490 results about "Rail traffic" patented technology

The invention relates to the technical field of rail traffic safety detection, in particular to a railway freight train key part online monitoring system based on an unmanned aerial vehicle, which comprises an unmanned aerial vehicle control module, a multi-modal data acquisition module, an edge calculation module, a central processing module and a feedback execution module. A dynamic three-dimensional grid flight path is generated by fusing a train Beidou positioning signal and a millimeter wave radar sensing result, a system is provided with an infrared thermal imager, a laser radar and a high-speed polarization camera, bearing temperature, train body point cloud and a train coupler image sequence are obtained, and temperature rise area identification, structural deformation extraction and coupling state modeling are completed on the edge side. The central processing module outputs a multi-dimensional safety assessment result, and the feedback module generates a compensation control instruction and a graded early warning signal based on the risk fusion index. The method has the advantages of being high in autonomy degree, high in recognition precision and high in response speed, and is suitable for full-time structural intelligent inspection and early warning of the freight train in a high-speed operation environment.

The invention discloses an obstacle detection method and an obstacle detection system for a track, relates to the technical field of track detection, and is used for solving the problem of insufficient safety of track traffic. Comprising a data acquisition module, a data storage module, a data processing and fusion module, an intelligent analysis and decision module and an execution module which are in signal connection. The data acquisition module dynamically adjusts the working range and frequency of the sensor according to environmental changes. The collected data is processed and fused through the data processing and fusion module to generate a consistent orbit environment model, and a high-precision obstacle model is generated in combination with multi-source data. The intelligent analysis and decision-making module carries out classification, tracking and risk assessment on obstacles and generates a reasonable coping strategy according to the risk level. And the execution module executes related operation according to the generated strategy instruction. According to the method, track obstacles can be accurately detected, self-adaptive adjustment can be carried out according to dynamic environment changes, and the safety and operation efficiency of track traffic are remarkably improved.

The invention discloses an energy storage rapid compensation method and system based on track overhead line system voltage fluctuation feature recognition, and relates to the technical field of track traffic traction power supply. The method comprises the following steps: synchronously acquiring voltage and current signals of the overhead line system, and extracting a composite feature vector containing disturbance root attributes and transient change rate; on the basis of the vector, a transient energy vacancy sequence covering the ultra-short-term future is output in real time through a prediction model fusing dynamic phasor analysis and a feedforward neural network; according to the sequence, a cooperative control strategy fusing overshoot and active damping is generated in combination with a proximity compensation principle and a voltage recovery state so as to drive an along-line energy storage unit; the strategy is executed in advance, compensation energy is injected, and finally double closed-loop correction is conducted based on the voltage residual error. According to the method, the problems of response lag, unclear disturbance identification, poor collaboration and lack of adaptive ability in the prior art are solved, and advanced, accurate, collaborative and self-optimized rapid suppression of the voltage fluctuation of the overhead line system is realized.

The invention relates to the field of rail traffic intelligent control, and discloses a rail obstacle real-time detection and braking system based on multi-sensor redundancy, which comprises at least two groups of sensing modules arranged at the front end and the rear end of a train, and each group of sensing module comprises a laser radar used for collecting three-dimensional point cloud data of a forward or backward rail area of the train; the binocular camera is used for acquiring color image data and depth image data in corresponding directions; and the robot controller is in communication connection with the sensing module and is used for receiving sensing data acquired by the laser radar and the binocular camera and executing obstacle recognition, redundant information fusion and brake control logic. By constructing a multi-sensor redundancy sensing structure based on the laser radar and the binocular camera, high-robustness recognition of a dynamic or static obstacle target in a complex orbit environment is realized, and the effect of remarkably improving the obstacle detection accuracy and the false alarm suppression capability is achieved.

The invention discloses a track digital twinning real-time online deduction method and system, and belongs to the technical field of traffic simulation based on machine learning. The problem that in the prior art, a traditional traffic simulation and rail passenger flow dynamic allocation method is low in solving efficiency, and consequently the large-scale rail traffic network dynamic passenger flow allocation requirement is difficult to meet is solved. The method comprises the following steps: constructing a track road network model; generating road network passenger flow data and line shift data; further, simulation individuals of the train and the passengers are generated, path track matching based on time and space is carried out, and passenger-train dynamic traffic distribution and passenger-train interactive operation deduction are completed; according to the real-time detection data and the simulation result, dynamic line shift and passenger flow adjustment is carried out until a preset convergence condition is reached, and dynamic traffic checking is completed; and simulation is carried out to realize reduction and prediction of the passenger flow / flow direction of the whole line network. The method effectively improves the rail passenger flow dynamic distribution efficiency, and can be applied to large-scale traffic network simulation.

