2523results about "Signalling indicators on vehicle" patented technology

The invention relates to the technical field of railways, and discloses a railway passenger train operation state monitoring system based on artificial intelligence, which comprises a multi-modal sensor array, an edge AI judgment platform and a cloud intelligent decision center. According to the railway passenger train operation state monitoring method and system based on artificial intelligence, 28 parameters of a contact network, a running gear and the like are collected in real time through a multi-modal sensor array, an edge AI judgment platform utilizes a cross-modal fusion algorithm to deeply mine multi-source data potential association, the fault diagnosis accuracy is improved, and the fault diagnosis efficiency is improved. The cloud intelligent decision center dynamically aggregates gradient parameters of the edge end model based on federated learning, filters abnormal nodes and updates the abnormal nodes in an hour-level period, and constructs a digital twinborn model in combination with a Spark framework to realize dynamic parameter optimization; the fire-fighting early warning fusion model is linked with the air conditioner pressure and the compartment sealing state correction threshold value through a three-stage mechanism of parameter initial judgment, visual verification and environment verification, it is ensured that the early warning response time is shorter than 200 ms, and cooperation with the overall state of the train is achieved.

The invention discloses a railway freight train data acquisition method and system based on multi-sensor fusion, and relates to the technical field of railway transportation, and the method comprises the steps: detecting the operation state and position of a train in real time through wireless communication, and carrying out the self-inspection of each sensor when the train is detected to be about to enter a monitoring region; constructing a three-dimensional health state model of the train through three-dimensional reconstruction and synchronous positioning according to the comprehensive state data of the train; in combination with a three-dimensional health state model and a side cloud collaborative architecture, layered processing and dynamic optimization of train comprehensive state data are accelerated by using a quantum algorithm, and abnormal features are identified in real time; the abnormal features are analyzed through deep learning and a time sequence analysis algorithm, and alarm information is generated and fed back to the edge computing terminal; according to the method, the running state of the train and the cargo state data are deeply fused through the convolution operation of the three-dimensional health state model and the space-time diagram, so that the global perception capability of the data is improved.

The invention relates to the technical field of big data, and discloses an urban rail transit emergency processing method and system based on a visual large model, and the method comprises the steps: collecting visual data, sound data and equipment operation data at a platform and a carriage of urban rail transit, and carrying out the preprocessing and timestamp synchronization; performing dynamic frame difference processing on continuous video frames of the visual data to generate a two-dimensional motion heat map, and performing space-time aggregation; constructing a three-dimensional digital model based on engineering drawings of the platform and the carriage, and establishing a mapping relation between the two-dimensional motion heat map and the three-dimensional digital model; performing abnormal behavior detection on a mapping result, performing multi-modal fusion analysis in combination with sound data and equipment operation data, and determining the severity of an abnormal event; emergency response strategies are formulated according to severity levels of the abnormal events, a control instruction is sent to the rail transit equipment through an industrial protocol interface, and abnormal event information is pushed to a control center, inspection personnel and passenger terminals.

The invention relates to the technical field of electric vehicle control, and provides an intelligent new energy locomotive power distribution and energy recovery control system and method. The system comprises a multi-source information sensing layer, an intelligent decision control layer and an execution feedback layer. The multi-source information sensing layer collects the state of a vehicle and external environment data. The intelligent decision control layer generates a power distribution and energy recovery instruction through data fusion and preprocessing, fuzzy logic assistance, reinforcement learning decision and cooperative work of a multi-objective optimization module; and the execution feedback layer executes the instruction, monitors feedback in real time, and optimizes related actions. According to the method, advanced technologies such as reinforcement learning and fuzzy logic are fused, complex and changeable driving scenes are accurately dealt with, self-adaptive optimization of power distribution and energy recovery strategies is achieved, the energy recovery efficiency is improved, power distribution is accurate and efficient, dynamic adjustment can be achieved according to driving intentions and working conditions, the driving safety and comfort are guaranteed, and meanwhile the driving efficiency is improved. And efficient utilization of energy is realized.

A system and method generate a trip plan for a trip of a vehicle system along a route. The usage of an engine during the trip is determined based on engine operational parameters, energy storage device operational parameters, and one or more objectives of the trip desired to be achieved. The usage of the energy storage device during the trip is also determined based on the engine operational parameters, the energy storage device operational parameters, and the one or more objective, including when to charge or discharge the energy storage device during the trip.

