses big data to calculate driving behavior scores and build a dynamic premium pricing model. The vehicle score data is then organized into vehicle data, generating weekly, monthly, and accident reports, which are transmitted to customers and drivers. This allows for dynamic adjustments to driver behavior, reducing the accident rate and thus lowering insurance costs. Simultaneously, the cloud platform also connects to the insurance company's claim records and data, transmitting them to the vehicle manufacturer. The manufacturer can then use this insurance data to perform vehicle maintenance and provide precise services.

[0044] The key functions of the cloud management platform are as follows: a. Total Vehicles Display: Displays the number of vehicles in operation today, the number of vehicles currently online, and an alarm distribution pie chart. The display is based on the actual alarm types in the project and is not configurable. It also shows the online status of operating vehicles, which defaults to supporting data queries for the most recent month. Vehicle operating hours are displayed according to fixed categories and are not configurable. The number of valid alarms is calculated based on the number of alarms that resulted in a decrease in vehicle speed after the alarm was triggered and is not configurable. Vehicle update status is also supported by default, supporting data queries for the most recent month. Finally, it compares alarm information, displaying the alarm quantity distribution for the most recent 7 days, with alarm types displayed according to actual types and not configurable. b. Vehicle Management: Supports vehicle filtering and location, adding vehicle devices and binding them to the platform, and vehicle information query. It supports filtering and locating vehicles by license plate, device serial number (SN), device group, vehicle identification number (VIN), contact information, compulsory traffic accident liability insurance expiration date, insurance information, vehicle quota, and device type; it supports viewing the current online status of vehicles; it supports viewing device status, limited to camera and radar malfunctions; it supports viewing driver contact information; it supports viewing version information; and it supports viewing the location of the most recent vehicles. c. Accident Records: Input and export vehicle accident information, and query accident information. Supports data filtering by accident time, report number, license plate number, accident type, collision location, accident classification, insurer, and affiliated fleet; supports exporting accident data (Excel format); supports adding, editing, and deleting accident data entries (data dimensions are fixed and cannot be modified); supports batch import of accident data using templates; supports exporting single-vehicle and fleet claims statistical reports (Word format, report content cannot be modified). d. Driving Behavior Analysis: Query alarm, vehicle body, and location data within a specified time period to assist in analyzing the vehicle's historical behavior. This is commonly used for manual analysis of pre- and post-accident scenarios. It supports filtering and selecting vehicle operation data by license plate number and time (maximum 24 hours), including alarm information, location information, and vehicle signal information (vehicle information shows whether the left and right turn signals and brake lights are on). It supports filtering by data type, with filtering conditions including location information, vehicle body information, FCW, AEB, LDW, and HMW. e. Driving Trajectory Query: Query the driving trajectory of a vehicle within a specified time range and plot the trajectory on a map. Supports querying trajectories by license plate number and start / end time; supports plotting vehicle trajectories on the map; supports statistics on mileage and driving time (duration calculated in minutes). f. Alarm Query: Query vehicle alarm data by alarm type and time. Data can be filtered by selecting vehicle, alarm type, and time range. The list page displays license plate, device serial number (SN), alarm type, alarm time, and vehicle speed. Alarm details can be displayed in a new window. Statistics and display of the number of alarms for different types are also supported. g. Accident Report: Generates an accident analysis report by specifying the vehicle and the time of the accident. It supports generating an accident report by specifying the license plate number and the accident time, and compiling data for 30 minutes before and after the accident. It also supports adding analytical notes to the data, which can be included in the report. Device access conclusions must be entered manually and only text is supported. Reports can be exported (Word format).

[0045] In this embodiment of the invention, the system supports two operating modes: one where the insurance company has not intervened and the other where it has, forming a data closed loop respectively. In non-intervention mode, vehicle alarm data is transmitted from the cloud to the vehicle manufacturer's after-sales department for investigation; In the intervened mode, vehicle alarm data and insurance claim data are analyzed together and fed back to the vehicle manufacturer and insurance company. The vehicle manufacturer prepares spare parts in advance based on the accident attribution report and notifies the vehicle owner or operator to arrange for the vehicle to be brought in for repair, thus achieving a rapid response.

[0046] like Figure 5 As shown in the flowchart, the process for handling technical services related to insurance control and maintenance of new energy commercial vehicles is currently divided into two types: models for which insurance companies are involved and accept data, and models for which insurance companies are not involved. Each type has its own distinct technical service handling method. a) For companies not involved: The cloud platform receives vehicle alarm data uploaded by the vehicle's TBOX and feeds it back to the vehicle manufacturer's after-sales service department. The after-sales service department will assess the authenticity of the alarm incidents based on the vehicle data and conduct preliminary data screening. The selected genuine alarm data will be transmitted to the professional R&D department for troubleshooting and professional optimization. The professional troubleshooting report will be distributed to the car owner's APP and the fleet management company through the cloud platform. This data and driving behavior will be summarized into weekly and monthly reports. The vehicle manufacturer's marketing department will assist in training the fleet management drivers, providing full lifecycle monitoring training from the terminal to the customer, thereby reducing accidents, becoming high-quality insurance customers, and reducing insurance premiums.

