Transportation integrated hub station control system for low altitude aircraft and light rail

Abstract

The application discloses a low-altitude aircraft and light rail combined transport traffic comprehensive hub station control system and relates to the field of traffic transportation.The traffic comprehensive hub station control system, through full-process automation and integrated intelligent scheduling, greatly shortens the ground turnaround time of the aircraft, significantly improves the unit time throughput capacity of the hub station, and enables the "air-rail combined transport" to have the conditions for commercial high-density operation; seamless transfer, full-process non-sensing passage and personalized service can be realized, public traffic travel becomes unprecedentedly convenient, comfortable and efficient, and the public's acceptance of the new three-dimensional traffic is greatly enhanced; predictive maintenance reduces the equipment failure rate, the global safety prevention and control system realizes early discovery and early disposal of risks, and digital twin assisted decision-making reduces human errors, which jointly build a multi-dimensional safety defense line; efficient operation reduces labor costs, intelligent energy management reduces power consumption costs and improves the proportion of green energy use. Modular design also reduces the cost of construction and later expansion.

Description

Technical Field

[0001] This invention relates to transportation technology, specifically to a control system for a transportation hub that integrates low-altitude aircraft and light rail. Background Technology

[0002] Currently, the low-altitude economy is rapidly emerging, with electric vertical takeoff and landing (eVTOL) aircraft and other low-altitude vehicles gradually being applied to urban short-distance transportation. These vehicles complement light rail, which serves as the "main artery" of urban transportation, and integrated transportation hubs combining low-altitude aircraft and light rail have become important carriers for the development of smart transportation. However, existing hub station control systems mostly manage light rail and low-altitude aircraft independently, lacking a collaborative scheduling mechanism. This makes it difficult to achieve efficient linkage between the two, resulting in problems such as low scheduling efficiency, insufficient safety control, and poor transfer experience, thus hindering the large-scale application of intermodal transport models.

[0003] Meanwhile, urban renewal continues to advance, with the core objectives of optimizing urban spatial layout, improving transportation infrastructure, enhancing urban operational efficiency and residents' travel quality, and addressing pain points such as traffic congestion, aging infrastructure, and limited travel options in traditional urban areas. During urban renewal, the upgrading and renovation of existing transportation hubs and the planning and construction of new hubs must both consider the needs of multi-modal transportation development. Low-altitude aircraft and light rail intermodal transport are important transportation solutions suited to urban renewal, effectively revitalizing urban airspace and ground transportation resources, realizing the construction of an "air-ground integrated" multi-modal transportation network, and contributing to the upgrading and improvement of transportation functions in urban renewal.

[0004] However, in the current urban renewal process, the renovation and construction of existing transportation hubs have not fully integrated the management and control needs of low-altitude and light rail intermodal transport. There is a lack of an integrated control system adapted to the concept of urban renewal, which makes it difficult for intermodal transport hubs to accurately match the spatial layout and traffic flow demand after urban renewal. This makes it impossible to fully leverage the advantages of intermodal transport in alleviating ground traffic pressure and improving travel efficiency, and also makes it difficult to meet the requirements of urban renewal for the construction of intelligent and three-dimensional transportation infrastructure. Therefore, it is urgent to develop a comprehensive transportation hub control system adapted to low-altitude aircraft and light rail intermodal transport in the context of urban renewal, to break through existing technical bottlenecks, and to help urban renewal and the development of three-dimensional transportation deeply integrate.

[0005] To address the accelerating pace of urbanization and the trend of integrated air-ground transportation, it is imperative to deeply integrate traditional ground transportation systems with manned aircraft supporting facilities to construct an integrated air-ground collaborative transportation system. This system comprises urban light rail transit stations and vertical take-off and landing (VTOL) aircraft transportation stations structurally integrated atop them. The light rail station adopts a conventional layout, including a concourse level on the first floor and a platform level on the second floor, with elevators and escalators providing vertical transportation for passengers between the two.

[0006] The aircraft transportation station consists of a waiting hall and a boarding hall. The boarding hall is equipped with a sliding shaft lift system that drives the aircraft platform (with integrated parking function) and the aircraft vertically down from a pre-designated parking position on the light rail station roof to the boarding hall level, enabling seamless passenger transfers. Passengers in the waiting hall enter the boarding area after ticket verification and through an automated access control system. A segmented traction drive system connects the roof parking area and the aircraft platform, enabling automated transfer of the aircraft between the parking position and the lift platform.

[0007] The boarding hall has a comprehensive support cabin at its bottom, divided into an energy support area and an equipment maintenance area. The energy support area is equipped with an automatic aircraft battery replacement device, intelligent charging equipment, and a battery directional transport system; the equipment maintenance area has a multi-degree-of-freedom robotic arm and modular tool racks, and can accurately deliver maintenance tools via a sliding shaft transport platform and a battery replacement lifting mechanism, allowing professional support personnel to carry out aircraft maintenance operations in the boarding hall.

[0008] The aforementioned structural system collectively constitutes the hardware infrastructure of the air-ground intermodal transport hub. However, if the traditional transportation station operation mode is adopted, the independent operation of each subsystem will lead to low efficiency in inter-system coordination and frequent operational interference, which will not only restrict the overall operational efficiency of the hub but also significantly increase the complexity of system operation and maintenance. Therefore, it is urgent to develop an integrated command system that integrates multi-system collaborative control and artificial intelligence decision-making based on the special operational requirements of this hub system, so as to achieve efficient connection, intelligent scheduling, and integrated operation of manned aircraft and urban light rail systems. Summary of the Invention

[0009] The purpose of this invention is to provide a control system for a transportation hub that integrates low-altitude aircraft and light rail, in order to solve the problems of low integration, low automation, and weak intelligent decision-making capabilities in existing transportation hub operation systems.