The invention relates to the technical field of rail traffic safety monitoring, and discloses a railway foreign matter invasion real-time monitoring and alarm system based on an SAR radar, and the system comprises an SAR multi-dimensional information depth perception module which extracts polarization, coherence, texture and other multi-dimensional features from SAR data; the multi-scale space-time attention fusion module adaptively focuses the key space-time change through a space and time attention mechanism to generate space-time fusion features; and the railway foreign matter invasion evolution knowledge graph construction and reasoning module integrates the space-time fusion features and multi-source information such as railway infrastructure, environment and historical events to construct a dynamic knowledge graph, and performs risk reasoning and alarming by using a graph neural network. According to the invention, through deep fusion of multi-dimensional perception, intelligent attention and knowledge graph reasoning, the accuracy, robustness and intelligent level of foreign matter invasion monitoring are significantly improved, and deep understanding and adaptive early warning of risks are realized.

The invention discloses a single board detection system and method, and relates to the field of rail transit, and the system comprises an adapter plug-in box which is provided with at least one first slot and at least one second slot, the first slot is used for connecting a detected plug-in, and the second slot is used for connecting an accompanying test plug-in; and the main control assembly is connected with the adapter plug-in box and is configured to send test information corresponding to the tested plug-in to the accompanying test plug-in when the tested plug-in is a first type of plug-in, determine a test result of the tested plug-in based on test data, and output a preset test signal to the tested plug-in when the tested plug-in is a second type of plug-in, obtaining a test result of the tested plug-in; and the accompanying test plug-in is configured to load configuration parameters corresponding to the test information so as to disguise the accompanying test plug-in as a target interaction plug-in of the tested plug-in, then interact with the tested plug-in and collect test data in the interaction process. According to the invention, the cost of developing special detection equipment for different plug-in types can be reduced, and the universality of the detection system is improved.

The invention relates to the field of underground engineering and rail traffic engineering, in particular to a deformation control method for a double-line shield tunnel to underpass an existing railway soft soil roadbed, which comprises the following steps: S1, determining a grouting reinforcement range; s2, pile position and grouting hole position lofting is conducted in the reinforcing area, and a groove is excavated; s3, construction is conducted after the MJS pile main machine is in place, and drill bit trial spraying is conducted before a drill rod is placed; s4, after the drill rod reaches the specified depth, jet grouting is conducted till the designed elevation is reached, and the MJS pile main machine is moved to the next pile position sample placing point; s5, after the MJS pile reaches the designed strength, a drilling machine is arranged in place, and a formed hole is drilled to the designed depth; and S6, grouting is conducted, and then grouting and grout stopping section construction is conducted. The method has the advantages that corresponding reinforcement measures are taken in combination with the model, the shear strength of the soft soil is improved, the shear damage risk of the soft soil is reduced, deformation of the soft soil roadbed is controlled in time, and safety and stability in the shield underneath pass construction process are ensured.

The invention discloses an urban rail transit automatic fare collection virtual transfer method and system, and the method comprises the steps: judging whether the station is a virtual transfer station or not according to the information obtained from an entrance gate, if yes, judging whether the last departure station and the current entry station are the same operation day or not, if yes, continuing to judge whether the last departure station is an associated virtual transfer station or not, and if not, continuing to judge whether the last departure station is an associated virtual transfer station; if yes, judging whether the distance from last outbound is within a preset transfer duration, and if yes, retaining a newly added transaction field about transfer; judging whether a virtual transfer station is available according to the information acquired from the exit gate, if so, judging whether the exit of this time and the entrance of the last time are the same operation date, if so, continuing to judge whether a continuous transfer condition is met, and if so, charging according to a billing rule and emptying a newly added transaction field about transfer according to a preset rule; and if the continuous transfer condition is not met, normally charging and filling in a newly added transaction field according to a preset rule. According to the invention, the transfer efficiency of the urban rail transit can be improved and enhanced.

The invention relates to the field of rail traffic intelligent driving, and discloses a rail car safety state real-time monitoring and early warning system based on deep learning, which comprises a multi-modal data acquisition module for deploying sensors on key components of a rail car and acquiring time sequence data including vibration, temperature, pressure and operation parameters; the cross-modal feature conversion module encodes the collected time sequence data into a three-channel color image; the safety state evaluation module is used for performing deep modeling and feature learning on the three-channel color image, predicting a current state classification result of the rail car in real time, and obtaining a safety state evaluation result of the rail car; and the early warning and intelligent decision-making module is used for carrying out anomaly detection and alarm prompt when potential risks exist in the rail car according to the safety state evaluation result. According to the invention, high-precision early fault identification and automatic early warning are realized.

