A Multi-Node Collaborative Transportation Scheduling Method for Heavy Truck Fleets

Abstract

This application provides a multi-node collaborative transportation scheduling method for heavy-duty truck fleets, relating to the field of vehicle technology. The method includes: acquiring the battery status data and first fatigue characteristic data of each charging locomotive at each of multiple replacement points on a target transportation route; acquiring the driving status data of each trailer, the locomotive status data of each carrier locomotive, and second fatigue characteristic data of multiple trailers in the target heavy-duty truck fleet; determining candidate replacement points based on the driving status data of each trailer, the battery status data of each charging locomotive at each replacement point, and the locomotive status data of each carrier locomotive; determining target replacement points for each trailer based on the first fatigue characteristic data and the battery status data of each charging locomotive at the candidate replacement points; and issuing a replacement scheduling request based on the target replacement point and the second fatigue characteristic data. This application reduces the refueling cost for heavy-duty truck fleets and improves the versatility of refueling for heavy-duty truck fleets.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more specifically, to a multi-node collaborative transportation scheduling method for heavy truck fleets. Background Technology

[0002] In recent years, battery technology has made significant progress, with battery energy density gradually increasing, enabling electric heavy trucks to store more electrical energy and making long-distance travel possible. Battery costs are declining, alleviating the problem of high initial purchase costs for electric heavy trucks. Optimization of motor technology has made the power output of electric heavy trucks more efficient and stable, allowing them to exhibit good performance under various working conditions.

[0003] Currently, the main energy replenishment solutions for electric vehicles in long-distance transportation include mid-journey charging and mid-journey battery swapping. Mid-journey charging provides charging services for electric heavy-duty trucks by deploying high-power charging piles in highway service areas; mid-journey battery swapping relies on a network of battery swapping stations and uses automated equipment to quickly replace battery packs.

[0004] However, while the mid-journey charging mode has a relatively simple infrastructure layout, the long charging time seriously affects transportation efficiency; while the mid-journey battery swapping mode can significantly shorten the charging time, it faces problems such as high construction costs and inconsistent battery standards, which limits its economic efficiency and versatility. Summary of the Invention

[0005] The purpose of this application is to address the shortcomings of the prior art by providing a multi-node collaborative transportation scheduling method for heavy truck fleets, thereby reducing the refueling cost of heavy truck fleets and improving the versatility of heavy truck fleet refueling.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows:

[0007] In a first aspect, one embodiment of this application provides a multi-node collaborative transportation scheduling method for heavy truck fleets, the method comprising:

[0008] Acquire the battery status data of each charging vehicle head at each of the multiple replacement points on the target transportation route, as well as the first fatigue characteristic data of the driver corresponding to each charging vehicle head;

[0009] Acquire driving status data of each trailer in multiple trailers of the target heavy truck fleet, cab status data of each tractor unit, and second fatigue characteristic data of the drivers corresponding to each tractor unit;

[0010] Based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head, candidate replacement points are determined from the plurality of replacement points.

[0011] Based on the first fatigue characteristic data of the driver corresponding to each charging vehicle head and the power status data of each charging vehicle head in the candidate replacement points, the target replacement point for each trailer is determined from the candidate replacement points.

[0012] Based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each transport vehicle head, a first vehicle head replacement scheduling request is issued for each trailer to instruct the transport vehicle head corresponding to each trailer to travel to the target replacement point for vehicle head replacement.

[0013] Secondly, another embodiment of this application provides a multi-node collaborative transportation scheduling device for heavy truck fleets, the device comprising:

[0014] The acquisition module is used to acquire the power status data of each charging vehicle head at each of the multiple replacement points on the target transportation route, as well as the first fatigue characteristic data of the driver corresponding to each charging vehicle head; and to acquire the driving status data of each trailer, the vehicle head status data of each transport vehicle head, and the second fatigue characteristic data of the driver corresponding to each transport vehicle head in the multiple trailers of the target heavy truck fleet.

[0015] The determining module is used to determine candidate replacement points from the plurality of replacement points based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head; and to determine target replacement points for each trailer based on the first fatigue characteristic data of the driver corresponding to each charging head and the power status data of each charging head in the candidate replacement points.

[0016] The sending module is used to issue a first tractor replacement scheduling request for each trailer based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each tractor unit, so as to instruct the tractor unit corresponding to each trailer to travel to the target replacement point for tractor replacement.

[0017] Thirdly, another embodiment of this application provides a computer device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the multi-node collaborative transportation scheduling method for heavy truck fleets as described in any of the first aspects above.

[0018] Fourthly, another embodiment of this application provides a storage medium storing a computer program, which, when executed by a processor, performs the steps of the multi-node collaborative transportation scheduling method for heavy truck fleets as described in any of the first aspects above.

[0019] The beneficial effects of this application are:

[0020] This application provides a multi-node coordinated transportation scheduling method for heavy truck fleets. It acquires the battery status data of each charging locomotive at each of multiple replacement points along a target transportation route, as well as the first fatigue characteristic data of the drivers corresponding to each charging locomotive. It also acquires the driving status data of each trailer, the locomotive status data of each carrier locomotive, and the second fatigue characteristic data of the drivers corresponding to each carrier locomotive in the target heavy truck fleet. Based on the driving status data of each trailer, the battery status data of each charging locomotive at each replacement point, and the locomotive status data of each carrier locomotive, candidate replacement points are determined from multiple replacement points. Based on the first fatigue characteristic data of the drivers corresponding to each charging locomotive at the candidate replacement points and the battery status data of each charging locomotive, a target replacement point for each trailer is determined from the candidate replacement points, enabling intelligent matching of replacement points. Based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each carrier locomotive, a first locomotive replacement scheduling request is issued for each trailer to instruct the carrier locomotive of each trailer to travel to the target replacement point for locomotive replacement, thus enhancing driver safety. This application replaces each transport vehicle head by setting up replacement points, eliminating the need to build battery swapping stations, thus reducing the cost of recharging electric heavy-duty trucks. Furthermore, it can recharge electric heavy-duty trucks even when the battery models are different, improving the versatility of recharging electric heavy-duty trucks. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application;

[0023] Figure 2 This is a flowchart illustrating the process of determining candidate replacement points in a multi-node coordinated transportation scheduling method for a heavy truck fleet provided in an embodiment of this application.

[0024] Figure 3A flowchart illustrating the process of determining the readiness conditions of a tractor unit in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application;

[0025] Figure 4 A flowchart illustrating the process of determining the target change point in the multi-node collaborative transportation scheduling method for a heavy truck fleet provided in this embodiment of the application;

[0026] Figure 5 A schematic diagram illustrating trailer fleet management in a multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application embodiment;

[0027] Figure 6 This is a flowchart illustrating the process of determining a scheduling request in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application.

[0028] Figure 7 A flowchart illustrating the process of determining a scheduling request in another multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application embodiment;

[0029] Figure 8 A flowchart illustrating the process of determining a scheduling request in another multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application embodiment;

[0030] Figure 9 This is a flowchart illustrating the process of determining scheduling parameters in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application.

[0031] Figure 10 A flowchart illustrating the determination of priority evaluation parameters in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application;

[0032] Figure 11 A multi-node collaborative transportation scheduling scenario diagram of a heavy truck fleet is provided for embodiments of this application;

[0033] Figure 12 A schematic diagram of a multi-node collaborative transportation scheduling device for a heavy truck fleet provided in an embodiment of this application;

[0034] Figure 13 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0036] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0037] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0038] Currently, battery technology has made significant progress, enabling electric heavy-duty trucks to store more electrical energy and achieve long-distance travel. Electric heavy-duty trucks are recharged or swapped mid-journey during long-distance transport; however, these methods severely impact the transport efficiency and costs of heavy-duty trucks, resulting in excessively high recharging costs. To address this, this application provides a multi-node collaborative transport scheduling method for heavy-duty truck fleets. This method acquires the battery status data of each charging locomotive at each of multiple replacement points along the target transport route, as well as the first fatigue characteristic data of the driver corresponding to each charging locomotive. It also acquires the driving status data of each trailer, the tractor head status data of each transport locomotive, and the second fatigue characteristic data of the driver corresponding to each transport locomotive in the target heavy-duty truck fleet. Based on the driving status data of each trailer, the battery status data of each charging locomotive at each replacement point, and the tractor head status data of each transport locomotive, candidate replacement points are determined from the multiple replacement points. Finally, based on the first fatigue characteristic data of the driver corresponding to each charging locomotive and the battery status data of each charging locomotive at the candidate replacement points, target replacement points for each trailer are determined from the candidate replacement points. Based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each tractor unit, a first tractor unit replacement scheduling request is issued for each trailer to instruct the tractor unit corresponding to each trailer to travel to the target replacement point for tractor unit replacement. The multi-node collaborative transportation scheduling method for heavy truck fleets in this application can improve the versatility of electric heavy truck refueling while reducing the economic cost of electric heavy truck refueling.

