Vehicle transfer method and device, transfer server and vehicle transfer server

Abstract

The present application relates to the technical field of vehicle transfer, in particular to a vehicle transfer method, device, transfer server and vehicle transfer server. A dynamic environment map corresponding to a target park is acquired; vehicle scheduling information corresponding to each transfer vehicle is generated according to the dynamic environment map; the vehicle scheduling information corresponding to each transfer vehicle is transmitted to each transfer vehicle and each site monitoring device, so that each transfer vehicle performs transfer based on the vehicle scheduling information, and each site monitoring device monitors each transfer vehicle based on the vehicle scheduling information. The problem of high manual dependence, poor flexibility and insufficient cloud coordination adaptability of the existing factory internal vehicle transfer technology is solved.

Description

Technical Field

[0001] This invention relates to the field of vehicle transfer technology, specifically to vehicle transfer methods, devices, transfer servers, and vehicle transfer servers. Background Technology

[0002] As the automotive industry accelerates its transformation towards intelligence, connectivity, and automation, the level of smart factory construction in vehicle manufacturing enterprises continues to improve. Among these processes, the vehicle assembly line roll-off stage, as a critical node in the factory's internal logistics, directly impacts vehicle quality, operational accuracy, and labor cost control, and is figuratively referred to as the factory's "dam." Currently, most factories still rely on professional drivers to manually operate transfer vehicles to complete the transfer of vehicles off the assembly line. This model not only incurs high labor costs and low operational efficiency but also carries the risk of damage such as scratches and collisions due to human error. Furthermore, it cannot achieve continuous 24 / 7 operation and is ill-suited to the high-efficiency operational requirements of a smart factory.

[0003] Existing vehicle-road-cloud collaborative technologies are mostly concentrated in public road scenarios such as urban expressways and restricted highways, primarily focusing on optimizing vehicle road safety and traffic efficiency. A comprehensive unmanned vehicle-road-cloud collaborative solution for the closed environment of factories has not yet been developed. Furthermore, existing vehicle transfer technologies generally have application limitations, failing to achieve multi-point, multi-link transfer connections, lacking deep integration capabilities between road perception and cloud collaboration, and failing to provide differentiated route customization solutions for transfer needs involving mixed vehicle types and different vehicle configurations. This makes it difficult to meet the requirements of complex and dynamic transfer scenarios within factories.

[0004] The current state of vehicle transfer technology within factories suffers from high reliance on manual labor, poor flexibility, and insufficient adaptability to vehicle-road-cloud collaboration. There is an urgent need for a vehicle-road-cloud collaborative solution that can overcome these limitations and achieve high-efficiency, high-precision, and high-safety operation of multiple transfer nodes throughout the entire process within the factory. Summary of the Invention

[0005] This invention provides a vehicle transfer method, device, transfer server, and vehicle transfer server to solve the problems of high reliance on manual labor, poor flexibility, and insufficient adaptability to vehicle-road-cloud collaboration in existing factory vehicle transfer technologies.

[0006] In a first aspect, the present invention provides a vehicle transfer method, applied to a transfer server in a vehicle transfer system, the vehicle transfer system also including at least one transfer vehicle and at least one site monitoring device, each site monitoring device being installed at a site corresponding to a target park; the transfer server is communicatively connected to each transfer vehicle and each site monitoring device, the method comprising: acquiring a dynamic environment map corresponding to the target park; and generating vehicle scheduling information corresponding to each transfer vehicle based on the dynamic environment map. The vehicle dispatch information corresponding to each transfer vehicle is transmitted to each transfer vehicle and each station monitoring device, so that each transfer vehicle can carry out transfers based on the vehicle dispatch information, and each station monitoring device can monitor each transfer vehicle based on the vehicle dispatch information.

[0007] The vehicle transfer method provided in this application obtains a dynamic environmental map corresponding to the target park. It can monitor the park's road network, obstacle distribution, station layout, and road condition changes in real time, providing accurate and real-time underlying geographic data support for vehicle dispatching and avoiding inaccurate dispatching due to lagging environmental information. Based on the dynamic environmental map, vehicle dispatching information for each transfer vehicle is generated. Intelligent planning is performed based on the real-time environmental situation, rationally allocating driving routes, transfer sequences, and station stopping arrangements to balance road network load, reduce vehicle conflicts, lower congestion and unnecessary detours, and improve overall transfer efficiency. Vehicle dispatching information is then distributed to transfer vehicles and station monitoring equipment. On the one hand, this ensures that transfer vehicles follow the prescribed routes and stop at the designated times, guaranteeing the orderly conduct of transfer operations; on the other hand, it allows station monitoring equipment to anticipate vehicle arrival times, enabling precise docking, advance verification and passage preparation, and facilitating full-process collaborative monitoring and control of vehicle arrival, queuing, and stopping status. Through collaborative interaction between vehicles, factories, and the cloud, transfer vehicles can automatically drive in accordance with regulations, and station equipment can prepare for monitoring and release in advance. This achieves fully unmanned operation across the entire chain, with vehicles autonomously executing tasks and stations collaboratively managing operations. It eliminates reliance on human drivers and on-site dispatchers. At the same time, two-way data interaction enhances the adaptability of vehicle-road-cloud collaboration, ensuring efficient and safe connection of multi-node transfer processes. This solves the problems of high reliance on manual labor, poor flexibility, and insufficient adaptability of existing vehicle transfer technologies within factories.

[0008] In one optional implementation, obtaining a dynamic environment map corresponding to the target park includes: obtaining first environmental perception information collected in real time by each transfer vehicle within a preset range; obtaining second environmental perception information collected in real time by each site monitoring device within a preset range and site status information corresponding to each site; obtaining a high-precision map corresponding to the target park; and fusing the first environmental perception information, the second environmental perception information, the site status information and the high-precision map to generate a dynamic environment map.

[0009] The vehicle transfer method provided in this application acquires first environmental perception information within a preset range collected in real time by each transfer vehicle. It relies on onboard sensing equipment to collect local environmental information such as surrounding obstacles, lane conditions, pedestrians, and temporary material stacks in real time, achieving full coverage perception of the near-field environment around the vehicle and providing a real-time data source for dynamic environmental updates. It acquires second environmental perception information within a preset range collected in real time by monitoring equipment at each station, as well as the corresponding station status information. Station-side equipment supplements environmental information such as obstacles, personnel activity, and channel occupancy in the station area, while simultaneously acquiring station operating status such as gate status, queuing status, and verification status, compensating for blind spots in fixed areas of the station's onboard sensing. It acquires a high-precision map corresponding to the target park. Using the high-precision map as the underlying foundation, it possesses accurate road network topology, lane boundaries, station coordinates, and restricted areas, ensuring the positional accuracy benchmark for subsequent environmental fusion and trajectory planning. The first environmental perception information, second environmental perception information, and station status information are fused with the high-precision map to generate a dynamic environmental map. It integrates multi-source sensing data from vehicles and stations with static high-precision maps, and updates dynamic changes in the park's road network, traffic congestion, and station conditions in real time, forming a real-time dynamic environmental view of the entire area. This provides accurate and comprehensive data support for vehicle route planning, anomaly tracing, intelligent scheduling, and visual monitoring.

[0010] In one optional implementation, the vehicle scheduling information includes the preset start time, globally planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time for each transfer vehicle. Based on the dynamic environment map, vehicle scheduling information for each transfer vehicle is generated, including: obtaining vehicle attribute information for each transfer vehicle; determining the vehicle transfer route and transfer priority for each transfer vehicle based on the vehicle attribute information; the vehicle transfer route includes the stations the transfer vehicle needs to pass through; generating a globally planned route for each transfer vehicle based on the vehicle transfer route and the dynamic environment map; extracting the global speed limit of the factory area from the dynamic environment map; planning the global driving speed, preset start time, and dwell time at each station for each transfer vehicle based on the globally planned route and the transfer priority; determining the preset arrival time for each transfer vehicle based on the preset start time, globally planned route, global driving speed, and dwell time at each station; and generating vehicle scheduling information based on the preset start time, globally planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time.

[0011] The vehicle transfer method provided in this application obtains vehicle attribute information corresponding to each transfer vehicle. It understands inherent attributes such as vehicle size, load capacity, driving performance, operation type, and task level, providing a foundation for subsequent route adaptation, priority allocation, speed and timing planning, and avoiding mismatches between scheduling schemes and vehicle characteristics. Based on vehicle attribute information, it determines vehicle transfer routes and transfer priorities. It plans a sequence of stops along the route based on vehicle attribute differences, while simultaneously allocating transfer priorities to achieve hierarchical task management; ensuring high-priority tasks have priority passage and stopping, and reasonably matching vehicle operating capacity with transfer task requirements. Based on vehicle transfer routes and a dynamic environment map, it generates a globally planned route. Combining fixed station paths with real-time road conditions, obstacles, and traffic constraints in the park, it avoids congested sections and restricted areas, planning a smooth, conflict-free, and reasonably spaced global route to reduce detours and intermediate delays. It extracts global speed limits and, combined with the globally planned route and transfer priorities, plans the global driving speed, preset start time, and station dwell time. Adhering to factory speed limits, vehicles are configured with differentiated speeds, departure times, and stop durations based on priority. Off-peak departures and balanced traffic flow across the road network prevent multiple vehicles from congesting at stations simultaneously, reducing congestion at the source. Preset arrival times are determined based on start time, planned routes, speed, and stop duration. Accurate prediction of vehicle arrival times at each station ensures predictable and traceable timing throughout the entire process, facilitating station preparation for verification, gate opening, and operations, thus improving station coordination efficiency. Vehicle dispatch information is generated based on various time sequences, routes, speeds, priorities, and arrival times. Integrating all dispatch elements such as route, speed, departure time, arrival time, stop duration, and task priority, standardized and executable dispatch instructions are formed, enabling vehicles to drive according to regulations and facilitating collaborative station monitoring, ensuring the orderly, efficient, and coordinated operation of the entire park's transfer operations.

[0012] In one optional implementation, after transmitting the vehicle scheduling information corresponding to each transfer vehicle to each transfer vehicle and each station monitoring device, the method further includes: receiving in real time vehicle driving data and vehicle environmental perception data sent by each transfer vehicle; receiving in real time vehicle monitoring data and station monitoring result data sent by each station monitoring device for monitoring each transfer vehicle; detecting whether there are any abnormalities in each transfer vehicle based on the number of vehicle trips, vehicle environmental perception data, vehicle monitoring data, and station monitoring result data; if there are any abnormalities in the transfer vehicle, determining the cause of the abnormality; processing the abnormal transfer vehicle according to the cause of the abnormality; if there are no abnormalities in the transfer vehicle, controlling each transfer vehicle to continue executing the scheduling task until the scheduling task is completed, storing the vehicle driving data, vehicle monitoring data, and station monitoring result data, and generating scheduling task data.

[0013] The vehicle transfer method provided in this application embodiment receives vehicle driving data and vehicle environmental perception data sent by each transfer vehicle in real time. It aggregates vehicle location, speed, driving status, and surrounding environmental perception information in real time, achieving dynamic real-time acquisition of vehicle operating status and surrounding environment, providing raw real-time data support for subsequent anomaly detection. It also receives vehicle monitoring data and station monitoring result data sent by monitoring equipment at each station in real time. Station-side equipment supplements information on vehicle arrival, queuing, parking, turnstiles, and on-site operating conditions in the station area, filling blind spots in vehicle-mounted perception, achieving data complementarity between the vehicle and station ends, and improving the completeness of overall monitoring. It detects whether there are any abnormalities in each transfer vehicle based on multi-source data. By integrating multi-dimensional data from the vehicle and station ends for joint analysis, it can promptly and accurately identify various anomalies such as trajectory, speed, equipment, and station operations, avoiding misjudgments and omissions caused by single data analysis. If an anomaly is found in a transfer vehicle, the cause of the anomaly is determined. It accurately traces the root cause of the anomaly, distinguishing different causes such as trajectory deviation, speed fluctuation, equipment failure, and station congestion, providing a basis for subsequent targeted handling measures and avoiding blind dispatching intervention. Abnormal transfer vehicles are handled according to the cause of the anomaly. Precise handling is implemented based on the type and level of the anomaly, promptly correcting routes, adjusting vehicle speeds, managing malfunctioning vehicles, and alleviating station congestion to quickly eliminate the impact of the anomaly and ensure transfer order and driving safety. If no anomaly is found, the vehicle continues its task. After the task is completed, data is stored and scheduling task data is generated. This ensures the continuous and stable execution of normal transfer tasks; simultaneously, complete operational and monitoring data throughout the entire process is retained, forming a traceable task archive, providing data support for subsequent algorithm optimization, rule iteration, and scheduling strategy improvement.

[0014] In one optional implementation, the abnormal transport vehicle is handled according to the cause of the abnormality, including: If the cause of the anomaly is an obstacle in the path, the type of obstacle is determined. If the type of obstacle is a dynamic traffic participant, the dynamic traffic participant is driven away by calling the monitoring equipment at the corresponding station. If the type of obstacle is a temporary obstacle, a temporary detour route for the transfer vehicle is planned based on the location of the temporary obstacle. The temporary detour route is sent to the transfer vehicle and the monitoring equipment at each station. If a temporary detour route cannot be generated or the dynamic traffic participant cannot be driven away, an emergency stop command is issued to the abnormal transfer vehicle, and other transfer vehicles within the preset range of the abnormal transfer vehicle are dispatched to slow down and give way.

[0015] The vehicle transfer method provided in this application determines the type of obstacle if the cause of the anomaly is an obstacle in the path. By classifying obstacles by type, precise handling can be achieved, avoiding the scheduling problems caused by uniform processing, and providing a basis for determining subsequent differentiated response strategies.