The invention provides a metro driver abnormal behavior recognition method based on multi-modal data fusion. The method comprises the steps that metro driver abnormal behaviors are recognized based on multi-modal data fusion, track positioning and platform screen door sensor data are fused to detect the position of a train, and a station entering confirmation instruction is generated; according to the data of the seat pressure distribution sensor, driver off-seat inspection is judged; generating an outbound completion event in combination with a track circuit signal, an ATO instruction and the like; analyzing console touch pressure, voice instructions, hand actions and the like to verify operation compliance, and triggering an alarm when the operation is abnormal; aggregating results at edge computing nodes, encrypting and transmitting the aggregated results to a central scheduling system, dynamically mapping driver behaviors in a digital twin cockpit, and automatically triggering hierarchical alarms and associating data snapshots when the driver behaviors are abnormal; according to the invention, accurate recognition and real-time early warning of subway driver behaviors can be realized by means of multi-modal data fusion and intelligent analysis, and the subway operation safety and the emergency response efficiency are greatly improved.

The invention discloses a train dispatcher behavior anomaly detection system based on LSTM-FCN and a dynamic intervention method thereof, and relates to the technical field of intelligent monitoring. Scheduling operation time sequence data, environment state data and physiological monitoring data are collected in real time, a space-time joint feature vector is constructed, and a train dispatcher behavior anomaly detection result is obtained. The LSTM-FCN hybrid network is used to extract time sequence dependence features and spatial pattern features, and an attention weight matrix generated by physiological data and a compensation factor matrix generated by environmental parameters are combined to dynamically calculate a comprehensive abnormal probability value; and when the probability value exceeds a self-adaptive adjustment threshold value, triggering a hierarchical intervention mechanism based on the driving scheduling knowledge graph to realize progressive intervention from interface prompting to manual takeover. By fusing multi-modal data and self-adaptive dynamic compensation, the problem of poor adaptability to complex scenes due to adoption of a static model in traditional train monitoring is solved, and the accuracy and intervention timeliness of abnormal behavior detection of the train dispatcher are remarkably improved.

The invention discloses a train control method and a train control system based on credible interval entry check. The train control method comprises the following steps: starting a backup command; the temporary speed limit server starts a sending module used for sending authorization to a train self-protection system; performing interval credible entry check; determining the existence condition of the train in the interval; the temporary speed limit server updates a train existence condition list in the interval; the train obtains a front driving permission; the train runs according to the running permission. According to the train control method and the train control system based on the credible interval entry check, the axle counting equipment is arranged at the interval entrance, software of the temporary speed limit server only needs to adjust individual modules, and the software of the temporary speed limit server can be only used for recording the train condition in the interval and is not used for authorized calculation, so that the train control method and the train control system are convenient to use. The deployment cost of the temporary speed limit server is reduced, the transportation efficiency under the condition of a CTCS-2 system fault is improved, and the toughness of the CTCS-2 system is improved.

According to the novel transponder and the Beidou short message-combined realization function and application method and system, multiple functions are realized by utilizing multiple combinations of ground and vehicle-mounted transponder system equipment, the novel transponder can be applied to multiple scenes, the equipment types can be simplified, the construction cost can be reduced, and the maintenance workload can be reduced; beidou positioning and short message functions, positioning and communication of wireless communication and the like are used as supplements to perfect train operation control and other functions, and the transportation efficiency and safety are improved.

The invention discloses an electric locomotive rail obstacle identification method, device and system and electronic equipment, and relates to the technical field of rail transit. The method comprises the following steps: acquiring geographic information along a track and current positioning information, acquiring current radar information to perform obstacle detection when a driving state is determined according to the current positioning information, and performing a first alarm and acquiring current video image information when a suspected obstacle is detected; performing time-space synchronization and data fusion on the current positioning information, the current radar information and the current video image information, and inputting the fused data, the locomotive running state data and the geographic information into a pre-established obstacle recognition model to recognize a suspected obstacle to obtain a recognition result; and determining a risk level according to the identification result, so that the electric locomotive gives a second alarm according to the risk level and takes countermeasures. According to the invention, multi-source data is acquired through various sensors, accurate identification of small targets is realized, and the safety of railway transportation is guaranteed.

