Intelligent order dispatching methods, systems, computer equipment, and storage media

Abstract

This application belongs to the field of vehicle rescue technology and relates to an intelligent dispatching method, system, computer equipment, and storage medium, including: screening all drivers based on the new service type and new service location of the new order to obtain multiple candidate drivers, including a first candidate driver and a second candidate driver; determining a first target mileage value required to execute the new order based on the first candidate driver's first current location, new service type, and new service location; determining a second target mileage value required to execute the new order based on the second candidate driver's second current location, current service type, current service location, new service type, and new service location; sorting the multiple candidate drivers according to the first and second target mileage values ​​to obtain a dispatching priority list; and assigning the new order to the highest priority candidate driver in the dispatching priority list within a preset time period, thereby improving the accuracy of dispatching strategies in the roadside assistance industry.

Description

Technical Field

[0001] This application relates to the field of vehicle rescue technology, and in particular to an intelligent dispatching method, system, computer equipment, and storage medium. Background Technology

[0002] With the rapid expansion of the roadside assistance industry, rescue services have covered diverse scenarios such as vehicle relocation, towing, vehicle registration, and jump-starting. The service cycles and route planning of different services vary significantly, and the demand for order dispatch accuracy and capacity matching efficiency is increasing day by day.

[0003] Current dispatching technologies in the industry are mostly based on a single dimension to formulate strategies. Common criteria include the straight-line distance between the driver and the order's origin, the driver's historical order volume, etc. By simply sorting and generating a dispatch list, they can only achieve basic order allocation and meet basic needs in scenarios with simple business types and small order volumes.

[0004] However, existing dispatching technology fails to fully integrate with drivers' actual business situations, leading to unreasonable capacity allocation. For example, drivers whose business types are suitable may be idle because they are not prioritized. At the same time, issues such as high dispatch conflict rates and order response delays occur frequently, making it difficult to adapt to the complex needs of diversified businesses. In fact, insufficient accuracy of dispatching strategies has become a bottleneck restricting the improvement of service efficiency and quality in the industry.

[0005] In view of the above, this application is hereby submitted. Summary of the Invention

[0006] The purpose of this application is to propose an intelligent dispatching method, system, computer equipment, and storage medium to solve the technical problem of insufficient accuracy of dispatching strategies in the roadside assistance industry.

[0007] To address the aforementioned technical problems, this application provides an intelligent order dispatch method, employing the following technical solution: In response to a new order dispatch instruction, the new service type and new service location of the new order are obtained according to the dispatch instruction; Based on the new service type and the new service location, all drivers are screened to obtain multiple candidate drivers who can receive the new orders. The candidate drivers include multiple first candidate drivers who are idle and multiple second candidate drivers who are in service. Obtain the first current location of each first candidate driver, and determine the first target mileage value required for each first candidate driver to execute the new order based on the first current location, the new service type, and the new service location; Obtain the second current location of each second candidate driver, the current service type of the current order, and the current service location. Based on the second current location, the current service type, the current service location, the new service type, and the new service location, determine the second target mileage value required for each second candidate driver to execute the new order. Based on multiple first target mileage values ​​and multiple second target mileage values, multiple candidate drivers are sorted to obtain a dispatch priority list; The new order is assigned to the highest priority candidate driver in the dispatch priority list within a preset time period.

[0008] Furthermore, determining the first target mileage value required for each of the first candidate drivers to execute the new order based on the first current location, the new service type, and the new service location includes: Obtain the urgency weight of the new service type; The arrival mileage is determined based on the first current location and the new service location; The arrival mileage value and the urgency weight are fused to obtain the first target mileage value.

[0009] Furthermore, determining the second target mileage value required for each of the second candidate drivers to execute the new order based on the second current location, the current service type, the current service location, the new service type, and the new service location includes: The current mileage value is determined based on the second current location and the current service location; Determine the standard operation time for the current order based on the current service type; The operation mileage value is determined based on the preset basic mapping coefficient and the standard operation duration; The second target mileage value is determined based on the current mileage value, the operational mileage value, the new service type, and the new service location.

[0010] Furthermore, determining the second target mileage value based on the current mileage value, the operational mileage value, the new service type, and the new service location includes: The new service mileage value is determined based on the current service location and the new service location; Obtain the urgency weight of the new service type; The current mileage value, the operational mileage value, the new service mileage value, and the urgency weight are combined to obtain the second target mileage value.

[0011] Furthermore, determining the operation mileage value based on the preset basic mapping coefficient and the standard operation duration includes: Obtain the work progress of the second candidate driver in executing the current order, convert the work progress, and obtain the progress correction coefficient; The target working time is determined based on the work progress and the standard work duration. Obtain the environmental correction coefficient, and determine the target mapping coefficient based on the schedule correction coefficient, the environmental correction coefficient, and the basic mapping coefficient; The target operation duration is mapped according to the target mapping coefficient to obtain the operation mileage value.

[0012] Furthermore, based on the new service type and the new service location, all drivers are screened to obtain multiple candidate drivers who can receive the new orders, including: Based on the new service locations, candidate areas are determined; Obtain the location information of all the drivers, and filter all the drivers based on the location information and the candidate regions to obtain initial candidate drivers; Based on the new service type, the initial candidate drivers are screened to obtain the candidate drivers.

[0013] Furthermore, after assigning the new order to the highest-priority candidate driver in the dispatch priority list within the preset time period, the method further includes: Obtain the number of responses from the highest priority candidate driver to the new order; Based on the number of responses and the number of candidate drivers in the dispatch priority list, it is determined whether the new order has been successfully dispatched. If the new order is successfully dispatched, a dispatch success instruction will be sent to the management platform. If the new order fails to be dispatched, the new order is marked as an overdue order and the overdue order is sent to the management platform.

[0014] To address the aforementioned technical problems, this application also provides an intelligent order dispatch system, which employs the following technical solution: An intelligent order dispatching system includes: The response module is used to respond to the dispatch instruction of a new order and, based on the dispatch instruction, obtain the new service type and new service location of the new order; The filtering module is used to filter all drivers according to the new service type and the new service location to obtain multiple candidate drivers who can receive the new order. The candidate drivers include multiple first candidate drivers who are in an idle state and multiple second candidate drivers who are in a service state. The first determining module is used to obtain the first current location of each first candidate driver, and determine the first target mileage value required for each first candidate driver to execute the new order based on the first current location, the new service type and the new service location; The second determining module is used to obtain the second current location of each second candidate driver and the current service type and current service location of the current order, and to determine the second target mileage value required for each second candidate driver to execute the new order based on the second current location, the current service type, the current service location, the new service type and the new service location; The sorting module is used to sort the multiple candidate drivers according to multiple first target mileage values ​​and multiple second target mileage values ​​to obtain a dispatch priority list; The allocation module is used to allocate the new order to the highest priority candidate driver in the dispatch priority list within a preset time period.

