An electronic fence-based vehicle dynamic scheduling and compliance monitoring system and method

Abstract

This invention relates to the field of vehicle monitoring and dispatching technology, and particularly to a vehicle dynamic dispatching and compliance monitoring system and method based on electronic fences. The system includes a dynamic dispatching information access module, a dynamic electronic fence engine, a judgment and early warning module, a visualization output terminal, and a data storage and learning module. Its core function is to dynamically generate temporary task electronic fences with lifecycles and reasonable path authorizations for controlled vehicles by acquiring dispatching information in real time, forming a multi-layered fence logic with basic static fences. The judgment and early warning module performs contextual analysis based on the vehicle's real-time location and dispatching context, effectively distinguishing between reasonable boundary crossings and violations, thereby significantly reducing the false alarm rate. Simultaneously, the system continuously optimizes fence parameters and rules through learning. This invention solves the problems of poor applicability and high false alarm rate of fixed electronic fences in dynamic dispatching scenarios, achieving a balance between regulatory rigidity and business flexibility, and improving the intelligence and accuracy of vehicle monitoring.

Description

Technical Field

[0001] This invention relates to the field of vehicle dispatch and monitoring technology, and more specifically, to a vehicle dynamic dispatch and compliance monitoring system and method based on electronic fences. Background Technology

[0002] Electronic fence technology has become a core tool for modern business travel vehicle management and compliance monitoring. This system typically uses pre-defined static boundaries based on geographic information. When a vehicle triggers the fence boundary via its onboard positioning device, the system automatically records the status and issues an early warning. Currently, this type of system is widely used in logistics, corporate fleets, and business travel, aiming to regulate driving areas, prevent operational risks, and improve management efficiency. The static preset mode of electronic fences offers good controllability and operability in typical fixed-route scenarios.

[0003] However, in real-world business travel scenarios, route adjustments due to unforeseen changes in customer plans, sudden business negotiations, or traffic conditions are extremely common, requiring vehicles to dynamically respond to these changes. Because existing geofencing systems are mostly statically preset and their updated boundaries cannot match the actual task requirements of vehicles in real time, vehicles temporarily crossing boundaries for legitimate business reasons are uniformly judged as violations by the system. This misjudgment triggers numerous invalid warnings, not only interfering with the accuracy of the system's judgment but also forcing fleet managers to invest significant time in manual verification and interpretation, significantly increasing operational costs and reducing the efficiency of monitoring genuine violations. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that legitimate boundary crossings caused by temporary route adjustments are misjudged. In view of the above-mentioned defects of the prior art, a vehicle dynamic scheduling and compliance monitoring system and method based on electronic fence is provided.

[0005] The technical solution adopted by this invention to solve its technical problem is: on the one hand A vehicle dynamic dispatching and compliance monitoring system based on electronic fences includes: The dynamic scheduling information access module is used to obtain real-time scheduling information change data of the target vehicle. The scheduling information change data includes at least order status and target coordinate information. The dynamic electronic fence engine receives scheduling information change data output by the dynamic scheduling information access module and dynamically generates, adjusts, or binds temporary task electronic fences for controlled vehicles. The temporary task electronic fence has a preset lifecycle, i.e., monitoring rules. The judgment and warning module receives real-time location information data of the controlled vehicle and the effective fence set output by the dynamic electronic fence engine, and performs compliance judgment in combination with the scheduling context. The dynamic electronic fence engine constructs a multi-layer fence logic of basic static fence and temporary task electronic fence. The judgment and warning module distinguishes between reasonable boundary crossing and illegal behavior based on the judgment logic of whether the vehicle is within the authorized temporary task fence association range. A visualization output terminal, connected to the judgment and early warning module, is used to visually display static fences, temporary task electronic fences, and vehicle compliance status.

[0006] Preferably, the scheduling information change data that the dynamic scheduling information access module can identify includes at least one of the following: new order, order destination change, order cancellation, dispatched, started, ended status identifier, and estimated arrival time.