The invention discloses a traction energy-saving method and system based on dynamic load flow calculation for rail transit, electronic equipment and a readable storage medium, and the traction energy-saving method comprises the steps: planning a multi-vehicle collaborative energy-saving module through an ATO single-vehicle energy-saving + ATS working diagram, a dynamic diagram adjustment module according to passenger flow requirements, a regenerative braking energy feedback module and other modules; multi-dimensional coupling conditions of power supply, vehicles, signals, tracks and the like are dynamically analyzed, dynamic load flow calculation is performed from the perspective of energy flow through a dynamic load flow calculation and analysis module of the traction power supply system, technical means such as ATO energy saving, ATS energy saving and regenerative braking energy recovery device energy saving are dynamically coordinated, unified management and cooperative linkage are performed, and the dynamic load flow calculation and analysis module of the traction power supply system is realized. Energy consumption monitoring and statistical analysis are carried out for different traction energy-saving measures, and long-term energy-saving operation effect tracking and evaluation are carried out; and an energy-saving control strategy is continuously adjusted and optimized according to an analysis result through a prediction model between line energy consumption and operation data variables, so that a better energy-saving effect in a real sense is achieved.

The invention relates to the field of rail transit equipment, and discloses a rail transit equipment multi-source sensing data real-time fault-tolerant decision-making system, which comprises a multi-source sensing module used for collecting rail environment and locomotive state data through a 3D laser radar, a binocular camera and a Beidou positioning terminal, including obstacle, turnout, signal lamp and locomotive position information; the data fusion processing module is used for carrying out preprocessing, redundancy check and feature extraction on the multi-source sensing data to generate a fusion sensing result; and the fault-tolerant decision module is used for judging the safety state of the track based on the fusion sensing result, triggering an alarm / braking instruction and executing self-checking logic when the sensor is abnormal. Through the combination of double groups of redundant sensors and a three-level progressive fault-tolerant strategy, closed-loop control from data acquisition to safety decision is formed, the system robustness under complex working conditions is remarkably improved, and an omnibearing safety protection barrier is constructed for rail transit equipment.

Disclosed is an adaptive control method and system for train operating condition identification. The method includes acquiring train operating state data under various traction conditions and calculating traction and braking performance data. An adhesion condition characteristic data set is formed, and train adhesion conditions are divided into Nz grades based on this data set, where Nz is a natural number. The current adhesion condition grade Nd is identified using the number of adhesion condition grades and current operating state data, where Nd≤Nz, establishing a mapping relationship between an adhesion coefficient and maximum deceleration for braking under the identified grade. An optimal train protection curve is generated. By clustering and grading adhesion conditions through a clustering algorithm, the method achieves more accurate adhesion condition analysis. Adaptively generating optimal train protection curves based on adhesion condition grades enhances the reliability and safety of train operations.

The invention discloses a multi-dimensional train derailment monitoring method based on vision and vibration, and belongs to the field of rail transit, the method comprises the following steps: respectively collecting a wheel-rail contact area image and vibration data of each wheel in different directions, and carrying out space-time alignment on the wheel-rail contact area image and the vibration data; combining an edge detection algorithm and a Hough transform technology to extract visual features from the wheel-rail contact area image, extracting vibration features from the vibration data, and associating the visual features with the vibration features to generate a wheel flange transverse position-vibration feature mapping table; and establishing a D-S evidence theory fusion model based on the wheel flange transverse position-vibration feature mapping table, fusing the visual features and the vibration features by using the D-S evidence theory fusion model, and judging the train derailment risk according to a feature fusion result. According to the invention, deep coupling analysis of visual images and vibration data is realized, and the defects that the prior art cannot adapt to working condition changes, false alarms are easily generated and operation is affected are overcome.

The invention provides a backup degradation train control system based on rail transit intelligent perception, the system comprises existing vehicle-mounted signal subsystems loaded at two ends of a train, a vehicle interface, a bridge and an intelligent perception subsystem, the intelligent perception subsystem comprises an ATO, an ATP, an ITE, a perception device and a speed measurement device; the sensing equipment is connected with the existing vehicle-mounted signal subsystem; the switching equipment is used for switching to the intelligent sensing subsystem to run in an autonomous sensing mode when the train with the CBTC is degraded due to a fault, and the existing vehicle-mounted signal subsystem is still maintained in an RM mode; when the train which autonomously perceives running runs to the area with the upgraded CBTC, the vehicle-mounted equipment is switched back to recover running of the train CBTC; the wireless communication device is used for being in wireless connection with the vehicle-mounted signal subsystem and the trackside device. The intelligent sensing subsystem operates when the CBTC breaks down and degrades, toughness is improved, and it is achieved that the train does not get off line in the peak period.