The invention belongs to the technical field of rail traffic rail detection, and discloses a method for online detection of a rail corrugation fault based on a sliding time sequence window. The method is realized by adopting a sliding time sequence window analysis processing method, a wavelength range band-pass filtering method and a weighted calculation and normal value ratio method for vibration acceleration signals acquired by a plurality of measuring point sensors on the same side of the train, so that missed judgment caused by value errors can be avoided; and misjudgment caused by non-rail corrugation frequency signal interference, wheel abnormity and the like can be avoided. Meanwhile, sliding window value judgment is carried out according to the preset track resolution length, and refined judgment and positioning can be carried out on the rail corrugation fault in combination with a kilometer post. According to the rail corrugation fault detection method, the monitoring result is accurate and stable, the requirement for system performance is low, and the requirement for a real-time online monitoring system of low-cost embedded equipment is met.

The invention provides a door-shaped steel bar optimization method and system based on ballastless track interface damage analysis, and relates to the field of track traffic, the method comprises the following steps: determining track interlayer bonding parameters of a ballastless track based on interface comprehensive mechanical property test data of a concrete material composite test piece of the ballastless track, and establishing a finite element model of the ballastless track; a service temperature field of the ballastless track is calculated, and equivalent simulation of shrinkage of the self-compacting concrete layer is completed; on the basis of the multiple structure optimization variables, multiple door-shaped steel bar optimization schemes are determined, and the track interface damage area and distribution of the ballastless track under the combined action of shrinkage of the self-compacting concrete layer and the temperature load are calculated by utilizing a finite element analysis method based on a finite element model of the ballastless track corresponding to the door-shaped steel bar optimization schemes; the method has the advantages that the early-stage interface damage risk is reduced, and the durability and reliability of the track structure are improved.

The invention discloses a platform unmanned aerial vehicle charging control method and system based on cooperative communication and a medium. Relates to the technical field of unmanned aerial vehicle control. High-precision positioning and docking are realized through cooperative communication between the track platform and the unmanned aerial vehicle in combination with global path planning and local path planning; the environment of the track platform is detected in real time, the flight path of the unmanned aerial vehicle is corrected in real time, the flight path of the unmanned aerial vehicle is dynamically adjusted, sudden interference of moving obstacles is avoided, and accurate docking is ensured; through cooperative communication of the rail platform and the unmanned aerial vehicle, a multi-target optimization algorithm, cooperation of global and local path planning and intelligent charging management, the limitation of an existing unmanned aerial vehicle positioning and alignment method in complex environments such as the rail traffic platform is effectively solved.

The invention discloses a railway marshalling station intelligent scheduling control method and system based on hierarchical reinforcement learning, and belongs to the technical field of rail transit. In the hierarchical reinforcement learning framework, the upper layer achieves a global marshalling priority strategy by using a deep Q network trained in stages and by means of dynamic reward function design; and the lower layer optimizes a PPO algorithm by means of a near-end strategy of dynamic action space cutting, and regulates and controls the state of the debugging equipment in real time. A security policy distillation technology is adopted in a marshalling station scheduling control process, and a security policy passing verification is extracted as a rule tree to serve as an initial policy for reinforcement learning, so that a training convergence process is accelerated. A transfer learning method is further applied, so that the method can adapt to the dynamic flow distribution requirements of marshalling stations of different scales. By adopting the technical scheme of the invention, the physical limitation and the operation safety standard of the railway marshalling station can be met as far as possible.

The present invention is based on the object of specifying a method for blocking and / or unblocking track sections in which human errors in the context of incorrect manipulations can be reliably excluded.This object is achieved according to the invention by a method for blocking and / or unblocking a track section in rail-bound traffic, which method comprises the following method steps: a) by means of an application executed on a mobile device, a blocking of a track and / or a switch is requested in a control system used to control rail-bound traffic; b) with this request, a secret key is generated, which is exchanged between the mobile device and the control system; c) every transaction that now takes place between a security chief and a train dispatcher operating the control system is always secured in the background by the mobile device and the control technology using cryptological methods based on the secret key, and is mutually controlled with regard to the desired blocking and / or unblocking.This ensures that only persons / authorities with the secret key can perform locking and / or unlocking actions that affect only the track section and / or switch identified by this key. This reliably prevents inadvertent access to the locked elements by third parties.