[0007] Preferably, the temporary task electronic fence is generated according to the following rules: it is automatically generated around the target coordinates in the scheduling information change data according to a preset radius or geographical range parameter; the life cycle of the temporary task electronic fence includes an activation period and an expiration period. The activation period is the time period from when the driver confirms the order to when the order status is updated to "arrived" or "completed". The expiration period is automatically triggered after a preset buffer time after the order is completed.

[0008] Preferably, the multi-layer fence logic of the dynamic electronic fence engine includes priority rules: a reasonable path associated with a temporary task fence can temporarily break through the prohibited area restrictions in the basic static fence, and the reasonable path is determined by a route planning algorithm.

[0009] Preferably, the determination logic of the determination and warning module includes: When a vehicle is near the temporary task fence or on the associated path, even if it exceeds the basic static fence, only a status prompt will be output and no violation warning will be triggered. A violation warning is triggered when a vehicle leaves all valid temporary task fences and enters an unauthorized area, or fails to return to the authorized area within the specified time after the task is completed. The violation warning is divided into three levels: information prompt, minor attention, and serious violation. The status prompt includes the identification information "heading to a temporary task point".

[0010] Preferably, it also includes a data storage and learning module, which is used to store historical scheduling data, vehicle trajectory data and early warning records, and to optimize the generation parameters of temporary task electronic fences through machine learning, or to automatically generate frequently occurring temporary fence templates.

[0011] on the other hand A method for dynamic vehicle scheduling and compliance monitoring based on electronic fences, implemented through any of the systems described above, includes the following steps: S1. Monitor the interface or message queue of the scheduling system in real time and capture scheduling change events containing target coordinates and order status; S2. Based on the scheduling change information data, generate a temporary task electronic fence with a preset range and life cycle for the corresponding controlled vehicle. The temporary task electronic fence and the basic static fence form a multi-layer fence structure. S3. Receive real-time vehicle location information data and perform compliance assessment based on the multi-layer fence structure and scheduling context: If the vehicle is near a temporary task fence or on an associated path, output a status prompt; if the vehicle leaves the valid temporary task fence and enters an unauthorized area, trigger a violation warning. S4. Display the basic static fence, temporary task electronic fence, vehicle status and early warning information through a visual output terminal. The early warning information is associated with the dispatch order number. S5. After the order status is updated to "completed", after a preset buffer time, the corresponding temporary task electronic fence is set to invalid state, and the monitoring rules of the basic static fence are restored.

[0012] Preferably, in step S2, the generation parameters of the temporary task electronic fence include the radius range around the target coordinates and the activation duration, and these parameters can be automatically configured through rules trained from historical data; the steps for generating the temporary task electronic fence include: S21. Parse the scheduling information change data and extract the changed destination coordinates or waypoint coordinates; S22. Using the destination coordinates or waypoint coordinates as the center, generate a temporary geographical area as the temporary task electronic fence according to preset rules; S23. Set the status of the temporary task electronic fence to active, and bind the lifecycle of the temporary task electronic fence to the status of the currently scheduled task.

[0013] Preferably, in S3, the compliance assessment further includes route deviation judgment: when the vehicle deviates from the reasonable path of the temporary task fence to a preset threshold, a route anomaly warning is triggered, and the reasonable path is generated by a route planning algorithm.

[0014] Preferably, the method also includes step S6: storing historical scheduling data, vehicle trajectory data and early warning records, analyzing reasonable boundary crossing patterns through machine learning, and optimizing the generation rules and compliance assessment thresholds for temporary task electronic fences.