[0047] b. Intervention with insurance companies: Vehicle active alarm data: The cloud platform receives vehicle alarm data uploaded by the vehicle's TBOX and feeds it back to the vehicle manufacturer's after-sales service department. The after-sales service department will assess the authenticity of the alarm incidents based on the vehicle data and conduct preliminary data screening. The selected real alarm data will be transmitted to the professional R&D department for troubleshooting and professional optimization. The professional troubleshooting report will be distributed to the car owner's APP and fleet management company through the cloud platform. This data and driving behavior will be summarized into weekly and monthly reports, and the vehicle manufacturer's marketing department will assist in training the fleet management drivers.

[0048] Insurance Company Data: The cloud platform receives accident data from insurance companies and proactively notifies after-sales service departments and relevant research departments at vehicle manufacturers. This data is used to investigate the accident attribution and handling methods for affected vehicles, generating reports that are then fed back to the vehicle manufacturer's quality assurance department. The quality assurance department then notifies the after-sales service department in the vehicle's service area. Based on the accident attribution, the after-sales department, through the vehicle manufacturer's spare parts department, prepares parts in advance and notifies the customer to come in for service, achieving rapid and accurate service. The accident data is also fed back to the insurance company, which uses it to further iterate its dynamic premium pricing model, thereby reducing insurance costs. Accident reports are also quickly pushed to vehicle owners and fleet management companies via the owner's app and the cloud platform to optimize driving behavior and standards. The vehicle manufacturer's marketing department can also collect pain points from vehicle owners and fleet management, developing new products to address these issues and iterating on the manufacturer's product development. This multi-faceted empowerment—problem-driven service, service-resolved pain points, and pain point-optimized product development—creates a unique operation and maintenance system. Deep collaboration with insurance companies provides "people-vehicle-cargo" safety, thereby reducing accident rates and vehicle insurance premiums.

[0049] In this embodiment of the invention, innovations in cloud platforms and data services are achieved: 1. Implement a visualized, full lifecycle management platform; The platform supports visualization and report generation of multi-dimensional data such as vehicle status, alarm distribution, driving behavior, accident records, accident reports, and trajectory playback; It supports the automatic generation of weekly reports, monthly reports, accident analysis reports, and claims reports, and pushes them to car owners and insurance companies.

[0050] 2. Supports multi-dimensional data integration and open interfaces; Standardized data interfaces are reserved to allow insurance companies to access TBOX and video data, enabling efficient cross-system interaction; It supports data backtracking and analysis at the fleet and vehicle levels, improving operational transparency and insurance risk control capabilities.

[0051] 3. It can form an edge-cloud collaborative processing mechanism. Enables rapid risk detection and emergency control at the vehicle end; Long-term trend prediction and optimization are performed in the cloud, achieving a dual improvement in real-time performance and intelligence.

[0052] In this embodiment of the invention, the insurance data interaction unit is used to receive accident data from the insurance company, compare and analyze the accident data with vehicle operation data, and generate an accident attribution report. Accident attribution reports are transmitted to the vehicle manufacturer's after-sales service module via a cloud management platform for vehicle maintenance scheduling and parts preparation. In this embodiment of the invention, the operation and maintenance management unit includes a data screening module, a problem investigation module, and a driving behavior optimization module; it is used to dynamically adjust and hierarchically manage driving behavior based on cloud feedback data.

[0053] Secondly, embodiments of the present invention also provide a method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles based on the above-mentioned system, comprising the following steps: 1) The vehicle terminal unit collects vehicle operation data and driver status data; 2) Uploaded to the cloud management platform via the communication transmission unit; 3) The cloud management platform integrates and analyzes the data to generate driving behavior scores and accident reports; 4) Update the dynamic insurance pricing model based on driving behavior scores; 5) Feedback the analysis results to vehicle manufacturers and insurance companies for vehicle operation and maintenance scheduling and risk intervention.

[0054] The fusion analysis in step 3) includes joint analysis of vehicle AEB trigger records, DMS detection results, and location data to identify driving behavior characteristics; The feedback in step 5) includes pushing accident reports and driving behavior reports to the driver's terminal and classifying and managing driver behavior.

[0055] The new energy commercial vehicle insurance cost reduction and operation and maintenance management system and method of this invention have the following technical effects: 1. Improve driving safety by using technology to detect risks in real time, regulate driving behavior, and enhance risk management capabilities; 2. Achieve loss reduction and compensation reduction by decreasing accident rate, accident losses, and insurance payouts, thereby promoting business model upgrades; 3. Achieve a win-win situation for all parties, including transportation companies, drivers, insurance companies, operating companies, and new energy vehicle manufacturers.