[0039] The following description, in conjunction with several accompanying drawings, illustrates a multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application. Figure 1 This is a flowchart illustrating a multi-node collaborative transportation scheduling method for heavy truck fleets provided in an embodiment of this application, as shown below. Figure 1 As shown, the method includes:

[0040] Step 101: Obtain the power status data of each charging vehicle at each of the multiple replacement points on the target transportation route, as well as the first fatigue characteristic data of the driver corresponding to each charging vehicle.

[0041] The charging head is the tractor unit in an electric heavy-duty truck that provides power to the vehicle by charging. For example, when the electric heavy-duty truck is the tractor unit, the charging head is the tractor unit itself, and a semi-trailer can be connected to the charging head to form a tractor unit. First fatigue characteristic data. By using a pre-set fatigue estimation model Sure, , These are parameters that affect multiple fatigue characteristics.

[0042] Optionally, the battery status data may include: the remaining battery power of each charging station, the charging status of each charging station, the charging completion time of each charging station, and the full charge level of each charging station. The charging status indicates whether the charging station is charging. The battery status data can be obtained through the battery management system inside the charging station's battery. Each charging station corresponds to one driver, and the driver's fatigue characteristics can include: eyelid closure time ratio, head tilt angle frequency, heart rate variability, and steering wheel grip force changes. These fatigue characteristic parameters are obtained by installing multiple sensors inside the charging station. The eyelid closure time ratio can be obtained by recording the driver's eyelid closure data using an image acquisition device or infrared eye tracker installed in the driver's cab. The head tilt angle frequency can be obtained by acquiring images of the driver's head using an image acquisition device installed in the driver's cab. Heart rate variability can be measured using a heart rate measuring device installed for the driver. Steering wheel grip force changes can be detected by installing a pressure sensor on the steering wheel.

[0043] Optionally, the battery status data of each charging vehicle head is obtained from the battery management system inside the battery of each charging vehicle head, and the first fatigue characteristic data of the driver corresponding to each charging vehicle head is obtained through multiple image acquisition devices and sensors installed in the cab.

[0044] Step 102: Obtain the driving status data of each trailer in the target heavy truck fleet, the cab status data of each tractor unit, and the second fatigue characteristic data of the driver corresponding to each tractor unit.

[0045] Each trailer can be an electric heavy-duty truck, which can be a freight truck or a tractor unit. It consists of two parts: a carrier cab and a body. When the carrier cab is disconnected from the body for charging, the carrier cab becomes the charging cab. In other words, the carrier cab and the charging cab are two different states of the trailer cab.

[0046] The driving status data for each trailer includes: the location information of each trailer, the real-time speed information of each trailer, and the speed fluctuation noise of each trailer. Specifically, the real-time speed information of each trailer can be obtained from the speed sensors installed on each trailer, and the location information of each trailer can be obtained from the GPS receiver installed on each trailer. The tractor unit's status data can include: the remaining battery power of the tractor unit. The tractor unit's status data can be obtained through the battery management system inside the tractor unit's battery. The second fatigue characteristic data is calculated in the same way as the first fatigue characteristic data. The driver's second fatigue characteristic data is determined by the driver's fatigue characteristic influence parameters, which can include: eyelid closure time ratio, head tilt angle frequency, heart rate variability, steering wheel grip force changes, etc. The driver's second fatigue characteristic data can be obtained by installing multiple sensors inside the vehicle's cab. The eyelid closure time ratio can be obtained by installing image acquisition equipment or an infrared eye tracker in the cab to record the driver's eyelid closure data, thus obtaining the eyelid closure time ratio. The head tilt angle frequency can be obtained by installing image acquisition equipment in the cab to acquire images of the driver and obtain the driver's head tilt angle, thus obtaining the head tilt angle frequency. Heart rate variability can be obtained by installing a heart rate measuring device for the driver. Steering wheel grip force can be obtained by installing a pressure sensor on the steering wheel to detect changes in steering wheel grip force.

[0047] Optionally, the driving status data of each trailer is obtained from the speed sensors and GPS receivers installed on each trailer; the power status data of each charging vehicle is obtained from the battery management system inside the battery of each carrier vehicle; and the second fatigue characteristic data of the driver obtained by each carrier vehicle is obtained from multiple image acquisition devices and sensors installed in the cab.

[0048] Specifically, when the first fatigue characteristic data corresponding to the driver of the charging vehicle or the second fatigue characteristic data corresponding to each transport vehicle exceeds 0.5, the driver is forced to rest, and the rest time for each driver is guaranteed to be greater than 20 minutes every 4 hours of driving. A reward mechanism can also be set up to incentivize drivers to rest by determining corresponding rewards based on rest time.

[0049] Step 103: Based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head, determine the candidate replacement points from multiple replacement points.

[0050] The location of the replacement points is determined based on the trailer's range, with the distance between each replacement point being less than 80% of the trailer's range. For example, when the trailer's range is 500 kilometers, the distance between each replacement point is less than 400 kilometers. The number of replacement points is determined based on the distance between each replacement point and the total length of the target transport route.

[0051] Optionally, based on the driving status data of each trailer and the location between multiple replacement points, the distance of each trailer to each replacement point and the arrival time of each trailer to each replacement point are determined. Based on the distance of each trailer to each replacement point, the arrival time of each trailer to each replacement point, and the tractor unit status data of each transport vehicle, replacement points that each trailer can reach are determined from each replacement point. Based on the battery status data of each charging vehicle at the replacement points that each trailer can reach, the charging completion time of each charging vehicle at the reachable replacement points is determined. Based on the charging completion time of each charging vehicle at the replacement points that each trailer can reach, candidate replacement points are determined from the replacement points that each trailer can reach.

[0052] Step 104: Based on the first fatigue characteristic data of the driver corresponding to each charging vehicle head in the candidate replacement points and the power status data of each charging vehicle head, determine the target replacement point for each trailer from the candidate replacement points.

[0053] Optionally, based on the first fatigue characteristic data of the driver corresponding to each charging vehicle in the candidate replacement points and the power status data of each charging vehicle, the charging vehicles are sorted, and the target replacement point for each trailer is determined from the candidate replacement points based on the sorting results of each charging vehicle.

[0054] For example, if there are two replacement points, A and B, as candidate replacement points, all charging vehicles at replacement points A and B are sorted. If the charging vehicle at replacement point A is ranked higher, then replacement point A is determined as the target replacement point.

[0055] Step 105: Based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each transport vehicle head, issue a first vehicle head replacement scheduling request for each trailer to instruct the transport vehicle head corresponding to each trailer to travel to the target replacement point for vehicle head replacement.

[0056] Optionally, the replacement priority of each transport vehicle head is determined based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each transport vehicle head. Based on the replacement priority of each transport vehicle head, a first vehicle head replacement scheduling request is issued for each trailer to instruct the transport vehicle head corresponding to each trailer to travel to the target replacement point for vehicle head replacement.