[0010] To achieve the above objectives, this invention provides the following technical solution: a comprehensive transportation hub control system for low-altitude aircraft and light rail intermodal transport, the system adopting a three-level distributed architecture of cloud hub – edge nodes – terminal equipment, including:

[0011] The passenger waiting guidance system is used to build a seamless guidance and personalized service system. It locates passengers by collecting data in the station, intelligently plans the movement route based on the passenger's location, and sends the movement route to the user terminal through multiple channels to guide passengers to transfer according to the movement route to reduce the average transfer time.

[0012] The manned aircraft scheduling system is used to automate the entire process of aircraft parking, scheduling, takeoff and landing, and takeoff, ensuring that multiple aircraft operate in parallel and in an orderly manner.

[0013] The energy management system is used to build a green energy collection-intelligent energy storage-efficient replenishment cycle system to realize automatic replacement of aircraft batteries, full life cycle management of batteries, and energy management of hub stations;

[0014] The maintenance and support system is used to achieve predictive maintenance and efficient repair of aircraft and equipment within the station, thereby reducing downtime caused by failures at the hub station.

[0015] The peacetime-wartime integrated emergency system is used to enable the hub station to switch between daily operation, emergency response and wartime support, and to enhance the hub station’s emergency support capabilities in the event of emergencies and special scenarios.

[0016] The intelligent decision-making central module uses AI big data models to achieve full-scenario data fusion analysis, autonomous optimization of decision-making strategies, and intelligent solution of complex problems, ensuring the normal operation of other functional systems.

[0017] Preferably, the cloud-based central layer consists of an AI decision engine, a digital twin platform, a big data analysis platform, and a cloud storage cluster. It is used for global data fusion analysis, scheduling strategy optimization and generation, digital twin model updates, remote system status monitoring, and emergency command issuance. It also connects to the city traffic command center and the low-altitude flight management platform. The edge control is deployed in the hub station's smart cabin and surrounding nodes, including edge computing servers, area controllers, and communication gateways. It is used to process sensor data in real time, execute control commands issued from the cloud, and achieve rapid local decision-making to ensure the normal operation of the system under extreme network environments. The terminal device layer includes sensing devices, execution devices, service devices, energy devices, and security devices distributed throughout the hub station.

[0018] Preferably, the passenger waiting guidance system operation steps include:

[0019] By using facial recognition cameras, WIFI probes, and light rail vehicle positioning systems, the entire trajectory of passengers—from entering the station to waiting for the train, transferring, and boarding the plane—can be accurately tracked.

[0020] Using route planning AI algorithms and real-time traffic prediction models, based on light rail arrival times, aircraft takeoff plans, and station facility congestion status, personalized route instructions with optimal time and highest comfort are generated.

[0021] The passenger terminal receives personalized route instructions and pushes these instructions based on the passenger's location via the station's broadcasting equipment.

[0022] The system identifies elderly, children, and disabled passengers through ticketing information and proactively declared information, and automatically triggers exclusive services for these passengers.

[0023] Preferably, the operation steps of the manned spacecraft scheduling system include:

[0024] Combining aircraft model, battery status, mission priority, and light rail station roof load-bearing data, the optimal parking space is allocated to each aircraft using a greedy algorithm and a conflict detection model, and aircraft without parking spaces are kept in the air waiting.

[0025] Control the traction track to pull the designated aircraft from the parking position to the lifting platform used as a parking apron, control the lifting platform to lift the aircraft up and down, pick up passengers in the waiting room, lift the passenger aircraft to the roof of the light rail station, and then control the traction track to pull the aircraft on the lifting platform back to the parking position to wait for flight.

[0026] Connect to the city's low-altitude flight management platform to obtain airspace control information in real time, complete route verification and conflict warning before the aircraft takes off, and connect with the light rail dispatch management platform to match the time nodes between light rail arrival, passenger boarding and aircraft takeoff.

[0027] When a mechanical failure occurs in the aircraft, the emergency brake is automatically triggered, and the traction device is controlled to tow the aircraft to the backup maintenance area.

[0028] Preferably, the energy management system includes:

[0029] An automated battery swapping system is used to remove the aircraft's power supply battery, replace it with a fully charged battery, and simultaneously charge the power supply battery for backup.

[0030] The battery lifecycle management subsystem establishes an electronic identity file for each battery and monitors battery parameters, including voltage, temperature, and cycle count, in real time through the electronic identity file.

[0031] The green energy integration subsystem includes a renewable energy collection component installed on the top of the hub station. The renewable energy collection component includes a moving plate and a fixed plate connected to the hub station. A telescopic support is hinged between the moving plate and the fixed plate, and a solar panel is installed on the telescopic support. The moving plate drives the telescopic support and the solar panel to unfold and collect solar energy when the waiting position is vacant. The renewable energy is stored in the energy storage system of the hub station. Through the peak-valley electricity price difference optimization model, the system stores electricity during the off-peak period and prioritizes the use of stored electricity and renewable energy during the peak period.

[0032] The energy supply and demand dynamic balance subsystem is used to monitor the energy consumption and energy supply of hub station equipment in real time, and dynamically allocate energy through energy allocation AI algorithms.

[0033] Preferably, the maintenance and support system includes:

[0034] The predictive maintenance subsystem collects real-time operational data from aircraft and hub stations using sensors installed on equipment inside the aircraft and hub stations. It then uses an LSTM neural network model to predict potential faults, generates maintenance warnings 72 hours in advance, and generates maintenance task instructions.

[0035] The intelligent scheduling subsystem for maintenance resources automatically matches maintenance personnel with corresponding skills based on the task type and urgency of the maintenance task instructions, and pushes task work orders containing fault location, predicted cause, and a list of required tools via APP; the tool management adopts the "RFID + smart shelf" mode, maintenance personnel can scan the code to take the tools, and the system automatically records the tool usage status and return time;

[0036] The remote collaborative maintenance subsystem is used to assist maintenance personnel in transmitting on-site images to cloud experts in real time through AR devices. Experts can then use AR annotations to directly guide operations on the on-site images. At the same time, a maintenance knowledge base is established to automatically push historical maintenance cases and operation manuals based on the type of fault.