[0056] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A cost reduction and operation and maintenance management system for new energy commercial vehicle insurance, characterized in that, include: The vehicle terminal unit is used to collect vehicle operation data, environmental data, and driver status data. A communication transmission unit is used to upload the vehicle operation data, environmental data, and driver status data to the cloud. The cloud management platform is used to integrate and analyze data uploaded to the cloud, generate vehicle risk scores, and establish dynamic insurance pricing models. An insurance data interaction unit is used to enable data sharing and feedback between the cloud management platform and the insurance company. as well as The operation and maintenance control unit is used to perform vehicle maintenance scheduling, driving behavior analysis and risk intervention control based on the vehicle risk information output by the cloud management platform; The vehicle terminal unit includes an automatic emergency braking module and a driver monitoring module. The cloud management platform identifies driving behavior types and accident scenarios based on the operating data uploaded by the automatic emergency braking module and the driver monitoring module, and dynamically adjusts the insurance pricing model.

2. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to claim 1, characterized in that, The vehicle terminal unit includes vehicle radar, camera, reversing image system, and instrument display module, which are used to realize forward collision avoidance, reversing assistance and panoramic monitoring functions.

3. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to claim 1, characterized in that, The cloud management platform includes a data access module, a driving behavior analysis module, an accident record module, a trajectory query module, and an alarm query module. The driving behavior analysis module is used to calculate driving behavior characteristic indicators based on the vehicle operation data and output the risk level; The data access module is configured to support the access of insurance company data collectors, and extracts vehicle TBOX data, automatic emergency braking module and driver monitoring module video data through reserved interfaces to achieve multi-source data fusion.

4. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to any one of claims 1 to 3, characterized in that, The system is configured sequentially according to the implementation phases as follows: The first phase is the economic version, the second phase is the upgraded version, and the third phase is the full-featured version; Each stage is equipped with basic AEB+DMS monitoring, intelligent navigation and cargo management, short-term automatic takeover and third-party ecosystem connectivity functions; The second phase adds a cargo hold management module that includes a cargo hold camera, radar, and temperature and humidity sensors to monitor cargo hold environmental parameters and cargo status. The short-term automatic takeover module configured in the third stage is used to autonomously decelerate or brake the vehicle to a stop in dangerous situations.

5. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to any one of claims 1 to 3, characterized in that, The cloud management platform's dynamic insurance pricing model is based on driving behavior scores, accident records, and runtime parameters to dynamically adjust premiums.

6. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to any one of claims 1 to 5, characterized in that, The calculation of the driving behavior score includes the identification of at least one of the following driving behaviors: rear-end collision risk behavior, blind spot reversing behavior, fatigued driving behavior, dangerous driving behavior, or aggressive driving behavior.

7. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to any one of claims 1 to 5, characterized in that, The system supports two operating modes: one where the insurance company has not intervened and the other where it has. In non-intervention mode, vehicle alarm data is transmitted from the cloud to the vehicle manufacturer's after-sales department for investigation; In the intervened mode, vehicle alarm data and insurance claim data are analyzed together and fed back to the vehicle manufacturer and insurance company. The vehicle manufacturer prepares spare parts in advance based on the accident attribution report and notifies the vehicle owner or operator to arrange for the vehicle to be brought in for repair, thus achieving a rapid response.

8. The new energy commercial vehicle insurance cost reduction and operation and maintenance management system according to any one of claims 1 to 5, characterized in that, The insurance data interaction unit is used to receive accident data from insurance companies, compare and analyze the accident data with vehicle operation data, and generate an accident attribution report. The accident attribution report is transmitted to the vehicle manufacturer's after-sales service module via a cloud management platform for vehicle maintenance scheduling and parts preparation. The operation and maintenance management unit includes a data screening module, a problem investigation module, and a driving behavior optimization module; it is used to dynamically adjust and hierarchically manage driving behavior based on cloud feedback data.

9. A method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles based on the system described in any one of 1 to 8, characterized in that, Includes the following steps: 1) The vehicle terminal unit collects vehicle operation data and driver status data; 2) Uploaded to the cloud management platform via the communication transmission unit; 3) The cloud management platform integrates and analyzes the data to generate driving behavior scores and accident reports; 4) Update the dynamic insurance pricing model based on driving behavior scores; 5) Feedback the analysis results to vehicle manufacturers and insurance companies for vehicle operation and maintenance scheduling and risk intervention.

10. The method for reducing insurance costs and managing operation and maintenance of new energy commercial vehicles according to claim 9, characterized in that, The fusion analysis in step 3) includes joint analysis of vehicle AEB trigger records, DMS detection results and positioning data to identify driving behavior characteristics; The feedback in step 5) includes pushing accident reports and driving behavior reports to the driver's terminal and classifying and managing driver behavior.

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