[0015] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution: A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the intelligent dispatching method as described above.

[0016] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below: A computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of the intelligent dispatching method as described above.

[0017] Compared with the prior art, this application has the following main advantages: The intelligent dispatching method disclosed in this application obtains new service locations and service types by responding to dispatching instructions for new orders, and filters out candidate drivers with both available and service statuses, expanding the selection range of drivers who can accept orders and avoiding the waste of capacity caused by limiting oneself to only available drivers. Obtaining the current location of available drivers and determining their first target mileage value for executing new orders directly reflects the distance cost for these drivers to accept new orders, making dispatching more aligned with actual trip needs. Combining the current location and current orders of drivers with service status to determine a second target mileage value fully considers the work progress and subsequent connection possibilities of these drivers, avoiding overlooking potential capacity that is currently serving but can quickly respond to new orders. Ranking candidate drivers according to the two target mileage values ​​forms a dispatching priority list, ensuring a reasonable dispatching order and avoiding response chaos caused by disordered dispatching. Dispatching orders according to the priority list within a preset time period can quickly match the most suitable driver, reduce order waiting time, improve overall service efficiency, and effectively balance the workload of various drivers, making capacity allocation more reasonable and fundamentally improving the accuracy of dispatching strategies in the roadside assistance industry. Attached Figure Description

[0018] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is an exemplary system architecture diagram to which this application can be applied; Figure 2 This is a flowchart of one embodiment of the intelligent order dispatching method according to this application; Figure 3 This is a structural schematic diagram of an embodiment of the intelligent order dispatch system according to this application; Figure 4 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0023] like Figure 1 As shown, the system architecture 100 may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0024] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0025] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, e-book readers, MP3 (Moving Picture Experts Group Audio Layer Ⅲ) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptops, and desktop computers, etc.

[0026] Server 105 can be a server that provides various services, such as a backend server that supports the pages displayed on the first terminal device 101, the second terminal device 102, and the third terminal device 103.

[0027] It should be noted that the intelligent order dispatching method provided in this application embodiment is generally executed by the server, and correspondingly, the intelligent order dispatching system is generally set up in the server.

[0028] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0029] Continue to refer to Figure 2 A flowchart of an embodiment of the intelligent order dispatching method according to this application is shown. The intelligent order dispatching method includes the following steps: Step S201: In response to the dispatch instruction for the new order, obtain the new service type and new service location of the new order according to the dispatch instruction.

[0030] In this embodiment, the intelligent order dispatch method runs on electronic devices (e.g., Figure 1 The server shown can send or receive data via wired or wireless connections. It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, Wi-Fi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra-wide band) connections, and other currently known or future-developed wireless connection methods.

[0031] In this embodiment, the dispatch instruction is automatically generated after a user submits a new rescue order through the app, or it can be manually triggered by the platform dispatcher or administrator after viewing new or overdue orders in the background. The received dispatch instruction contains a complete order data packet, which undergoes format verification and integrity checks to exclude abnormal orders with missing data or incorrect formats, ensuring that subsequent processes can proceed normally. Subsequently, the new service type and new service location, as well as time-related information and other auxiliary information, are extracted from the valid order data packet. The new service type includes at least one of the following: vehicle relocation, towing, vehicle registration, jump-start, tire repair / change, and unlocking; the new service location includes the origin and destination based on the business content. For example, a vehicle relocation service requires staff to go to the origin to move the vehicle from the origin to the destination, while an unlocking service only requires staff to go to the destination; time-related information refers to the urgency level of the order, such as highway accidents being the highest priority and non-urgent vehicle relocation being the lowest priority; other auxiliary information includes the user's contact information and a brief description of the vehicle malfunction.

[0032] Step S202: Based on the new service type and the new service location, all drivers are screened to obtain multiple candidate drivers who can receive the new order. The candidate drivers include multiple first candidate drivers who are in an idle state and multiple second candidate drivers who are in a service state.

[0033] In this embodiment, "all drivers" refers to all compliant drivers within the platform, regardless of whether they are currently idle, in service, or in other temporary states. The first candidate driver in an idle state refers to a driver who is not currently performing any rescue missions and has not set any order-accepting restrictions; the second candidate driver in a service state refers to a driver who is currently performing a valid rescue mission but has been determined to have the reasonable ability to connect with new orders. Specifically, the real-time location and trajectory of drivers are obtained through GPS / BeiDou positioning technology, linked to order data (bound to order status and service type), driver operation records (order acceptance settings, job confirmation), and the reservation order database. The service progress is verified by matching key locations of old orders, while simultaneously confirming order acceptance status and the absence of reservations within one hour. Ultimately, the business status of all drivers can be determined.

[0034] Based on the new service type and location, all registered drivers on the platform are screened using the new order information to exclude drivers who are clearly unable to accept the new order. The screening process first identifies the driver's real-time operational status. Drivers currently not performing any rescue tasks and without any restrictions such as pausing orders or locking appointments are identified as the first-line candidate drivers, possessing the basic conditions to immediately accept new orders. Simultaneously, drivers currently performing vehicle relocation, towing, vehicle registration, or other rescue services, but whose work progress, current location, and remaining service load are monitored in real-time and determined to be able to take on the new order within a reasonable timeframe, are identified as the second-line candidate drivers in service status. Examples include drivers performing tire repair services with 80% completion and less than 10 minutes of service remaining, or drivers performing short-distance relocation services with routes reasonably connected to the new order's service location. The remaining service load refers to the total time, mileage, and environmental pressure incurred by drivers in service status for any unfinished tasks in their current rescue missions. Finally, through the above screening, a total of multiple candidate drivers who can accept the new order are obtained. This set of candidate drivers includes both the first candidate driver and the second candidate driver.

[0035] Step S203: Obtain the first current location of each first candidate driver, and determine the first target mileage value required for each first candidate driver to execute the new order based on the first current location, the new service type, and the new service location.