[0037] The maintenance effectiveness closed-loop verification subsystem is used to verify the maintenance effectiveness through sensor data detection and no-load operation tests after the maintenance operation is completed, ensuring that the equipment is put back into use only after it has returned to normal operation, and updating the maintenance records.

[0038] Preferably, the peacetime-wartime integrated emergency response system includes:

[0039] The multi-mode intelligent switching subsystem is used to switch the hub station's operating status between preset daily mode, emergency mode, and wartime mode through one-click triggering or automatic sensing.

[0040] The emergency resource rapid allocation subsystem is used to automatically convert the waiting room and power exchange room into an emergency material storage area in emergency mode or wartime mode, and realize the rapid sorting and loading of materials, and link with the energy management system to prioritize the supply of power to emergency equipment.

[0041] The cross-departmental emergency response subsystem is used to share the operational status of the hub station in real time with fire, medical, public security and emergency management departments through communication interfaces, and automatically push rescue demand information to relevant departments in the event of an emergency.

[0042] The emergency simulation and drill subsystem, based on a digital twin platform, regularly conducts emergency scenario simulation drills and optimizes emergency dispatch strategies through simulation data.

[0043] Preferably, the intelligent decision-making central module includes:

[0044] The multi-source data fusion and processing subsystem is used to access data from all subsystems within the hub station and external data. It uses AI big data models to perform data cleaning, correlation analysis and feature extraction to form a unified data asset pool.

[0045] The dynamic scheduling strategy optimization subsystem, based on a data asset pool, automatically optimizes passenger travel routes, aircraft scheduling schemes, and energy management strategies using a large AI model.

[0046] The intelligent simulation subsystem for complex scenarios uses a large AI model to simulate and extrapolate complex traffic scenarios, predict the implementation effects of different decision-making schemes, and provide optimal decision-making suggestions for managers.

[0047] The natural language interaction interface is used to support managers to interact with the system via voice or text, and the system uses a large AI model to understand natural language commands and execute them.

[0048] Preferably, the system further includes a comprehensive intelligent security control system, which includes:

[0049] The multimodal safety perception subsystem is used to identify safety events and perceive safety risks from multiple dimensions by collecting multi-source data, including images, gas, heat and radar signals, through sensors.

[0050] The intelligent event identification and hierarchical handling subsystem is used to automatically identify the type of security event and classify its risk level, and automatically trigger the hierarchical handling process according to the risk level.

[0051] The personnel and materials security management subsystem is used to connect with the public security identity recognition system to conduct rapid security checks and identity verification on people entering and leaving the station, automatically identify dangerous personnel, and identify and manage personnel entering restricted areas within the station.

[0052] The security incident tracing and analysis subsystem automatically stores all security incident video footage, sensor data, and handling process data to the cloud, supports administrators in retrospective queries, regularly analyzes security incident patterns, and generates prevention and control optimization suggestions.

[0053] Preferably, the system further includes a smart mobility full-scenario service system, which includes:

[0054] The seamless travel service subsystem uses facial recognition technology to enable passengers to pass through the entire process of ticket purchase, security check, ticket inspection, and boarding. It also automatically links passengers' light rail ticket information and aircraft ticket information to generate an integrated travel itinerary and pushes station information, including ticket inspection time and boarding gate changes, to passenger user terminals in real time.

[0055] The personalized service customization subsystem generates customized service plans based on passenger profiles.

[0056] The public service subsystem includes luggage storage, express delivery, emergency medical services, and charging services located inside the hub station;

[0057] The travel experience feedback and optimization subsystem is used to collect passenger feedback through information collection channels including apps, mini-programs, and in-station questionnaire terminals. The AI ​​big data model analyzes the passenger feedback information and automatically generates service optimization suggestions, forming a closed loop for service improvement.

[0058] Compared with existing technologies, the integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport provided by this invention significantly shortens the ground turnaround time of the aircraft through full-process automation and integrated intelligent scheduling, greatly improving the throughput capacity of the hub station per unit time and enabling commercial high-density operation of "air-rail intermodal transport." It achieves seamless transfers, imperceptible passage throughout the entire process, and personalized services, making public transportation more convenient, comfortable, and efficient than ever before, greatly enhancing public acceptance of the new three-dimensional transportation system. Predictive maintenance reduces equipment failure rates, and the comprehensive safety control system enables early detection and handling of risks. Digital twin-assisted decision-making reduces human error and jointly constructs a multi-dimensional safety defense line. Efficient operation reduces labor costs, and intelligent energy management reduces electricity costs and increases the proportion of green energy use. Modular design also reduces construction and subsequent expansion costs; the "peacetime-wartime integration" design endows urban transportation hubs with new social functions, making them important nodes in the city's resilient emergency response system and enhancing the city's ability to respond to public emergencies. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0060] Figure 1 A structural block diagram of a transportation hub control system for low-altitude aircraft and light rail intermodal transport provided in an embodiment of the present invention;

[0061] Figure 2 This is a block diagram of the cloud-based central layer structure provided in an embodiment of the present invention;

[0062] Figure 3 A structural block diagram of an energy management system provided in an embodiment of the present invention;

[0063] Figure 4 This is a structural block diagram of a maintenance and support system provided in an embodiment of the present invention;

[0064] Figure 5 This is a structural block diagram of a peacetime-wartime integrated emergency response system provided in an embodiment of the present invention;

[0065] Figure 6 This is a block diagram of the intelligent decision-making central module provided in an embodiment of the present invention;

[0066] Figure 7 This is a structural block diagram of the all-domain intelligent security and control system provided in an embodiment of the present invention;

[0067] Figure 8 This is a structural block diagram of the intelligent mobility full-scenario service system provided in an embodiment of the present invention;

[0068] Figure 9 This is a schematic diagram of the top structure of a transportation hub provided in an embodiment of the present invention;

[0069] Figure 10 This is a schematic diagram of the renewable energy harvesting component structure provided in an embodiment of the present invention;

[0070] Figure 11 This is a schematic diagram of the overall structure of a transportation hub provided in an embodiment of the present invention.