[0015] The beneficial effects of this invention are as follows: 1. Traditional static electronic fence systems, when handling dynamic scheduling tasks, generate numerous false alarms due to their inability to distinguish between legitimate boundary crossings and violations, leading to alarm fatigue in the monitoring center and the overwhelming of valuable information. This application introduces a dynamic electronic fence engine and multi-layered fence priority logic to generate an authorized area and a legitimate path with a lifecycle for each temporary scheduling task. The judgment and early warning module analyzes the situation in conjunction with the real-time scheduling context. When a vehicle enters a static restricted area to perform an authorized task, the system only provides a status notification without triggering a violation alarm. This represents a leap from mechanical geographic comparison to contextualized intelligent judgment, significantly reducing false alarms caused by legitimate business behavior, allowing managers to focus on genuine violations, thereby improving the reliability and availability of the monitoring system.

[0016] 2. By dynamically binding and automatically deactivating temporary task geofences, the system provides flexibility for necessary temporary business operations while ensuring adequate oversight. The system automatically creates temporary authorizations for compliant tasks, eliminating the cumbersome process of drivers manually applying for exemptions or administrators manually adjusting rules before each temporary task, thus ensuring smooth task execution. Simultaneously, the preset buffer time accommodates reasonable operating time after the task ends, avoiding operational pressure from mechanical, immediate judgments. This ensures that safety oversight is no longer an obstacle to smooth business operations, but rather a guarantee for its efficient and compliant operation.

[0017] 3. The introduction of data storage and learning modules endows the system with self-optimization capabilities. The system continuously accumulates historical data such as vehicle trajectories, task completion status, and warning records, and analyzes this data using machine learning techniques. For example, it automatically learns the actual location distribution of vehicles arriving at their destinations in different scenarios (such as specific business districts or peak traffic hours), thereby optimizing the recommended radius of temporary fences; or it analyzes frequently occurring task patterns to automatically generate fence templates. This allows the system's monitoring rules to continuously iterate and become more realistic as actual operational data accumulates, reducing manual maintenance and configuration costs and achieving intelligent evolution from static configuration to dynamic growth.

[0018] 4. A visual output terminal deeply integrates and graphically displays complex multi-layered fence logic, real-time vehicle status, early warning information, and dispatch orders. Administrators can not only visually see where early warnings occur on a map, but also understand why an early warning occurred (the associated specific orders and tasks) through reverse lookup of early warning information and dispatch order numbers. This status-visible and root-cause-traceable design transforms isolated event alerts into a management view with a complete business context, greatly improving the transparency of supervision and the efficiency of handling. Simultaneously, the accumulated full historical data provides a solid data foundation for analyzing operational bottlenecks, assessing regional risks, and optimizing dispatch strategies, assisting managers in making informed decisions.

[0019] 5. The system employs a clear functional module division (information access, rule engine, analysis, display, and learning), with each module collaborating through standardized data interfaces. This modular design ensures excellent scalability and maintainability. For example, the dynamic scheduling information access module can adapt to the APIs or message protocols of different scheduling systems; the dynamic electronic fence engine supports access to different map services and path planning algorithms; and the rule base of the judgment and early warning module allows for easy addition, deletion, or adjustment of judgment logic. This flexibility ensures the system can quickly respond to future business changes or technological upgrades, reducing long-term evolution costs and guaranteeing the sustainability of technology investments. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort: Figure 1 This is a schematic diagram of the vehicle dynamic scheduling and compliance monitoring system based on electronic fences, as described in this application.

[0021] Figure 2 This is a flowchart illustrating the implementation method of the vehicle dynamic scheduling and compliance monitoring system based on electronic fences according to an embodiment of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, a clear and complete description will be provided below in conjunction with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0023] Preferred embodiments of the present invention, for example Figure 1 As shown, a vehicle dynamic dispatching and compliance monitoring system based on electronic fences includes a dynamic dispatching information access module, a dynamic electronic fence engine, a judgment and early warning module, a visualization output terminal, and a data storage and learning module. These modules communicate and collaborate through an internal system data bus.