[0036] In this embodiment, the current location of each first candidate driver is obtained in real time using the Global Positioning System (GPS). Simultaneously, based on the new service type and location of the new order, and combined with the first candidate driver's current location, a route planning algorithm calculates the mileage cost required for the driver to accept and execute the new order, i.e., the first target mileage value. This first target mileage value refers to the mileage consumed by the first candidate driver in an idle state from their current location to the service location of the new order. For example, if the business requirement of the new order is vehicle relocation, then the first target mileage value is the mileage from the first candidate driver's current location to the location of the vehicle to be relocated, excluding the mileage between the vehicle's current location and the target location.

[0037] Step S204: Obtain the second current location of each second candidate driver and the current service type and current service location of the current order. Based on the second current location, the current service type, the current service location, the new service type, and the new service location, determine the second target mileage value required for each second candidate driver to execute the new order.

[0038] In this embodiment, the second target mileage value measures the mileage cost required for the second candidate driver to connect to a new order. Specifically, it includes three categories: first, the mileage incurred by the second candidate driver from their current location to the current service location of the current order, such as the mileage in a vehicle relocation service (moving the vehicle from its current location to the initial location of the vehicle to be relocated, and then to the target relocation location); second, the mileage value mapped from the time consumed in the current order service, such as for single-point services like vehicle registration, where the actual time required to complete registration is mapped to equivalent mileage using a basic mapping coefficient; and third, the distance between the driver's current service location and the new service location of the new order after the current order service is completed. The current order includes the current service type, current service location, time-related information, and other auxiliary information. The current service type includes at least one of vehicle relocation, towing, vehicle registration, jump-starting, tire repair / change, and unlocking, depending on the specific needs of the ordering user; the new service location includes the origin and destination based on the service content; time-related information refers to the urgency level of the current order; other auxiliary information includes user contact information and a brief description of the vehicle malfunction.

[0039] Specifically, the system uses GPS to obtain the second current location of each candidate driver in real time. This second current location represents the driver's real-time geographic location during the execution of the current order. Simultaneously, it retrieves information about the candidate driver's current order, such as the service location, execution progress, and remaining task scope. Combined with key information such as the new service location for the new order, a comprehensive assessment is made of the total mileage required for the candidate driver to transition from their current location to completing the remaining tasks of the current order and then executing the new order. This second target mileage value reflects the difficulty and mileage cost of connecting the driver to the new order during the service process. It considers both the impact of the incomplete status of the current order on the connection and the service requirements of the new order, serving as an indicator to measure the efficiency of different candidate drivers in responding to new orders.

[0040] Step S205: Sort the candidate drivers according to the multiple first target mileage values ​​and the multiple second target mileage values ​​to obtain a dispatch priority list.

[0041] In this embodiment, all first candidate drivers and their first target mileage values, and all second candidate drivers and their second target mileage values, are included in the same sorted dataset. Driver records with data anomalies (such as empty mileage values ​​or exceeding reasonable service ranges) are removed to ensure the validity of the sorted data. The mileage values ​​are sorted in ascending order; the smaller the first or second target mileage value, the higher the response efficiency and mileage cost of the corresponding candidate driver for accepting new orders, and the higher the dispatch priority. A built-in sorting algorithm is used to perform a global sort on the dataset, ultimately generating a unified dispatch priority list. The list clearly marks each candidate driver's driver identifier, current status (idle / serviced), and corresponding target mileage value, facilitating direct access in subsequent dispatch processes. This dispatch priority list breaks down the boundaries of driver status, achieving unified sorting of idle and serviced drivers. Drivers with higher priority in the list have better overall efficiency in responding to new orders.

[0042] Step S206: Within a preset time period, the new order is assigned to the candidate driver with the highest priority in the dispatch priority list.

[0043] In this embodiment, the preset time period can be 15-60 seconds, which can be differentiated according to different service types. For example, 30 seconds is commonly used, which is suitable for most routine rescue orders (such as routine jump-starting in urban areas, tire repair, non-emergency relocation, etc.). 30 seconds allows drivers enough time to check order information (service location, type, connection route) and respond, while also preventing users from experiencing a decline in experience due to excessive waiting time. For more urgent orders, the preset time can be appropriately shortened. For example, orders such as highway accidents and rescues in remote areas late at night have extremely high time requirements and need to be dispatched quickly, shortening the driver's response waiting time and avoiding the risk of rescue delays exacerbating the situation. For rescues during peak hours in urban areas or routine daytime rescues, the preset time can be appropriately extended to balance driver response time and user waiting experience.

[0044] Specifically, first, the system reads the number of times drivers respond to new orders and initializes a dispatch failure counter to record the number of consecutive dispatch failures. Then, dispatch requests are initiated sequentially from the highest-priority candidate drivers, according to the dispatch priority list. Information about the new order (including the new service location, service type, urgency level, and estimated connection distance) can be pushed to the driver's app.

[0045] This application expands the selection of drivers available for accepting orders by obtaining new service locations and service types through dispatch instructions in response to new orders, and filters out candidate drivers with both available and service statuses. This avoids the waste of capacity caused by limiting oneself to only available drivers. Obtaining the current location of available drivers and determining their first target mileage for executing new orders directly reflects the distance cost for these drivers to accept new orders, allowing dispatch to be more aligned with actual trip requirements. Combining the current location and current orders of drivers with service status to determine a second target mileage fully considers the work progress and subsequent connection possibilities of these drivers, avoiding overlooking potential capacity that is currently serving but can quickly respond to new orders. Ranking candidate drivers based on the two target mileage values ​​forms a dispatch priority list, ensuring a reasonable dispatch order and avoiding response chaos caused by disordered dispatch. Dispatching orders according to the priority list within a preset time period quickly matches the most suitable driver, reduces order waiting time, improves overall service efficiency, and effectively balances the workload of various drivers, making capacity allocation more rational and fundamentally improving the accuracy of dispatch strategies in the roadside assistance industry.

[0046] In some optional implementations of this embodiment, the step of determining the first target mileage value required for each of the first candidate drivers to execute the new order based on the first current location, the new service type, and the new service location includes: Obtain the urgency weight of the new service type; The arrival mileage is determined based on the first current location and the new service location; The arrival mileage value and the urgency weight are fused to obtain the first target mileage value.