The invention discloses a shunting automatic driving and protection technology in a full operation scene. In order to improve the safety and efficiency of shunting operation, the shunting operation system is composed of a shunting protection and auxiliary driving platform, a vehicle-mounted intelligent sensing platform, an intelligent management and control data platform and a communication subsystem. The shunting protection and auxiliary driving subsystem comprises a vehicle-mounted subsystem and a ground subsystem, the vehicle-mounted subsystem is provided with a shunting auxiliary driving vehicle-mounted host and the like, and the ground subsystem comprises a host unit and the like. The vehicle-mounted intelligent sensing subsystem can detect obstacles and give an alarm. The intelligent management and control data platform is divided into four layers including a data layer and the like. And the communication subsystem realizes communication of each module. The shunting auxiliary driving vehicle-mounted host is provided with a host and an expansion unit which are consistent in structure, the host and the expansion unit comprise a main controller and the like, two links are established between the units through communication board cards, and the controller of one system can use adjacent communication board cards. The system is used for intelligent management of railway traffic, and has the advantages of safety, high efficiency, full-scene applicability and the like.

Disclosed in the present invention are a backup system, and a train control system and an application method thereof. The backup system comprises: a lineside electronic unit, which communicates with a TIS or a station computer-based interlocking device to obtain a signal state and turnout position information; and an active balise connected to the lineside electronic unit and an onboard device, respectively; wherein the lineside electronic unit determines sent movement authority information and line data information on the basis of the obtained signal state and turnout position information; when a train passes through the position where the active balise is located, the active balise sends the obtained movement authority information and line data information to the onboard device; and when entering an enhanced backup mode, the onboard device in the train control system calculates a speed-distance control curve on the basis of the movement authority information and the line data information obtained from the active balise, so as to perform train operation supervision and protection. According to the prevent invention, when train-ground wireless communication is interrupted and a train control system is degraded to a backup mode, a train is allowed to enter a station at a higher speed.

An electronic train device suitable of use on a railway vehicle includes a radio module configured, through operation of at least one processor, to support and monitor a plurality of communication channels for messages transmitted between multiple electronic train devices on multiple railway vehicles, and to repeat and / or route a transmitted message using a channel of the plurality of communication channels to provide reliable communication between the multiple electronic train devices.

The invention discloses a rack rail trapped rail vehicle and a driving part and a driving assembly thereof. The rack rail trapped rail vehicle comprises a driving disc support; the driving disc assembly is installed on the driving disc support and used for being in meshing transmission with a rack on the rack rail; the driving part is connected with the driving disc assembly and used for driving the pin shaft wheel on the driving disc assembly to rotate; the wheel swing frame assemblies are arranged on the two sides of the lower portion of the driving disc support, and rolling wheels used for being matched with the special-shaped rails on the two sides of the rack rail are arranged on the wheel swing frame assemblies; the first braking device is arranged on the driving disc support and used for clamping the driving disc assembly to achieve working braking of the locomotive; the second braking device is arranged on the wheel swing frame assembly and used for clamping the special-shaped rail to achieve emergency braking of the locomotive; and the speed limiting device is mounted on the driving disc bracket, triggers the first braking device to act when the speed of the locomotive reaches a first preset speed threshold value, and triggers the second braking device to act when the speed detected by the speed limiting device is still greater than zero after the first braking device brakes.

The invention discloses an unmanned vehicle optimal action sequence generation system and method based on cooperation of a large model and a special model, and relates to the technical field of unmanned vehicle control. In the system, after a task understanding and decision vertical large model generates cue word segments based on instruction text information, scene state information and a task planning knowledge base, the cue word segments are divided into a plurality of cue word segments; decomposing the received task into various sub-tasks for task planning, and generating a plurality of action strategies and specific parameter calling information corresponding to the various sub-tasks, so as to obtain multiple types of action schemes; calling corresponding special model analytic operation based on specific parameter calling information of the special model of each action strategy in the current scheme, and dynamically integrating each analytic operation result to obtain an action sequence of the current scheme; and based on the action sequence of each action scheme, determining a comprehensive evaluation value of each action scheme so as to determine an optimal action sequence. The accuracy, the efficiency, the adaptability and the automation degree of generating the action sequence of the unmanned vehicle are improved.