[0024] The dynamic dispatch information access module is used to acquire and standardize dispatch information change data of target vehicles from external dispatch systems in real time. As an optional embodiment, the access method of the dynamic dispatch information access module may include real-time polling by calling the application programming interface provided by the external dispatch system, or subscribing to specific topic messages published by the external dispatch system to message middleware (such as Kafka, RabbitMQ). The processing flow of dispatch information change data can be set up so that after receiving the raw data (usually in JSON or XML format), the built-in parser extracts key fields and converts them into a unified standardized data model within the system. The standardized data model of the dispatch information change data includes at least: Vehicle Unique Identifier (VID), Dispatch Order Number (OrderID), Event Timestamp, Change Type, and Target Geographic Coordinates (Latitude and Longitude). Specifically, the change type can be identified as at least one of the following status indicators: New Order, Order Destination Change, Order Cancellation, Dispatched, Started, Arrived, and Finished. The standardized dispatch information change data is then pushed to the dynamic electronic fence engine in real time.

[0025] The dynamic electronic fence engine receives scheduling information change data from the dynamic scheduling information access module and dynamically generates, adjusts, or binds temporary task electronic fences for controlled vehicles. These temporary task electronic fences have preset lifecycles, i.e., monitoring rules. The generation rules for temporary task electronic fences are: automatically generated around the target coordinates in the scheduling information change data, according to preset radius or geographical range parameters.

[0026] As an optional embodiment, the temporary task electronic fence can be generated by creating a circular fence with the target point as the center and a preset radius. The preset radius is a configurable parameter, typically ranging from 50 meters to 5000 meters. For example, it can be configured to 500 meters for urban delivery and 2000 meters for intercity transportation. Alternatively, for fixed locations (such as logistics parks or large customer factory areas), a predefined geographic polygon can be associated as a temporary fence. The lifecycle of the temporary task electronic fence includes an activation period and an expiration period. The activation period is the time from when the driver confirms the order until the order status is updated to "arrived" or "completed." The expiration period is automatically triggered after a preset buffer time following the completion of the order.

[0027] The multi-layered fence logic of the dynamic electronic fence engine includes priority rules: a reasonable path associated with a temporary task fence can temporarily bypass the prohibited area restrictions in the basic static fence. The reasonable path is determined by a route planning algorithm. The basic static fence is used to define permanent authorized or prohibited areas. When both a basic static prohibited fence and an active temporary task electronic fence exist for the same vehicle, the temporary task fence has a higher priority. When a temporary task fence is activated, the engine calculates a reasonable driving path from the vehicle's previous authorized location or current location to the center of the temporary fence based on the current road network information and using a route planning algorithm (such as Dijkstra's algorithm or A* algorithm). The path corridor formed by extending a certain width (such as 50 meters) on both sides of this path as the center line is considered the authorized passage area for performing the temporary task.

[0028] As an optional implementation, the activation period begins when the order status changes to "dispatched" or "started" and ends when the order status is updated to "arrived" or "completed." During this period, the fence remains active and participates in compliance assessment. The expiration period is after the order is "completed." The fence is not immediately deleted but enters a preset buffer period (which can be set to 10-120 minutes, for example, 30 minutes). The buffer period is used to accommodate reasonable activities after the task is completed (such as the vehicle finding a parking space after unloading, or the driver taking a break). The fence automatically expires at the end of the buffer period.

[0029] The judgment and warning module receives real-time location information of controlled vehicles and the valid fence set output by the dynamic electronic fence engine, and performs compliance assessment in conjunction with the scheduling context. The dynamic electronic fence engine constructs a multi-layered fence logic consisting of basic static fences and temporary task electronic fences. The judgment and warning module distinguishes between legitimate boundary crossings and violations based on its judgment logic regarding whether the vehicle is within the authorized temporary task fence association range. The judgment logic of the judgment and warning module includes: When a vehicle is near a temporary task fence or on an associated path, or within a reasonable path corridor associated with it, even if it is outside the basic static fence, only a status message is output without triggering a violation warning; for example, "Vehicle [VID] is en route to the destination of Order [OrderID]", without triggering a violation warning.