[0016] If the obstacle is a dynamic traffic participant, the corresponding station monitoring equipment will be used to remove it. Using the station monitoring equipment, pedestrians, work vehicles, and other dynamic participants can be persuaded and removed on-site without changing vehicle routes. This ensures traffic safety while maintaining the original scheduling sequence and planned routes, without affecting the overall transfer pace. If the obstacle is a temporary obstacle, a temporary detour route will be planned for the transfer vehicles based on its location. For static temporary obstacles such as material stacks and equipment blocking the road, local detour routes will be quickly generated, allowing vehicles to autonomously avoid the obstacle area without prolonged waiting, improving traffic efficiency and route planning flexibility. The temporary detour route will be sent to the transfer vehicles and the monitoring equipment at each station. Vehicles can autonomously adjust their driving trajectory according to the temporary detour route; the station monitoring equipment will be notified of route changes in advance and will adjust its monitoring and release logic accordingly, achieving station coordination and avoiding intersection conflicts and station scheduling disconnects. If a temporary detour route cannot be generated or the dynamic traffic participant cannot be removed, an emergency stop command will be issued to the abnormal transfer vehicle, and other transfer vehicles within the preset range will be dispatched to slow down and give way. In extreme scenarios where clearing obstacles and detouring are not possible, a safety protection loop is formed by parking nearby and surrounding vehicles slowing down to avoid collisions, thus maximizing the operational safety of autonomous driving transportation in the park and preventing secondary traffic anomalies.

[0017] In one optional implementation, the method further includes: calculating the station transfer time for each transfer vehicle at each station based on scheduling task data; the station transfer time includes the transfer time between any two adjacent stations and the parking waiting time at each station; for each transfer vehicle, determining the station time at each station based on the station transfer time corresponding to the transfer vehicle; if the station time exceeds the corresponding station preset time, determining that there is an abnormal time consumption situation; determining the actual mileage of the transfer vehicle based on vehicle driving data; and comparing the actual mileage with the globally planned path corresponding to the transfer vehicle. The system compares the actual driving speed with the global driving speed to detect any speed anomalies. If the absolute value of the speed difference between the actual driving speed and the global driving speed exceeds a preset speed difference threshold, a speed anomaly is identified. Based on vehicle driving data, vehicle monitoring data, and station monitoring results, the system determines the cause of the transfer vehicle's time consumption and / or detour and / or speed anomaly. Based on the cause of the time consumption and / or detour and / or speed anomaly, the system generates a target optimization plan for the transfer vehicle.

[0018] The vehicle transfer method provided in this application calculates the transfer time of each transfer vehicle at each corresponding station based on scheduling task data. It accurately breaks down the interval travel time and station parking waiting time, quantifying the entire process time consumption and providing refined time-dimensional data for judging time-consuming anomalies. For each transfer vehicle, the station-specific time consumption is determined based on the station transfer time. The overall dwell and passage time at a single station is aggregated and calculated to form standardized station time consumption statistics, facilitating comparison with standard times. If the station time consumption exceeds the station's preset time, an anomaly is identified. Threshold comparison automatically identifies time-consuming issues such as station congestion, queueing, and verification delays, achieving automated anomaly screening without manual verification of each order. Based on vehicle travel data, the actual mileage of the transfer vehicle is determined. Accurate statistics of the vehicle's actual travel distance provide mileage benchmark data for the rationality of subsequent route planning and the judgment of detour behavior. The actual mileage is compared with the globally planned route to obtain the detour distance. The system quantifies the mileage deviation between the actual and planned routes to intuitively identify non-standard driving behaviors such as invalid detours and trajectory deviations. If the detour distance exceeds a preset detour distance threshold, a route detour is determined to exist. Using the quantified threshold as the judgment standard, it automatically and accurately identifies detours exceeding the standard, avoiding errors from subjective human judgment. The actual driving speed is compared with the global driving speed to detect any speed anomalies. Real-time benchmarking between planned speed limits and actual vehicle speeds establishes a routine monitoring mechanism from a speed perspective, promptly identifying issues such as speeding, slow driving, and speed fluctuations. If the absolute value of the speed difference exceeds a preset speed difference threshold, a speed anomaly is confirmed. The quantified threshold filters out significant speed deviation behaviors and eliminates interference from normal small speed fluctuations, improving the accuracy of speed anomaly identification. Based on multi-source data, the system determines the causes of time consumption, detours, and speed anomalies for transport vehicles. It integrates multi-dimensional data from both vehicle and station ends for source tracing analysis to accurately locate the root causes of various anomalies, providing causal support for optimization plan formulation. Based on the causes of various anomalies, it generates target optimization plans for the transport vehicles. Customized matching and optimization strategies are developed for different causes of anomalies. Iterative optimizations are made from dimensions such as route planning, timing scheduling, vehicle speed control, and station management to reduce the recurrence of similar time-consuming, detour, and speed anomalies, and continuously improve the overall transfer efficiency and operational standardization of the park.

[0019] In one optional implementation, a target optimization scheme for the transfer vehicle is generated based on the reasons for time delay and / or detour and / or abnormal speed, including: determining preset optimization rules corresponding to the reasons for time delay and / or detour and / or abnormal speed, respectively; generating a basic optimization strategy based on the preset optimization rules corresponding to the reasons for time delay and / or detour and / or abnormal speed; predicting the basic optimization strategy to obtain the prediction effect; and determining the target optimization scheme for the transfer vehicle based on the prediction effect.

[0020] The vehicle transfer method provided in this application matches corresponding preset optimization rules based on the causes of time consumption, detours, and speed anomalies. This achieves precise binding between the causes of anomalies and hierarchical optimization rules, establishing differentiated evaluation criteria based on risk level, impact scope, frequency of occurrence, and task priority. It clarifies the optimization weight and processing priority of various anomalies, providing a standardized basis for strategy formulation. Based on the matched preset optimization rules, basic optimization strategies are generated. Specific optimization measures are formulated for the three types of anomalies—time consumption, detours, and speed—from the dimensions of station processes, route planning, and vehicle control, forming multiple sets of basic strategies with different focuses to cover various anomaly rectification needs. The basic optimization strategies are predicted to obtain the predicted effects. Simulation analysis quantifies the improvement effects of each basic strategy on travel time, detour distance, and vehicle speed stability, evaluating the merits of the strategies in a data-driven manner to avoid subjective selection based on experience. The target optimization scheme for the transfer vehicles is determined based on the predicted effects. The solution with the strongest adaptability and the best overall optimization effect is selected from multiple basic strategies to accurately match the abnormal scenario. At the same time, it can feed back into the scheduling system iteration, effectively reducing the recurrence rate of similar time-consuming, detour, and speed anomalies, and improving the overall operational efficiency and management level of the park's transfer.

[0021] In one alternative implementation, the method further includes: By combining vehicle driving data, vehicle environmental perception data, vehicle monitoring data, and dynamic environmental maps, the transfer process of each transfer vehicle can be visualized in real time.

[0022] The vehicle transfer method provided in this application integrates and overlays vehicle driving data, vehicle environmental perception data, vehicle monitoring data, and dynamic environmental maps, mapping multi-source information such as vehicle location, driving status, surrounding environment, and station operating conditions onto the dynamic map. This enables real-time visualization of all transfer vehicles throughout the entire process, allowing for intuitive understanding of vehicle driving trajectories, station parking status, and changes in the surrounding environment. It also facilitates timely detection of various anomalies such as time consumption, detours, and speed, enabling unified cloud-based supervision, rapid intervention, and scheduling. This enhances the intuitiveness, real-time nature, and overall control capabilities of park transfer management.

[0023] Secondly, the present invention provides a vehicle transfer device, applied to a transfer server in a vehicle transfer system. The vehicle transfer system also includes at least one transfer vehicle and at least one site monitoring device, with each site monitoring device installed at a corresponding site in the target area. The transfer server is communicatively connected to each transfer vehicle and each site monitoring device. The device includes: The acquisition module is used to acquire a dynamic environment map corresponding to the target park. The generation module is used to generate vehicle scheduling information for each transfer vehicle based on the dynamic environment map. The vehicle scheduling information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time for each transfer vehicle. The sending module is used to transmit the vehicle dispatch information corresponding to each transfer vehicle to each transfer vehicle and each station monitoring device, so that each transfer vehicle can carry out transfers based on the vehicle dispatch information, and each station monitoring device can monitor each transfer vehicle based on the vehicle dispatch information.

[0024] Thirdly, the present invention provides a transit server, comprising: The memory and the processor are interconnected and communicate with each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the vehicle transfer method of the first aspect or any of its corresponding embodiments.

[0025] Fourthly, the present invention provides a vehicle transfer system, comprising: a transfer server, at least one transfer vehicle, and at least one site monitoring device, wherein each site monitoring device is installed at a corresponding site within the target park; the transfer server is communicatively connected to each transfer vehicle and each site monitoring device, wherein: Each transfer vehicle is used to collect first environmental perception information within a preset range of the transfer vehicle in real time, and transmit the first environmental perception information to the transfer server. Each site monitoring device is used to collect second environmental perception information and corresponding site status information within a preset range of the site in real time, and transmit the second environmental perception information and corresponding site status information to the transfer server. A transfer server for performing the vehicle transfer method described in the first aspect or any of its corresponding embodiments; Each transfer vehicle is also used to perform transfer scheduling tasks based on vehicle scheduling information.

[0026] Fifthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the vehicle transfer method of the first aspect or any corresponding embodiment described above.

[0027] In a sixth aspect, the present invention provides a computer program product, including computer instructions for causing a computer to execute the vehicle transfer method of the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0028] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of the structure of a vehicle transfer system according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of a first method for vehicle transfer according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating the workflow of a transfer vehicle according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a second process for a vehicle transfer method according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the process of the internal transfer station of the target park according to an embodiment of the present invention; Figure 6 This is a flowchart of the operation of a site monitoring device according to an embodiment of the present invention. Figure 7 This is a structural block diagram of a vehicle transfer method apparatus according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of the transfer server according to an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0032] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0033] According to an embodiment of the present invention, a vehicle transfer method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] This embodiment provides a vehicle transfer method, applied to a transfer server in a vehicle transfer system, such as... Figure 1 As shown, the vehicle transfer system also includes at least one transfer vehicle and at least one site monitoring device, with each site monitoring device installed at a corresponding site within the target park; the transfer server is communicatively connected to each transfer vehicle and each site monitoring device. Figure 2 This is a flowchart of a vehicle transfer method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Obtain the dynamic environment map corresponding to the target park.

[0035] Specifically, the transfer server can receive dynamic environmental maps of the target area sent by other devices. These other devices can be various transfer vehicles and monitoring equipment at various stations. The server can also generate a dynamic environmental map of the target area based on the high-precision map of the target area.

[0036] The dynamic environment map includes the overall static road network of the factory park (high-precision map), real-time dynamic obstacles and targets, traffic status of each lane / channel / station, location and task status of vehicles on the road, risk areas, restricted areas, emergency areas, drivable routes and suggested passage areas, etc.

[0037] This step will be explained in detail below.

[0038] Step S202: Generate vehicle dispatch information for each transfer vehicle based on the dynamic environment map.

[0039] The vehicle dispatch information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time for the transfer vehicle.

[0040] Specifically, the transfer server can generate a global planned route for each transfer vehicle based on the attribute information of each transfer vehicle and the dynamic environment map, and then generate vehicle scheduling information for each transfer vehicle based on the global planned route.

[0041] This step will be explained in detail below.

[0042] Step S203: Transmit the vehicle dispatch information corresponding to each transfer vehicle to each transfer vehicle and each station monitoring device, so that each transfer vehicle can carry out transfers based on the vehicle dispatch information, and each station monitoring device can monitor each transfer vehicle based on the vehicle dispatch information.

[0043] Specifically, the transfer server can transmit vehicle dispatch information corresponding to each transfer vehicle to each transfer vehicle via the 5G Uu interface. The transfer server can also transmit vehicle dispatch information corresponding to each transfer vehicle to the monitoring equipment at each site via communication connections.

[0044] After receiving the corresponding vehicle dispatch information, each transfer vehicle can parse the information to confirm that the global planned route, global driving speed, transfer priority, dwell time at each station, start time and arrival time are complete and valid, and verify whether the task number and VIN code match.

[0045] Then, the transport vehicle starts a fully automatic self-check based on the vehicle dispatch information, including: whether the environmental perception unit is normal, whether the combined positioning unit is normal, whether the vehicle control unit is normal, whether the communication module is connected stably, and only after the self-check is passed can it enter the standby state.

[0046] Once the preset start time has elapsed, the transfer vehicles enter idle standby mode, strictly awaiting the preset start time issued by the transfer server, neither ahead nor behind, ensuring orderly traffic flow within the factory area, avoiding congestion and overcrowding. Then, after starting according to the globally planned route, the vehicles strictly adhere to the globally planned route, maintaining the global driving speed, keeping to their lanes, avoiding obstacles, and following speed limits. Based on their own transfer priority, transfer vehicles follow priority passage rules when merging, queuing, and passing through stations: high-priority vehicles can pass first, and low-priority vehicles automatically yield, ensuring dispatch order and efficiency. At each station, vehicles complete the prescribed stop time according to the stop time specified in the dispatch information: identity verification, task confirmation, status synchronization, precise parking, and automatic departure after the stop time expires, without exceeding the time limit or lingering.

[0047] During the transport process, the transfer vehicles report their driving status to the transfer server in real time, including real-time location, real-time speed, vehicle status, and environmental perception data, ensuring that the dispatch system can monitor the entire process.

[0048] In addition, during the transfer process, the vehicle status monitoring unit monitors the communication status and command interaction status of the transfer vehicle, the station monitoring equipment, and the transfer server in real time. Any of the following situations will be immediately identified as an anomaly: Uu interface (5G cellular) communication interruption; loss of PC5 direct connection communication signal; command transmission timeout, errors, or mismatches; heartbeat disconnection between the transfer vehicle and the station monitoring equipment / transfer server. Once an anomaly is confirmed, the emergency response procedure will be initiated immediately.