The invention relates to the technical field of air conditioner monitoring, in particular to a subway ventilation air conditioner monitoring system. The method comprises the following modules: a working state identification module S1, which is used for carrying out multi-parameter real-time monitoring on a target subway ventilation air conditioner to obtain an air conditioner operation parameter set; recognizing the working state of the target subway ventilation air conditioner according to the air conditioner operation parameter set to obtain real-time working state data of the air conditioner; the passenger flow monitoring module S2 is used for carrying out panoramic shooting on the target subway carriage to obtain a real-time panoramic image of the carriage; passenger density distribution calculation is conducted on a target subway carriage according to the real-time panoramic image of the carriage, carriage passenger density distribution data are obtained, and the target subway carriage is the subway carriage where the target subway ventilation air conditioner is located. The problems that a traditional ventilation air conditioner monitoring system is poor in flexibility, slow in response, single in parameter regulation and control and waste in energy are effectively solved, and the comfort level of subway passengers is remarkably improved.

The invention provides a train integrity detection method and system for constructing a dynamic envelope based on a multi-mass-point model, and belongs to the technical field of rail transit train operation safety detection. Estimating the real-time length of the baseline by using Kalman filtering; pID control is adopted to analyze and calculate the telescopic displacement of the carriages in the train running process; and comparing the calculated baseline length with the train safety envelope, and judging whether the integrity state of the train is normal or not according to a comparison result. According to the invention, the train length is detected by using the double-difference carrier phase; a train dynamic safety envelope is constructed, a train multi-mass-point model is constructed by researching longitudinal stress analysis such as resistance and workshop acting force of a high-speed train, and compartment extrusion displacement in the train running process is analyzed and calculated through PID control. A train dynamic safety envelope is formed by the data, communication delay and a redundancy threshold value and serves as a judgment basis of train integrity detection, and the efficiency and the real-time performance of train integrity detection are improved.

The invention relates to the field of heavy-load train safety, and discloses a heavy-load train control safety evaluation method and system and electronic equipment. The method comprises the following steps: collecting monitoring data of the heavy-load train, wherein the monitoring data comprises slow change data and time sequence data; performing flexible section division on the operation line based on line features, and performing feature extraction on data acquired by each flexible section unit to obtain a total feature set corresponding to each unit; constructing a feature relationship multi-graph for representing the relationship between the features based on the correlation analysis result of the total feature set; analyzing the feature relationship multi-graph to obtain an optimal feature set of each flexible section unit; and on the basis of the optimal feature set of each flexible section unit, abnormal monitoring is performed on the operation state through a preset context sensing model, and operation safety is evaluated according to a monitoring result. The system construction and maintenance cost is reduced, analysts can be supported to carry out deeper insight, and the intelligent degree of multi-dimensional monitoring data analysis is improved.

The invention discloses a train driving control method and related equipment, and relates to the technical field of rail transit, the method comprises the steps that multi-source sensing data of a target train in a running state is acquired, and the multi-source sensing data comprises a speed characteristic parameter, a space positioning parameter and an environment disturbance parameter; performing dynamic feature extraction on the multi-source sensing data to obtain time-space correlation feature parameters; inputting the time-space correlation characteristic parameters into a preset data fusion model, and performing dynamic compensation through adaptive weight adjustment to obtain accurate train speed information and accurate position information; and performing driving control on the target train according to the accurate train speed information and the accurate position information. According to the invention, through multi-source information fusion and high-precision speed positioning extraction, the sensing accuracy and active adjustment capability of the train control system can be improved.

The invention relates to the technical field of train operation optimization, and discloses an air braking efficiency uncertainty-oriented freight train operation optimization method, which comprises the following steps of: generating a state value function approximate value and a working condition selection set by adopting a constraint-based state value function table learning algorithm according to an initial state and a disturbance sampling value of a freight train; according to the state value function approximate value and the working condition selection set, a state value function table approximate algorithm based on operation time estimation is adopted to generate an operation time approximate value and an operation time estimation value; and according to the operation time approximate value and the operation time estimated value, a freight train operation sequence meeting the air braking constraint, the speed limit constraint and the operation time limit is generated by adopting an operation optimization algorithm meeting the time constraint. According to the method, the freight train operation sequence meeting various constraints can be calculated in a short time, meanwhile, the influence caused by uncertain disturbance is reduced, and the overall optimization effect of the calculation result is improved.