[0057] In this embodiment, the system acquires the battery status data of each charging locomotive at each of the multiple replacement points on the target transportation route, as well as the first fatigue characteristic data of the driver corresponding to each charging locomotive; it also acquires the driving status data of each trailer, the locomotive status data of each transport locomotive, and the second fatigue characteristic data of the driver corresponding to each transport locomotive in the target heavy truck fleet; based on the driving status data of each trailer, the battery status data of each charging locomotive at each replacement point, and the locomotive status data of each transport locomotive, candidate replacement points are determined from the multiple replacement points; based on the first fatigue characteristic data of the driver corresponding to each charging locomotive and the battery status data of each charging locomotive at the candidate replacement points, target replacement points for each trailer are determined from the candidate replacement points, enabling intelligent matching of replacement points. Based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each transport locomotive, a first locomotive replacement scheduling request is issued for each trailer to instruct the transport locomotive corresponding to each trailer to drive to the target replacement point for locomotive replacement, enhancing driver safety. This application replaces each transport vehicle head by setting up replacement points, eliminating the need to build battery swapping stations, reducing the energy replenishment cost for each trailer, and also enabling energy replenishment for electric heavy-duty trucks even when the battery models of the electric heavy-duty trucks are different, thus improving the universality of energy replenishment for electric heavy-duty trucks.

[0058] Based on the above embodiments, this application also provides a process for determining candidate changeover points in a multi-node coordinated transportation scheduling method for heavy truck fleets. Figure 2 This is a flowchart illustrating the process of determining candidate replacement points in a multi-node coordinated transportation scheduling method for heavy truck fleets provided in an embodiment of this application. Figure 2 As shown, in step 103 above, candidate replacement points are determined from multiple replacement points based on the driving status data of each trailer, the battery status data of each charging head at each replacement point, and the head status data of each transport head, including:

[0059] Step 201: Based on the driving status data of each trailer, obtain the estimated arrival time of each trailer for each changeover point.

[0060] Optionally, based on the location information in the driving status data of each trailer and the location information of each replacement point, a preset distance calculation formula is used to calculate the distance from each trailer to each replacement point.

[0061] For example, the preset distance calculation formula can be formula (1), and the distance from each trailer to each replacement point can be calculated using formula (1).

[0062] (1)

[0063] The coordinates of the point to be replaced are ( The trailer's location information is ( ). ), This represents the distance from the trailer to each changeover point.

[0064] Optionally, based on the distance of each trailer to each replacement point, the real-time speed information of each trailer in the driving status data of each trailer, and the speed fluctuation noise of each trailer, a preset time calculation formula is used to calculate the estimated arrival time of each trailer for each replacement point.

[0065] For example, the preset time calculation formula can be formula (2), and the estimated arrival time of the trailer to each replacement point can be calculated by formula (2).

[0066] (2)

[0067] in, For trailer speed fluctuation noise, It follows a normal distribution with a mean of 0 and a standard deviation of 5, and is used to simulate speed changes during actual driving. This is the distance from the trailer to the changeover point. This provides real-time speed information for the trailer. This represents the estimated arrival time of the trailer at each changeover point.

[0068] Step 202: Determine the remaining charging time for each charging vehicle based on its battery status data.

[0069] Optionally, the remaining charging time for each charging vehicle can be determined based on the charging end time and the current time in the power status data of each charging vehicle.

[0070] Step 203: Based on the vehicle head status data of each transport vehicle head, determine the arrival and replacement time of each transport vehicle head for each replacement point.

[0071] The carrier truck head is the cab of each trailer, excluding the trailer body. The carrier truck head can be charged to replenish the power of the trailer.

[0072] Optionally, based on the position information in the vehicle head status data of each transport vehicle head and the position information of each replacement point, a preset distance calculation formula is used to calculate the distance from each transport vehicle head to each replacement point.

[0073] Optionally, the estimated arrival time of each transport vehicle for each replacement point can be calculated based on the distance from each transport vehicle to each replacement point and the real-time speed information of each transport vehicle.

[0074] Step 204: Based on the remaining charging time of each charging vehicle head, the arrival and replacement time of each transport vehicle head at each replacement point, and the estimated arrival time of each trailer at each replacement point, determine whether each trailer meets the vehicle head replacement readiness conditions at each replacement point.

[0075] Optionally, based on the remaining charging time of each charging head, the arrival and replacement time of each transport head at each replacement point, and the estimated arrival time of each trailer at each replacement point, it is determined whether each charging head can be charged and ready before the trailer arrives. If there is a charging head that can be charged and ready before the trailer arrives, then it is determined that each trailer meets the head-changing readiness condition at each replacement point.

[0076] Step 205: Select candidate replacement points from multiple replacement points that meet the conditions for tractor replacement readiness and whose distance from each trailer is within a preset distance range.

[0077] The preset distance range can be determined based on the corrected effective range of the trailer. The corrected effective range can be determined based on the cab load of each trailer, the maximum cab load of the trailer, the real-time slope of each trailer, the current temperature, and the preset effective range calculation formula.

[0078] For example, the preset effective range calculation formula can be formula (3).

[0079] (3)

[0080] in, This is the corrected effective range for the trailer. To extend the trailer's range when fully loaded, For the trailer's cab to carry loads, This is the maximum load capacity of the trailer tractor. This is the real-time slope of the trailer. Real-time temperature.

[0081] Optionally, from multiple replacement points, the conditions for meeting the requirements for changing the tractor unit are determined. The distances between the multiple replacement points and each trailer are compared with the preset distance ranges, and the replacement points within the preset distance ranges of each trailer are selected as candidate replacement points.

[0082] In this embodiment, based on the remaining charging time of each charging tractor, the arrival and replacement time of each transport tractor at each replacement point, and the estimated arrival time of each trailer at each replacement point, it is determined whether each trailer meets the tractor-to-trailer readiness condition for each replacement point. Replacement points within a preset distance range are selected as candidate replacement points from multiple replacement points. This application ensures that when a trailer arrives, a ready charging tractor exists among the candidate replacement points, thereby improving the charging efficiency of the tractors.

[0083] Based on the above embodiments, this application also provides a process for determining the readiness conditions of tractor units in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 3 This application provides a flowchart illustrating the process of determining the readiness conditions of a tractor unit in a multi-node collaborative transportation scheduling method for heavy truck fleets, as shown in the embodiments of this application. Figure 3 As shown, in step 204 above, based on the remaining charging time of each charging vehicle, the arrival and replacement time of each transport vehicle at each replacement point, and the estimated arrival time of each trailer at each replacement point, it is determined whether each trailer meets the vehicle replacement readiness conditions at each replacement point, including:

[0084] Step 301: Determine the minimum time from the remaining charging time of each charging vehicle head and the arrival time of each transport vehicle head for each replacement point as the replacement ready time for each transport vehicle head.

[0085] Optionally, the remaining charging time of each charging vehicle head is used to indicate the completion time of each charging vehicle head, and the minimum of the arrival time of each transport vehicle head at the replacement point and the remaining charging time of each charging vehicle head is used to indicate that the charging of each charging vehicle head is completed and the transport vehicle head has arrived at the replacement point.

[0086] Example: Replacement readiness time for each carrier vehicle. It can be based on the remaining charging time of each charging station. Each transport vehicle head has a designated arrival and replacement time at each replacement point. The minimum time is determined as the replacement readiness time for each transport vehicle head, which is the replacement readiness time for each transport vehicle head. .

[0087] Step 302: Determine the estimated arrival time of each trailer for each replacement point, and the sum of the first preset buffer time as the replacement reference time for each trailer.

[0088] Optionally, the first preset buffer time is determined based on the current driving route, current temperature, current weather, and current driving speed of each trailer; this embodiment does not impose any limitations on this. The replacement reference time for each trailer is used to indicate the maximum replacement readiness time for each trailer, and the replacement readiness time for each trailer is less than or equal to the replacement reference time for each trailer.

[0089] For example, the reference time for replacing each trailer can be the estimated arrival time of each trailer for each replacement point. and the first preset buffer time sum.

[0090] Step 303: If the replacement readiness time corresponding to each transport vehicle head is less than or equal to the replacement reference time of each trailer, then it is determined that each trailer meets the vehicle head replacement readiness condition at each replacement point.

[0091] Optionally, if the replacement readiness time corresponding to each transport vehicle head is less than or equal to the replacement reference time of each trailer, then each trailer is determined to meet the vehicle head replacement readiness condition at each replacement point. If the replacement readiness time corresponding to each transport vehicle head is greater than the replacement reference time of each trailer, it means that after the first preset buffer time has elapsed since each trailer arrived at the replacement point, there is still no ready charging vehicle head available, and then each trailer is determined not to meet the vehicle head replacement readiness condition at each replacement point.