[0049] Upon detecting an anomaly, the transfer vehicle immediately initiates an emergency stop procedure, performing emergency braking to ensure rapid deceleration to a safe state. Simultaneously, it switches to a backup communication link (short-range wireless communication) and continuously sends out warning signals. The warning information is also pushed to the site monitoring equipment module and the transfer server platform, indicating a "communication anomaly." The transfer vehicle continuously times the communication interruption to determine if it exceeds a preset duration threshold (e.g., 30 seconds): if the interruption duration is less than or equal to the preset threshold (e.g., 30 seconds), it remains parked and continuously attempts to reconnect, waiting for communication to resume; if the interruption duration is greater than the preset threshold (e.g., 30 seconds), it immediately activates the combined inertial navigation autonomous navigation mode and enters autonomous emergency driving. Specifically, based on its current coordinates and the factory's global map, the transfer vehicle uses a KNN nearest neighbor search algorithm to search for the nearest emergency parking area. These emergency parking areas are pre-set within the factory area, one every 500 meters along both sides of the transfer route. If the nearest emergency parking area is occupied, the next nearest emergency parking area is automatically searched. An available emergency parking area is locked as the emergency driving destination. Then, the transfer vehicle's path planning unit calls an improved A-path algorithm to generate a safe, smooth, and fast emergency path. The improved cost function A is: f(n) = g(n) + h(n) + smoothing coefficient + distance cost; where g(n) is the actual driving distance from the current location to station n; h(n) is the Manhattan distance from station n to the emergency parking area (replacing the Euclidean distance, which is faster and more efficient); the path smoothing coefficient avoids sharp turns, ensures smooth driving, and prevents jitter; the distance cost prioritizes the shortest and safest path. This generates a collision-free, short-distance, low-steering, and directly executable emergency driving route. Finally, the transport vehicle autonomously drives according to the route planned in Improved A, relying solely on combined inertial navigation positioning, without depending on the perception of the transport vehicle / station monitoring equipment or commands from the transport server. It smoothly drives to the target emergency parking area, performs a safe parking maneuver upon arrival, deactivates the unmanned transport mode, and activates its hazard lights to alert surrounding vehicles and personnel.

[0050] Once communication is successfully reconnected: the transfer vehicle, site monitoring equipment, and transfer server re-authenticate each other. The transfer server verifies the current task of the transfer vehicle to confirm that the task has not been lost and the path is valid. If no anomalies are found, the transfer server issues a continue transfer command, and the transfer vehicle restarts unmanned transfer mode; it continues to travel from its current location to complete the remaining transfer task. If the anomaly is not a communication problem but an equipment malfunction (such as a failure of the transfer vehicle's sensing unit), the transfer vehicle continuously outputs a fault warning signal. Upon receiving the fault, the transfer server platform immediately dispatches on-site personnel to handle the situation. Personnel arrive at the site to inspect, repair, or manually move the vehicle. After repairs are completed, the transfer vehicle returns to the network, the transfer server reissues the task, and the transfer continues.

[0051] Finally, the vehicle that has reached the destination and completed the task arrives at the target station (parking area / repair area / road test area) according to the preset arrival time, performs the final parking, reports the completion of the task, and ends the transfer.

[0052] For example, such as Figure 3 This is a flowchart of the transfer vehicle workflow. (For example...) Figure 3As shown, the cloud-based path planning (global decision-making layer) is the source of the entire process, responsible for generating the vehicle's global driving route. Inputs: Global task instructions, dynamic environment maps, task priorities, and other information from the park's cloud-based dispatch platform. Output: The generated global planned route is sent to the vehicle-side path planning unit in the form of instructions (dashed arrows in the diagram indicate non-periodic or asynchronous sending). It provides the transport vehicles with a macroscopic driving target and a sequence of stops, serving as the basis for all subsequent local decisions. The vehicle-side path planning unit is the "brain" of the entire vehicle-side control system, receiving multi-source inputs and comprehensively generating executable local paths and driving strategies. Its inputs include: Cloud-based path planning: Global route instructions. Plant-side path guidance: Local access instructions from fixed monitoring equipment in the plant area, such as stop release, intersection control, temporary route changes, etc. Vehicle-side environmental perception unit: Real-time environmental data such as obstacles, lane lines, and surrounding dynamic participants. Vehicle status monitoring unit: Current vehicle speed, battery level, fault status, and other operational data. Its outputs are divided into two categories: Downward: Sending the generated local paths and driving strategies to the vehicle control unit. Upward: Does not directly output, but relies on data support from the perception layer. Perception Layer: Vehicle-side environmental perception unit + integrated inertial navigation positioning + factory-side environmental perception. Provides the "eyes" and "position" for the vehicle-side path planning unit, constructing a complete environmental model. Vehicle-side environmental perception unit: Receives integrated inertial navigation positioning data to obtain the vehicle's own position, attitude, and speed information. Receives factory-side environmental perception data, i.e., environmental information from factory cameras, radar, and other equipment, compensating for blind spots of onboard sensors. Output: The fused environmental perception information (obstacles, lane lines, drivable areas) is transmitted to the vehicle-side path planning unit. Simultaneously, the perception data is uploaded to the cloud for data fusion, used to update the global dynamic map. Execution Layer: Vehicle control unit + vehicle driving control translates path planning commands into actual vehicle actions. Vehicle control unit: Receives local path and driving strategy commands from the vehicle-side path planning unit. Simultaneously receives vehicle status feedback from the vehicle status monitoring unit for closed-loop control. Output: Specific control commands such as steering, acceleration, and braking are sent to the vehicle driving control module. Vehicle Driving Control: Directly executes the vehicle's underlying control, driving the vehicle along the planned path. Status Monitoring and Feedback: The vehicle status monitoring unit achieves real-time monitoring and multi-terminal synchronization of vehicle operating status, forming a safety closed loop. Input: Operating data from various vehicle systems, such as vehicle speed, battery, electronic control, and sensor status. Output: Feedback to the vehicle-side path planning unit for dynamic adjustment of driving strategies. Synchronization with the plant-side status monitoring system for real-time monitoring by the plant management platform. Synchronization with the cloud-based status monitoring system (dashed lines indicate non-real-time aggregated reporting) for global scheduling and fault diagnosis.

[0053] The vehicle transfer method provided in this application obtains a dynamic environmental map corresponding to the target park. It can monitor the park's road network, obstacle distribution, station layout, and road condition changes in real time, providing accurate and real-time underlying geographic data support for vehicle dispatching and avoiding inaccurate dispatching due to lagging environmental information. Based on the dynamic environmental map, vehicle dispatching information for each transfer vehicle is generated. Intelligent planning is performed based on the real-time environmental situation, rationally allocating driving routes, transfer sequences, and station stopping arrangements to balance road network load, reduce vehicle conflicts, lower congestion and unnecessary detours, and improve overall transfer efficiency. Vehicle dispatching information is then distributed to transfer vehicles and station monitoring equipment. On the one hand, this ensures that transfer vehicles follow the prescribed routes and stop at the designated times, guaranteeing the orderly conduct of transfer operations; on the other hand, it allows station monitoring equipment to anticipate vehicle arrival times, enabling precise docking, advance verification and passage preparation, and facilitating full-process collaborative monitoring and control of vehicle arrival, queuing, and stopping status. Through collaborative interaction between vehicles, factories, and the cloud, transfer vehicles can automatically drive in accordance with regulations, and station equipment can prepare for monitoring and release in advance. This achieves fully unmanned operation across the entire chain, with vehicles autonomously executing tasks and stations collaboratively managing operations. It eliminates reliance on human drivers and on-site dispatchers. At the same time, two-way data interaction enhances the adaptability of vehicle-road-cloud collaboration, ensuring efficient and safe connection of multi-node transfer processes. This solves the problems of high reliance on manual labor, poor flexibility, and insufficient adaptability of existing vehicle transfer technologies within factories.

[0054] This embodiment provides a vehicle transfer method, applied to a transfer server in a vehicle transfer system. Figure 4 This is a flowchart of a vehicle transfer method according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps: Step S301: Obtain the dynamic environment map corresponding to the target park.

[0055] Specifically, step S301 above may include the following steps: Step S3011: Obtain the first environmental perception information within the preset range of each transfer vehicle collected in real time.

[0056] Specifically, each transport vehicle uses onboard LiDAR, millimeter-wave radar, ultrasonic radar, and forward / surround / all-around cameras to collect real-time environmental perception information within a preset range around the vehicle. This information includes: obstacles around the vehicle, lane markings, road conditions, dynamic traffic participants (personnel, other vehicles), and route congestion. Then, each transport vehicle uploads this environmental perception information to the transport server in real-time via a 5G+C-V2X communication link.

[0057] The transfer server receives and temporarily stores the initial environmental awareness information from all transfer vehicles, maintaining time and location synchronization.

[0058] Step S3012: Obtain the second environmental perception information within the preset range of each site and the corresponding site status information collected in real time by the monitoring equipment at each site.

[0059] Specifically, monitoring equipment at each station uses high-definition cameras, millimeter-wave radar, and infrared sensors to collect real-time environmental information within a preset range, i.e., second environmental perception information. The collected information includes: obstacles around the station, road congestion, road occupancy, personnel / vehicle intrusion, road anomalies, etc. Simultaneously, each station uploads its own station status information to the transfer server in real time, including: station availability / occupancy, queue length, permitted passage status, workstation workload, and gate status. The transfer server uniformly receives the second environmental perception information and station status information from all stations and performs time alignment.

[0060] Step S3013: Obtain a high-precision map corresponding to the target park.

[0061] Specifically, the transfer server can retrieve a pre-collected and produced high-precision map of the target park (the closed environment of a factory) from a map library or local storage module. This high-precision map includes: park lanes, road topology, transfer nodes, speed limit zones, restricted areas, safe parking areas, emergency parking areas, route guidance signs, lane lines, coordinate references, etc. The high-precision map is static data and does not change with real-time road conditions, providing a unified geographic reference for dynamic fusion.

[0062] Step S3014: The first environmental perception information, the second environmental perception information, the status information of each station, and the high-precision map are fused together to generate a dynamic environmental map.

[0063] Specifically, the transfer server can align the first environmental perception information, the second environmental perception information, and the site status information according to a unified timestamp, ensuring that all data reflects the park's status at the same moment. Then, the first environmental perception information, the second environmental perception information, and the site status information are mapped to the global coordinate system used by the high-precision map to achieve consistent location benchmarks and ensure that subsequent fusion does not result in offsets or misalignments.

[0064] Then, the transfer server can identify and filter out duplicate reports, signal interference, data distortion, and abnormal jumps in the perceived data, eliminating invalid targets, false detections, and location or velocity data that exceeds reasonable ranges. This filtering process improves the reliability of environmental information and ensures the accuracy and stability of the dynamic environmental map.

[0065] Finally, the transfer server overlays the cleaned data layer by layer onto the high-precision map to complete the information labeling. Specifically, the transfer server labels the real-time location, driving posture, and surrounding obstacles, lane lines, and dynamic targets of each transfer vehicle on the high-precision map, all derived from the first environmental perception information. It also labels road congestion, static / dynamic obstacles, pedestrian intrusions, and lane obstruction in each station area on the high-precision map, all derived from the second environmental perception information. Simultaneously, the current occupancy status, idle status, queue length, and busy level of each transfer node are simultaneously labeled on the high-precision map, forming a complete node operation status.

[0066] By overlaying the above information, the transfer server constructs an integrated, fully covered, and real-time updated dynamic environment map. This map includes a static road network base (from a high-precision map), dynamic obstacle information (from vehicle and station perception), real-time traffic flow status (from vehicle driving data), and station scheduling status (from station status information). Ultimately, this forms a three-in-one full-domain dynamic environment model integrating static map, dynamic real-time data, and scheduling situation.

[0067] Step S302: Generate vehicle dispatch information for each transfer vehicle based on the dynamic environment map.

[0068] The vehicle dispatch information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time for the transfer vehicle.

[0069] Specifically, step S302 above may include the following steps: Step S3021: Obtain the vehicle attribute information corresponding to each transfer vehicle.

[0070] The vehicle attribute information includes the vehicle identification information and vehicle status information corresponding to the transfer vehicle.

[0071] Specifically, the site monitoring equipment can identify the vehicle identification information of the transfer vehicle by scanning the QR code on the windshield. This vehicle identification information may include the VIN and configuration information. The site monitoring equipment then uploads this vehicle identification information to the transfer server. The transfer server can obtain information such as the inspection results, production batch, and vehicle configuration for each transfer vehicle from the factory's production scheduling system. The transfer server can then aggregate this information to form complete vehicle attribute information, including two categories: vehicle identification information (VIN code, vehicle ID, vehicle model, and vehicle configuration); and vehicle status information (qualified and awaiting transfer, unqualified and requiring repair, awaiting road testing, awaiting verification, etc.).

[0072] Step S3022: Based on the vehicle attribute information corresponding to each transfer vehicle, determine the vehicle transfer route and transfer priority corresponding to each transfer vehicle.

[0073] The vehicle transfer route includes the stations that the transfer vehicles need to pass through.

[0074] Specifically, the transfer server can allocate transfer routes for each transfer vehicle based on the vehicle status information in the vehicle attribute information. Specifically, for qualified vehicles: the route is: production line decommissioning area → road test area → functional verification area → mass production parking area; for unqualified vehicles: the route is: production line decommissioning area → rework area; for specially configured vehicles: a customized route is used; all routes include all the stops that the vehicle must pass through. For example, such as... Figure 5 As shown, this is a schematic diagram of the transfer station process within the target park.

[0075] The transfer server can assign transfer priorities to each transfer vehicle based on its vehicle type, production urgency, and whether it is a vehicle to be returned for repair. Transfer priorities are divided into: Level 1 (Urgent), Level 2 (Important), Level 3 (Regular), and Level 4 (Low Priority).