[0047] In this embodiment, each service type has a corresponding urgency level, and each urgency level has a corresponding urgency weight. The urgency levels are divided into 1 to 5 based on timeliness requirements: Level 1 = Highway accident / safety endangerment, highest priority; Level 2 = Nighttime remote area rescue; Level 3 = Routine urban rescue; Level 4 = Daytime general rescue; Level 5 = Non-emergency service, lowest priority. The urgency weight W is preset accordingly. E Calculation formula: W E =1 + (L-3) × 0.2, where L is the urgency level. For example, if the new service type of a new order is highway accident towing, the corresponding urgency level is L=1 (highest priority). Substituting this into the above formula, the urgency weight can be calculated. This urgency weight is used to reduce the first target mileage value of urgent orders, thereby increasing their dispatch priority.

[0048] For example, the GPS positioning module obtains the first candidate driver's current location (accurate to latitude and longitude coordinates), and simultaneously extracts the new service location of the new order (such as a specific intersection, highway kilometer marker, etc.). The real-time route planning interface is then called to calculate the actual travel distance between the two, i.e., the arrival mileage. During the calculation, real-time traffic data is prioritized for optimal route planning. If real-time traffic data is unavailable, it is estimated using conventional road distribution data to ensure the mileage value closely matches the actual travel scenario. Finally, the arrival mileage value is fused with the urgency weight to obtain the final first target mileage value. The fusion is performed according to the formula "First target mileage value = Arrival mileage value × Urgency weight," and the priority of orders with different urgency levels is adjusted using the urgency weight.

[0049] This application obtains the urgency weight corresponding to the new service type and combines it with the determined arrival mileage value for integrated calculation. This not only reflects the differences in timeliness requirements of different orders and gives urgent orders a reasonable priority, but also ensures that the mileage value matches the actual traffic conditions, optimizes the dispatch logic of idle drivers, reduces unreasonable dispatches, and improves the overall service response efficiency and the rationality of resource allocation.

[0050] In some optional implementations of this embodiment, the step of determining the second target mileage value required for each of the second candidate drivers to execute the new order based on the second current location, the current service type, the current service location, the new service type, and the new service location includes: The current mileage value is determined based on the second current location and the current service location; Determine the processing time for the current order based on the current service type; The operation mileage value is determined based on the preset basic mapping coefficient and the standard operation duration; The second target mileage value is determined based on the current mileage value, the operational mileage value, the new service type, and the new service location.

[0051] In this embodiment, the basic mapping coefficient is set based on the standard latency of each service type. For example, power-on is a fast service type, and based on a large number of historical cases, the standard latency is generally around 10 minutes. In the power-on scenario, the basic mapping coefficient K is... T The speed can be 0.3 km / min; tire repair is a medium-speed service, with a standard service time of approximately 30 minutes. In this tire repair scenario, the basic mapping coefficient K... T The speed can be 0.5 km / min; towing is a slow service type, with a standard delivery time of approximately 60 minutes. In this towing scenario, the basic mapping coefficient K... T The speed can be 0.8 km / min; relocation or vehicle registration is a non-emergency service, with a standard processing time of approximately 120 minutes. In this relocation or vehicle registration scenario, the basic mapping coefficient K... T It can be 0.2 km / min.

[0052] Specifically, the system obtains the second candidate driver's current location (accurate to latitude and longitude coordinates) through a real-time positioning module, and simultaneously extracts the current service location of the current order (i.e., the target completion location of the current order). A path planning algorithm is then used to calculate the planned path distance between the two locations, yielding the current mileage value. Next, the current service type of the second candidate driver's current order (e.g., towing, tire repair, vehicle registration, relocation, etc.) is extracted. Based on numerous historical cases, the standard time required for each type is determined, i.e., the standard operation time for the current order. Then, the operation time is mapped to the operation mileage value according to a preset basic mapping coefficient. During the mapping process, it is possible to consider whether the second candidate driver is already at the operation site of the current order and the influence of environmental factors. For example, the current mileage value determined based on the second current location and the current service location can be used to determine whether the second candidate driver has arrived at the operation site of the current service location. If not, no adjustment to the operation time is needed; if the driver has arrived, it indicates that part of the current order's process has been completed, and the operation time needs to be adjusted. Simultaneously, the current environmental conditions are detected to determine if there is any interference. If interference is present, adjustments can be made based on the mapping coefficient. Finally, by summing the current mileage value, the operational mileage value, and the required mileage value from the new order information, the second target mileage value can be obtained.

[0053] This application determines the current mileage value by combining the second current location with the current service location, converts the operation time into operation mileage value by matching the basic mapping coefficient according to the current service type, and then calculates the second target mileage value by integrating the relevant requirements of new orders. It comprehensively considers the driver's current operation status and connection costs in the service, optimizes the capacity allocation, reduces dispatch conflicts, makes the dispatch logic more in line with the actual rescue scenario, and improves the overall service response efficiency.

[0054] In some optional implementations of this embodiment, the step of determining the second target mileage value based on the current mileage value, the operational mileage value, the new service type, and the new service location includes: The new service mileage value is determined based on the current service location and the new service location; Obtain the urgency weight of the new service type; The current mileage value, the operational mileage value, the new service mileage value, and the urgency weight are combined to obtain the second target mileage value.

[0055] In this embodiment, the current service location of the second candidate driver's current order is extracted. If the current service type is a single-point service such as jump-starting or unlocking, the current service location is the location where the current service type is performed. If the current service type is a round-trip or one-way service such as vehicle relocation or vehicle registration, the current service location is the target completion location of the current order. The new service mileage value between the current service location and the new service location of the new order is obtained by calculating the planned path distance between the two based on the real-time route planning interface. The new service location of the new order refers to the initial location of the operation; that is, for one-way services like vehicle relocation or round-trip services like vehicle registration, the new service location is the initial location of the vehicle to be relocated or the initial location of the vehicle to be registered. This new service mileage value reflects the connection cost for the driver to reach the service location of the new order after completing the current order. Real-time traffic data is used preferentially in the calculation process to ensure consistency with actual traffic scenarios.