[0092] For example, when Then, it is determined that each trailer meets the ready conditions for changing the locomotive at each changing point.

[0093] In this embodiment, the conditions for switching truck heads are determined based on the earliest available time of the charging truck head and the latest acceptable time of each trailer. This allows for precise time matching of the charging truck head and each trailer, avoiding long waiting times for trailers due to charging delays or truck head scheduling delays, thereby optimizing resource utilization and improving scheduling robustness.

[0094] Based on the above embodiments, this application also provides a process for determining the target changeover point in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 4 This is a flowchart illustrating the process of determining the target change point in the multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application, as shown below. Figure 4 As shown, in step 104 above, based on the first fatigue characteristic data of the driver corresponding to each charging vehicle in the candidate replacement points and the power status data of each charging vehicle, the target replacement point for each trailer is determined from the candidate replacement points, including:

[0095] Step 401: Based on the first fatigue characteristic data of the driver corresponding to each charging vehicle in the candidate replacement points and the power status data of each charging vehicle, obtain the comprehensive evaluation index of each charging vehicle in the candidate replacement points.

[0096] Optionally, based on the first fatigue characteristic data of the driver corresponding to each charging head at the replacement point and the power status data of each charging head, a comprehensive evaluation index for each charging head at the candidate replacement point is calculated using a preset comprehensive evaluation formula.

[0097] For example, the preset comprehensive evaluation formula can be formula (4).

[0098] (4)

[0099] in, Comprehensive evaluation indicators The current remaining power (kWh) of each charging vehicle. The charging head has a full charge capacity (kWh). is the weight coefficient, The weighting coefficients are determined based on the actual situation. The fatigue coefficient, The larger the value, the more fatigued the driver.

[0100] Optionally, each trailer continues to perform its dispatching task according to its assigned order, and enters a rest period after completing its task. After a trailer has rested for a period of time, the charging locomotive is fully charged, and the driver's rest period is deemed adequate. The charging locomotives are then sorted in descending order based on comprehensive evaluation indicators and assigned to the queue accordingly. A fully charged locomotive indicates that its battery level has recovered to over 80%, and a driver's rest period is deemed adequate, indicating that the driver's rest time exceeds 20 minutes.

[0101] Step 402: Sort the candidate replacement points according to the comprehensive evaluation index of each charging vehicle head in the candidate replacement points.

[0102] Optionally, based on the comprehensive evaluation index of each charging vehicle in the candidate replacement points, the charging vehicles are sorted from high to low according to the comprehensive evaluation index, and the candidate replacement points are sorted according to the sorting of the charging vehicles.

[0103] Step 403: Based on the ranking, determine the replacement point with the highest comprehensive evaluation index from the candidate replacement points as the target replacement point.

[0104] Optionally, the charging vehicle with the highest comprehensive evaluation index is determined according to the ranking, and the replacement point where the charging vehicle with the highest comprehensive evaluation index is located is used as the target replacement point.

[0105] For example, Figure 5 This is a schematic diagram of trailer fleet management in a multi-node collaborative transportation scheduling method for heavy truck fleets provided in an embodiment of this application, as shown below. Figure 5 As shown, each trailer queues in the order of departure. When a trailer needs to change its tractor unit and arrives at the target replacement point, the corresponding carrier tractor unit is replaced with a charging tractor unit according to the charging tractor unit's order. At this point, the carrier tractor unit becomes the charging tractor unit, and it is added to the end of the charging queue to replenish its power. When the charging tractor unit is fully charged, meaning its battery level has recovered to over 80% and the driver's rest period exceeds 20 minutes, the charging tractor units that meet the comprehensive evaluation criteria of having over 80% battery level and having exceeded 20 minutes of rest time are then prioritized, and the charging tractor unit is replaced with the carrier tractor unit according to this priority.

[0106] In this embodiment, a comprehensive evaluation index for each charging vehicle among the candidate replacement points is obtained based on the first fatigue characteristic data of the driver corresponding to each charging vehicle and the battery status data of each charging vehicle. The candidate replacement points are then ranked according to this comprehensive evaluation index, and the replacement point containing the charging vehicle with the highest comprehensive evaluation index is selected as the target replacement point. This application calculates the comprehensive evaluation index based on driver fatigue characteristic data and vehicle battery status data, balancing driver fatigue levels and vehicle battery status data. By using multi-dimensional data to make decisions on the target replacement point, it avoids the bias of a single dimension and optimizes resource allocation efficiency.

[0107] Based on the above embodiments, this application also provides a process for determining a scheduling request in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 6 This is a flowchart illustrating the process of determining a scheduling request in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application, as shown below. Figure 6 As shown, before issuing the first truck head replacement scheduling request for each trailer based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each truck head in step 105 above, the method further includes:

[0108] Step 601: Calculate the first reference time for each trailer based on the difference between the estimated arrival time of each trailer at the target change point and the first preset time.

[0109] The first preset duration is determined based on the driving environment and driving status of each trailer; for example, it can be ten minutes.

[0110] For example, the estimated arrival time of each trailer at the target changeover point. Subtract the difference of the first preset duration of 10 to obtain the first reference time for each trailer. .

[0111] In step 105 above, based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each transport vehicle head, a first vehicle head replacement scheduling request is issued for each trailer, including:

[0112] Step 602: If the replacement readiness time corresponding to each transport vehicle head is less than or equal to the first reference time of the corresponding trailer, and the second fatigue characteristic data of the driver corresponding to each transport vehicle head is less than or equal to the preset fatigue lower limit threshold, then issue a first vehicle head replacement scheduling request for the corresponding trailer according to the target replacement point.

[0113] The preset fatigue threshold can be determined based on the driver's average age, current environmental parameters, and the distance of the driving segment; for example, it can be 0.3. The first locomotive replacement dispatch request is to maintain the current dispatch plan.

[0114] For example, if the replacement readiness time for each carrier head is... Less than or equal to the first reference time of the corresponding trailer This indicates that the charging vehicle's readiness time is much earlier than the trailer's arrival time, and the second fatigue characteristic data of the driver corresponding to each transport vehicle is... If the value is less than or equal to the preset fatigue lower limit threshold of 0.3, it indicates that the driver's fatigue level is low. If the replacement readiness time corresponding to each transport vehicle head is less than or equal to the first reference time of the corresponding trailer, and the second fatigue characteristic data of the driver corresponding to each transport vehicle head is less than or equal to the preset fatigue lower limit threshold, it means that the charging vehicle head is ready earlier than the arrival time of each trailer and the driver's fatigue level is low. Then, based on the target replacement point, a request to maintain the current scheduling plan for the corresponding trailer is issued.

[0115] In this embodiment, a first reference time for each trailer is calculated based on the difference between the estimated arrival time of each trailer at the target replacement point and a first preset duration. If the replacement readiness time corresponding to each tractor unit is less than or equal to the first reference time of the corresponding trailer, and the second fatigue characteristic data of the driver corresponding to each tractor unit is less than or equal to a preset fatigue lower limit threshold, then a first tractor unit replacement scheduling request is issued for the corresponding trailer based on the target replacement point. This application ensures that the charging tractor unit replacement readiness time is strictly aligned with the trailer's demand time by setting a first preset duration, reducing empty running waiting time and improving tractor unit replacement efficiency.

[0116] Based on the above embodiments, this application also provides a process for determining scheduling requests in another multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 7 A flowchart illustrating the process of determining a scheduling request in another multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application embodiment is shown below. Figure 7 As shown, based on steps 601-602 above, the method further includes:

[0117] Step 701: Calculate the second reference time for each trailer based on the sum of the estimated arrival time of each trailer at the target change point and the second preset duration.

[0118] The second preset duration is determined based on the driving environment and driving status of each trailer; for example, it can be five minutes. The second reference time is longer than the first reference time.

[0119] For example, the estimated arrival time of each trailer for the target changeover point. Adding the sum of the second preset durations, we obtain the second reference time for each trailer. .

[0120] Step 702: If the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer and less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, then according to the target replacement point, an acceleration command is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to accelerate to the target replacement point for vehicle head replacement.

[0121] The preset fatigue limit threshold can be determined based on parameters such as the driver's average age, current environmental parameters, and the distance of the driving segment. This application embodiment does not impose any restrictions on this, and for example, it can be 0.7.