The present invention discloses a method and system for real-time monitoring of the wheel-rail matching state and wheel wear of a rail vehicle. The method comprises the following steps: establishing and performing wear simulation processing on a multi-body dynamics model to obtain vehicle wheel wear at different mileages; collecting axle box vibration accelerations of wheels at different wheel wear levels and performing feature analysis on the axle box vibration accelerations, and extracting axle box lateral vibration accelerations from the axle box vibration accelerations as a training data set; calculating that there is a positive relationship between the wheel wear level and the equivalent taper, and using a correlation model to verify that there is a mapping relationship between wheel wear, equivalent taper, and axle box lateral vibration acceleration; constructing a pre-trained spectrum model, and inputting the training data set into the pre-trained spectrum model for feature training to obtain a spectrum model; collecting a set of axle box lateral vibration accelerations as a test data set and inputting the test data set into the spectrum model to obtain the vehicle wheel-rail matching state and wheel wear level under the axle box lateral vibration accelerations.

A coupling assembly (100) in a first car (12) configured to move relative to a second car (18), the coupling assembly (100) includes an extender (88) and a connector (99). While the first and second cars (12, 18) are both in motion, the extender (88) is configured to extend away from the first car (12) for connecting with the second car (18). The connector (99) is coupled to the extender (88) and is configured to perform the following while the first and second cars (12, 18) are both in motion: (i) connect with a mating connector (98) of the second car (18) when connecting between the first and second cars (12, 18), and (ii) disconnect from the mating connector (98) when disconnecting the first car (12) from the second car (18).

The invention discloses a bullet train section / bullet train station remote shunting system and method, and belongs to the technical field of high-speed railway train operation control. By additionally arranging a ground remote control server, a remote console, a vehicle-mounted remote control unit, a dormancy awakening unit, an environment sensing unit and other devices and combining an ATP / ATO system and a 5G communication technology, the functions of automatic dormancy awakening, remote driving and unmanned shunting of the motor train unit in a motor train section / a motor train station are achieved. The problems that traditional manual shunting is high in labor intensity, low in efficiency and multiple in potential safety hazards are solved.

The invention relates to a train wake-up test method and an implementation system, and the method comprises the steps: enabling DWUs at the head end and the tail end to achieve the power-on of a train through a double-end alternate wake-up mechanism according to a preset sequence after the DWUs at the head end and the tail end receive a wake-up command from an ATS and the state of the train meets a remote wake-up condition in a dormant state of the train; after the train is awakened and powered on, the vehicle-mounted controllers VOBCs at the head end and the tail end execute self-inspection, and the self-inspection state of the train is obtained through the TCMS; entering a static test stage after the self-inspection is passed, sequentially activating the vehicle-mounted controllers VOBCs at the head end and the tail end to be upgraded to a master system, enabling the vehicle-mounted controller VOBCs at the opposite end of the master system to be a slave system, and performing static test on the vehicle-mounted controller VOBCs of the master system; and when the VOBCs at the head end and the tail end serve as main systems to complete the static test and the test is passed, it is confirmed that awakening succeeds. Compared with the prior art, the reliability of the main-standby switching mechanism and the effectiveness of the whole redundancy architecture can be fully verified at the initial stage of starting of the vehicle-mounted operation control system.

The invention discloses a train protection zone processing method based on a train-to-train communication architecture, which comprises the following steps that: an ATP (Automatic Train Protection) of a fault train submits an application for requesting to establish a protection zone to an RC (Remote Control), and the RC sends inquiry information to all trains which establish communication with the RC in a control zone of the RC; after receiving inquiry information of the RC, the trains check the relation between the trains and the protection area and reply, and if all the trains reply to agree to establish the protection area, the RC establishes the protection area; according to the distance between the train inside and outside the protection area and the fault train and the corresponding driving direction, the running state of the train is determined; the running state is emergency braking or continuous running; and after the fault train does not report derailment to the RC or an obstacle exists on the track, the protection area of the fault train is cancelled. The safety and efficiency of train operation are improved.