[0030] A violation warning is triggered when a vehicle leaves all valid temporary task fences and enters an unauthorized area, or fails to return to the authorized area within the specified time after the task is completed.

[0031] Violation warnings are categorized into three levels: Informational Alert, Minor Concern, and Serious Violation. Status alerts include the indicator "Heading to a temporary task point." Informational alerts are only used to record compliance status; Minor Concern applies to situations such as route deviation or failure to return as the buffer period nears its end; Serious Violation applies to situations such as explicitly entering unauthorized areas.

[0032] The visualization output terminal connects to the judgment and early warning module to visually display static fences, temporary task electronic fences, and vehicle compliance status. The visualization output terminal uses different colors or styles to distinguish between static fences and temporary task electronic fences. Early warning information is automatically associated with the dispatch order number, and it supports reverse querying of corresponding dispatch change data through early warning information. As an optional embodiment, an electronic map API (such as Baidu Maps or Gaode Maps) can be used for graphical display. Solid red boundaries represent basic static prohibition fences; dashed blue boundaries represent active temporary task electronic fences, and mouse hover can display associated order details; green lines highlight the reasonable path calculated for temporary tasks; vehicle icon colors dynamically reflect their status: green represents compliance, yellow represents a minor warning, and red represents a serious violation. All early warning information is automatically associated with the dispatch order number. Users can click on early warning information to reverse query detailed dispatch change data, vehicle trajectory, and fence information that triggered the warning.

[0033] The data storage and learning module stores historical scheduling data, vehicle trajectory data, and early warning records. It optimizes the generation parameters of temporary task geofences through machine learning, or automatically generates frequently occurring temporary geofence templates. The database stores historical scheduling data, high-precision vehicle trajectory data, all geofence generation and failure logs, and complete early warning records. It analyzes data from historical successful tasks, using clustering algorithms to analyze the distribution of actual vehicle stops, common routes, and time consumption, automatically optimizing the recommended radius and buffer time parameters for temporary geofences in different areas and for different business types. For temporary tasks with frequently occurring target coordinates, the system can automatically analyze and generate frequently occurring temporary geofence templates, including suggested range and lifecycle parameters. After administrator confirmation, these templates can be stored in the template library for quick use in subsequent similar tasks.

[0034] on the other hand A method for dynamic vehicle scheduling and compliance monitoring based on electronic fences, for implementation using any of the systems described in Example 1; refer to Figure 2 This includes the following steps: S1. Monitor the interface or message queue of the scheduling system in real time, capture scheduling change events containing target coordinates and order status, and parse and standardize the event data.

[0035] S2. Based on the scheduling change information data, generate a temporary task electronic fence with a preset range and lifespan for the corresponding controlled vehicle. The temporary task electronic fence forms a multi-layered fence structure with the basic static fence. The generation parameters of the temporary task electronic fence include the radius range around the target coordinates and the activation duration. The parameters can be automatically configured through rules trained from historical data. The steps for generating the temporary task electronic fence include: S21. Parse the standardized scheduling information change data, determine the event type, and extract the changed destination coordinates or key waypoint coordinates; S22. Using the destination coordinates or key waypoint coordinates as the center, generate a temporary geographic area as a temporary task electronic fence according to preset rules (i.e., system-configured parameters or recommended parameters obtained from the data storage and learning module). S23. Set the temporary task electronic fence to active and bind the lifecycle of the temporary task electronic fence to the status of the current scheduled task, that is, bind the "dispatched" status to activate the fence and bind the "completed" status to start the buffer countdown.

[0036] S24. Based on the real-time road network, calculate a reasonable path from the vehicle's current location to the temporary fence for this task, and generate a path corridor.