[0076] For example, the highest priority (Level 1, Emergency) transfer priority is primarily for non-conforming vehicles undergoing repair or malfunctioning vehicles. These vehicles need to enter the repair area quickly and efficiently to avoid obstructing access or disrupting production, thus they are assigned the highest priority. The second highest priority (Important) transfer priority is primarily for vehicles from key production batches and planned critical vehicles. These vehicles are strongly related to the day's production tasks and must be transferred to the road test or functional verification area on time, thus they are assigned the second highest priority. The third highest priority (Regular) transfer priority is primarily for ordinary qualified vehicles and vehicles transferred according to standard procedures. These vehicles are transferred according to the normal production rhythm and have no special emergency needs, thus they are assigned the regular priority. The fourth highest priority (Low Priority) transfer priority is primarily for temporary vehicle relocation, non-emergency vehicle movement, and vehicles adjusted for backup parking spaces. These vehicles can proactively give way to high-priority vehicles and are transferred when access is available, thus they are assigned the lowest priority.

[0077] Step S3023: Based on the transfer routes of each vehicle and the dynamic environment map, generate the global planning route corresponding to each transfer vehicle.

[0078] Specifically, the transfer server first maps the sequence of stations along the vehicle transfer route onto the dynamic environment map of the target park, according to the geographical location and passage order of the stations, forming a chain of station locations and passage nodes that the vehicle needs to pass through from the starting point to the destination, and establishing a correspondence between the route and the map.

[0079] Then, the transfer server filters and verifies all passable road sections based on real-time traffic information in the dynamic environment map, filtering out all impassable paths, including: congested and impassable road sections, road sections with obstacles, restricted areas designated by the factory, temporary construction closure areas, damaged roads, and areas that are occupied or blocked, retaining only safe, unobstructed, and permissible routes as the basis for subsequent route planning.

[0080] Within the filtered legal path range, the transfer server employs the A-path planning algorithm, taking the vehicle's origin as the starting point, the final destination as the ending point, and all necessary stops along the way as mandatory nodes, to solve for the optimal path. It comprehensively considers path distance, smoothness of travel, and safety to generate a collision-free, smoothest, and shortest travel path. The generated global planned route contains complete, accurate, and directly executable driving information, specifically including: the vehicle's precise driving path within the park, lane information, turning points, steering angles and directions, areas to be avoided, obstacles and detour areas, and driving rules for each road segment.

[0081] Finally, after completing the route planning, the transfer server outputs the global planned route for each transfer vehicle, which serves as the basis for subsequent driving control, speed planning, station scheduling, and time prediction.

[0082] Step S3024: Extract the global speed limit of the factory area from the dynamic environment map, and plan the global driving speed, preset start time and station dwell time of each transfer vehicle according to the global planned route and transfer priority of each transfer vehicle.

[0083] Specifically, the transfer server can extract the unified road speed limit standards for the factory's closed campus from the dynamic environment map, serving as the upper limit for the overall driving speed. For example, in the main transfer channel area: the driving speed shall not exceed 15km / h; in the station connection, intersection, and densely populated areas, the driving speed shall not exceed 5km / h.

[0084] This speed limit is the maximum constraint on vehicle speed, and all speed planning is carried out within this range.

[0085] Then, based on speed limit constraints and the actual road conditions of the globally planned route, a base driving speed is determined according to the total route length, straight sections, and curve distribution. The speed is then smoothly adjusted based on obstacle density, turning angles, and road width. Fine-tuning is further performed based on transport priorities; high-priority vehicles can use a higher, more reasonable speed within a safe range, while low-priority vehicles use a stable, conservative speed. Finally, a globally optimized driving speed that is suitable for the entire route, safe, stable, and directly executable is generated.

[0086] To avoid congestion caused by concentrated departures, the transfer server can determine the departure order based on transfer priorities: Level 1 priority departure, Level 4 staggered departure. Then, it reads the idle time windows of roads, intersections, and stations in the dynamic environment map to avoid congested periods; combined with the distance to vehicles ahead and the queue length at stations, it determines a safe departure interval, matches the factory's production line rhythm, and generates a preset start time that avoids conflicts, crowding, and orderly passage.

[0087] The transfer server can allocate stop time for each transit station based on station function, vehicle priority, and regional congestion status. Specifically, the transfer server can allocate a basic stop time according to station type. Road test areas and functional verification areas: used for task confirmation and status verification, using short stop times; mass production parking areas and rework areas: used for precise parking and task handover, using standard stop times. Then, time adjustments are made according to transfer priority: high-priority vehicles: shorten stop time for faster passage and improved efficiency; ordinary-priority vehicles: execute according to the basic time; low-priority vehicles: can appropriately extend stop time, actively avoiding high-priority vehicles to prevent node congestion. When station queues are long, the stop time of preceding vehicles is appropriately reduced; when stations are idle, operations are allowed to be completed within the standard time. After the above calculations, the transfer server synchronously outputs: global driving speed, preset start time, and stop time at each station, providing a unified basis for subsequent preset arrival time calculation, vehicle execution, and station monitoring.

[0088] Step S3025: Based on the preset start time, global planned route, global driving speed and dwell time at each station for each transfer vehicle, determine the preset arrival time for each transfer vehicle.

[0089] Specifically, the transfer server can calculate the basic travel time of the transfer vehicle without stopping or waiting, based on the total length of the globally planned route and the global travel speed, using the formula: Basic Travel Time = Total Length of Globally Planned Route ÷ Global Travel Speed. This serves as the benchmark for time calculation. Then, the transfer server sums up the stop times at each station the transfer vehicle needs to pass through on the globally planned route to obtain the total stop time. Based on the sum of the basic travel time and the total stop time, the transfer server adds three types of correction time for precise calibration. These three types of correction time include: congestion compensation time: buffer time added based on road congestion conditions in the dynamic environment map; priority compensation time: traffic efficiency compensation time adjusted according to transfer priority; and node waiting time: waiting time that may occur due to station queuing, intersection avoidance, etc. Finally, the complete estimated total travel time from vehicle start to destination is obtained.

[0090] Finally, the transfer server starts from the preset start time and calculates and outputs the preset arrival time of the transfer vehicle to each station along the route and the total preset arrival time of the transfer vehicle to the final destination, according to the station order of the globally planned route, by successively adding the segmented travel time + the corresponding station dwell time + the segmented correction time.

[0091] The transfer server ultimately outputs the preset arrival time for each transfer vehicle, including the arrival time of each station along the way and the final destination arrival time, which is used for vehicle driving control, station monitoring and prediction, and coordinated scheduling with the transfer server.

[0092] Step S3026: Generate vehicle scheduling information based on the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time of the transfer vehicle.

[0093] Specifically, the transfer server can integrate and structure the following six pieces of information: preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time, ultimately forming structured, downloadable, parsable, and executable vehicle scheduling information, which is then sent to vehicles and stations for execution.

[0094] Step S303: Transmit the vehicle dispatch information corresponding to each transfer vehicle to each transfer vehicle and each station monitoring device, so that each transfer vehicle can carry out transfers based on the vehicle dispatch information, and each station monitoring device can monitor each transfer vehicle based on the vehicle dispatch information.

[0095] Please refer to the above description of step S203 for details on this step, which will not be repeated here.

[0096] Step S304: Receive vehicle driving data and vehicle environmental perception data sent by each transfer vehicle in real time.

[0097] The vehicle driving data includes vehicle location information, vehicle speed information, vehicle attitude information, and vehicle status information.

[0098] Specifically, the transfer server can receive vehicle driving data and vehicle environmental perception data uploaded by each transfer vehicle in real time at high frequency through dual communication links of 5G and C-V2X. Among them, the vehicle driving data and vehicle environmental perception data correspond to the identification information of the transfer vehicle.

[0099] Vehicle driving data includes: vehicle location information: real-time vehicle coordinates, latitude and longitude, and road network location; Vehicle speed information: real-time vehicle speed, acceleration, and braking status; vehicle attitude information: vehicle heading angle, pitch angle, and yaw angle; vehicle status information: unmanned mode status, power status, braking status, communication connection status, and equipment fault codes. Among these, vehicle identification information includes: vehicle VIN code and unique vehicle number, used for vehicle identity binding.

[0100] The transfer server synchronously receives vehicle environmental perception data, namely environmental information such as surrounding obstacles, dynamic personnel, road conditions, and drivable areas collected by vehicle-mounted LiDAR, cameras, and millimeter-wave radar.

[0101] The transfer server can timestamp and cache all vehicle driving data and vehicle environmental perception data uploaded by all transfer vehicles to ensure data continuity in time sequence.

[0102] Step S305: Receive vehicle monitoring data and site monitoring result data sent by the monitoring equipment at each site in real time.

[0103] The vehicle monitoring data includes collected vehicle images, vehicle locations detected by radar, vehicle presence status, lane occupancy status, vehicle speed monitoring, and vehicle identification information; the station monitoring results data include: whether the vehicle deviates from the path, whether the vehicle is speeding, whether the vehicle has exceeded the parking time limit, whether the vehicle is not identified, whether there is abnormal lingering, whether the vehicle does not match the map, whether there are obstacles in the point area, and whether there are intruders.

[0104] Specifically, the monitoring equipment at each station continuously monitors the station area using high-definition cameras, millimeter-wave radar, and infrared sensors. It then uploads vehicle monitoring data to the transfer server in real time, including: collected vehicle images; vehicle positions detected by radar; vehicle presence status within the station; current lane occupancy status; vehicle speed monitored at the station; and vehicle identification information (VIN recognition results).

[0105] After acquiring raw vehicle monitoring data such as vehicle images, radar positions, lane occupancy, and vehicle speed, the station monitoring equipment performs intelligent analysis and processing locally. It then makes a point-by-point judgment on the operating status, traffic compliance, and environmental safety of the transfer vehicles within the station area, generating standardized station monitoring result data.

[0106] Specifically, the station monitoring equipment retrieves the preset global planning driving path of the transfer vehicles, combines it with the actual vehicle location obtained from radar positioning and image recognition, and compares the real-time driving trajectory of the transfer vehicles. This determines whether the transfer vehicles have left the designated lane or deviated from the preset driving path, and identifies violations such as abnormal lane changes and deviations from the intended route.

[0107] Based on the speed limit standards of the node area and combined with the real-time monitoring of vehicle speed by radar, the station equipment determines whether the transfer vehicle exceeds the prescribed speed limit when entering the station area; it also identifies abnormal speed behaviors such as high-speed entry and failure to slow down by the transfer vehicle.

[0108] The station monitoring equipment records the time when the transfer vehicle enters the station and, combined with the preset station dwell time in the dispatch information, monitors the station dwell time of the transfer vehicle in real time. If the stationary dwell time of the transfer vehicle exceeds the prescribed dwell time threshold, it is determined that the parking time has exceeded the limit.

[0109] The site monitoring equipment collects the identification information of the transfer vehicles through camera image recognition and RFID identification. It compares the identified vehicle number and VIN code with the dispatch vehicle information issued by the transfer server. If the vehicle cannot be identified, the identification number is inconsistent, or the vehicle identity cannot be matched, the identification is deemed to have failed.

[0110] The station monitoring equipment continuously monitors the movement status of the transfer vehicles. If a transfer vehicle remains stationary for a long time without dispatch instructions or yielding requirements, and does not belong to a normal stopping point, it is determined that the vehicle is abnormally delayed.

[0111] The site monitoring equipment compares the actual physical location of the vehicle detected by radar with the theoretical matching location of the vehicle in a high-precision map. If the spatial deviation between the two exceeds the preset error threshold, it indicates that the positioning of the transfer vehicle has drifted and the map matching is abnormal, and it is determined that the vehicle and the map position do not match.

[0112] The site monitoring equipment uses cameras and millimeter-wave radar to scan the site's access area in real time, detecting whether there are static obstacles such as piled-up debris or fallen objects in the area; at the same time, it dynamically identifies pedestrians and external moving targets to determine whether there are people entering the access area and to identify potential safety hazards in the site environment.

[0113] For example, such as Figure 6The diagram shows the workflow of the site monitoring equipment. The site monitoring equipment comprises three collaborative units that guide, perceive, and monitor vehicles within the park: The Path Guidance Unit acts as the vehicle's "park navigator." It issues localized passage instructions to autonomous vehicles, including intersection clearance, site access, temporary route changes, and controlled area prompts, ensuring vehicles move orderly within the park according to preset rules and avoiding conflicts and congestion. The Park Environment Perception Unit acts as the vehicle's "park lookout tower." Through cameras, radar, and other equipment deployed at key nodes in the park, it collects environmental information such as obstacles, personnel activity, temporary storage materials, and construction areas around the site. This data is directly synchronized to the autonomous vehicles, compensating for blind spots in onboard sensors and forming "vehicle-park collaborative perception," significantly improving traffic safety in complex scenarios. The Status Monitoring Unit acts as the vehicle's "park administrator." It monitors the status of vehicles entering and leaving the site in real time, including vehicle location, arrival time, parking duration, queuing status, and work progress, achieving visualized control over the entire vehicle process and providing data support for the cloud-based dispatch system. The diagram illustrates a complete main flow of a vehicle from production line rollout to mass production, along with exception handling branch paths. The aforementioned monitoring equipment is deployed at each key node: 1. Main Flow: Vehicle Rollout → Road Test → Functional Verification → Mass Production Parking. This is the core path for normal vehicle flow, with each node supported by monitoring equipment: Vehicle Rollout Area: Monitoring equipment is deployed to initially locate and guide newly rolled-out vehicles, initiating the transfer process. Vehicle Road Test Area: Path guidance and environmental sensing equipment is deployed to provide route guidance and safety monitoring for road tests, ensuring safety and compliance during the process. Functional Verification Area: Status monitoring equipment is deployed to record various status data of the vehicle during the verification process in real time, providing a basis for functional verification. Mass Production Parking Area: Path guidance equipment is deployed to guide vehicles into parking spaces in an orderly manner, with the status monitoring unit completing the final parking confirmation.