[0071] In the diagram: 1. Top floor of the hub station; 2. Parking platform; 3. Lifting platform; 4. Traction track; 5. Maintenance door; 6. Waiting room; 7. Waiting position; 8. Renewable energy collection component; 81. Fixed plate; 82. Telescopic support; 83. Moving plate; 84. Solar panel; 9. Dispatch tractor. Detailed Implementation

[0072] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0073] As attached Figure 1-11 As shown:

[0074] Example:

[0075] This invention provides a comprehensive transportation hub control system for low-altitude aircraft and light rail intermodal transport. The system adopts a three-level distributed architecture of cloud hub – edge nodes – terminal equipment, including:

[0076] The passenger waiting guidance system is used to build a seamless guidance and personalized service system. It locates passengers by collecting data in the station, intelligently plans the movement route based on the passenger's location, and sends the movement route to the user terminal through multiple channels to guide passengers to transfer according to the movement route to reduce the average transfer time.

[0077] The manned aircraft scheduling system is used to automate the entire process of aircraft parking, scheduling, takeoff and landing, and takeoff, ensuring that multiple aircraft operate in parallel and in an orderly manner.

[0078] The energy management system is used to build a green energy collection-intelligent energy storage-efficient replenishment cycle system to realize automatic replacement of aircraft batteries, full life cycle management of batteries, and energy management of hub stations;

[0079] The maintenance and support system is used to achieve predictive maintenance and efficient repair of aircraft and equipment within the station, thereby reducing downtime caused by failures at the hub station.

[0080] The peacetime-wartime integrated emergency system is used to enable the hub station to switch between daily operation, emergency response and wartime support, and to enhance the hub station’s emergency support capabilities in the event of emergencies and special scenarios.

[0081] The intelligent decision-making central module uses AI big data models to achieve full-scenario data fusion analysis, autonomous optimization of decision-making strategies, and intelligent solution of complex problems, ensuring the normal operation of other functional systems.

[0082] The cloud-based central layer consists of an AI decision engine, a digital twin platform, a big data analysis platform, and a cloud storage cluster. It is used for global data fusion analysis, scheduling strategy optimization and generation, digital twin model updates, remote system status monitoring, and emergency command issuance. It also connects to the city traffic command center and the low-altitude flight management platform. The edge control is deployed in the hub station's smart cabin and surrounding nodes, including edge computing servers, area controllers, and communication gateways. It is used to process sensor data in real time, execute control commands issued from the cloud, and achieve rapid local decision-making to ensure the normal operation of the system under extreme network conditions. The terminal equipment layer includes five categories of equipment located in the hub station: sensing (multimodal sensors, high-definition cameras, etc.), execution (intelligent robotic arms, traction tracks, etc.), service (dynamic guide screens, self-service terminals, etc.), energy (intelligent charging stations, energy storage modules, etc.), and security (intelligent gates, emergency alarm devices, etc.). It is the core carrier for the implementation of system functions.

[0083] As can be seen from the above, through full-process automation and integrated intelligent scheduling, the ground turnaround time of aircraft is significantly shortened, and the throughput capacity of hub stations per unit time is significantly improved, enabling "air-rail intermodal transport" to meet the conditions for commercial high-density operation. Seamless transfers, unobtrusive passage throughout the entire process, and personalized services are achieved, making public transportation more convenient, comfortable, and efficient than ever before, greatly enhancing public acceptance of the new three-dimensional transportation system. Predictive maintenance reduces equipment failure rates, and the comprehensive safety control system enables early detection and early handling of risks. Digital twin-assisted decision-making reduces human error and jointly constructs a multi-dimensional safety defense line. Efficient operation reduces labor costs, and intelligent energy management reduces electricity costs and increases the proportion of green energy use. Modular design also reduces construction and subsequent expansion costs. The "peacetime-wartime integration" design endows urban transportation hubs with new social functions, making them important nodes in the city's resilient emergency response system and enhancing the city's ability to respond to public emergencies.

[0084] The passenger waiting guidance system operation steps include:

[0085] Expanded data collection dimensions: Through facial recognition cameras, UWB positioning tags (optional, for special passengers), Wi-Fi 6 probes and light rail vehicle positioning systems, accurate tracking of passengers' entire trajectory from "entering the station - waiting for the train - transferring - boarding the plane" can be achieved, with a positioning accuracy of ≤1 meter;

[0086] Intelligent route planning upgrade: adopts "improved A* algorithm + real-time traffic prediction model", combined with light rail arrival time, aircraft take-off plan, and congestion status of station facilities (such as elevator queue length) to calculate personalized routes with "optimal time and highest comfort" (such as prioritizing elevator routes for passengers with luggage and planning the shortest route for passengers in a hurry).

[0087] Multi-channel precise push: In addition to the original APP, query terminal and guide screen, new station broadcast zone broadcast (targeted push based on passenger location), smart bracelet / watch message synchronization (for elderly passengers) and AR guide function (real-time overlay of path guidance signs through mobile phone camera).

[0088] Special passenger care: The system identifies elderly, children, and disabled passengers through ticketing information or proactive declaration, and automatically triggers exclusive services such as arranging volunteers to assist them, opening barrier-free channels, reserving priority boarding seats, and synchronizing location information with fellow passengers through the APP.

[0089] The technical components used in the passenger waiting guidance system include UWB positioning base stations, AR navigation development kits, smart bracelet communication modules, zone broadcast controllers, improved route planning algorithm engines, and passenger profile databases.