[0122] For example, if the replacement readiness time corresponds to each transport vehicle head... Greater than the first reference time for the corresponding trailer Less than or equal to the second reference time of the corresponding trailer This indicates that the replacement readiness time for each transport vehicle head is close to, but within a reasonable range, the arrival time of each trailer.

[0123] For example, the second fatigue characteristic data of the drivers corresponding to each transport vehicle. If the fatigue level is greater than the preset lower fatigue threshold of 0.3 but less than or equal to the preset upper fatigue threshold of 0.7, it indicates that the driver is fatigued to a certain extent.

[0124] Optionally, if the replacement readiness time corresponding to each tractor unit is greater than the first reference time of the corresponding trailer but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, it indicates that there is a situation where the replacement readiness time corresponding to each tractor unit is close to the arrival time of each trailer but does not exceed a reasonable range, or the driver corresponding to the tractor unit has a certain degree of fatigue. In this case, an acceleration command is issued for the corresponding trailer to instruct the tractor unit of the corresponding trailer to accelerate to the target replacement point for tractor unit replacement.

[0125] Alternatively, proceed to step 703.

[0126] Step 703: If the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer and less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, then according to the nearest replacement point of the target replacement point, a second vehicle head replacement scheduling request is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to travel to the nearest replacement point, and the spare vehicle head at the nearest replacement point is used for vehicle head replacement.

[0127] The second replacement dispatch request is used to indicate a request to change the replacement point for the corresponding trailer.

[0128] Optionally, if the remaining mileage of each trailer is short or the road conditions are good, then step 702 is executed; otherwise, step 703 is executed, thereby avoiding the risk of energy consumption surge or speeding caused by blind acceleration.

[0129] Optionally, if the replacement readiness time corresponding to each tractor unit is greater than the first reference time of the corresponding trailer but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, it indicates that there is a situation where the replacement readiness time corresponding to each tractor unit is close to the arrival time of each trailer but does not exceed a reasonable range, or the driver corresponding to the tractor unit has a certain degree of fatigue. In this case, based on the nearest replacement point of the target replacement point, a second tractor unit replacement scheduling request is issued for the corresponding trailer to instruct the tractor unit of the corresponding trailer to travel to the nearest replacement point, and the spare tractor unit at the nearest replacement point is used for tractor unit replacement.

[0130] Optionally, if the replacement readiness time corresponding to each tractor unit is greater than the first reference time of the corresponding trailer but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, it indicates that there is a situation where the replacement readiness time corresponding to each tractor unit is close to the arrival time of each trailer but does not exceed a reasonable range, or the driver corresponding to the tractor unit has a certain degree of fatigue. In this case, an acceleration command is issued for the corresponding trailer to instruct the tractor unit of the corresponding trailer to accelerate to the target replacement point for tractor unit replacement. Alternatively, an acceleration command is issued for the corresponding trailer, and simultaneously, based on the nearest replacement point to the target replacement point, a second tractor unit replacement scheduling request is issued to instruct the tractor unit of the corresponding trailer to travel to the nearest replacement point, and a spare tractor unit at the nearest replacement point is used for tractor unit replacement.

[0131] In this embodiment, if the replacement readiness time for each tractor unit is greater than the first reference time for the corresponding trailer but less than or equal to the second reference time for the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than a preset lower fatigue threshold but less than or equal to a preset upper fatigue threshold, then an acceleration command is issued for the corresponding trailer based on the target replacement point, instructing the tractor unit of the corresponding trailer to accelerate to the target replacement point for tractor unit replacement. Alternatively, based on a nearby replacement point of the target replacement point, a second tractor unit replacement scheduling request is issued for the corresponding trailer, instructing the tractor unit of the corresponding trailer to travel to the nearby replacement point, and using a spare tractor unit at the nearby replacement point for tractor unit replacement. This application optimizes scheduling resources based on tractor unit replacement readiness time or driver fatigue level, thereby balancing timeliness and energy consumption costs and reducing the probability of overall scheduling failure due to insufficient local resources.

[0132] Based on the above embodiments, this application also provides a process for determining a scheduling request in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 8 A flowchart illustrating the process of determining a scheduling request in another multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application embodiment is shown below. Figure 8 As shown, based on steps 701-703 above, the method further includes:

[0133] Step 801: If the replacement readiness time corresponding to each transport vehicle head is greater than the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset fatigue upper limit threshold, then activate the standby vehicle head at each replacement point.

[0134] Optionally, if the replacement readiness time for each tractor unit is greater than the second reference time for the corresponding trailer, it indicates that the replacement time for each tractor unit is significantly delayed compared to the arrival time of the trailer.

[0135] Optionally, if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset fatigue upper limit threshold, it indicates that the fatigue level of the driver corresponding to the transport vehicle head is very high.

[0136] Optionally, if the replacement readiness time for each tractor unit is greater than the second reference time for the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than a preset fatigue upper limit threshold, then there exists at least one of the following situations: the replacement time for each tractor unit is significantly delayed compared to the trailer arrival time, or the driver corresponding to the tractor unit is highly fatigued. In this case, an emergency replacement of the tractor unit is required, and the standby tractor unit at each replacement point is activated. After the trailer arrives at the replacement point, the driver is forced to rest for at least 40 minutes to avoid driver fatigue during transport.

[0137] Step 802: Determine the path loss parameters from each transport vehicle head to each replacement point.

[0138] Among them, the path loss parameter is used to reflect the congestion level, charging time, and negative impact of driver fatigue on each path.

[0139] For example, based on the congestion level, charging time, and driver fatigue level of each route, a weighting coefficient is determined for each route, and the path loss parameters from each transport vehicle head to each replacement point are determined based on the weighting coefficient of each route.

[0140] Step 803: Determine the replacement point with the minimum path loss parameter from multiple replacement points as the nearest replacement point, and initiate a dynamic driving route for the corresponding trailer to the nearest replacement point, so as to instruct the corresponding trailer to drive to the nearest replacement point first for tractor replacement.

[0141] Optionally, the path loss parameters of multiple paths from the corresponding trailer to multiple replacement points are calculated respectively. Based on the path loss parameters of multiple paths, the replacement point corresponding to the path with the smallest path loss parameter is determined as the nearest replacement point. A dynamic driving route is initiated to the corresponding trailer for the nearest replacement point to instruct the corresponding trailer to drive to the nearest replacement point first for tractor replacement.

[0142] In this embodiment, if the replacement readiness time corresponding to each tractor unit is greater than the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each tractor unit is greater than a preset fatigue upper limit threshold, then the standby tractor units at each replacement point are activated. The path loss parameters from each tractor unit to each replacement point are determined, and the replacement point with the smallest path loss parameter is selected as the nearest replacement point from among multiple replacement points. A dynamic driving route is then initiated to the corresponding trailer for the nearest replacement point. This application determines the corresponding replacement point through path loss parameters, ensuring scientific route selection and improving resource utilization. Simultaneously, generating dynamic priorities based on real-time multi-dimensional data and combining edge computing to achieve distributed decision-making can avoid congestion caused by centralized tractor unit replacement and improve the throughput of multiple replacement points. Furthermore, by intelligently determining replacement points, the empty running rate of trailers and the risk of fatigue accidents are reduced, energy utilization is improved, and transportation safety is ensured, achieving efficient and low-carbon logistics management through human-vehicle-road collaboration.

[0143] Based on the above embodiments, this application also provides a process for determining path loss parameters in a multi-node collaborative transportation scheduling method for heavy truck fleets. In step 802 above, the path loss parameters from each transport vehicle to each changeover point are determined, including:

[0144] Based on the charging demand of each replacement point, the second fatigue characteristic data of the driver corresponding to each transport vehicle, and the real-time traffic data from each transport vehicle to each replacement point, the path loss parameters from each transport vehicle to each replacement point are calculated.

[0145] Among them, the charging demand of the vehicle head at each replacement point is the shortest remaining charging time of the charging vehicle head, and the real-time traffic data from each transport vehicle head to each replacement point includes: road congestion data.