[0056] Next, extract the new service type of the new order, match it with the corresponding urgency level (level 1~5, level 1 is the highest priority, level 5 is the lowest priority), and then apply the preset formula W. E=1 + (L-3) × 0.2 to calculate the urgency weight. Then, first summarize the current mileage value, the work mileage value, and the new service mileage value, and then adjust it through the urgency weight to form the final second target mileage value. That is, the physical mileage of the second candidate driver to complete the current order, plus the equivalent mileage mapped by the remaining time of the current order, plus the mileage connecting the old and new orders, and then adjust it through the urgency weight to obtain the second target mileage value. The formula is: Second target mileage value = (current mileage value + work mileage value + new service mileage value) × urgency weight.

[0057] This application determines the new service mileage value between the current service location and the new service location, incorporates the urgency weight corresponding to the new service type, and obtains a second target mileage value. It comprehensively considers the driver's connection cost and order timeliness requirements during the service, allowing urgent orders to be matched with suitable drivers first, avoiding the disconnect between timeliness requirements and order dispatch, and improving the rationality of order dispatch and overall response efficiency.

[0058] In some optional implementations of this embodiment, the step of determining the operation mileage value based on the preset basic mapping coefficient and the operation duration includes: Obtain the work progress of the second candidate driver in executing the current order, convert the work progress, and obtain the progress correction coefficient; The target working time is determined based on the work progress and the standard work duration. Obtain the environmental correction coefficient, and determine the target mapping coefficient based on the schedule correction coefficient, the environmental correction coefficient, and the basic mapping coefficient; The target operation duration is mapped according to the target mapping coefficient to obtain the operation mileage value.

[0059] In this embodiment, the progress of the second candidate driver in executing the current order can be initially determined based on the second current location and the current service location. For example, if the second candidate driver is heading to the current service location based on the second current location, the progress can be determined to be 0%, and the target operation time at this time is the standard operation time. If the second current location coincides with the current service location, it can be determined that the second candidate driver is currently performing the current order. Then, combined with the real-time operation status, the remaining unfinished operation time is calculated. For example, if the current service type is towing, the preset standard total operation time is 60 minutes, and the current order has been executed for 30 minutes, then the remaining operation time is 30 minutes, and this remaining operation time is the target operation time. The current operation progress S is determined based on the total operation time and the executed time. The progress correction coefficient (K) is adjusted based on the operation progress S. S When S≥80%, it is considered close to completion, K S=0.7 (reflecting stronger responsiveness); when 50%≤S<80%, proceed according to the normal schedule, K S =1.0; when S < 50%, it is determined that the job has just started, K S =1.2 (reflects weak responsiveness). For dynamic environmental information (including real-time road conditions, work area type, and real-time weather), match the corresponding environmental correction coefficient (K). Env For smooth traffic / urban operations, use 1.0; for congested roads / remote areas, use 1.2; for nighttime / severe weather operations, use 1.1~1.2 (adjusted according to the degree of impact). For example, if the second candidate driver is currently performing a tire repair order, with a work progress S=85%, and the work area is a highway section encountering light rain (severe weather), the corresponding environmental correction factor K is... Env =1.2; Work progress S=85%≥80%, corresponding progress correction factor K S =0.7.

[0060] The target mapping coefficient is synthesized by multiplying the basic mapping coefficient, the schedule correction coefficient, and the environmental correction coefficient. The formula is: Target mapping coefficient = K T ×K S ×K Env The basic mapping coefficient for tire repair services is 0.5 km / min, combined with K. S =0.7, K Env =1.2, the target mapping coefficient is calculated to be 0.5 × 0.7 × 1.2 = 0.42 km / min. Finally, the target operation time T of the current order is multiplied by the target mapping coefficient to obtain the operation mileage value. For example, the standard time for a tire repair order is 30 minutes, the remaining service time T = (1 - 85%) × 30 = 4.5 minutes, and the corresponding operation mileage value is 4.5 × 0.42 = 1.89 km.

[0061] This application generates a progress correction coefficient by converting the work progress into a progress correction coefficient, and then combines it with a basic mapping coefficient and an environmental correction coefficient to generate a target mapping coefficient, which is used to map the work mileage value. It fully considers the actual working conditions of drivers and the influence of the on-site environment, avoiding the rigidity of fixed coefficients, making the work mileage value more realistic, optimizing the assessment of drivers' remaining load during service, and improving the rationality of dispatching logic and scheduling adaptability.

[0062] In some optional implementations of this embodiment, the step of filtering all drivers based on the new service type and the new service location to obtain multiple candidate drivers who can receive the new order includes: Based on the new service locations, candidate areas are determined; Obtain the location information of all the drivers, and filter all the drivers based on the location information and the candidate regions to obtain initial candidate drivers; Based on the new service type, the initial candidate drivers are screened to obtain the candidate drivers.

[0063] In this embodiment, the new service location for a new order is extracted, and a candidate area is defined based on the service type characteristics and the required rescue radius. This candidate area is a dynamically adjusted adaptation range based on the service scenario. For example, if the new service location is a highway, the candidate area is defined as a 15-kilometer stretch of highway before and after the location, plus a 3-kilometer radius around the entrance and exit, which is designed to meet the rapid response requirements of highway rescue. If the service location is in an urban area, such as an intersection in a commercial district, the candidate area is defined as a circular area with a radius of 10 kilometers centered on the location. If the location is in a remote suburban area, the radius of the candidate area is expanded to 15 kilometers to accommodate scenarios with lower driver density in suburban areas.

[0064] The platform collects real-time location information of all compliant drivers using GPS and BeiDou positioning modules. After data verification to exclude location data with location drift or abnormal signals, each driver's location is matched with a designated candidate area. If a driver's real-time location is within the candidate area, they are included in the initial candidate driver list; if outside the area, they are excluded. New service types for new orders (such as highway accident towing, urban jump-starting, and suburban tire repair) are extracted, and the qualification registration information of the initial candidate drivers (including vehicle configuration, service qualifications, and areas of expertise) is retrieved to filter out drivers capable of undertaking that service type, i.e., the aforementioned candidate drivers. For example, if the new service type is highway accident towing, the driver must be equipped with professional towing equipment and possess highway rescue qualifications; if it is jump-starting, the driver must carry jump-start tools and have registered relevant service qualifications; if it is tire repair, the driver must possess tire repair skills and the necessary tools.

[0065] This application defines suitable candidate areas by identifying new service locations, filters out initial candidate drivers whose geographical ranges fit the new service, and then matches drivers with the corresponding service capabilities based on the new service type. This dual screening process not only eliminates invalid participation from long-distance drivers but also avoids order rejections due to mismatched qualifications, optimizes the quality of candidate drivers, makes order dispatch more aligned with actual needs, and improves subsequent dispatch efficiency and the rationality of resource allocation.