[0037] S3. Receive real-time vehicle location information data and perform compliance assessment based on the multi-layer fence structure and scheduling context: If the vehicle is near the temporary task fence or on the associated reasonable path corridor, output a status prompt; if the vehicle deviates from the reasonable path of the temporary task fence to a preset threshold, trigger a route anomaly warning, and the reasonable path is generated by the route planning algorithm; if the vehicle leaves the effective temporary task fence and enters an unauthorized area, or fails to return to the authorized area within the buffer period after the task ends, trigger a violation warning.

[0038] S4. Display basic static fences, temporary task electronic fences, vehicle status and warning information through the map interface of the visual output terminal, ensuring that the warning information is strongly associated with the dispatch order number, and supporting interactive reverse query of details from the interface.

[0039] S5. When the order status is updated to "completed", after a preset buffer time, the corresponding temporary task electronic fence is set to invalid and removed from the valid fence set of the authorized vehicle, and the monitoring rules of the basic static fence are restored.

[0040] S6 continuously stores historical scheduling data, vehicle trajectory data, and early warning records. It uses machine learning to analyze reasonable boundary crossing patterns and optimizes the generation rules and compliance assessment thresholds for temporary task electronic fences.

[0041] The implementation principle of a vehicle dynamic scheduling and compliance monitoring method based on electronic fences in this application is as follows: A dynamic scheduling information access module captures and standardizes order change data (including vehicle identification, target coordinates, status, and other core information) from an external scheduling system in real time. The dynamic electronic fence engine dynamically generates or adjusts temporary task electronic fences bound to the scheduling task based on the scheduling change information data. Simultaneously, it constructs a multi-layered priority fence logic (temporary task fences and associated path corridors have higher priority than basic static prohibition fences) by combining predefined basic static fences. A lifecycle is configured for the temporary fence, including an activation period (order execution phase) and a buffer expiration period (reasonable activity phase after task completion). The judgment and early warning module receives vehicle... Vehicle location data and valid fence sets are combined with scheduling context to conduct compliance assessments, distinguishing between legitimate boundary crossings and violations such as deviating from tasks or entering unauthorized areas during task execution, and outputting prompts or warnings according to the level; the visualization output terminal presents fence, vehicle status and warning information in a differentiated display mode, supporting two-way query and traceability; the data storage and learning module continuously accumulates historical data, optimizes fence generation parameters and generates commonly used fence templates through machine learning, forming a closed-loop optimization; the entire process is automated through inter-module data bus collaboration, realizing full-process automation from scheduling information access, dynamic fence construction, compliance judgment, visualization display to data optimization, ensuring both the flexibility of vehicle scheduling and the accuracy of operational compliance monitoring.

[0042] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A vehicle dynamic dispatching and compliance monitoring system based on electronic fences, characterized in that, include: The dynamic scheduling information access module is used to obtain real-time scheduling information change data of the target vehicle. The scheduling information change data includes at least order status and target coordinate information. The dynamic electronic fence engine receives scheduling information change data output by the dynamic scheduling information access module and dynamically generates, adjusts, or binds temporary task electronic fences for controlled vehicles. The temporary task electronic fence has a preset lifecycle, i.e., monitoring rules. The judgment and warning module receives real-time location information data of the controlled vehicle and the effective fence set output by the dynamic electronic fence engine, and performs compliance judgment in combination with the scheduling context. The dynamic electronic fence engine constructs a multi-layered fence logic of basic static fence and temporary task electronic fence. The judgment and warning module distinguishes between reasonable boundary crossing and illegal behavior based on the judgment logic of whether the vehicle is within the authorized temporary task fence association range. A visualization output terminal, connected to the judgment and early warning module, is used to visually display static fences, temporary task electronic fences, and vehicle compliance status.

2. The vehicle dynamic dispatching and compliance monitoring system based on electronic fence according to claim 1, characterized in that, The dynamic scheduling information access module can identify at least one of the following scheduling information change data: new order, order destination change, order cancellation, dispatched, started, ended status, and estimated arrival time.