[0114] Branch Process: Safe Parking Area & Vehicle Return Area. This is the handling path for abnormal vehicle conditions, also supported by monitoring equipment: Safe Parking Area: Used to store faulty or abnormal vehicles. The equipment continuously monitors the vehicle status to ensure it is in a safe area and avoids affecting normal traffic flow within the factory. Vehicle Return Area: Used to store vehicles awaiting repair. The equipment records the vehicle's return status and dwell time, and redirects the vehicle back to the main process after repair is completed.

[0115] Step S306: Based on the number of vehicle trips, vehicle environmental perception data, vehicle monitoring data, and station monitoring results, detect whether there are any abnormalities in each transfer vehicle.

[0116] Abnormal situations include at least one of the following: abnormal vehicle location or route, abnormal vehicle speed, abnormal vehicle status, or abnormal station access.

[0117] Specifically, the transfer server performs timestamp alignment, spatial coordinate unification, and noise data cleaning on the aforementioned multi-source data to eliminate data delays, location deviations, and data interference between different devices, ensuring that all data are consistent in time sequence, location, and authenticity, thus providing an accurate data foundation for anomaly detection.

[0118] The transfer server categorizes transfer vehicle anomalies into four main types based on preset anomaly detection rules: vehicle location or route anomaly, vehicle speed anomaly, vehicle status anomaly, and station access anomaly. A vehicle is considered to be abnormal if it meets any one of these anomaly detection criteria.

[0119] Specifically, the transfer server combines vehicle location information from vehicle driving data, vehicle environmental perception data, and station radar monitoring locations to compare with the vehicle's globally planned route. It determines whether the vehicle deviates from the preset driving trajectory, enters a restricted area, or exhibits map matching misalignment, positioning offset, or other anomalies, thus completing path and location anomaly detection.

[0120] The transfer server detects vehicle driving status based on vehicle speed information in the vehicle driving data, station-monitored vehicle speeds, and road speed limits. It determines whether the vehicle exhibits abnormal behavior such as speeding, coasting at low speeds, or frequent acceleration and deceleration without reasonable cause.

[0121] The transfer server detects the vehicle's hardware and operational status based on vehicle status information from vehicle driving data and vehicle environmental perception data. It determines whether the vehicle is experiencing communication fluctuations, sensor malfunctions, electronic control failures, exit from unmanned mode, braking abnormalities, or other vehicle-specific fault conditions.

[0122] The transfer server relies on site monitoring data to determine the vehicle's passage within the site area. It detects whether vehicles have exceeded the parking time limit, are abnormally delayed, have failed identity verification, or are experiencing queue congestion. It also detects whether there are obstacles or people entering the site that are interfering with the normal passage of vehicles.

[0123] The transfer server performs a comprehensive assessment after completing four dimensions of checks. If a transfer vehicle fails to meet the driving specifications in any of the following aspects—location path, driving speed, vehicle status, or station access—it is determined that the transfer vehicle is in an abnormal situation; if all four checks are normal, the transfer vehicle is determined to be driving normally.

[0124] Step S307: If there is an abnormality in the transfer vehicle, determine the cause of the abnormality.

[0125] Specifically, the transfer server combines vehicle location information, planned routes, station monitoring locations, and perception information to conduct source analysis and determine the cause of the anomaly. The causes of the anomaly include: map matching deviation, positioning drift, excessive vehicle correction, and obstacles in the route.

[0126] The transfer server combines vehicle speed curves, road speed limits, station-monitored vehicle speeds, control commands, and perception data to conduct source analysis and determine the causes of anomalies, including: active speed reduction on curves, braking triggered by falsely detected obstacles, interference from vehicles ahead, fluctuations in control algorithm parameters, and changes in road speed limits.

[0127] The transfer server combines the vehicle's reported status, communication quality, sensor status, and autonomous driving mode to conduct source analysis and determine the cause of the anomaly, including: communication link fluctuations, sensor anomalies, electronic control failures, and abnormal exit from unmanned mode.

[0128] The transfer server combines station queuing status, vehicle dwell time, station environment monitoring, gate status, and personnel detection results to conduct source tracing analysis and determine the causes of anomalies, including: node queuing congestion, identity verification delay, vehicle dwell time exceeding the limit, foreign objects entering the station area, personnel interference, and gate opening and closing delay.

[0129] Step S308: Handle the abnormal transfer vehicle according to the cause of the abnormality.

[0130] In one optional implementation, for trajectory path anomalies such as map matching deviation, positioning drift, and excessive vehicle correction, the transfer server prioritizes correcting the vehicle's driving trajectory to ensure compliance with the driving route. The server recalibrates the vehicle's positioning coordinate system, corrects the map matching algorithm parameters, and eliminates positional deviations caused by positioning drift; it reduces the intensity of vehicle correction to avoid frequent over-correction that could cause vehicle shaking or lane departure; for obstacles present in the path, it determines the type of obstacle based on environmental perception information. If it is a temporary obstacle, a local fine-tuning trajectory is generated; if it is a fixed obstacle, a temporary detour instruction is issued to allow the vehicle to smoothly avoid the obstacle and resume normal route travel.

[0131] To address speed anomalies such as active speed reduction on curves, braking triggered by falsely detected obstacles, interference from vehicles ahead, fluctuations in control algorithm parameters, and changes in road speed limits, the transfer server dynamically adjusts vehicle speed. For normal speed reduction on curves and reasonable speed fluctuations caused by changes in road speed limits, the server updates road speed limit labels and simultaneously corrects the vehicle's speed adjustment range. For abnormal braking and frequent acceleration / deceleration caused by false detections or interference from vehicles ahead, the server optimizes the perception recognition threshold, filters false obstacles, increases the following safety distance, and avoids interference from vehicles ahead. For fluctuations in control algorithm parameters, the server recalibrates vehicle control parameters to stabilize acceleration and braking force, eliminating irregular speed fluctuations.

[0132] In response to equipment anomalies such as communication link fluctuations, sensor malfunctions, electronic control failures, and abnormal exits from autonomous driving mode, the transfer server performs safety management and fault handling. For communication fluctuations, it switches to a backup communication channel, retransmits missing data, and ensures continuous data transmission. For sensor anomalies, it shields abnormal sensor data and activates redundant sensors to collect information. For electronic control failures and abnormal exits from autonomous driving mode, the server limits vehicle speed, prohibits vehicles from entering main roads, issues a stop order to the nearest safe area, and guides the vehicle to a safe location to prevent safety hazards caused by autonomous driving malfunctions, awaiting manual inspection and troubleshooting.

[0133] To address station time anomalies such as queuing congestion, identity verification delays, vehicle overstaying, foreign objects entering the station area, personnel interference, and gate opening / closing delays, the transfer server optimizes the station access control logic. For queuing congestion, the vehicle entry order is adjusted to implement staggered entry; for verification delays and gate jams, the verification process is simplified and the gate control module is restarted to reduce equipment downtime; for foreign objects entering the station or personnel interference, warning instructions are issued to remind vehicles to slow down and give way, while simultaneously triggering early warnings from station monitoring equipment; for vehicles overstaying without cause, departure instructions are issued to urge vehicles to complete their work and leave the station, reducing unnecessary dwell time and alleviating station congestion.

[0134] After handling this abnormal vehicle, the transfer server records and archives all abnormality types, causes, handling measures, and rectification effects. Simultaneously, the abnormal data is input into a deep learning model to update preset optimization rules, optimize path matching parameters, vehicle control algorithms, and station scheduling logic, reducing the probability of similar abnormalities recurring and achieving closed-loop optimization of transfer vehicle abnormality handling.

[0135] Specifically, step S308 above may include the following steps: Step a1: If the cause of the abnormality is that there are obstacles in the path, then determine the type of obstacle.

[0136] Specifically, after determining that the abnormality of the transfer vehicle is due to obstacles in its travel path, the transfer server combines vehicle environmental perception data and station monitoring data to perform feature recognition, contour extraction, and attribute determination of the obstacles. Based on the obstacle's motion state and object attributes, the obstacles are classified into two categories: dynamic traffic participants and temporary obstacles.

[0137] Among them, dynamic traffic participants mainly include pedestrians, mobile devices, and other non-task vehicles that have entered the passage area; temporary obstacles mainly include fixed temporary obstructions such as fallen debris, piled materials, and stationary faulty equipment, and the obstacle type is identified and determined.

[0138] Step a2: If the obstacle is a dynamic traffic participant, then the dynamic traffic participant is driven away by calling the monitoring equipment at the site corresponding to the obstacle.

[0139] Specifically, when the transfer server determines that an obstacle is a dynamic traffic participant, it matches the nearest monitoring device based on the obstacle's location. The transfer server issues a removal control command, calling on the corresponding station's audible and visual warning devices and voice prompt devices to provide audible and visual reminders and voice guidance to the dynamic traffic participant, warning personnel or mobile devices to leave the traffic lane, quickly clearing dynamic interference, ensuring the original planned route is unobstructed, and allowing transfer vehicles to pass normally without changing their routes.

[0140] Step a3: If the obstacle is a temporary obstacle, then plan a temporary detour route for the transfer vehicle based on the location of the temporary obstacle.

[0141] Specifically, after the transfer server determines that the current obstacle is an immovable temporary obstacle, it first extracts the obstacle's key physical parameters, including the obstacle's precise coordinates, the actual lane range it occupies, and the length of its obstruction along the road. This clarifies the area the obstacle occupies on the road, the degree of obstruction, and determines the extent to which the obstacle blocks the original travel route, providing data for subsequent area searches.

[0142] The transfer server uses the location of the temporary obstacle as the center and relies on a real-time updated dynamic environment map to search the road network around the obstacle. Combining the lane distribution, restricted areas, and road boundaries on the map, it filters out unoccupied, safe, and compliant passable areas, excluding congested, closed, and impassable sections.

[0143] Within the passable area, the transfer server performs trajectory calculations based on multiple constraints. Specifically, it considers real-time road congestion to avoid sections with heavy traffic and queues; it prioritizes high-priority vehicles to ensure smooth detours; and it matches road connectivity, turning nodes, and lane connections with the park's road topology to ensure the detour trajectory conforms to the park's road driving rules.

[0144] The transfer server avoids road sections directly blocked by obstacles, refits and calculates the vehicle's trajectory within the passable area, changes the vehicle's original path, and moves the vehicle away from the location of the temporary obstacle, eliminating the obstruction to the vehicle's passage.

[0145] The transfer server considers spatial security, driving smoothness, and travel distance to generate a safe, smooth, and shortest temporary detour route. This route avoids fixed temporary obstacles while meeting the park's speed limits, smooth turning, and conflict-free driving requirements, ensuring that the transfer vehicles can complete the detour stably and safely.

[0146] Step a4: Send the temporary detour route to the transfer vehicles and the monitoring equipment at each station.

[0147] Specifically, after the transfer server generates a temporary detour route, it simultaneously sends the detour route information to the abnormal transfer vehicle and the monitoring equipment at each station along the route. After receiving the route instruction, the transfer vehicle switches its driving trajectory and drives autonomously according to the temporary detour route; the monitoring equipment at the stations along the route updates the vehicle's passage route in real time, and performs lane verification, passage release, and trajectory monitoring in advance to ensure that the entire process of vehicle detour is controllable and monitorable.

[0148] Step a5: If a temporary detour route cannot be generated or dynamic traffic participants cannot be driven away, an emergency stop command is sent to the abnormal transfer vehicle, and other transfer vehicles within the preset range of the abnormal transfer vehicle are dispatched to slow down and give way.

[0149] Specifically, if obstacle handling fails, there are two scenarios: first, dynamic traffic participants cannot be driven away, and road interference persists; second, there are no available lanes nearby, and the transfer server cannot generate a compliant temporary detour route. The transfer server immediately issues an emergency stop command to the abnormal transfer vehicle, controlling the vehicle to brake smoothly and park safely in place to prevent collisions caused by forced passage. Simultaneously, the transfer server searches for other transfer vehicles within a preset range of the abnormal vehicle and issues deceleration and avoidance commands to reduce the speed of surrounding vehicles, increase vehicle distance, avoid chain reactions, and achieve safe traffic flow management in the area.

[0150] Step S309: If there are no abnormalities in the transfer vehicles, control each transfer vehicle to continue to perform the scheduling task until the scheduling task is completed, store the vehicle driving data, vehicle monitoring data and station monitoring result data, and generate scheduling task data.

[0151] In one optional embodiment of this application, after generating the scheduling task data, the following steps may be further included: Step b1: Based on the scheduling task data, calculate the transfer time of each transfer vehicle at each corresponding station.

[0152] The station transfer time includes the transfer time of each transfer vehicle between any two adjacent stations and the parking waiting time at each station.

[0153] Specifically, after the scheduling task is completed, the transfer server reads the scheduling task data stored in the system and performs time breakdown and statistics on the transfer process of each transfer vehicle. The station transfer time is divided into two parts: the first part is the road segment transfer time, which refers to the travel time consumed by the transfer vehicle during normal travel between two adjacent stations; the second part is the parking waiting time, including the time spent by the vehicle after arriving at the station for parking adjustment, identity verification, and queuing. The transfer server integrates and calculates the two types of time to obtain the complete station transfer time of the transfer vehicle at each station.

[0154] Step b2: For each transfer vehicle, determine the time spent at each station based on the transfer time at the corresponding station.

[0155] Specifically, the transfer server uses a single transfer vehicle as the statistical object, summarizing the transfer time of all stations the vehicle passes through. It integrates and aggregates the travel time and parking time within a single station to form a comprehensive time index, accurately determining the station time of each transfer vehicle at the corresponding station, and can intuitively reflect the total time consumed by the vehicle on the travel route and at the stops.

[0156] Step b3: If the time taken for a site exceeds the corresponding preset time, then an abnormal time consumption situation is identified.