[0066] In some optional implementations of this embodiment, after the step of assigning the new order to the highest priority candidate driver in the dispatch priority list within a preset time period, the method further includes: Obtain the number of responses from the highest priority candidate driver to the new order; Based on the number of responses and the number of candidate drivers in the dispatch priority list, it is determined whether the new order has been successfully dispatched. If the new order is successfully dispatched, a dispatch success instruction will be sent to the management platform. If the new order fails to be dispatched, the new order is marked as an overdue order and the overdue order is sent to the management platform.

[0067] In this embodiment, after assigning a new order to the candidate driver with the highest priority in the dispatch priority list, the response count counter is automatically initialized (initial value is 0), and the total number of candidate drivers in the dispatch priority list (denoted as N) is read, and a 30-second timeout timer is started (the timeout time can be configured by the administrator in the background, with a default of 30 seconds).

[0068] The system monitors the feedback behavior of the highest priority candidate drivers in real time. If a driver clicks "Accept Order" within the timeout period, the response count counter remains at its current value. If a driver clicks "Reject Order" or fails to respond within the timeout period, the response count counter automatically increments by 1, and the driver is marked as having failed to complete the order assignment. When the response count counter value for the candidate driver is greater than or equal to 1, the order is automatically assigned to the next highest priority candidate driver in the order assignment priority list, and response monitoring and count are repeated. If the number of order assignments reaches the total number of candidate drivers, and the response count counter is still greater than or equal to 1 when the number of order assignments equals N, then all candidate drivers have received the order assignment but failed to accept it successfully (rejected or timed out). The new order is then marked as an overdue order and sent to the management platform. If any candidate driver clicks "Accept Order" before the timeout period, and the counter is less than 1, the new order is considered successfully assigned. The assignment of the new order ends, and a successful assignment instruction is sent to the management platform.

[0069] When overdue orders are sent to the management platform, they are prominently displayed in the overdue order management module of the platform's backend system, with information such as the order's urgency level, new service location, and service type. At the same time, reminders are pushed to the administrator via SMS and platform-embedded messages, informing them that there are overdue orders that require manual intervention. This ensures that the administrator is aware of the situation in a timely manner and can take measures such as manually dispatching orders and supplementing scheduling resources to avoid order omissions.

[0070] This application tracks the number of responses from candidate drivers to new orders. When multiple candidate drivers in the priority list fail to accept a new order consecutively, the order is marked as overdue and pushed to the management platform. This prevents orders from remaining unclaimed for extended periods, promptly alerts administrators to intervene, facilitates remedial measures such as manual order dispatch, prevents order omissions, ensures the continuity and timeliness of rescue services, and improves the completeness and reliability of order processing.

[0071] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0072] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0073] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0074] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0075] Further reference Figure 3 As a response to the above Figure 2 The implementation of the method shown in this application provides an embodiment of an intelligent order dispatching system, which is similar to... Figure 2 Corresponding to the method embodiments shown, the system can be specifically applied to various electronic devices.

[0076] like Figure 3As shown, the intelligent order dispatch system 300 described in this embodiment includes: a response module 301, a filtering module 302, a first determination module 303, a second determination module 304, a sorting module 305, and an allocation module 306. Wherein: The response module 301 is used to respond to the dispatch instruction of a new order and obtain the new service type and new service location of the new order according to the dispatch instruction; The filtering module 302 is used to filter all drivers according to the new service type and the new service location to obtain multiple candidate drivers who can receive the new order. The candidate drivers include multiple first candidate drivers who are in an idle state and multiple second candidate drivers who are in a service state. The first determining module 303 is used to obtain the first current location of each of the first candidate drivers, and determine the first target mileage value required for each of the first candidate drivers to execute the new order based on the first current location, the new service type and the new service location; The second determining module 304 is used to obtain the second current location of each second candidate driver and the current service type and current service location of the current order, and determine the second target mileage value required for each second candidate driver to execute the new order based on the second current location, the current service type, the current service location, the new service type and the new service location; The sorting module 305 is used to sort the multiple candidate drivers according to the multiple first target mileage values ​​and the multiple second target mileage values ​​to obtain a dispatch priority list; The allocation module 306 is used to allocate the new order to the highest priority candidate driver in the dispatch priority list within a preset time period.

[0077] The intelligent dispatch system provided in this application expands the selection of drivers who can accept orders by responding to dispatch instructions for new orders, obtaining new service locations and service types, and filtering out candidate drivers with both available and service statuses. This avoids the waste of capacity caused by limiting oneself to only available drivers. Obtaining the current location of available drivers and determining their first target mileage for executing new orders directly reflects the distance cost for these drivers to accept new orders, making dispatching more aligned with actual trip requirements. Combining the current location and current orders of drivers with service status to determine a second target mileage fully considers the work progress and subsequent connection possibilities of these drivers, avoiding overlooking potential capacity that is currently serving but can quickly respond to new orders. Ranking candidate drivers based on the two target mileage values ​​forms a dispatch priority list, ensuring a reasonable dispatching order and avoiding response chaos caused by disordered dispatching. Dispatching orders according to the priority list within a preset time period quickly matches the most suitable driver, reduces order waiting time, improves overall service efficiency, and effectively balances the workload of various drivers, making capacity allocation more rational and fundamentally improving the accuracy of dispatching strategies in the roadside assistance industry.

[0078] In some optional implementations of this embodiment, the first determining module 303 is further configured to: Obtain the urgency weight of the new service type; The arrival mileage is determined based on the first current location and the new service location; The arrival mileage value and the urgency weight are fused to obtain the first target mileage value.

[0079] The intelligent dispatch system provided in this application obtains the urgency weight corresponding to the new service type and combines it with the determined arrival mileage value for integrated calculation. This not only reflects the differences in timeliness requirements of different orders and gives urgent orders a reasonable priority, but also ensures that the mileage value matches the actual traffic conditions, optimizes the dispatch logic for idle drivers, reduces unreasonable dispatches, and improves the overall service response efficiency and the rationality of resource allocation.