[0090] The operation steps of the manned spacecraft scheduling system include:

[0091] Intelligent berth allocation: The system combines aircraft model (weight, size), battery status, mission priority (commercial flight / emergency rescue) and load-bearing data of the roof parking area to dynamically allocate the optimal berth through a "greedy algorithm + conflict detection model" to avoid space waste and safety risks;

[0092] Precise traction and lifting: The traction track adopts a "segmented independent control" design, which, together with a visual recognition camera and lidar, corrects the aircraft's position deviation in real time; the sliding shaft lifting mechanism incorporates gravity sensors and buffer devices, improving the smoothness of the descent / ascent process, and can automatically adjust the operating speed according to the aircraft's weight;

[0093] Cross-system scheduling and collaboration: A new interface with the urban low-altitude flight management platform has been added to obtain airspace control information in real time and complete route verification and conflict warning before the aircraft takes off; at the same time, it is linked with the light rail scheduling system to achieve precise matching of time nodes of "light rail arrival - passenger boarding - aircraft take-off";

[0094] Abnormal emergency handling: When the aircraft experiences parking deviation or mechanical failure, the system automatically triggers emergency braking, dispatches emergency towing equipment to transfer it to the backup maintenance area, and uses AI visual recognition to make a preliminary judgment on the type of failure, providing advance information for maintenance personnel.

[0095] The technical components used in the manned aircraft scheduling system include lidar sensors, segmented traction control modules, low-altitude flight management platform interfaces, gravity sensing buffer devices, emergency traction devices, and conflict early warning algorithm engines.

[0096] The energy management system includes:

[0097] The automated battery swapping system can adopt a "dual robotic arm collaborative operation" mode, where one robotic arm removes the depleted battery while the other prepares a fully charged battery simultaneously. With the help of the battery quick positioning interface, the battery swapping process can be processed in parallel. The battery transportation platform uses AGV intelligent vehicles to replace traditional sliding shafts, improving transportation flexibility and path adaptability.

[0098] The battery lifecycle management subsystem establishes a unique electronic identity file for each battery and monitors parameters such as voltage, temperature, and cycle count in real time through the BMS (Battery Management System). It adopts a "health-based charging strategy"—using a standard charging mode for new batteries and a slow charging protection mode for aging batteries to extend battery life.

[0099] The green energy integration subsystem lays flexible solar panels on the roof of the light rail and combines them with wind power generation devices (suitable for open-air hub stations) to connect renewable energy to the energy storage system. The system uses a "peak-valley electricity price difference optimization model" to store electricity during off-peak hours and prioritize the use of stored electricity or renewable energy during peak hours, thereby reducing electricity costs.

[0100] The energy supply and demand dynamic balance subsystem adds an energy dispatch submodule to monitor the overall energy consumption of the hub station (including light rail auxiliary equipment, station lighting, aircraft battery swapping, etc.) and energy supply (grid, solar energy, energy storage) in real time. It dynamically allocates energy through AI algorithms to avoid energy waste or insufficient supply.

[0101] For the specific structural layout of the solar panels, please refer to Figure 9 and Figure 10 :

[0102] A row of waiting positions 7 is arranged at the top of the top floor 1 of the hub station. A relatively wide space is left on one side of each waiting position 7 for dispatching and transfer, and a renewable energy collection component 8 is installed on the other side. The renewable energy collection component 8 includes a fixed plate 81 and a movable plate 83. A telescopic support 82 is hinged between the fixed plate 81 and the movable plate 83. Multiple solar panels 84 are connected to the telescopic support 82. The telescopic support 82 and the solar panels 84 are electrically deployed and retracted by the movable plate 83. When a waiting aircraft is stationed at a waiting position 7, the solar panels 84 are in a retracted state. When the waiting position 7 is vacant, the telescopic support 82 and the solar panels 84 are retracted. Solar panels 84 are deployed to collect solar energy and connect it to the energy storage system. Charging facilities can be installed on one side of the renewable energy collection component 8 to replenish the power of aircraft with less power loss, avoiding the need for subsequent battery swapping and increasing the workload of staff. When staff at waiting position 7 need to load passengers, the dispatching towing vehicle 9 tows the aircraft to parking position 2, and then parking position 2 transfers it to the lifting platform 3 via the towing track 4. The lifting platform 3 then lowers the aircraft to dock in waiting room 6. During passenger pick-up and drop-off, maintenance staff can perform battery swapping, maintenance, and other operations on the aircraft through the maintenance opening and closing door 5.

[0103] The energy management system uses technical components including a dual-robotic arm collaborative control module, an AGV intelligent transport vehicle, a BMS battery management system, flexible solar panels, energy storage battery packs, peak-valley energy scheduling algorithms, and an energy monitoring dashboard.

[0104] The maintenance and support system includes:

[0105] The predictive maintenance subsystem collects operational data in real time through vibration and temperature sensors installed on key aircraft components (propellers, motors, battery interfaces) and station equipment (traction tracks, lifting mechanisms). It then combines this data with an LSTM neural network model to predict potential faults (such as abnormal motor noise and track wear) and generate maintenance warnings 72 hours in advance.

[0106] The intelligent scheduling subsystem for maintenance resources automatically matches maintenance personnel with corresponding skills based on the type of maintenance task (routine inspection / fault repair) and urgency. It also pushes task orders containing fault location, predicted cause, and a list of required tools via the APP. Tool management adopts the "RFID + smart shelf" mode, where maintenance personnel can scan the code to retrieve tools, and the system automatically records the tool usage status and return time.

[0107] The remote collaborative maintenance subsystem adds an AR remote assistance function, allowing maintenance personnel to transmit on-site images to cloud experts in real time via smart glasses. Experts can then provide direct guidance on the operation through AR annotations on the screen. At the same time, a maintenance knowledge base is established, and the system automatically pushes historical maintenance cases and operation manuals based on the fault type.

[0108] The maintenance effectiveness closed-loop verification subsystem verifies the maintenance effectiveness after maintenance is completed by means of sensor data monitoring, no-load operation testing, etc., to ensure that the equipment is put back into use only after it has returned to normal operation, and updates the maintenance records.