[0146] Optionally, based on the charging demand of the vehicle head at each replacement point, the second fatigue characteristic data of the driver corresponding to each transport vehicle head, and the real-time traffic data from each transport vehicle head to each replacement point, a preset path loss parameter calculation formula is used to calculate the path loss parameters from each transport vehicle head to each replacement point.

[0147] For example, the formula for calculating the preset path loss parameter can be formula (5).

[0148] (5)

[0149] in, For path loss parameters, This refers to the distance from the transport vehicle head to the replacement point. This represents the real-time speed of the trailer corresponding to the transport tractor. This is the congestion coefficient; the more severe the congestion, the higher the coefficient. The larger, This refers to the shortest remaining charging time for the charging vehicle at the replacement point. This is used to indicate whether the charging head is in a charging state corresponding to the shortest remaining charging time. This provides the second fatigue characteristic data for the drivers corresponding to each transport vehicle. This represents the fatigue coefficient.

[0150] In this embodiment, based on the charging demand of the vehicle at each replacement point, the second fatigue characteristic data of the driver corresponding to each vehicle, and the real-time traffic data from each vehicle to each replacement point, path loss parameters from each vehicle to each replacement point are calculated. This application can avoid driver fatigue, thereby reducing the accident rate during vehicle operation.

[0151] Based on the above embodiments, this application also provides a process for determining scheduling parameters in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 9 This is a flowchart illustrating the determination of scheduling parameters in a multi-node collaborative transportation scheduling method for a heavy truck fleet provided in an embodiment of this application, as shown below. Figure 9 As shown, based on steps 101-106 above, the method further includes:

[0152] Step 901: Determine the working cycle of a single vehicle head based on the preset single-segment driving time, preset charging recovery time, and second preset buffer time.

[0153] The preset single-segment travel time is the average travel time for each trailer between preset replacement points. The second preset buffer time is determined based on the actual driving environment of the trailer and is greater than or equal to six minutes. Specifically, the driving environment may include information such as road conditions and weather, which is not limited in this embodiment. The preset charging recovery time includes charging time and replacement time. The preset charging recovery time is the sum of charging time and recovery time.

[0154] Optionally, the effective range of the trailer is calculated based on its full-load range, where the effective range can be 80% of the full-load range. Based on the effective range and the average speed of the trailer on the target transport route, the preset single-segment travel time of the trailer on the target transport route is determined. The working cycle of a single tractor unit is determined based on the preset single-segment travel time, the preset charging recovery time, and the second preset buffer time.

[0155] For example, based on the trailer's full-load range The effective range of the trailer was calculated. Therefore, based on the effective range of the trailer and the average speed of the trailer on the target transport route. Determine the preset single-segment travel time of the trailer on the target transport route. Based on the preset single-segment travel time and charging time. Recovery time and the second preset buffer time Determine the working cycle of a single locomotive. .

[0156] Step 902: Calculate the required number of trucks for a single trailer based on the working cycle of a single truck head and the preset travel time for a single road segment.

[0157] Optionally, based on the working cycle of a single locomotive. And preset single-segment travel time Calculate the required number of tractors for a single trailer. .

[0158] Step 903: Calculate the lower limit of the total number of tractors required for the target heavy truck fleet based on the number of trailers in the target heavy truck fleet and the number of tractors required per trailer.

[0159] Optionally, based on the number of trailers in the target heavy truck fleet And the required number of trailers Calculate the lower limit of the total demand for truck heads of the target heavy truck fleet. .in, This is the redundancy coefficient. The value ranges from 0.1 to 0.2. Greater than the number of replacement points.

[0160] For example, if the target transport route requires at least [number] trailers... There are 3 tractor units and a total of 10 trailer units. It is 5. If it is 0.1, then , The target heavy truck fleet's total demand for truck heads is a minimum of 16.5, rounded up to 17 vehicles.

[0161] For example, when the queue length of the target heavy-duty truck fleet exceeds 1.2 times the lower limit of the total demand for truck heads, a diversion mechanism is activated. Multiple trailers in the target heavy-duty truck fleet are diverted to nearby charging stations to avoid overloading of charging piles at a single charging station and causing vehicle congestion. The value can be 1.2 times or other multiples; this embodiment does not limit this.

[0162] Step 904: Based on the lower limit of the total demand for truck heads in the target heavy truck fleet, allocate truck head resources for each replacement point.

[0163] Optionally, based on the lower limit of the total demand for truck heads of the target heavy truck fleet, the usage frequency of each replacement point is determined. More truck head resources are allocated to replacement points with high usage frequency, and fewer truck head resources are allocated to replacement points with low usage frequency, so that the sum of the total truck head resources of all replacement points equals the lower limit of the total demand for truck heads.

[0164] Optionally, 10% of spare locomotives can be pre-stored at frequently used replacement points to cope with emergencies. Emergencies could include equipment failures, extreme weather, etc.

[0165] Step 905: Determine the optimal departure interval based on the number of trailers in the target heavy truck fleet, the minimum total demand for truck heads, the working cycle of a single truck head, and the number of multiple changeover points. The optimal departure interval is the departure time of two adjacent trailers in the target heavy truck fleet.

[0166] The optimal departure interval is the departure time of two adjacent trailers in the target heavy truck fleet.

[0167] Optionally, the optimal departure interval can be determined by using a preset interval calculation formula based on the number of trailers in the target heavy truck fleet, the minimum total demand for truck heads, the working cycle of a single truck head, and the number of multiple changeover points.

[0168] For example, the preset interval calculation formula can be formula (6).

[0169] (6)

[0170] in, To achieve the optimal departure interval, For the number of trailers, This represents the lower limit of the total demand for locomotives. This refers to the working cycle of a single locomotive. and ,most This ensures the full-day recycling rate of trailer resources. This ensures that the charging recovery cycle of the vehicle head matches the dispatch frequency. The number of replacement points depends on the target transportation route. and the effective range of the trailer Specific, concrete .

[0171] In this embodiment of the application, the optimal departure interval is determined by using a preset interval calculation formula based on the number of trailers in the target heavy truck fleet, the lower limit of the total demand for tractor units, the working cycle of a single tractor unit, and the number of multiple replacement points. This can achieve optimal asset allocation, ensure the full-day recycling rate of trailer resources, and match the charging recovery cycle of tractor units with the scheduling frequency, thereby maximizing resource utilization.

[0172] Based on the above embodiments, this application also provides a process for determining priority evaluation parameters in a multi-node collaborative transportation scheduling method for heavy truck fleets. Figure 10 This is a flowchart illustrating the process of determining priority evaluation parameters in a multi-node collaborative transportation scheduling method for heavy truck fleets provided in an embodiment of this application, as shown below. Figure 10 As shown, based on steps 101-106 above, the method further includes:

[0173] Step 1001: Based on the cargo timeliness information, endurance status information, second fatigue characteristic data of the driver of the corresponding transport vehicle, and load information of the target replacement point, determine the priority evaluation parameters of each trailer for the target replacement point.

[0174] The evaluation dimension for cargo timeliness information is the type of transported goods. This information can be obtained from cargo order tags; for example, fresh produce and medical supplies have higher weightings. The evaluation dimension for range status information is the remaining range percentage. This information can be obtained from the battery management system. For example, when the range status information indicates a battery charge level of less than 30%, it has higher priority, prioritizing emergency charging needs. The evaluation dimension for the driver's second fatigue characteristic data is the fatigue score. This data can be obtained from fatigue monitoring sensors. For example, when the second fatigue characteristic data is greater than 0.6, it has higher priority, prioritizing driver rest. The evaluation dimension for the target replacement point's load information is the charging pile at the replacement point. This load information can be obtained from the site's IoT data. For example, when the target replacement point's load is greater than 80%, it has higher priority, triggering a diversion signal.

[0175] Step 1002: Based on the priority evaluation parameters of each trailer for the target replacement point, issue the first tractor replacement scheduling request for each trailer in sequence, so as to instruct each trailer to drive to the target replacement point in sequence for tractor replacement.

[0176] Optionally, when the priority evaluation parameters of each trailer for the target replacement point are the same, the first tractor replacement scheduling request for each trailer is issued in sequence according to the arrival time, so as to instruct each trailer and its corresponding tractor to travel to the target replacement point in sequence for tractor replacement.