The utility model relates to the technical field of rail traffic, in particular to an eccentric support type anti-falling guard rail which comprises a guard rail support, a walking rail and a guard rail, the walking rail is vertically locked at the middle bottom of the guard rail support through a first locking mechanism, a guard rail eccentric support with the top sleeved with an elastic sleeve shoe is arranged at the top of one side of the guard rail support in a clamped mode, and the elastic sleeve shoe is arranged on the guard rail eccentric support. The guard rail and the guard rail eccentric support are horizontally locked at the top of one side of the guard rail support through the second locking mechanism, the guard rail eccentric support and the elastic sleeve shoe are adopted to solve the problem that original cushion blocks are large in model number and prone to falling off, the transverse load is increased, the guard rail strength of the guard rail is further guaranteed, and the service life of the guard rail is prolonged. The eccentric support type anti-falling guard rail is convenient to install and not prone to falling off, meanwhile, the installation height is kept constant, the transverse load is high, and the strength of the guard rail is high.

The invention provides a rail vehicle part cleaning production line and method, belongs to the technical field of rail traffic, and aims to solve the problems of high cost, low efficiency, low cleaning degree and high working intensity due to manual cleaning of a brake unit of an existing rail train. Comprising a cleaning room, and a soaking tank, a spraying tank, an ultrasonic cleaning tank, an ultrasonic rinsing tank, a water blowing tank and a drying tank are sequentially arranged in the cleaning room in the length direction of the cleaning room; one side of the soaking tank and one side of the drying tank are each provided with a first conveyor used for conveying a mesh basket, one end of each first conveyor is located in the cleaning room, and the other end of each first conveyor extends out of the cleaning room; second conveyors perpendicular to the two first conveyors are further arranged outside the cleaning room. A sliding rail is arranged at the top in the cleaning room, the sliding rail is arranged in the length direction of the cleaning room, a sliding seat is connected to the sliding rail in a sliding mode, the sliding seat is driven by a motor, and a lifting appliance matched with the mesh basket is arranged at the bottom of the sliding seat. A traditional manual cleaning mode is abandoned, and the cleaning efficiency is improved.

The invention provides a sensor layout method and device and a train, and can be applied to the technical field of rail transit. The sensor layout method comprises the following steps: determining a plurality of to-be-screened position points for installing sensors in a train; clustering the plurality of position points according to the strain energy density and the information entropy of each position point, and determining at least one to-be-screened region according to a clustering result; the multiple position points, the to-be-screened area and mechanical and load data, obtained through pre-testing, of all the position points are input into a pre-constructed target layout model, at least one initial layout scheme is output, and the initial layout scheme comprises the number of sensors and the installation positions of the sensors; and optimizing the at least one initial layout scheme by utilizing a multi-objective optimization algorithm and executing multiple iterative optimization operations to obtain a target layout scheme.

The invention discloses an urban multi-layer traffic network modeling and toughness analysis method under the influence of rainstorm, and relates to the technical field of traffic control, a rainstorm ponding model is built based on historical rainfall information, and a runoff depth and a ponding depth are simulated based on the rainstorm ponding model; building a multi-mode traffic model based on SUMO software; a rainstorm ponding model and a multi-mode traffic model are integrated to construct a coupling model, ponding information is matched to a corresponding road through a road ID, failure mechanisms of different traffic modes under rainstorm ponding are obtained, ponding influences are considered for road traffic and rail traffic respectively, and corresponding influence parameters are set. Adjusting the road speed limit in real time and updating the route in real time; the SUMO simulation output result is utilized, the toughness index change in different scenes is calculated, the comprehensive traffic network toughness in different rainstorm scenes is analyzed from the four dimensions of topology, convenience, service and safety, the comprehensive traffic network toughness is evaluated, the dynamic capture of traffic characteristics is realized, and the analysis depth and breadth are improved.

The invention relates to the technical field of rail traffic engineering, and particularly discloses a protection mechanism for a subway platform, which comprises a subway platform body, an adjusting cavity is formed in the upper portion of the outer wall of the subway platform body, two adjusting mechanisms are jointly installed between the top inner wall and the bottom inner wall of the adjusting cavity, a telescopic mechanism is installed in the adjusting cavity, and a buffering mechanism is installed on the outer wall of the telescopic mechanism. The adjusting mechanism comprises a spline shaft, an adjusting frame, an electric telescopic rod, a fixing frame and a telescopic gear. The telescopic gear can be driven to rotate through the adjusting frame, then the telescopic mechanism is driven to stretch out through power generated by door opening and closing, meanwhile, the telescopic mechanism can monitor the size of a gap between the telescopic mechanism and a train in real time, and after the stretching length is determined, the electric telescopic rod can push the adjusting frame to move upwards to cancel meshing; therefore, the extension length of the telescopic mechanism is automatically adjusted according to the actual gap size, and the application range and universality of the protection mechanism are expanded.