[0080] In some optional implementations of this embodiment, the second determining module 304 is further configured to: The current mileage value is determined based on the second current location and the current service location; Determine the processing time for the current order based on the current service type; The operation mileage value is determined based on the preset basic mapping coefficient and the standard operation duration; The second target mileage value is determined based on the current mileage value, the operational mileage value, the new service type, and the new service location.

[0081] The intelligent dispatch system provided in this application determines the current mileage value by combining the second current location with the current service location, converts the operation time into operation mileage value by matching the basic mapping coefficient according to the current service type, and then calculates the second target mileage value by integrating the relevant requirements of new orders. It comprehensively considers the driver's current operation status and connection cost in the service, optimizes the transportation capacity configuration, reduces dispatch conflicts, makes the dispatch logic more in line with the actual rescue scenario, and improves the overall service response efficiency.

[0082] In some optional implementations of this embodiment, the second determining module 304 is further configured to: The new service mileage value is determined based on the current service location and the new service location; Obtain the urgency weight of the new service type; The current mileage value, the operational mileage value, the new service mileage value, and the urgency weight are combined to obtain the second target mileage value.

[0083] The intelligent dispatch system provided in this application determines the new service mileage value between the current service location and the new service location, incorporates the urgency weight corresponding to the new service type, and obtains a second target mileage value. It comprehensively considers the driver's connection cost and the timeliness requirements of the order during the service, so that urgent orders are prioritized to match suitable drivers, avoids the disconnect between timeliness requirements and dispatch, and improves the rationality of dispatch and overall response efficiency.

[0084] In some optional implementations of this embodiment, the second determining module 304 is further configured to: Obtain the work progress of the second candidate driver in executing the current order, convert the work progress, and obtain the progress correction coefficient; The target working time is determined based on the work progress and the standard work duration. Obtain the environmental correction coefficient, and determine the target mapping coefficient based on the schedule correction coefficient, the environmental correction coefficient, and the basic mapping coefficient; The target operation duration is mapped according to the target mapping coefficient to obtain the operation mileage value.

[0085] The intelligent dispatching system provided in this application converts the work progress into a progress correction coefficient, combines it with a basic mapping coefficient and an environmental correction coefficient to generate a target mapping coefficient, and then maps this coefficient to obtain the work mileage value. It fully considers the driver's actual working status and the influence of the on-site environment, avoiding the rigidity of fixed coefficients, making the work mileage value more realistic, optimizing the assessment of the driver's remaining load during service, and improving the rationality of dispatching logic and scheduling adaptability.

[0086] In some optional implementations of this embodiment, the filtering module 302 is further configured to: Based on the new service locations, candidate areas are determined; Obtain the location information of all the drivers, and filter all the drivers based on the location information and the candidate regions to obtain initial candidate drivers; Based on the new service type, the initial candidate drivers are screened to obtain the candidate drivers.

[0087] The intelligent dispatching system provided in this application defines suitable candidate areas by identifying new service locations, filters out initial candidate drivers whose geographical ranges match the new service type, and then matches drivers with corresponding service capabilities based on the new service type. This dual screening not only eliminates invalid participation from long-distance drivers but also avoids order rejections due to mismatched qualifications, optimizes the quality of candidate drivers, makes dispatching more aligned with actual needs, and improves subsequent scheduling efficiency and the rationality of resource allocation.

[0088] In some optional implementations of this embodiment, the allocation module 306 is further configured to: Obtain the number of responses from the highest priority candidate driver to the new order; Based on the number of responses and the number of candidate drivers in the dispatch priority list, it is determined whether the new order has been successfully dispatched. If the new order is successfully dispatched, a dispatch success instruction will be sent to the management platform. If the new order fails to be dispatched, the new order is marked as an overdue order and the overdue order is sent to the management platform.

[0089] The intelligent order dispatch system provided in this application, based on the number of responses from candidate drivers to new orders, marks orders as overdue and pushes them to the management platform when multiple candidate drivers in the priority list fail to accept new orders consecutively. This avoids long-term order backlogs, promptly alerts administrators to intervene, facilitates remedial measures such as manual order dispatch, prevents order omissions, ensures the continuity and timeliness of rescue services, and improves the completeness of order processing and service reliability.

[0090] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0091] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected via a system bus. It should be noted that only the computer device 4 with components 41, 42, and 43 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0092] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0093] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and its external storage device of the computer device 4. In this embodiment, the memory 41 is typically used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for intelligent dispatching methods. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or will be output.

[0094] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions stored in the memory 41 or to process data, for example, to execute computer-readable instructions for the intelligent dispatch method.

[0095] The network interface 43 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 4 and other electronic devices.

[0096] The computer equipment provided in this application expands the selection of drivers who can accept orders by responding to dispatch instructions for new orders, obtaining new service locations and service types, and filtering out candidate drivers with both available and service statuses. This avoids the waste of capacity caused by limiting oneself to only available drivers. Obtaining the current location of available drivers and determining their first target mileage for executing new orders directly reflects the distance cost for these drivers to accept new orders, allowing dispatching to be more aligned with actual travel needs. Combining the current location and current orders of drivers with service status to determine a second target mileage fully considers the work progress and subsequent connection possibilities of these drivers, avoiding overlooking potential capacity that is currently serving but can quickly respond to new orders. Ranking candidate drivers according to the two target mileage values ​​forms a dispatch priority list, ensuring a reasonable dispatching order and avoiding response chaos caused by disordered dispatching. Dispatching orders according to the priority list within a preset time period quickly matches the most suitable driver, reduces order waiting time, improves overall service efficiency, and effectively balances the workload of various drivers, making capacity allocation more rational and fundamentally improving the accuracy of dispatching strategies in the roadside assistance industry.

[0097] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the intelligent dispatching method as described above.