[0109] The technical components used in the maintenance and support system include vibration / temperature sensors, LSTM prediction models, RFID tool tags, smart shelves, AR smart glasses, remote collaboration platforms, and a maintenance knowledge base management system.

[0110] The peacetime-wartime integrated emergency response system includes:

[0111] The multi-mode intelligent switching subsystem has three preset operating modes, which can be switched through one-click triggering or automatic sensing (such as receiving instructions from the emergency command center or detecting extreme weather). The daily mode focuses on efficiency and service; the emergency mode prioritizes the transportation of materials and the evacuation of personnel; and the wartime mode connects to the military dispatch system to realize the rapid transfer of military materials and personnel.

[0112] The emergency resource rapid deployment subsystem automatically converts the waiting room and power exchange room into an emergency material storage area in emergency / wartime mode, and uses AGV carts to quickly sort and load materials; at the same time, it links with the energy system to prioritize the supply of stored power to emergency equipment (such as emergency lighting and communication devices) to ensure that emergency functions are not affected by power grid interruption.

[0113] The cross-departmental emergency response subsystem adds communication interfaces with fire, medical, public security and emergency management departments to share the hub station's operational status in real time (such as personnel density, number of available aircraft, and material reserves); when an emergency occurs, it automatically pushes rescue request information to relevant departments to help formulate rescue plans.

[0114] The emergency simulation and drill subsystem, based on a digital twin platform, regularly conducts emergency scenario simulation drills (such as fire evacuation and emergency landing of aircraft). It optimizes emergency dispatch strategies through simulation data and improves the emergency response capabilities of staff.

[0115] The technical components used in the peacetime-wartime integrated emergency system include a multi-mode switching controller, an emergency material AGV sorting system, an emergency communication gateway, a digital twin simulation exercise platform, an emergency command center interface, and a backup power priority controller.

[0116] The intelligent decision-making central module includes:

[0117] The multi-source data fusion and processing subsystem accesses data from all subsystems within the station (passenger flow, aircraft status, energy consumption, equipment operation, etc.) as well as external data (urban traffic conditions, weather, airspace control information). Through large-scale models, it performs data cleaning, correlation analysis, and feature extraction to form a unified data asset pool.

[0118] The dynamic scheduling strategy optimization subsystem, based on real-time and historical operational data, uses a large model to autonomously optimize passenger guidance routes, aircraft scheduling schemes, and energy allocation strategies. For example, during peak holiday periods, it automatically adjusts aircraft flight intervals and berth allocation rules to cope with sudden surges in passenger flow; in severe weather, it optimizes aircraft takeoff sequences and route planning to reduce safety risks.

[0119] The intelligent simulation subsystem for complex scenarios uses a large model to simulate and predict the effects of different decision-making schemes (such as operational efficiency, safety risks, and user experience) for complex scenarios such as "simultaneous scheduling of multiple aircraft + large passenger flow transfer + equipment failure". It provides optimal decision-making suggestions for managers.

[0120] The natural language interaction interface allows administrators to interact directly with the system via voice or text, such as "query the aircraft scheduling plan for the next hour" or "activate emergency mode". The system understands natural language commands through a large model and executes corresponding operations, reducing the operational threshold.

[0121] The technical components used in the intelligent decision-making central module include a large model training and inference server, a multi-source data fusion platform, a natural language processing (NLP) module, a decision inference engine, and a visual decision dashboard.

[0122] The integrated transportation hub control system for the low-altitude aircraft and light rail intermodal transport also includes a comprehensive intelligent safety and security system, which includes:

[0123] The multimodal safety perception subsystem uses AI video cameras (to identify abnormal behaviors such as people falling, climbing over guardrails, and boarding without authorization), gas sensors (to monitor leaking gas from batteries in the battery swapping room), infrared sensors (to monitor equipment overheating), and radar (to monitor aircraft illegally intruding into the airspace around the hub station) to achieve multi-dimensional safety risk perception.

[0124] The intelligent event recognition and tiered response subsystem uses AI algorithms to automatically identify the type of safety event (such as personnel conflict, equipment fire, airspace intrusion) and classify it into risk levels (general / significant / major). Based on the level, it automatically triggers the response process: general events (such as personnel loitering) push reminders to on-site management personnel; significant events (such as abnormal equipment noise) trigger local area warnings and dispatch maintenance personnel; major events (such as fire) immediately activate the emergency mode, cut off the power supply to the relevant area, and activate the fire suppression system to extinguish the fire.

[0125] The personnel and materials security management subsystem connects to the public security identity recognition system to conduct rapid security checks and identity verification on personnel entering the station, and automatically identify fugitives or dangerous individuals; for personnel entering restricted areas such as equipment areas and power swapping rooms, precise control is achieved through facial recognition and access management, and an alarm is automatically triggered when unauthorized personnel enter;

[0126] The safety incident tracing and analysis subsystem automatically stores video footage, sensor data, and handling processes of all safety incidents to the cloud, supporting managers to review and query them afterward. The system regularly analyzes the patterns of safety incidents through large models and proposes prevention and optimization suggestions (such as adding warning signs in areas where people are prone to falling).

[0127] The technical components used in the comprehensive intelligent security and control system include AI video analysis cameras, gas / infrared sensors, low-altitude monitoring radar, identity verification system, access control platform, and security event tracing database.

[0128] The system also includes a smart mobility full-scenario service system, which includes:

[0129] The seamless travel service subsystem enables passengers to complete the entire process of ticket purchase, security check, ticket inspection, and boarding by "scanning their face," without having to show physical tickets or mobile phones. The system automatically links passengers' light rail tickets and aircraft flight ticket information to generate an integrated travel itinerary and pushes information such as ticket inspection time and boarding gate changes in real time.

[0130] The personalized service customization subsystem provides customized services based on passenger profiles (generated through ticketing information and historical travel records)—recommending fast security checkpoints and VIP waiting areas for business travelers; providing guidance to children's play areas and information on the location of baby care facilities for families; and pushing recommendations for attractions and restaurants around the hub station to tourist travelers.