The invention discloses a remote rail fault intelligent detection system based on big data driving, and relates to the technical field of rail traffic intelligent monitoring and state maintenance. The problems that a traditional detection method is high in manual dependence, slow in response and lack of prediction and self-repairing capacity are solved. According to the method, multi-source data are acquired through a fixed sensing network and a mobile inspection vehicle, a multi-scale digital twin is constructed and updated, and a probabilistic fault evolution graph is generated based on a random phase field model; collaborative judgment is carried out based on distributed edge computing nodes, and a maintenance scheme is generated by adopting a hybrid geometric distance retrieval immune memory bank; and finally, collaborative repair is executed through mixed reality and a micro-robot cluster, and continuous optimization of the system is realized based on federated learning and case-based reasoning. According to the system, integrated closed loop of track state sensing, fault prediction, intelligent decision making and self-repairing is achieved, and the detection foreseeability, the maintenance accuracy and the system self-adaptive capacity are improved.

The invention relates to a train positioning method based on a digital track map, which belongs to the technical field of satellite navigation and track traffic positioning, and is characterized in that a track is fitted by acquired track data to obtain a high-precision track curve model. Then, in the train positioning process, the train position calculated by the GNSS is matched with the fitted track curve, and a track constraint optimization method is adopted to correct the train position. A GNSS positioning result is projected to a nearest point of a fitting track curve, deviation correction is carried out in combination with track geometric information, positioning errors caused by environmental interference are eliminated, and therefore the relative positioning precision of a train is improved; according to the method, the train positioning precision is further improved by performing accurate fitting on the track line features and combining a global navigation satellite system (GNSS) positioning technology, the ambiguity fixing rate is effectively improved, and the problems of insufficient train positioning precision, low ambiguity fixing rate and the like in the prior art are solved.

The invention belongs to the technical field of rail traffic signals, particularly relates to a rail circuit interference test analysis method, system and equipment, and aims to solve the problems that a mixed interference source is difficult to accurately position, accidental faults cannot be captured and diagnosis is subjective. The method comprises the following steps: performing multi-channel synchronous acquisition and real-time storage on a voltage signal and a current signal of a track circuit; processing the original signal in real time, analyzing different frequency components through high-resolution spectrum analysis, and comparing with a preset threshold in combination with time domain analysis to trigger an alarm and generate a real-time analysis report; and performing intelligent analysis on historical data, performing verification and feature recognition on fault period data by establishing a probability model of a normal working condition, and generating a diagnosis analysis report. According to the method, the interference source can be accurately separated and positioned, the transient fault is automatically captured, objective and intelligent fault diagnosis is provided, and the efficiency and reliability of track circuit troubleshooting are remarkably improved.

The invention provides a construction method of a maglev traffic rail, which comprises the following steps: S1, modularly pouring and prefabricating a bridge deck in a factory, S2, mounting, adjusting and locking a maglev rail in the factory, S3, remeasuring the levelness and straightness of the maglev rail in a maglev rail assembly and the mounting precision of the maglev rail and an induction plate assembly to ensure that the maglev rail meets the dynamic matching requirement of a vehicle rail, and S4, mounting the bridge deck on a construction site. According to the construction method, modular pouring is mainly adopted to prefabricate the bridge deck slab, and the bridge deck slab is integrated with the shear nails, the iron cores and the pre-embedded sleeves; the method is simple in operation, high-precision, efficient and low-cost installation of the maglev traffic track is achieved, the construction efficiency is greatly improved, the cost of a medium-low-speed maglev track traffic system is reduced, and large-scale application and popularization are achieved.