[0157] Specifically, the system pre-sets the preset time for each station based on the factory's transfer specifications and station operation rhythm, and uses the preset time as the benchmark for anomaly detection. The transfer server compares the actual station time obtained from the statistics with the preset time for each station. When the actual time taken at a station exceeds the preset time, it is determined that the transfer vehicle has experienced a time consumption anomaly at the corresponding station.

[0158] Step b4: Based on the vehicle driving data, determine the actual mileage of the transfer vehicle.

[0159] Specifically, the transfer server parses the vehicle driving data retained from this mission, extracts the vehicle's continuous positioning trajectory throughout the entire journey, records the vehicle's entire driving trajectory from the starting position of departure to the end position of the mission, and obtains the vehicle's actual driving distance by accumulating and statistically analyzing the trajectory, and finally determines the actual driving mileage of the transfer vehicle.

[0160] Step b5: Compare the actual mileage with the globally planned path corresponding to the transfer vehicle to obtain the detour distance.

[0161] Specifically, the transfer server retrieves the globally planned path initially issued for this task and extracts the theoretical mileage data of the planned path. The difference between the actual mileage traveled by the vehicle and the planned theoretical mileage is calculated to obtain the detour distance incurred by the vehicle during the transfer process, quantifying the length of time the vehicle deviates from the planned route.

[0162] Step b6: If the detour distance is greater than the preset detour distance threshold, it is determined that there is a detour.

[0163] Specifically, the transfer server can preset a detour distance threshold as a criterion for judging abnormal detours. The transfer server compares the calculated actual detour distance with the preset threshold. If the detour distance is greater than the preset detour distance threshold, it is determined that the transfer vehicle has engaged in abnormal route detour behavior during this transfer process.

[0164] Step b7: Compare the actual driving speed with the global driving speed to detect any speed anomalies.

[0165] Specifically, the transfer server extracts the actual driving speed data of the vehicles throughout the entire process and compares it segment by segment with the global driving speed set in the early scheduling and planning stage, according to the road segment division method. It screens for situations such as speed fluctuations, sudden increases or decreases, and long-term deviations from the planned speed during the vehicle's journey, completing the initial screening for abnormal vehicle speeds.

[0166] Step b8: If the absolute value of the speed difference between the actual driving speed and the global driving speed is greater than the preset speed difference threshold, then an abnormal speed situation is determined to exist.

[0167] Specifically, the transfer server can preset a speed difference threshold, and the transfer server calculates the absolute value of the difference between the actual driving speed and the global driving speed segment by segment. When the absolute value of the speed difference is greater than the preset speed difference threshold, it is determined that the transfer vehicle has an abnormal speed.

[0168] Step b9: Based on vehicle driving data, vehicle monitoring data, and station monitoring results, determine the reasons for the time delay and / or detour and / or abnormal speed of the transfer vehicle.

[0169] Specifically, the transfer server aggregates vehicle driving data, vehicle monitoring data, and station monitoring results retained from this task, and conducts a retrospective review of the three types of issues identified: abnormal time consumption, route detours, and abnormal speeds. By combining road condition information, vehicle status, and station monitoring records, the specific causes of abnormal time consumption, route detours, and speeds are accurately determined, completing the post-transfer task anomaly source analysis.

[0170] Step b10: Based on the reasons for the time consumption and / or detours and / or abnormal speeds, generate the target optimization plan corresponding to the transfer vehicle.

[0171] Specifically, step b10 above may include the following steps: Step b101: Based on the reasons for the time delay and / or detour and / or abnormal speed, determine the preset optimization rules corresponding to the reasons for the time delay and / or detour and / or abnormal speed respectively.

[0172] Specifically, after completing the data analysis of the transfer task, the transfer server accurately determines the reasons for the time delay, detour, and abnormal speed of the transfer vehicles, clarifies the cause, location, and manifestation of each abnormality, and completes the classification and sorting of all abnormalities, providing basic data support for rule matching.

[0173] The transit server invokes pre-edited and stored preset optimization rules in the backend. These rules form a hierarchical judgment system, mainly based on four dimensions: the level of anomaly risk, the scope of impact, the frequency of anomalies, and the importance of the transit task. Different evaluation criteria are established for different types of anomalies, forming a standardized optimization rule library.

[0174] The transit server compares and matches each of the identified time-consuming, detour-related, and speed-related anomalies with the preset optimization rules. Based on the specific characteristics of each type of anomaly, the cause is categorized into the corresponding rule level, achieving a precise match between anomalies and optimization rules.

[0175] The transfer server determines the optimization direction for each type of anomaly based on the pre-defined optimization rules after matching. It also assigns optimization weights to anomalies according to four evaluation dimensions, distinguishing between primary and secondary impacts; and prioritizes the handling of various anomalies, giving priority to high-risk, high-impact, high-frequency, and high-task-level anomalies.

[0176] For example, preset optimization rules are set based on speed anomalies: speed anomalies involve driving safety, have the highest risk level, and the highest rule priority; rule definition: vehicles that exceed the speed limit, frequently accelerate or decelerate, or deviate significantly from the planned speed are judged as high-risk anomalies; optimization weight: highest level, priority for rectification; processing priority: ahead of time-consuming anomalies and detour anomalies. Applicable scenarios: speeding on main roads within the factory area, failure to slow down when turning, and inconsistent vehicle speed.

[0177] Preset optimization rules for time-consuming anomalies: Time-consuming anomalies affect the overall transfer rhythm, are prone to causing station congestion, have a wide impact range, and occur frequently, so the rule priority is secondary: Rule definition: When vehicles stop at stations for too long, queues are delayed, or verification waits are too long, causing subsequent vehicles to back up, they are classified as medium-to-high level anomalies. Optimization weight: second only to speed anomaly, higher than ordinary detour anomaly; processing priority: second only to speed anomaly; applicable scenarios: excessive timeout at loading and unloading stations, gate queuing congestion, and excessively long handover process.

[0178] Preset optimization rules for detour anomalies: Detour anomalies are mostly temporary obstacle avoidance and occasional occurrences, with low frequency and low safety risk, and have the lowest rule priority: Rule definition: Compliant detours caused by temporary obstacles or temporary road control are low-risk and occasional anomalies; Optimization weight: lowest; Processing priority: after time consumption anomalies and speed anomalies; Applicable scenarios: Passive detours to avoid temporary material piles and temporary construction sections.

[0179] Step b102: Generate a basic optimization strategy based on the preset optimization rules corresponding to the reasons for time consumption and / or detours and / or abnormal speeds.

[0180] Specifically, after the transfer server completes the matching of its preset optimization rules based on the reasons for time consumption, detours, and speed anomalies, it assigns optimization weights and prioritizes the handling of various anomalies according to the anomaly risk level, impact range, frequency of occurrence, and importance of the transfer task determined by the preset optimization rules. Optimization measures are formulated for anomalies corresponding to high-risk, high-impact, high-frequency, and high-priority tasks.

[0181] First, the transfer server formulates basic optimization strategies at the vehicle driving control level based on preset optimization rules for speed anomalies and their corresponding highest priority. Since speed anomalies directly affect driving safety, they have the highest optimization weight and are processed with the highest priority. The transfer server combines the specific manifestations of speed anomalies, such as speeding, frequent acceleration and deceleration, and significant deviations from the planned speed, to optimize three aspects: vehicle speed adjustment range, road speed limits, and driving control parameters, in order to reduce safety risks and stabilize driving speed. For example, if a vehicle does not slow down on a turning section within the factory area or its speed on a main road consistently exceeds the planned speed, the transfer server limits the maximum speed on that section of road, compresses the vehicle speed fluctuation range, and corrects the vehicle acceleration parameters to avoid sudden acceleration and deceleration.

[0182] Secondly, for time-consuming anomalies and their corresponding second-highest priority preset optimization rules, the transfer server formulates basic optimization strategies at the station operation and traffic flow level. Since time-consuming anomalies affect the overall transfer cycle and easily cause station congestion, the transfer server, considering the specific causes of time-consuming anomalies such as station stop times exceeding limits, queuing delays, and excessively long verification wait times, optimizes three aspects: station queuing logic, vehicle stop duration, and identity verification process, to improve station traffic efficiency and reduce vehicle backlog. For example, if multiple vehicles are queuing together at loading / unloading stations and slow verification procedures cause stop times exceeding limits, the transfer server adjusts the vehicle entry queuing order, reasonably sets standard stop durations, and simplifies unnecessary verification steps to alleviate station congestion.

[0183] Finally, for detour anomalies and their corresponding lower-priority preset optimization rules, the transfer server formulates basic optimization strategies from the perspectives of path planning and road network management. Since detour anomalies are mostly caused by temporary obstacle avoidance or occasional factors, the safety risks and impact range are relatively small. The transfer server, considering the specific scenarios of detour anomalies, such as avoiding temporary material piles or temporary construction sections, optimizes three aspects: path planning constraints, obstacle avoidance logic, and road network access permissions, to reduce unnecessary detours and shorten actual travel distances. For example, if temporary material piles on the road cause vehicles to be forced to detour, the transfer server optimizes the obstacle identification logic, using fine-tuning of trajectories instead of large-scale detours for small temporary obstacles, tightening path deviation constraints, and reducing unnecessary travel distances.

[0184] The transfer server integrates the optimization measures formulated for speed anomalies, time consumption anomalies, and detour anomalies to form multiple targeted basic optimization strategies with different focuses and adapted to each anomaly type, providing a strategic foundation for subsequent performance prediction using deep learning algorithms.

[0185] Step b103: Predict the basic optimization strategy and obtain the prediction results.

[0186] Specifically, the transfer server inputs multiple basic optimization strategies generated for speed anomalies, time consumption anomalies, and detour anomalies into a pre-trained deep learning algorithm model, providing strategy objects for subsequent simulation predictions. Then, historical data and environmental parameters are loaded to provide a basis for simulation. The deep learning algorithm loads historical transfer data, including historical vehicle driving data, station passage data, road environment data, and records of various anomalies, using this as the basis for the realistic scenario in the simulation to ensure that the prediction results closely match actual transfer conditions. Simulation is performed on each basic optimization strategy. The algorithm simulates the operation of each basic optimization strategy, simulating the vehicle's driving status within the park, station parking and operation status, and route planning and passage status after the implementation of the corresponding optimization strategy, thus reconstructing the complete transfer process. Key evaluation indicators are quantified during the simulation, including vehicle speed fluctuation amplitude, average station passage time, vehicle queue length, route detour deviation distance, anomaly occurrence rate, and safety risk coefficient, forming comparable quantitative data. By comparing the indicators before and after optimization, the algorithm obtains the prediction effect by comparing the optimized indicators obtained from simulation with the actual abnormal data before optimization. It quantitatively calculates the degree of improvement of each basic optimization strategy on speed anomalies, time consumption anomalies, and detour anomalies, and finally outputs the prediction effect corresponding to each strategy, providing a basis for subsequent selection of target optimization schemes.

[0187] Step b104: Based on the predicted results, determine the target optimization scheme for the transfer vehicles.

[0188] Specifically, the transfer server, combining the hierarchical judgment logic in the pre-set optimization rules, uses anomaly weight as the screening basis, and clearly defines the screening order as speed anomaly, time anomaly, and detour anomaly. Prioritizes the optimization effect of high-risk, high-weight anomalies, taking driving safety as the first screening criterion, followed by transfer efficiency, and finally the optimization effect of route detours, establishing a multi-level comprehensive screening and evaluation system.

[0189] The transfer server performs a tiered evaluation of multiple basic optimization strategies based on sorting logic. First, it compares the improvement effects of each strategy on speed anomalies and selects optimization strategies with small speed fluctuations and high driving safety. Second, it compares the improvement effects on time-consuming anomalies and selects optimization strategies that can shorten station dwell time and alleviate station congestion. Finally, it compares the optimization capabilities for detour anomalies and selects optimization strategies with small detour deviations and shorter travel distances.

[0190] The transfer server comprehensively evaluates the remaining optimization strategies based on multiple indicators, including driving safety, transfer time, detour distance, and operational stability. It also investigates whether the optimization strategies have any secondary negative impacts, such as optimizing vehicle speed causing station congestion or optimizing routes increasing driving energy consumption. Optimization strategies with negative interference or poor adaptability are eliminated.

[0191] The transfer server selects the optimization strategy that best fits the cause of the anomaly, adapts to the current transfer environment, and has the best overall improvement effect from all basic optimization strategies, and determines it as the target optimization solution for the transfer vehicle.

[0192] The transfer server writes the determined target optimization plan into the scheduling and control system, updates vehicle driving parameters, station management logic, and route planning constraints, and applies it to subsequent similar transfer tasks. By continuously summarizing anomaly optimization experience, the transfer system can achieve continuous iteration, reducing the probability of recurring similar speed anomalies, time consumption anomalies, and detour anomalies.

[0193] In one optional embodiment of this application, after receiving in real time vehicle driving data and vehicle environmental perception data sent by each transfer vehicle, as well as vehicle monitoring data and site monitoring result data sent by each site monitoring device for monitoring each transfer vehicle, the above method further includes: By combining vehicle driving data, vehicle environmental perception data, vehicle monitoring data, and dynamic environmental maps, the transfer process of each transfer vehicle can be visualized in real time.

[0194] Specifically, the transfer server receives real-time vehicle driving data and vehicle environmental perception data uploaded by the transfer vehicles, as well as vehicle monitoring data collected by the station monitoring equipment. This includes real-time information such as vehicle location coordinates, driving speed, vehicle posture, surrounding obstacle information, station queuing status, and vehicle operation status, providing a complete data source for visualization. The transfer server cleans, analyzes, and organizes the multi-source data, removing invalid and interfering data and extracting key visualization elements. These include the vehicle's real-time location, driving trajectory, driving speed, distribution of obstacles around the vehicle, station parking status, and vehicle anomaly marker information.

[0195] Then, the transfer server uses a dynamic environmental map as its underlying platform to accurately match and map the processed vehicle driving data, environmental perception data, and vehicle monitoring data into the map coordinate system. This allows vehicle locations, road networks, station areas, obstacle distribution, and congested road sections to be overlaid and merged within the same map framework.