[0131] The public service subsystem includes smart terminals set up within the station, providing services such as luggage storage (accessible via facial recognition), express delivery (connected to major express delivery platforms), emergency medical care (equipped with automated external defibrillators (AEDs) and remote medical consultation functions), and charging services. Additionally, a hub station mini-program has been developed to allow passengers to book these services online.

[0132] The travel experience feedback and optimization subsystem is used to collect passenger feedback through the APP, mini-program and in-station questionnaire terminal, combine it with the AI ​​big data model to analyze passenger needs and pain points, and automatically generate service optimization suggestions (such as adding a certain type of convenient facilities or adjusting the position of the guide screen), forming a service improvement closed loop.

[0133] The technical components used in the intelligent travel full-scenario service system include a seamless access system, a passenger profile database, intelligent convenience terminals, AED devices, a remote medical interface, a travel service mini-program, and a feedback analysis platform.

[0134] By configuring the above system modules, the following can be achieved:

[0135] Integrated travel process for passengers: Online ticket purchase (light rail + aircraft combined ticket) → facial recognition entry → personalized route push from the system (including waiting time reminders) → contactless security check → smart waiting area (enjoy customized services) → facial recognition boarding → flight itinerary synchronization during flight → destination connection information push after arrival (such as ride-hailing, public transportation) → travel feedback submission;

[0136] The entire process of aircraft dispatching is as follows: receiving flight plans → digital twin model pre-simulation of dispatching schemes → low-altitude flight management platform verification of flight routes → allocation of parking spaces and guidance of aircraft to precise parking → towing to the battery swapping area to complete automatic battery swapping → simultaneous equipment status detection (real-time monitoring by digital twin model) → towing to the boarding area → after passengers have boarded, takeoff and landing to takeoff altitude → after confirming airspace safety, takeoff command → digital twin model updates aircraft status;

[0137] Equipment digital twin operation and maintenance process: Real-time data collection from terminal equipment → Synchronization to digital twin model → Model analysis of equipment operating status → Predictive maintenance model generates early warning (if any) → Push maintenance tasks to maintenance personnel → Maintenance personnel complete maintenance with AR assistance → Digital twin model verifies maintenance effect → Update equipment maintenance records;

[0138] Emergency Response Process: Safety sensors / AI cameras identify anomalies → System classifies and determines the event level → Pushes early warning information to relevant personnel → Automatically initiates corresponding response procedures (such as cutting off power and dispatching emergency equipment) → Digital twin model simulates the response effect → Links with external emergency departments → Generates a debriefing report after the event is resolved.

[0139] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A control system for a transportation hub integrating low-altitude aircraft and light rail, the system adopts a three-level distributed architecture of cloud-based central hub – edge nodes – terminal equipment, characterized in that… include: The passenger waiting guidance system is used to build a seamless guidance and personalized service system. It locates passengers by collecting data in the station, intelligently plans the movement route based on the passenger's location, and sends the movement route to the user terminal through multiple channels to guide passengers to transfer according to the movement route to reduce the average transfer time. The manned aircraft scheduling system is used to automate the entire process of aircraft parking, scheduling, takeoff and landing, and takeoff, ensuring that multiple aircraft operate in parallel and in an orderly manner. The energy management system is used to build a green energy collection-intelligent energy storage-efficient replenishment cycle system to realize automatic replacement of aircraft batteries, full life cycle management of batteries, and energy management of hub stations. The maintenance and support system is used to achieve predictive maintenance and efficient repair of aircraft and equipment within the station, thereby reducing downtime caused by failures at the hub station. The peacetime-wartime integrated emergency system is used to enable the hub station to switch between daily operation, emergency response and wartime support, and to enhance the hub station’s emergency support capabilities in the event of emergencies and special scenarios. The intelligent decision-making central module uses AI big data models to achieve full-scenario data fusion analysis, autonomous optimization of decision-making strategies, and intelligent solution of complex problems, ensuring the normal operation of other functional systems.

2. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 1, characterized in that, The cloud-based central layer consists of an AI decision engine, a digital twin platform, a big data analysis platform, and a cloud storage cluster. It is used for global data fusion analysis, scheduling strategy optimization and generation, digital twin model updates, remote system status monitoring, and emergency command issuance. It also connects to the city traffic command center and the low-altitude flight management platform. The edge control is deployed in the hub station's smart cabin and surrounding nodes, including edge computing servers, area controllers, and communication gateways. It is used to process sensor data in real time, execute control commands issued from the cloud, and achieve rapid local decision-making to ensure the normal operation of the system under extreme network environments. The terminal device layer includes sensing devices, execution devices, service devices, energy devices, and security devices distributed throughout the hub station.

3. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The passenger waiting guidance system operation steps include: By using facial recognition cameras, WIFI probes, and light rail vehicle positioning systems, the entire trajectory of passengers—from entering the station to waiting for the train, transferring, and boarding the plane—can be accurately tracked. Using route planning AI algorithms and real-time traffic prediction models, based on light rail arrival times, aircraft takeoff plans, and station facility congestion status, personalized route instructions with optimal time and highest comfort are generated. The passenger terminal receives personalized route instructions and pushes these instructions based on the passenger's location via the station's broadcasting equipment. The system identifies elderly, children, and disabled passengers through ticketing information and proactively declared information, and automatically triggers exclusive services for these passengers.

4. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The operation steps of the manned spacecraft scheduling system include: Combining aircraft model, battery status, mission priority, and light rail station roof load-bearing data, the optimal parking space is allocated to each aircraft using a greedy algorithm and a conflict detection model, and aircraft without parking spaces are kept in the air waiting. Control the traction track to pull the designated aircraft from the parking position to the lifting platform used as a parking apron, control the lifting platform to lift the aircraft up and down, pick up passengers in the waiting room, lift the passenger aircraft to the roof of the light rail station, and then control the traction track to pull the aircraft on the lifting platform back to the parking position to wait for flight. Connect to the city's low-altitude flight management platform to obtain airspace control information in real time, complete route verification and conflict warning before the aircraft takes off, and connect with the light rail dispatch management platform to match the time nodes between light rail arrival, passenger boarding and aircraft takeoff. When a mechanical failure occurs in the aircraft, the emergency brake is automatically triggered, and the traction device is controlled to tow the aircraft to the backup maintenance area.

5. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The energy management system includes: An automated battery swapping system is used to remove the aircraft's power supply battery, replace it with a fully charged battery, and simultaneously charge the power supply battery for backup. The battery lifecycle management subsystem establishes an electronic identity file for each battery and monitors battery parameters, including voltage, temperature, and cycle count, in real time through the electronic identity file. The green energy integration subsystem includes a renewable energy collection component installed on the top of the hub station. The renewable energy collection component includes a moving plate and a fixed plate connected to the hub station. A telescopic support is hinged between the moving plate and the fixed plate, and a solar panel is installed on the telescopic support. The moving plate drives the telescopic support and the solar panel to unfold and collect solar energy when the waiting position is vacant. The renewable energy is stored in the energy storage system of the hub station. Through the peak-valley electricity price difference optimization model, the system stores electricity during the off-peak period and prioritizes the use of stored electricity and renewable energy during the peak period. The energy supply and demand dynamic balance subsystem is used to monitor the energy consumption and energy supply of hub station equipment in real time, and dynamically allocate energy through energy allocation AI algorithms.

6. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The maintenance and support system includes: The predictive maintenance subsystem collects real-time operational data from aircraft and hub stations using sensors installed on equipment inside the aircraft and hub stations. It then uses an LSTM neural network model to predict potential faults, generates maintenance warnings 72 hours in advance, and generates maintenance task instructions. The intelligent maintenance resource scheduling subsystem automatically matches maintenance personnel with corresponding skills based on the task type and urgency of the maintenance task instruction, and pushes task work orders containing fault location, predicted cause, and required tool list through the APP; The remote collaborative maintenance subsystem is used to assist maintenance personnel in transmitting on-site images to cloud experts in real time through AR devices. Experts can then use AR annotations to directly guide operations on the on-site images. At the same time, a maintenance knowledge base is established to automatically push historical maintenance cases and operation manuals based on the type of fault. The maintenance effectiveness closed-loop verification subsystem is used to verify the maintenance effectiveness through sensor data detection and no-load operation tests after the maintenance operation is completed, ensuring that the equipment is put back into use only after it has returned to normal operation, and updating the maintenance records.

7. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The peacetime-wartime integrated emergency response system includes: The multi-mode intelligent switching subsystem is used to switch the hub station's operating status between preset daily mode, emergency mode, and wartime mode through one-click triggering or automatic sensing. The emergency resource rapid allocation subsystem is used to automatically convert the waiting room and power exchange room into an emergency material storage area in emergency mode or wartime mode, and realize the rapid sorting and loading of materials, and link with the energy management system to prioritize the supply of power to emergency equipment. The cross-departmental emergency response subsystem is used to share the operational status of the hub station in real time with fire, medical, public security and emergency management departments through communication interfaces, and automatically push rescue demand information to relevant departments in the event of an emergency. The emergency simulation and drill subsystem, based on a digital twin platform, regularly conducts emergency scenario simulation drills and optimizes emergency dispatch strategies through simulation data.

8. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The intelligent decision-making central module includes: The multi-source data fusion and processing subsystem is used to access data from all subsystems within the hub station and external data. It uses AI big data models to perform data cleaning, correlation analysis and feature extraction to form a unified data asset pool. The dynamic scheduling strategy optimization subsystem, based on a data asset pool, automatically optimizes passenger travel routes, aircraft scheduling schemes, and energy management strategies using a large AI model. The intelligent simulation subsystem for complex scenarios uses a large AI model to simulate and extrapolate complex traffic scenarios, predict the implementation effects of different decision-making schemes, and provide optimal decision-making suggestions for managers. The natural language interaction interface is used to support managers to interact with the system via voice or text, and the system uses a large AI model to understand natural language commands and execute them.

9. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The system also includes a comprehensive intelligent security control system, which comprises: The multimodal safety perception subsystem is used to identify safety events and perceive safety risks from multiple dimensions by collecting multi-source data, including images, gas, heat and radar signals, through sensors. The intelligent event identification and hierarchical handling subsystem is used to automatically identify the type of security event and classify its risk level, and automatically trigger the hierarchical handling process according to the risk level. The personnel and materials security management subsystem is used to connect with the public security identity recognition system to conduct rapid security checks and identity verification on people entering and leaving the station, automatically identify dangerous personnel, and identify and manage personnel entering restricted areas within the station. The security incident tracing and analysis subsystem automatically stores all security incident video footage, sensor data, and handling process data to the cloud, supports administrators in retrospective queries, regularly analyzes security incident patterns, and generates prevention and control optimization suggestions.

10. The integrated transportation hub control system for low-altitude aircraft and light rail intermodal transport according to claim 2, characterized in that, The system also includes a smart mobility full-scenario service system, which includes: The seamless travel service subsystem uses facial recognition technology to enable passengers to pass through the entire process of ticket purchase, security check, ticket inspection, and boarding. It also automatically links passengers' light rail ticket information and aircraft ticket information to generate an integrated travel itinerary and pushes station information, including ticket inspection time and boarding gate changes, to passenger user terminals in real time. The personalized service customization subsystem generates customized service plans based on passenger profiles. The public service subsystem includes luggage storage, express delivery, emergency medical services, and charging services located inside the hub station; The travel experience feedback and optimization subsystem is used to collect passenger feedback through information collection channels including apps, mini-programs, and in-station questionnaire terminals. The AI ​​big data model analyzes the passenger feedback information and automatically generates service optimization suggestions, forming a closed loop for service improvement.

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