3. The vehicle dynamic dispatching and compliance monitoring system based on electronic fence according to claim 1, characterized in that, The temporary task electronic fence is generated according to the following rules: it is automatically generated around the target coordinates in the scheduling information change data according to the preset radius or geographical range parameters; the life cycle of the temporary task electronic fence includes an activation period and an expiration period. The activation period is the time period from when the driver confirms the order to when the order status is updated to "arrived" or "completed". The expiration period is automatically triggered after a preset buffer time after the order is completed.

4. The vehicle dynamic dispatching and compliance monitoring system based on electronic fence according to claim 1, characterized in that, The multi-layered fence logic of the dynamic electronic fence engine includes priority rules: a reasonable path associated with a temporary task fence can temporarily break through the restricted area restrictions in the basic static fence, and the reasonable path is determined by a route planning algorithm.

5. A dynamic vehicle dispatching and compliance monitoring system based on electronic fences according to claim 1, characterized in that, The determination logic of the determination and early warning module includes: When a vehicle is near the temporary task fence or on the associated path, even if it exceeds the basic static fence, only a status prompt will be output and no violation warning will be triggered. A violation warning is triggered when a vehicle leaves all valid temporary task fences and enters an unauthorized area, or fails to return to the authorized area within the specified time after the task is completed. The violation warning is divided into three levels: information prompt, minor attention, and serious violation. The status prompt includes the identification information "heading to a temporary task point".

6. A dynamic vehicle dispatching and compliance monitoring system based on electronic fences according to claim 1, characterized in that, It also includes a data storage and learning module, which is used to store historical scheduling data, vehicle trajectory data and early warning records, and to optimize the generation parameters of temporary task electronic fences through machine learning, or to automatically generate frequently occurring temporary fence templates.

7. A method for dynamic vehicle scheduling and compliance monitoring based on electronic fences, characterized in that, For implementation via the system as described in any one of claims 1-6, the following steps are included: S1. Monitor the interface or message queue of the scheduling system in real time and capture scheduling change events containing target coordinates and order status; S2. Based on the scheduling change information data, generate a temporary task electronic fence with a preset range and life cycle for the corresponding controlled vehicle. The temporary task electronic fence and the basic static fence form a multi-layer fence structure. S3. Receive real-time vehicle location information data and perform compliance assessment based on the multi-layer fence structure and scheduling context: If the vehicle is near a temporary task fence or on an associated path, output a status prompt; if the vehicle leaves the valid temporary task fence and enters an unauthorized area, trigger a violation warning. S4. Display the basic static fence, temporary task electronic fence, vehicle status and early warning information through a visual output terminal. The early warning information is associated with the dispatch order number. S5. When the order status is updated to "completed", after a preset buffer time, the corresponding temporary task electronic fence is set to invalid state, and the monitoring rules of the basic static fence are restored.

8. A method for dynamic vehicle scheduling and compliance monitoring based on electronic fences according to claim 7, characterized in that, In S2, the generation parameters of the temporary task electronic fence include the radius range around the target coordinates and the activation duration. These parameters can be automatically configured through rules trained from historical data. The steps for generating the temporary task electronic fence include: S21. Parse the scheduling information change data and extract the changed destination coordinates or waypoint coordinates; S22. Using the destination coordinates or waypoint coordinates as the center, generate a temporary geographical area as the temporary task electronic fence according to preset rules; S23. Set the status of the temporary task electronic fence to active, and bind the lifecycle of the temporary task electronic fence to the status of the currently scheduled task.

9. As described in claim 7, characterized in that, In S3, the compliance assessment also includes route deviation judgment: when the vehicle deviates from the reasonable path of the temporary task fence to a preset threshold, a route abnormality warning is triggered, and the reasonable path is generated by a route planning algorithm.

10. As described in claim 7, characterized in that, It also includes step S6: storing historical scheduling data, vehicle trajectory data and early warning records, and using machine learning to analyze reasonable boundary crossing patterns to optimize the generation rules and compliance assessment thresholds for temporary task electronic fences.

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