[0196] Next, based on the data fusion results, the transfer server renders the dynamic driving trajectory, current road segment, vehicle operating status, and station stopping status of each transfer vehicle in real time. It also marks road obstacles, congested areas, and abnormal vehicle information, intuitively presenting the entire transfer process from departure, driving, entering the station, verification to completing the task.

[0197] Finally, after the transfer server completes the visualization processing, it forms an intuitive and dynamic visual interface. Staff can view the distribution location, driving status, station operation status, and environmental changes of all transfer vehicles in real time, realizing full-domain visual supervision of the transfer process. This facilitates the timely detection of problems such as vehicle delays, deviations from the route, and abnormal vehicle speeds, thereby improving the transfer scheduling and management capabilities.

[0198] The vehicle transfer method provided in this application acquires first environmental perception information within a preset range collected in real time by each transfer vehicle. It relies on onboard sensing equipment to collect local environmental information such as surrounding obstacles, lane conditions, pedestrians, and temporary material stacks in real time, achieving full coverage perception of the near-field environment around the vehicle and providing a real-time data source for dynamic environmental updates. It acquires second environmental perception information within a preset range collected in real time by monitoring equipment at each station, as well as the corresponding station status information. Station-side equipment supplements environmental information such as obstacles, personnel activity, and channel occupancy in the station area, while simultaneously acquiring station operating status such as gate status, queuing status, and verification status, compensating for blind spots in fixed areas of the station's onboard sensing. It acquires a high-precision map corresponding to the target park. Using the high-precision map as the underlying foundation, it possesses accurate road network topology, lane boundaries, station coordinates, and restricted areas, ensuring the positional accuracy benchmark for subsequent environmental fusion and trajectory planning. The first environmental perception information, second environmental perception information, and station status information are fused with the high-precision map to generate a dynamic environmental map. It integrates multi-source sensing data from vehicles and stations with static high-precision maps, and updates dynamic changes in the park's road network, traffic congestion, and station conditions in real time, forming a real-time dynamic environmental view of the entire area. This provides accurate and comprehensive data support for vehicle route planning, anomaly tracing, intelligent scheduling, and visual monitoring.

[0199] Next, obtain the vehicle attribute information for each transfer vehicle. Understand the inherent attributes such as vehicle size, load capacity, driving performance, operation type, and task level. This provides a foundation for subsequent route adaptation, priority allocation, speed and timing planning, avoiding mismatches between the scheduling plan and the vehicle's characteristics. Based on the vehicle attribute information, determine the vehicle transfer routes and transfer priorities. Plan the station sequence according to vehicle attribute differences, and simultaneously classify transfer priorities to achieve hierarchical task management; ensure high-priority tasks have priority passage and priority stopping, and reasonably match vehicle operating capacity with transfer task requirements. Based on the vehicle transfer routes and dynamic environment map, generate a global planned route. Combine fixed station paths with real-time road conditions, obstacles, and traffic constraints in the park to avoid congested sections and restricted areas, planning a smooth, conflict-free, and reasonably spaced global route to reduce detours and intermediate delays. Extract global speed limits, and combine the global planned route and transfer priorities to plan the global driving speed, preset start time, and station dwell time. Adhering to factory speed limits, vehicles are configured with differentiated speeds, departure times, and stop durations based on priority. Off-peak departures and balanced traffic flow across the road network prevent multiple vehicles from congesting at stations simultaneously, reducing congestion at the source. Preset arrival times are determined based on start time, planned routes, speed, and stop duration. Accurate prediction of vehicle arrival times at each station ensures predictable and traceable timing throughout the entire process, facilitating station preparation for verification, gate opening, and operations, thus improving station coordination efficiency. Vehicle dispatch information is generated based on various time sequences, routes, speeds, priorities, and arrival times. Integrating all dispatch elements such as route, speed, departure time, arrival time, stop duration, and task priority, standardized and executable dispatch instructions are formed, enabling vehicles to drive according to regulations and facilitating collaborative station monitoring, ensuring the orderly, efficient, and coordinated operation of the entire park's transfer operations.

[0200] Next, the system receives real-time vehicle driving data and environmental perception data from each transfer vehicle. It aggregates vehicle location, speed, driving status, and surrounding environment perception information in real time, enabling dynamic real-time acquisition of vehicle operating status and the surrounding environment, providing raw real-time data support for subsequent anomaly detection. It also receives real-time vehicle monitoring data and station monitoring results data from monitoring equipment at each station. Station-side equipment supplements information on vehicle arrival, queuing, parking, turnstiles, and on-site operating conditions within the station area, filling blind spots in vehicle-mounted perception and achieving data complementarity between the vehicle and station ends, improving the completeness of overall monitoring. Based on multi-source data, it detects whether any anomalies exist in each transfer vehicle. By integrating multi-dimensional data from both vehicle and station ends for joint analysis, it can promptly and accurately identify various anomalies such as trajectory, speed, equipment, and station operations, avoiding misjudgments and omissions caused by single-data analysis. If an anomaly is found in a transfer vehicle, the cause is determined. The root cause of the anomaly is accurately traced, distinguishing between different causes such as trajectory deviation, speed fluctuations, equipment failure, and station congestion, providing a basis for subsequent targeted handling measures and avoiding blind dispatching intervention. The abnormal transfer vehicle is then processed according to the cause of the anomaly. Anomalies are categorized and graded for precise handling, promptly correcting routes, adjusting vehicle speeds, managing malfunctioning vehicles, and alleviating station congestion to quickly eliminate their impact and ensure transport order and driving safety. If no anomalies are found, vehicles continue their tasks, and data is stored and dispatch task data is generated upon completion. This ensures the continuous and stable execution of normal transport tasks; simultaneously, it fully retains all operational and monitoring data, forming a traceable task archive, providing data support for subsequent algorithm optimization, rule iteration, and scheduling strategy improvement. Specifically, if the anomaly is due to obstacles on the path, the type of obstacle is determined. Obstacle classification enables precise handling, avoiding scheduling inconsistencies caused by uniform processing, and providing a basis for subsequent differentiated response strategies.

[0201] If the obstacle is a dynamic traffic participant, the corresponding station monitoring equipment will be used to remove it. Using the station monitoring equipment, pedestrians, work vehicles, and other dynamic participants can be persuaded and removed on-site without changing vehicle routes. This ensures traffic safety while maintaining the original scheduling sequence and planned routes, without affecting the overall transfer pace. If the obstacle is a temporary obstacle, a temporary detour route will be planned for the transfer vehicles based on its location. For static temporary obstacles such as material stacks and equipment blocking the road, local detour routes will be quickly generated, allowing vehicles to autonomously avoid the obstacle area without prolonged waiting, improving traffic efficiency and route planning flexibility. The temporary detour route will be sent to the transfer vehicles and the monitoring equipment at each station. Vehicles can autonomously adjust their driving trajectory according to the temporary detour route; the station monitoring equipment will be notified of route changes in advance and will adjust its monitoring and release logic accordingly, achieving station coordination and avoiding intersection conflicts and station scheduling disconnects. If a temporary detour route cannot be generated or the dynamic traffic participant cannot be removed, an emergency stop command will be issued to the abnormal transfer vehicle, and other transfer vehicles within the preset range will be dispatched to slow down and give way. In extreme scenarios where clearing obstacles and detouring are not possible, a safety protection loop is formed by parking nearby and surrounding vehicles slowing down to avoid collisions, thus maximizing the operational safety of autonomous driving transportation in the park and preventing secondary traffic anomalies.

[0202] Finally, based on the scheduling task data, the transfer time for each transfer vehicle at each station is calculated. The system accurately breaks down the interval travel time and station waiting time, quantifying the total time consumption and providing refined time-dimensional data for anomaly detection. For each transfer vehicle, the station time is determined based on the station transfer time. The overall dwell and passage time at a single station is aggregated and calculated to form standardized station time statistics, facilitating comparison with standard times. If the station time exceeds the preset station time, an anomaly is identified. Threshold comparison automatically identifies issues such as station congestion, queues, and verification delays, achieving automated anomaly screening without manual verification. Based on vehicle travel data, the actual mileage of the transfer vehicles is determined. Accurate statistics of the actual vehicle mileage provide mileage benchmark data for subsequent route planning rationality and detour behavior determination. The actual mileage is compared with the globally planned route to obtain the detour distance. The mileage deviation between the actual route and the planned route is quantitatively calculated, intuitively identifying invalid detours, trajectory deviations, and other non-standard driving behaviors. If the detour distance exceeds a preset detour distance threshold, a detour is identified. Using a quantified threshold as the criterion, excessive detours are automatically and accurately identified, avoiding errors from subjective human judgment. Actual driving speed is compared with the global driving speed to detect any speed anomalies. A routine monitoring mechanism is established based on real-time comparison of planned speed limits and actual vehicle speeds to promptly identify issues such as speeding, slow driving, and speed fluctuations. If the absolute value of the speed difference exceeds a preset speed difference threshold, a speed anomaly is confirmed. Significant speed deviations are filtered out using quantified thresholds, eliminating interference from normal small speed fluctuations and improving the accuracy of speed anomaly identification. Based on multi-source data, the causes of time delays, detours, and speed anomalies for transport vehicles are determined. Source analysis is performed by integrating multi-dimensional data from both vehicle and station ends to accurately pinpoint the root causes of various anomalies, providing causal support for optimization plan development. Based on the causes of time delays, detours, and speed anomalies, corresponding preset optimization rules are matched. This system precisely binds the causes of anomalies to hierarchical optimization rules, establishing differentiated evaluation criteria based on risk level, impact scope, frequency of occurrence, and task priority. It clarifies the optimization weight and processing priority of various anomalies, providing a standardized basis for strategy formulation. Basic optimization strategies are generated based on the matched preset optimization rules. Specific optimization measures are developed for three types of anomalies—time consumption, detours, and speed—from the dimensions of station processes, route planning, and vehicle control, forming multiple sets of basic strategies with different focuses to cover various anomaly rectification needs. The basic optimization strategies are predicted to obtain their predicted effects. Simulation analysis quantifies the improvement effects of each basic strategy on aspects such as travel time, detour distance, and vehicle speed stability, evaluating the merits of strategies in a data-driven manner to avoid subjective selection based on experience. The target optimization scheme for the transfer vehicles is determined based on the predicted effects.The solution with the strongest adaptability and the best overall optimization effect is selected from multiple basic strategies to accurately match the abnormal scenario. At the same time, it can feed back into the scheduling system iteration, effectively reducing the recurrence rate of similar time-consuming, detour, and speed anomalies, and improving the overall operational efficiency and management level of the park's transfer.

[0203] Furthermore, the vehicle transfer method provided in this application integrates and overlays vehicle driving data, vehicle environmental perception data, vehicle monitoring data, and dynamic environmental maps, mapping multi-source information such as vehicle location, driving status, surrounding environment, and station operating conditions onto the dynamic map. This enables real-time visualization of all transfer vehicles throughout the entire process, allowing for intuitive understanding of vehicle driving trajectories, station parking status, and changes in the surrounding environment. It also facilitates timely detection of various anomalies such as time consumption, detours, and speed, enabling unified cloud-based supervision, rapid intervention, and scheduling. This enhances the intuitiveness, real-time nature, and overall control capabilities of park transfer management.

[0204] This embodiment also provides a vehicle transfer method apparatus for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0205] This embodiment provides a vehicle transfer method apparatus, applied to a transfer server in a vehicle transfer system. The vehicle transfer system also includes at least one transfer vehicle and at least one site monitoring device, with each site monitoring device installed at a corresponding site within the target area. The transfer server is communicatively connected to each transfer vehicle and each site monitoring device, such as... Figure 7 As shown, it includes: Module 401 is used to acquire a dynamic environment map corresponding to the target park. The generation module 402 is used to generate vehicle scheduling information for each transfer vehicle based on the dynamic environment map. The vehicle scheduling information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time for each transfer vehicle. The sending module 403 is used to transmit the vehicle scheduling information corresponding to each transfer vehicle to each transfer vehicle and each station monitoring device, so that each transfer vehicle can carry out transfers based on the vehicle scheduling information, and each station monitoring device can monitor each transfer vehicle based on the vehicle scheduling information.

[0206] In some optional implementations, the acquisition module 401 is specifically used to acquire the first environmental perception information within a preset range of each transfer vehicle collected in real time; acquire the second environmental perception information within a preset range of each station collected in real time by each station monitoring device, as well as the station status information corresponding to each station; acquire the high-precision map corresponding to the target park; and fuse the first environmental perception information, the second environmental perception information, the station status information, and the high-precision map to generate a dynamic environmental map.

[0207] In some optional implementations, the generation module 402 is specifically used to obtain vehicle attribute information corresponding to each transfer vehicle; the vehicle attribute information includes vehicle identification information and vehicle status information corresponding to each transfer vehicle; based on the vehicle attribute information corresponding to each transfer vehicle, the vehicle transfer route and transfer priority corresponding to each transfer vehicle are determined; the vehicle transfer route includes the stations that the transfer vehicle needs to pass through; based on the vehicle transfer routes and the dynamic environment map, a global planned route corresponding to each transfer vehicle is generated; the global speed limit of the factory area is extracted from the dynamic environment map, and based on the global planned route and transfer priority corresponding to each transfer vehicle, the global driving speed, preset start time, and station dwell time corresponding to each transfer vehicle are planned; based on the preset start time, global planned route, global driving speed, and station dwell time corresponding to each transfer vehicle, the preset arrival time corresponding to each transfer vehicle is determined; based on the preset start time, global planned route, global driving speed, transfer priority, station dwell time, and preset arrival time corresponding to each transfer vehicle, vehicle scheduling information is generated.