[0098] The computer-readable storage medium provided in this application expands the selection of drivers who can accept orders by obtaining new service locations and service types in response to dispatch instructions for new orders, and filters out candidate drivers with both available and service statuses, thus avoiding the waste of capacity caused by limiting oneself to only available drivers. Obtaining the current location of available drivers and determining their first target mileage value for executing new orders directly reflects the distance cost for these drivers to accept new orders, allowing dispatching to be more aligned with actual trip requirements. Combining the current location of drivers with service status and their current orders to determine a second target mileage value fully considers the work progress and subsequent connection possibilities of these drivers, avoiding overlooking potential capacity that is currently serving but can quickly respond to new orders. Ranking candidate drivers according to the two target mileage values ​​forms a dispatch priority list, ensuring a reasonable dispatching order and avoiding response chaos caused by disordered dispatching. Dispatching orders according to the priority list within a preset time period quickly matches the most suitable driver, reduces order waiting time, improves overall service efficiency, and effectively balances the workload of various drivers, making capacity allocation more rational and fundamentally improving the accuracy of dispatching strategies in the roadside assistance industry.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0100] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. An intelligent dispatching method, characterized in that, Includes the following steps: In response to a new order dispatch instruction, the new service type and new service location of the new order are obtained according to the dispatch instruction; Based on the new service type and the new service location, all drivers are screened to obtain multiple candidate drivers who can receive the new orders. The candidate drivers include multiple first candidate drivers who are idle and multiple second candidate drivers who are in service. Obtain the first current location of each first candidate driver, and determine the first target mileage value required for each first candidate driver to execute the new order based on the first current location, the new service type, and the new service location; Obtain the second current location of each second candidate driver, the current service type of the current order, and the current service location. Based on the second current location, the current service type, the current service location, the new service type, and the new service location, determine the second target mileage value required for each second candidate driver to execute the new order. Based on multiple first target mileage values ​​and multiple second target mileage values, multiple candidate drivers are sorted to obtain a dispatch priority list; Within a preset time period, the new order is assigned to the highest priority candidate driver in the dispatch priority list; The step of determining the first target mileage value required for each of the first candidate drivers to execute the new order based on the first current location, the new service type, and the new service location includes: Obtain the urgency weight of the new service type; The arrival mileage is determined based on the first current location and the new service location; The arrival mileage value and the urgency weight are fused to obtain the first target mileage value, which is equal to the arrival mileage value multiplied by the urgency weight. The step of determining the second target mileage value required for each second candidate driver to execute the new order based on the second current location, the current service type, the current service location, the new service type, and the new service location includes: The current mileage value is determined based on the second current location and the current service location; Determine the standard operation time for the current order based on the current service type; The operation mileage value is determined based on the preset basic mapping coefficient and the standard operation duration; The second target mileage value is determined based on the current mileage value, the operational mileage value, the new service type, and the new service location; The step of determining the operation mileage value based on the preset basic mapping coefficient and the standard operation duration includes: Obtain the work progress of the second candidate driver in executing the current order, convert the work progress, and obtain the progress correction coefficient; The target operation duration is determined based on the operation progress and the standard operation duration. Obtain the environmental correction coefficient, and determine the target mapping coefficient based on the schedule correction coefficient, the environmental correction coefficient, and the basic mapping coefficient; The target operation duration is mapped according to the target mapping coefficient to obtain the operation mileage value. 2.The intelligent dispatching method according to claim 1, characterized in that, Determining the second target mileage value based on the current mileage value, the operational mileage value, the new service type, and the new service location includes: The new service mileage value is determined based on the current service location and the new service location; Obtain the urgency weight of the new service type; The current mileage value, the operational mileage value, the new service mileage value, and the urgency weight are combined to obtain the second target mileage value.

3. The intelligent order dispatching method according to claim 1, characterized in that, The process involves filtering all drivers based on the new service type and the new service location to obtain multiple candidate drivers who can accept the new orders, including: Based on the new service locations, candidate areas are determined; Obtain the location information of all the drivers, and filter all the drivers based on the location information and the candidate regions to obtain initial candidate drivers; Based on the new service type, the initial candidate drivers are screened to obtain the candidate drivers.

4. The intelligent order dispatching method according to any one of claims 1 to 3, characterized in that, After assigning the new order to the highest-priority candidate driver in the dispatch priority list within the preset time period, the method further includes: Obtain the number of responses from the highest priority candidate driver to the new order; Based on the number of responses and the number of candidate drivers in the dispatch priority list, it is determined whether the new order has been successfully dispatched. If the new order is successfully dispatched, a dispatch success instruction will be sent to the management platform. If the new order fails to be dispatched, the new order is marked as an overdue order and the overdue order is sent to the management platform.

5. An intelligent order dispatching system, characterized in that, include: The response module is used to respond to the dispatch instruction of a new order and, based on the dispatch instruction, obtain the new service type and new service location of the new order; The filtering module is used to filter all drivers according to the new service type and the new service location to obtain multiple candidate drivers who can receive the new order. The candidate drivers include multiple first candidate drivers who are in an idle state and multiple second candidate drivers who are in a service state. The first determining module is used to obtain the first current location of each first candidate driver, and determine the first target mileage value required for each first candidate driver to execute the new order based on the first current location, the new service type and the new service location; The second determining module is used to obtain the second current location of each second candidate driver and the current service type and current service location of the current order, and to determine the second target mileage value required for each second candidate driver to execute the new order based on the second current location, the current service type, the current service location, the new service type and the new service location; The sorting module is used to sort the multiple candidate drivers according to multiple first target mileage values ​​and multiple second target mileage values ​​to obtain a dispatch priority list; The allocation module is used to allocate the new order to the highest priority candidate driver in the dispatch priority list within a preset time period; The step of determining the first target mileage value required for each of the first candidate drivers to execute the new order based on the first current location, the new service type, and the new service location includes: Obtain the urgency weight of the new service type; The arrival mileage is determined based on the first current location and the new service location; The arrival mileage value and the urgency weight are fused to obtain the first target mileage value, which is equal to the arrival mileage value multiplied by the urgency weight. The step of determining the second target mileage value required for each second candidate driver to execute the new order based on the second current location, the current service type, the current service location, the new service type, and the new service location includes: The current mileage value is determined based on the second current location and the current service location; Determine the standard operation time for the current order based on the current service type; The operation mileage value is determined based on the preset basic mapping coefficient and the standard operation duration; The second target mileage value is determined based on the current mileage value, the operational mileage value, the new service type, and the new service location; The step of determining the operation mileage value based on the preset basic mapping coefficient and the standard operation duration includes: Obtain the work progress of the second candidate driver in executing the current order, convert the work progress, and obtain the progress correction coefficient; The target operation duration is determined based on the operation progress and the standard operation duration. Obtain the environmental correction coefficient, and determine the target mapping coefficient based on the schedule correction coefficient, the environmental correction coefficient, and the basic mapping coefficient; The target operation duration is mapped according to the target mapping coefficient to obtain the operation mileage value.

6. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the intelligent dispatching method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the intelligent dispatching method as described in any one of claims 1 to 4.

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