The invention provides an intelligent rail tramcar dynamic section road right release method and system based on V2X cooperation, and relates to the technical field of intelligent rail traffic control, and the method comprises the steps: deploying a sensing network at a key node of a road section based on V2X, and obtaining the multi-source data of the road section in real time based on the sensing network; acquiring real-time information of social vehicles and intelligent rail tramcars based on the multi-source data; according to the real-time information, dynamic division is carried out, a three-level section range is calculated in real time, a plurality of sections are obtained, and the sections comprise an emergency protection area, a dynamic buffer area and a free passing area; and carrying out differential control on the social vehicles and the intelligent rail tramcars based on a three-level section road right release strategy, and carrying out road right release on each section. The problem that a traditional fixed section division mode cannot adapt to a dynamic change scene and is difficult to meet the requirement for reasonable management and control of the intelligent rail tramcar and the social vehicle in an open road right scene is solved.

The invention relates to the technical field of rail traffic detection, in particular to a mounting seat and detection equipment based on rail installation, and the mounting seat comprises a frame and a rail clamp; the frame comprises a cross rod which is arranged between two adjacent sleepers and is positioned below the track; two rail clamps used for being connected with the two rails respectively are installed on the transverse rod. At least one rail clamp is movably installed on the transverse rod and can freely move on the transverse rod. According to the mounting seat, the frame can be quickly and conveniently mounted on the rail through the rail clamp, so that the required mounting time is short, the mounting is easy, the workload is small, and the mounting can be completed within one skylight point time. Besides, as at least one rail clamp is movably mounted on the cross rod, when the relative position between the two rails is changed, the relative position between the two rail clamps can also be changed, so that the whole mounting seat can adapt to rail distance deviation and lateral sliding of the rails during vehicle passing.

The invention discloses a road network traffic state prediction method based on large language model spatial-temporal feature embedding, and belongs to the technical field of calculation, reckoning or counting. According to the method, semantic embedding of space and time is extracted by pre-training a large language model, and the space-time heterogeneity of a traffic system is quantified; a dynamic adjacent matrix is constructed by using Tucker decomposition, and combined modeling is performed on historical traffic data in combination with a dynamic space-time diagram convolutional network, so that high-precision prediction of a future traffic state is realized. The method does not need manual feature design, has good generalization ability and multi-mode adaptability, can be widely applied to scenes of road traffic, rail traffic demand prediction and the like, and significantly improves prediction accuracy and control response ability in a complex traffic environment.

The utility model belongs to the technical field of rail traffic, and particularly discloses a dust collection type rail self-cleaning device which comprises a movable trolley, and a dust collection device used for sucking and collecting dust is arranged at the rear end of the top of the movable trolley. A sweeping assembly used for sweeping dust in the I-shaped steel rail and a symmetrical dust collecting assembly used for guiding and collecting swept dust and sundries are arranged below the movable trolley, the sweeping assembly comprises brush rollers symmetrically arranged on the two sides of the I-shaped steel rail, and the tops of the brush rollers are connected with a servo motor through a shaft rod. The servo motor is mounted at the bottom of the movable trolley; the dust collection assembly comprises a dust collection frame and a dust collection head which are symmetrically arranged on the two sides of the I-shaped steel rail, one end of the dust collection head is fixedly connected with the dust collection frame, and the other end of the dust collection head is fixedly connected with a dust collection device through a connecting pipe.

Embodiments of the application relate to a technical field of traffic trackside intelligent devices. A trackside device includes: a collection module configured to collect detection information at a side of a track; a processing module configured to process the detection information to obtain a processing result; a trackside resource control module configured to drive and control a trackside resource when a trackside resource request is received from a target train and the trackside resource is in a released state, wherein the trackside resource control module is further configured to monitor a state of the trackside resource; and a communication module configured to communicatively connect with a ground center and the target train.

The invention discloses a medium-low speed magnetic levitation bearing rail beam design method based on vehicle rail beam coupling analysis, and belongs to the technical field of magnetic levitation rail traffic, and the method comprises the following steps: determining a bearing rail beam structure; determining the structural size of the bearing rail beam; carrying out vehicle rail beam road coupling analysis on the bearing rail beam, and determining an elastic supporting beam calculation model of the bearing rail beam; according to a structural mechanics principle, determining structural internal force and deformation; carrying capacity design and adaptability design are carried out according to structural internal force and deformation; carrying capacity design, adaptability design and structural size drawing design drawings. According to the method for designing the medium-low-speed magnetic levitation rail bearing beam based on the vehicle rail beam coupling analysis, the rail bearing beam form and the component size adapting to the vehicle load dynamic effect can be conveniently and rapidly designed, so that the rail bearing beam can resist the influence of vehicle vibration on the rail bearing beam, and it is ensured that the design result has good economical efficiency and reliability; and the construction cost of the maglev track can be reduced while the safety and comfort of a medium-low speed maglev traffic system are ensured.