[0177] For example, if the cargo timeliness information is high, the endurance status information indicates low endurance, and the second fatigue characteristic data indicates high driver fatigue, then the corresponding trailer has a higher priority, and a replacement scheduling request for that trailer is sent first.

[0178] Optionally, the priority evaluation parameters of each trailer for non-urgent tasks at the target replacement point are updated according to a preset time threshold to ensure that the priority evaluation parameters are real-time data. The preset time threshold can be two minutes.

[0179] The following describes the multi-node collaborative transportation scheduling method for heavy truck fleets provided in this application, with reference to a scenario diagram. Figure 11 This application provides a multi-node collaborative transportation scheduling scenario diagram for a heavy truck fleet, as shown in the embodiments of this application. Figure 11As shown, when each trailer is traveling on the target transportation route, S is the starting point of the target transportation route, T is the ending point of the target transportation route, and P0 represents the positions of multiple change points during the journey from the starting point S to the ending point T on the target transportation route, including P01, P02, P03...P0n. During the journey, each trailer is scheduled according to the multi-node collaborative transportation scheduling method of the heavy truck fleet described above. When a trailer reaches its destination, it returns from the ending point T to the starting point S. Pi represents the change point positions during the journey from the ending point T to the starting point S on the target transportation route, including Pi1, Pi2, Pi3...Pin. During the return journey, each trailer is scheduled according to the multi-node collaborative transportation scheduling method of the heavy truck fleet described above.

[0180] Based on the same inventive concept, this application also provides a multi-node collaborative transportation scheduling device for heavy truck fleets, which corresponds to the multi-node collaborative transportation scheduling method for heavy truck fleets. Since the principle of the device in this application is similar to the multi-node collaborative transportation scheduling method for heavy truck fleets described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0181] Figure 12 This is a schematic diagram of a multi-node collaborative transportation scheduling device for a heavy truck fleet provided in an embodiment of this application. The device includes: an acquisition module 1201, a determination module 1202, and a sending module 1203. The acquisition module 1201 is used to acquire the battery status data of each charging vehicle at each of the multiple replacement points on the target transportation route, and the first fatigue characteristic data of the driver corresponding to each charging vehicle; and to acquire the driving status data of each trailer, the vehicle head status data of each transport vehicle, and the second fatigue characteristic data of the driver corresponding to each transport vehicle in the target heavy truck fleet.

[0182] The determination module 1202 is used to determine candidate replacement points from multiple replacement points based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head; and to determine the target replacement point for each trailer from the candidate replacement points based on the first fatigue characteristic data of the driver corresponding to each charging head and the power status data of each charging head in the candidate replacement points.

[0183] The sending module 1203 is used to send a first tractor replacement scheduling request for each trailer based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each tractor, so as to instruct the tractor corresponding to each trailer to travel to the target replacement point for tractor replacement.

[0184] In one possible implementation, the determining module 1202 is specifically used to: obtain the estimated arrival time of each trailer for each changeover point based on the driving status data of each trailer;

[0185] Based on the battery status data of each charging station, determine the remaining charging time for each charging station;

[0186] Based on the status data of each transport vehicle, determine the arrival and replacement time of each transport vehicle for each replacement point;

[0187] Based on the remaining charging time of each charging head, the arrival and replacement time of each transport head at each replacement point, and the estimated arrival time of each trailer at each replacement point, determine whether each trailer meets the head-changing readiness conditions at each replacement point.

[0188] Candidate replacement points are selected from multiple replacement points that meet the conditions for tractor replacement readiness and are within a preset distance range from each trailer.

[0189] In one possible implementation, the determining module 1202 is specifically used to: determine the minimum time from the remaining charging time of each charging head and the arrival time of each transport vehicle head for each replacement point as the replacement ready time corresponding to each transport vehicle head.

[0190] The estimated arrival time of each trailer at each replacement point is determined, and the sum of the first preset buffer time is used as the replacement reference time for each trailer.

[0191] If the replacement readiness time for each tractor unit is less than or equal to the replacement reference time for each trailer, then each trailer is determined to meet the tractor unit replacement readiness condition at each replacement point.

[0192] In one possible implementation, the determining module 1202 is specifically used to: obtain a comprehensive evaluation index for each charging head in the candidate replacement points based on the first fatigue characteristic data of the driver corresponding to each charging head in the candidate replacement points and the power status data of each charging head.

[0193] The candidate replacement points are ranked according to the comprehensive evaluation indicators of each charging vehicle head in the candidate replacement points.

[0194] Based on the ranking, the replacement point with the highest comprehensive evaluation index among the candidate replacement points is selected as the target replacement point.

[0195] In one possible implementation, the sending module 1203 is further configured to: calculate a first reference time for each trailer based on the difference between the estimated arrival time of each trailer at the target change point and a first preset duration;

[0196] In one possible implementation, the sending module 1203 is specifically used to: if the replacement readiness time corresponding to each transport vehicle head is less than or equal to the first reference time of the corresponding trailer, and the second fatigue characteristic data of the driver corresponding to each transport vehicle head is less than or equal to the preset fatigue lower limit threshold, then according to the target replacement point, issue a first vehicle head replacement scheduling request for the corresponding trailer.

[0197] In one possible implementation, the sending module 1203 is further configured to: calculate a second reference time for each trailer based on the sum of the estimated arrival time of each trailer at the target change point and the second preset duration; the second reference time is greater than the first reference time.

[0198] If the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer and less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, then according to the target replacement point, an acceleration command is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to accelerate to the target replacement point for vehicle head replacement.

[0199] Alternatively, if the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold but less than or equal to the preset upper fatigue threshold, then based on the nearest replacement point of the target replacement point, a second vehicle head replacement scheduling request is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to travel to the nearest replacement point, and the spare vehicle head at the nearest replacement point is used for vehicle head replacement.

[0200] In one possible implementation, the sending module 1203 is further configured to: activate the standby vehicle head at each replacement point if the replacement readiness time corresponding to each transport vehicle head is greater than the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset fatigue upper limit threshold.

[0201] Determine the path loss parameters from each transport vehicle head to each replacement point;

[0202] The nearest replacement point is determined from multiple replacement points based on the path loss parameter. A dynamic driving route is then initiated for the corresponding trailer to prioritize driving to the nearest replacement point for tractor replacement.

[0203] If the replacement readiness time for each transport vehicle head is greater than the second reference time for the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset fatigue upper limit threshold, then the standby vehicle head at each replacement point will be activated.

[0204] Determine the path loss parameters from each transport vehicle head to each replacement point;

[0205] The nearest replacement point is determined from multiple replacement points based on the path loss parameter. A dynamic driving route is then initiated for the corresponding trailer to prioritize driving to the nearest replacement point for tractor replacement.

[0206] In one possible implementation, the sending module 1203 is specifically used to: calculate the path loss parameters from each vehicle head to each replacement point based on the charging demand of the vehicle head at each replacement point, the second fatigue characteristic data of the driver corresponding to each vehicle head, and the real-time traffic data from each vehicle head to each replacement point.

[0207] In one possible implementation, the determining module 1202 is specifically used to: determine the working cycle of a single vehicle head based on a preset single-segment driving time, a preset charging recovery time, and a second preset buffer time; wherein, the preset single-segment driving time is the average driving time corresponding to the preset replacement point spacing;

[0208] Calculate the required number of trucks for a single trailer based on the working cycle of a single truck head and the preset travel time for a single road segment;

[0209] Calculate the lower limit of the total demand for tractors for the target heavy truck fleet based on the number of trailers in the target heavy truck fleet and the number of tractors required per trailer.

[0210] Based on the lower limit of the total demand for truck heads for the target heavy truck fleet, allocate truck head resources for each replacement point;

[0211] The optimal departure interval is determined based on the number of trailers in the target heavy truck fleet, the minimum total demand for truck heads, the working cycle of a single truck head, and the number of multiple changeover points. The optimal departure interval is the departure time of two adjacent trailers in the target heavy truck fleet.

[0212] In one possible implementation, the determining module 1202 is specifically used to: determine the priority evaluation parameters of each trailer for the target replacement point based on the cargo timeliness information, endurance status information, the second fatigue characteristic data of the driver of the corresponding carrier truck, and the load information of the target replacement point.