[0208] In some optional implementations, the sending module 403 is also used to receive in real time vehicle driving data and vehicle environmental perception data sent by each transfer vehicle; the vehicle driving data includes vehicle location information, vehicle speed information, vehicle attitude information, and vehicle status information; and to receive in real time vehicle monitoring data and station monitoring result data sent by monitoring equipment at each station for monitoring each transfer vehicle; the vehicle monitoring data includes collected vehicle images, vehicle location detected by radar, vehicle presence status, lane occupancy status, vehicle speed monitoring, and vehicle identification information; the station monitoring result data includes: whether the vehicle deviates from the path, whether the vehicle is speeding, whether the vehicle has exceeded the parking time limit, whether the vehicle is not identified, and abnormal delays. The system detects whether vehicles are mismatched with the map, whether there are obstacles in the designated area, and whether unauthorized personnel have entered the area. Based on vehicle mileage, vehicle environmental perception data, vehicle monitoring data, and station monitoring results, it checks for any abnormalities in each transfer vehicle. Abnormalities include at least one of the following: abnormal vehicle location or path, abnormal vehicle speed, abnormal vehicle status, or abnormal station access. If an abnormality is found in a transfer vehicle, the cause of the abnormality is determined. The abnormal transfer vehicle is then processed according to the cause. If no abnormality is found in a transfer vehicle, the system controls each transfer vehicle to continue executing the scheduling task until the scheduling task is completed. The system stores vehicle mileage data, vehicle monitoring data, and station monitoring results to generate scheduling task data.

[0209] In some optional implementations, the sending module 403 is specifically used to determine the type of obstacle if the cause of the abnormality is an obstacle in the path; if the type of obstacle is a dynamic traffic participant, the dynamic traffic participant is driven away by calling the station monitoring equipment corresponding to the obstacle; if the type of obstacle is a temporary obstacle, a temporary detour route corresponding to the transfer vehicle is planned based on the location of the temporary obstacle; the temporary detour route is sent to the transfer vehicle and each station monitoring equipment; if a temporary detour route cannot be generated or the dynamic traffic participant cannot be driven away, an emergency stop command is output to the abnormal transfer vehicle, and other transfer vehicles within a preset range of the abnormal transfer vehicle are dispatched to slow down and avoid it.

[0210] In some optional implementations, the sending module 403 is further configured to calculate the station transfer time of each transfer vehicle at each station based on the scheduling task data; the station transfer time includes the transfer time of each transfer vehicle between any two adjacent stations and the parking waiting time at each station; for each transfer vehicle, based on the station transfer time corresponding to the transfer vehicle, determine the station time of the transfer vehicle at each station; if the station time exceeds the corresponding station preset time, it is determined that there is an abnormal time consumption situation; based on the vehicle driving data, determine the actual driving mileage corresponding to the transfer vehicle; and compare the actual driving mileage with the global planning data corresponding to the transfer vehicle. The routes are compared to obtain the detour distance; if the detour distance is greater than the preset detour distance threshold, it is determined that a detour exists; the actual driving speed is compared with the global driving speed to detect whether there is a speed anomaly; if the absolute value of the speed difference between the actual driving speed and the global driving speed is greater than the preset speed difference threshold, it is determined that there is a speed anomaly; based on vehicle driving data, vehicle monitoring data, and station monitoring results, the causes of time delay and / or detour and / or speed anomaly for the transfer vehicle are determined; based on the causes of time delay and / or detour and / or speed anomaly, the corresponding target optimization scheme for the transfer vehicle is generated.

[0211] In some optional implementations, the sending module 403 is further configured to: determine preset optimization rules corresponding to the causes of time delay and / or detour and / or abnormal speed, respectively, based on the causes of time delay and / or detour and / or abnormal speed; generate a basic optimization strategy based on the preset optimization rules corresponding to the causes of time delay and / or detour and / or abnormal speed; predict the basic optimization strategy to obtain the prediction effect; and determine the target optimization scheme corresponding to the transfer vehicle based on the prediction effect.

[0212] In some optional implementations, the sending module 403 is also used to combine vehicle driving data, vehicle environmental perception data, vehicle monitoring data and dynamic environmental map to visualize the transfer process corresponding to each transfer vehicle in real time.

[0213] The vehicle transfer method and apparatus provided in this embodiment of the invention can execute the vehicle transfer method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0214] Figure 8 This is a schematic diagram of a transfer server provided in an embodiment of the present invention.

[0215] The following is a detailed reference. Figure 8The diagram illustrates a suitable structural schematic for implementing a transfer server in an embodiment of the present invention. The transfer server may include a processor (e.g., a central processing unit, graphics processing unit, etc.) 01, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 02 or a program loaded from memory 08 into random access memory (RAM) 03. RAM 03 also stores various programs and data required for the operation of the transfer server. The processor 01, ROM 02, and RAM 03 are interconnected via bus 04. Input / output (I / O) interface 05 is also connected to bus 04.

[0216] Typically, the following devices can be connected to I / O interface 05: input devices 06 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 07 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 08 including, for example, magnetic tapes, hard disks, etc.; and communication devices 09. Communication device 09 allows the transfer server to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 A transfer server with various devices is shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0217] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 09, or installed from memory 08, or installed from ROM 02. When the computer program is executed by processor 01, it performs the functions defined in the vehicle transfer method of the embodiments of the present invention.

[0218] Figure 8 The transit server shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0219] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the vehicle transfer method shown in the above embodiments is implemented.

[0220] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0221] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for vehicle transfer, characterized in that, A transfer server is used in a vehicle transfer system, which also includes at least one transfer vehicle and at least one site monitoring device, with each of the site monitoring devices installed at a corresponding site in the target park. The transfer server is communicatively connected to each of the transfer vehicles and each of the site monitoring devices, and the method includes: Obtain the dynamic environment map corresponding to the target park; Based on the dynamic environment map, generate vehicle scheduling information for each of the transfer vehicles; The vehicle scheduling information corresponding to each of the aforementioned transfer vehicles is transmitted to each of the transfer vehicles and each of the aforementioned station monitoring devices, so that each of the transfer vehicles can carry out transfers based on the vehicle scheduling information, and each of the aforementioned station monitoring devices can monitor each of the transfer vehicles based on the vehicle scheduling information.

2. The method according to claim 1, characterized in that, The acquisition of the dynamic environment map corresponding to the target park includes: Obtain the first environmental perception information within a preset range of each of the aforementioned transfer vehicles in real time; Acquire the second environmental perception information within a preset range of each site, as well as the site status information corresponding to each site, collected in real time by the monitoring devices at each site. Obtain a high-precision map corresponding to the target park; The first environmental perception information, the second environmental perception information, and the status information of each station are fused with the high-precision map to generate the dynamic environmental map.

3. The method according to claim 1, characterized in that, in, The vehicle dispatch information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time of the transfer vehicle. The step of generating vehicle dispatch information corresponding to each of the transfer vehicles based on the dynamic environment map includes: Obtain the vehicle attribute information corresponding to each of the aforementioned transfer vehicles; Based on the vehicle attribute information corresponding to each of the aforementioned transfer vehicles, the vehicle transfer route and transfer priority corresponding to each of the aforementioned transfer vehicles are determined; the vehicle transfer route includes the stations that the transfer vehicle needs to pass through. Based on the vehicle transfer routes and the dynamic environment map, a global planning route is generated for each of the transfer vehicles. Extract the global speed limit of the factory area from the dynamic environment map, and plan the global driving speed, the preset start time and the station stay time of each of the transfer vehicles according to the global planned route and the transfer priority of each of the transfer vehicles. Based on the preset start time, the globally planned route, the global driving speed, and the dwell time at each station for each of the aforementioned transfer vehicles, the preset arrival time for each of the aforementioned transfer vehicles is determined; The vehicle dispatch information is generated based on the preset start time, the globally planned route, the global driving speed, the transfer priority, the dwell time at each station, and the preset arrival time corresponding to the transfer vehicle.

4. The method according to claim 1, characterized in that, After transmitting the vehicle dispatch information corresponding to each of the transfer vehicles to each of the transfer vehicles and each of the station monitoring devices, the method further includes: Real-time reception of vehicle driving data and vehicle environmental perception data sent by each of the aforementioned transfer vehicles. The system receives vehicle monitoring data and site monitoring result data sent in real time from the monitoring devices at each of the aforementioned sites for monitoring each of the aforementioned transfer vehicles. Based on the vehicle mileage count, the vehicle environmental perception data, the vehicle monitoring data, and the station monitoring result data, detect whether there are any abnormalities in each of the transfer vehicles; If the transport vehicle is found to be abnormal, the cause of the abnormality shall be determined. The abnormal transport vehicle shall be handled according to the aforementioned cause of the abnormality; If there are no abnormalities in the transfer vehicles, control each transfer vehicle to continue to perform the scheduling task until the scheduling task is completed, store the vehicle driving data, the vehicle monitoring data and the station monitoring result data, and generate scheduling task data.

5. The method according to claim 4, characterized in that, The process of handling abnormal transport vehicles based on the stated cause of the abnormality includes: If the cause of the anomaly is an obstacle in the path, then determine the type of the obstacle; If the obstacle corresponds to a dynamic traffic participant, the dynamic traffic participant is driven away by calling the site monitoring equipment corresponding to the obstacle; If the obstacle is a temporary obstacle, then a temporary detour route for the transfer vehicle is planned based on the location of the temporary obstacle. The temporary detour route is sent to the transfer vehicle and the monitoring equipment at each of the stations; If a temporary detour route cannot be generated or the dynamic traffic participants cannot be driven away, an emergency stop command is issued to the abnormal transfer vehicle, and other transfer vehicles within a preset range of the abnormal transfer vehicle are dispatched to slow down and give way.

6. The method according to claim 5, characterized in that, The method further includes: Based on the scheduling task data, the station transfer time of each of the transfer vehicles at each of the stations is calculated; the station transfer time includes the transfer time of each of the transfer vehicles between any two adjacent stations and the parking waiting time at each of the stations. For each of the aforementioned transfer vehicles, the time spent at each of the aforementioned stations is determined based on the transfer time at the stations corresponding to the transfer vehicles. If the time taken at a site exceeds the corresponding preset time, then an abnormal time consumption situation is determined to exist; Based on the vehicle driving data, the actual mileage of the transfer vehicle is determined. The actual mileage is compared with the globally planned path corresponding to the transfer vehicle to obtain the detour distance; If the detour distance is greater than a preset detour distance threshold, it is determined that a detour path exists; The actual driving speed is compared with the global driving speed to detect whether there are any speed anomalies; If the absolute value of the speed difference between the actual driving speed and the global driving speed is greater than a preset speed difference threshold, then an abnormal speed situation is determined to exist; Based on the vehicle driving data, the vehicle monitoring data, and the station monitoring results, determine the reasons for the time delay and / or detour and / or abnormal speed of the transfer vehicle. Based on the reasons for the time consumption and / or the reasons for the detour and / or the reasons for the abnormal speed, a target optimization scheme corresponding to the transfer vehicle is generated.

7. The method according to claim 6, characterized in that, The step of generating a target optimization scheme for the transfer vehicle based on the reasons for the time consumption and / or the reasons for the detour and / or the reasons for the speed anomaly includes: Based on the reasons for the time consumption and / or the reasons for the detour and / or the reasons for the speed anomaly, determine the preset optimization rules corresponding to the reasons for the time consumption and / or the reasons for the detour and / or the reasons for the speed anomaly, respectively; Based on the preset optimization rules corresponding to the reasons for the time consumption and / or the reasons for the detour and / or the reasons for the speed anomaly, a basic optimization strategy is generated. The basic optimization strategy is used to make predictions, and the prediction results are obtained. Based on the predicted results, the target optimization scheme corresponding to the transfer vehicle is determined.

8. The method according to claim 4, characterized in that, The method further includes: By combining the vehicle driving data, the vehicle environmental perception data, the vehicle monitoring data, and the dynamic environment map, the transfer process corresponding to each of the transfer vehicles can be visualized in real time.

9. A vehicle transfer device, characterized in that, A transfer server is used in a vehicle transfer system, which also includes at least one transfer vehicle and at least one site monitoring device, with each of the site monitoring devices installed at a corresponding site in the target park. The transfer server is communicatively connected to each of the transfer vehicles and each of the site monitoring devices, and the device includes: The acquisition module is used to acquire a dynamic environment map corresponding to the target park. The generation module is used to generate vehicle scheduling information corresponding to each of the transfer vehicles based on the dynamic environment map; the vehicle scheduling information includes the preset start time, global planned route, global driving speed, transfer priority, dwell time at each station, and preset arrival time of the transfer vehicle. The sending module is used to transmit the vehicle scheduling information corresponding to each of the transfer vehicles to each of the transfer vehicles and each of the station monitoring devices, so that each of the transfer vehicles can carry out transfers based on the vehicle scheduling information, and each of the station monitoring devices can monitor each of the transfer vehicles based on the vehicle scheduling information.

10. A transshipment server, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the vehicle transfer method according to any one of claims 1 to 8.

11. A vehicle transfer system, characterized in that, include: The system includes a transfer server, at least one transfer vehicle, and at least one site monitoring device, with each of the site monitoring devices installed at a corresponding site in the target park. The transfer server is communicatively connected to each of the transfer vehicles and each of the site monitoring devices, wherein: Each of the aforementioned transfer vehicles is used to collect first environmental perception information within a preset range of the transfer vehicle in real time, and transmit the first environmental perception information to the transfer server. Each of the site monitoring devices is used to collect second environmental perception information within a preset range of the site and site status information corresponding to each site in real time, and transmit the second environmental perception information and site status information corresponding to each site to the transfer server. The transfer server is used to execute the vehicle transfer method according to any one of claims 1-8; Each of the aforementioned transfer vehicles is also used to perform transfer scheduling tasks based on the vehicle scheduling information.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the vehicle transfer method according to any one of claims 1 to 8.

13. A computer program product, characterized in that, Includes computer instructions for causing a computer to perform the vehicle transfer method according to any one of claims 1 to 8.

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