[0213] Based on the priority evaluation parameters of each trailer for the target replacement point, the first tractor replacement scheduling request is issued sequentially for each trailer to instruct each trailer to drive to the target replacement point for tractor replacement.

[0214] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0215] This application also provides a computer device. Figure 13 This application provides a schematic diagram of the structure of a computer device, as shown in the embodiment of the present application. Figure 13 As shown, the computer device includes: a processor 1301, a memory 1302, and optionally, a bus 1303. The memory 1302 stores machine-readable instructions executable by the processor 1301 (e.g., ...). Figure 12 The device includes a module 1201 for acquiring, a module 1202 for determining, and a module 1203 for sending execution instructions. When the computer device is running, the processor 1301 and the memory 1302 communicate via a bus 1303. When the machine-readable instructions are executed by the processor 1301, the steps of the multi-node collaborative transportation scheduling method for heavy truck fleets described above are executed.

[0216] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the multi-node collaborative transportation scheduling method for heavy truck fleets described above.

[0217] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0218] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0219] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A multi-node collaborative transportation scheduling method for heavy truck fleets, characterized in that, The method includes: Acquire the battery status data of each charging vehicle head at each of the multiple replacement points on the target transportation route, as well as the first fatigue characteristic data of the driver corresponding to each charging vehicle head; Acquire driving status data of each trailer in multiple trailers of the target heavy truck fleet, cab status data of each tractor unit, and second fatigue characteristic data of the drivers corresponding to each tractor unit; Based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head, candidate replacement points are determined from the plurality of replacement points. Based on the first fatigue characteristic data of the driver corresponding to each charging vehicle head and the power status data of each charging vehicle head in the candidate replacement points, the target replacement point for each trailer is determined from the candidate replacement points. Based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each transport vehicle head, a first vehicle head replacement scheduling request is issued for each trailer to instruct the transport vehicle head corresponding to each trailer to travel to the target replacement point for vehicle head replacement.

2. The method according to claim 1, characterized in that, The step of determining candidate replacement points from the plurality of replacement points based on the driving status data of each trailer, the power status data of each charging head at each replacement point, and the head status data of each transport head includes: Based on the driving status data of each trailer, the estimated arrival time of each trailer for each changeover point is obtained; Based on the battery status data of each charging vehicle, the remaining charging time of each charging vehicle is determined; Based on the vehicle head status data of each transport vehicle head, determine the arrival and replacement time of each transport vehicle head for each replacement point; Based on the remaining charging time of each charging head, the arrival and replacement time of each transport head at each replacement point, and the estimated arrival time of each trailer at each replacement point, determine whether each trailer meets the head-changing readiness condition at each replacement point. From the plurality of replacement points, the replacement points that meet the conditions for changing the tractor and whose distance from each trailer is within a preset distance range are selected as the candidate replacement points.

3. The method according to claim 2, characterized in that, The step of determining whether each trailer meets the truck head switching readiness condition at each switching point based on the remaining charging time of each charging truck head, the arrival and switching time of each transport truck head at each switching point, and the estimated arrival time of each trailer at each switching point includes: The minimum time is determined from the remaining charging time of each charging vehicle head and the arrival time of each transport vehicle head to each replacement point as the replacement ready time for each transport vehicle head. The estimated arrival time of each trailer for each replacement point and the sum of the first preset buffer time are determined as the replacement reference time for each trailer. If the replacement readiness time corresponding to each transport vehicle head is less than or equal to the replacement reference time of each trailer, then each trailer is determined to meet the vehicle head replacement readiness condition at each replacement point.

4. The method according to claim 1, characterized in that, The step of determining the target replacement point for each trailer from the candidate replacement points based on the first fatigue characteristic data of the driver corresponding to each charging vehicle and the battery status data of each charging vehicle in the candidate replacement points includes: Based on the first fatigue characteristic data of the driver corresponding to each charging head in the candidate replacement point and the power status data of each charging head, a comprehensive evaluation index of each charging head in the candidate replacement point is obtained. The candidate replacement points are ranked according to the comprehensive evaluation indicators of each charging vehicle head in the candidate replacement points; Based on the ranking, the replacement point with the highest comprehensive evaluation index among the candidate replacement points is selected as the target replacement point.

5. The method according to claim 3, characterized in that, Before issuing a first tractor replacement scheduling request for each trailer based on the target replacement point and the second fatigue characteristic data of the driver corresponding to each tractor unit, the method further includes: The first reference time for each trailer is calculated based on the difference between the estimated arrival time of each trailer at the target replacement point and the first preset time. The step of issuing a first tractor replacement scheduling request for each trailer based on the target replacement point and the second fatigue characteristic data of the drivers corresponding to each tractor unit includes: If the replacement readiness time corresponding to each transport vehicle head is less than or equal to the first reference time of the corresponding trailer, and the second fatigue characteristic data of the driver corresponding to each transport vehicle head is less than or equal to the preset fatigue lower limit threshold, then according to the target replacement point, a first vehicle head replacement scheduling request for the corresponding trailer is issued.

6. The method according to claim 5, characterized in that, The method further includes: The second reference time for each trailer is calculated based on the sum of the estimated arrival time of each trailer at the target replacement point and the second preset time; the second reference time is greater than the first reference time. If the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer, but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold, but less than or equal to the preset upper fatigue threshold, then according to the target replacement point, an acceleration command is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to accelerate to the target replacement point for head replacement; or... If the replacement readiness time corresponding to each transport vehicle head is greater than the first reference time of the corresponding trailer, but less than or equal to the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset lower fatigue threshold, but less than or equal to the preset upper fatigue threshold, then according to the nearest replacement point of the target replacement point, a second vehicle head replacement scheduling request is issued for the corresponding trailer to instruct the transport vehicle head of the corresponding trailer to travel to the nearest replacement point, and the spare vehicle head at the nearest replacement point is used for vehicle head replacement.

7. The method according to claim 6, characterized in that, The method further includes: If the replacement readiness time corresponding to each transport vehicle head is greater than the second reference time of the corresponding trailer, or if the second fatigue characteristic data of the driver corresponding to each transport vehicle head is greater than the preset fatigue upper limit threshold, then the standby vehicle head at each replacement point is activated. Determine the path loss parameters from each transport vehicle head to each replacement point; The nearest replacement point is determined from the multiple replacement points based on the path loss parameter. A dynamic driving route is then initiated for the corresponding trailer to the nearest replacement point, instructing the trailer to prioritize driving to the nearest replacement point for cab replacement.

8. The method according to claim 7, characterized in that, The determination of path loss parameters from each transport vehicle head to each replacement point includes: Based on the charging demand of the vehicle head at each replacement point, the second fatigue characteristic data of the driver corresponding to each vehicle head, and the real-time traffic data from each vehicle head to each replacement point, the path loss parameters from each vehicle head to each replacement point are calculated.

9. The method according to claim 1, characterized in that, The method further includes: The working cycle of a single vehicle head is determined based on the preset single-segment driving time, the preset charging recovery time, and the second preset buffer time; wherein, the preset single-segment driving time is the average driving time corresponding to the preset replacement point spacing; The required number of truck heads for a single trailer is calculated based on the working cycle of a single truck head and the preset single-segment travel time. Calculate the lower limit of the total number of tractors required for the target heavy truck fleet based on the number of trailers in the target heavy truck fleet and the number of tractors required for each trailer. Based on the lower limit of the total demand for truck heads for the target heavy truck fleet, truck head resources are allocated to each of the replacement points; The optimal departure interval is determined based on the number of trailers in the target heavy truck fleet, the lower limit of the total demand for truck heads, the working cycle of a single truck head, and the number of multiple changeover points. The optimal departure interval is the departure time of two adjacent trailers in the target heavy truck fleet.

10. The method according to claim 1, characterized in that, The method further includes: Based on the cargo timeliness information, endurance status information, second fatigue characteristic data of the driver of the corresponding carrier truck, and load information of the target replacement point, the priority evaluation parameters of each trailer for the target replacement point are determined. Based on the priority evaluation parameters of each trailer for the target replacement point, a first tractor replacement scheduling request is issued sequentially for each trailer to instruct the corresponding tractor of each trailer to travel to the target replacement point for tractor replacement.

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