16.7.2.7.29 Rail Traffic Controls, Trains

Sun, X., Lu, H., Dong, H.,
Energy-Efficient Train Control by Multi-Train Dynamic Cooperation,
ITS(18), No. 11, November 2017, pp. 3114-3121.
IEEE DOI 1711
Energy consumption, Mathematical model, Optimization, Power supplies, Public transportation, Substations, Synchronization, Regenerative braking energy, multi-train cooperation, power supply section, speed, profile BibRef

Wu, D., Schnieder, E.,
Scenario-Based Modeling of the On-Board of a Satellite-Based Train Control System With Colored Petri Nets,
ITS(17), No. 11, November 2016, pp. 3045-3061.
IEEE DOI 1609
Analytical models BibRef

Zhao, Y., Stow, J., Harrison, C.,
Estimating the frequency of trains approaching red signals: A case study for improving the understanding of SPAD risk,
IET-ITS(10), No. 9, 2016, pp. 579-586.
DOI Link 1609
frequency estimation BibRef

Siergiejczyk, M., Pas, J., Rosinski, A.,
Issue of reliability: exploitation evaluation of electronic transport systems used in the railway environment with consideration of electromagnetic interference,
IET-ITS(10), No. 9, 2016, pp. 587-593.
DOI Link 1609
electromagnetic interference BibRef

Huang, Y., Yang, L., Tang, T., Cao, F., Gao, Z.,
Saving Energy and Improving Service Quality: Bicriteria Train Scheduling in Urban Rail Transit Systems,
ITS(17), No. 12, December 2016, pp. 3364-3379.
IEEE DOI 1612
Energy consumption BibRef

Chen, D., Yin, J., Chen, L., Xu, H.,
Parallel Control and Management for High-Speed Maglev Systems,
ITS(18), No. 2, February 2017, pp. 431-440.
IEEE DOI 1702
Complex systems BibRef

Ghosh, S., Das, A., Basak, N., Dasgupta, P., Katiyar, A.,
Formal Methods for Validation and Test Point Prioritization in Railway Signaling Logic,
ITS(18), No. 3, March 2017, pp. 678-689.
IEEE DOI 1703
Communication system signaling BibRef

Wu, Y., Weng, J., Tang, Z., Li, X., Deng, R.H.,
Vulnerabilities, Attacks, and Countermeasures in Balise-Based Train Control Systems,
ITS(18), No. 4, April 2017, pp. 814-823.
IEEE DOI 1704
Air gaps BibRef

Zhu, T., Mera Sánchez de Pedro, J.M.,
Railway Traffic Conflict Detection via a State Transition Prediction Approach,
ITS(18), No. 5, May 2017, pp. 1268-1278.
IEEE DOI 1705
Analytical models, Delays, Mathematical model, Rail transportation, Real-time systems, Safety, Tracking, Conflict detection, dynamic environment, railway traffic management, state transition map, traffic, prediction BibRef

Li, S.[Sihui], Cai, B.G.[Bai-Gen], Wei, S.G.[Shang-Guan], Schnieder, E.[Eckehard], Toro, F.G.[Federico Grasso],
Switching LDS detection for GNSS-based train integrity monitoring system,
IET-ITS(11), No. 5, June 2017, pp. 299-307.
DOI Link 1705
BibRef

Zhao, N.[Ning], Chen, L.[Lei], Tian, Z.[Zhongbei], Roberts, C.[Clive], Hillmansen, S.[Stuart], Lv, J.[Jidong],
Field test of train trajectory optimisation on a metro line,
IET-ITS(11), No. 5, June 2017, pp. 273-281.
DOI Link 1705
BibRef

Liu, W.R.[Wei-Rong], Wang, D.Y.[Dong-Yang], Gao, K.[Kai], Huang, Z.W.[Zhi-Wu],
Design of distributed cooperative observer for heavy-haul train with unknown displacement,
IET-ITS(11), No. 4, May 2017, pp. 239-247.
DOI Link 1705
BibRef

Zhu, L., Yu, F.R., Tang, T., Ning, B.,
Handoff Performance Improvements in an Integrated Train-Ground Communication System Based on Wireless Network Virtualization,
ITS(18), No. 5, May 2017, pp. 1165-1178.
IEEE DOI 1705
Delays, Optimization, Quality of service, Rails, Virtualization, Wireless networks, Urban rail transit, handoff, train control, wireless, network, virtualization BibRef

Liu, J., Guo, H., Yu, Y.,
Research on the Cooperative Train Control Strategy to Reduce Energy Consumption,
ITS(18), No. 5, May 2017, pp. 1134-1142.
IEEE DOI 1705
Acceleration, Energy consumption, Force, Optimization, Public transportation, Rails, Energy-saving operation, cooperative train control, regenerative braking, subway, train BibRef

Nguyen, K.T.P., Beugin, J., Berbineau, M., Kassab, M.,
A New Analytical Approach to Evaluate the Critical-Event Probability Due to Wireless Communication Errors in Train Control Systems,
ITS(18), No. 6, June 2017, pp. 1380-1392.
IEEE DOI 1706
Delays, Handover, Optical wavelength conversion, Rail transportation, Safety, Wireless communication, Rail transportation communication, intelligent transportation systems, probabilistic model, rail transportation reliability, wireless, communication, errors BibRef

Gao, M., Wang, P., Cao, Y., Chen, R., Cai, D.,
Design and Verification of a Rail-Borne Energy Harvester for Powering Wireless Sensor Networks in the Railway Industry,
ITS(18), No. 6, June 2017, pp. 1596-1609.
IEEE DOI 1706
Electromagnetics, Rail transportation, Rails, Testing, Vehicles, Vibrations, Wireless sensor networks, Energy harvester, electromagnetics, rail-borne device, railway vibration, wheelset/track excitation, wireless, sensor, networks BibRef

Ahmadi, S.[Saeed], Dastfan, A.[Ali], Assili, M.[Mohsen],
Improving energy-efficient train operation in urban railways: employing the variation of regenerative energy recovery rate,
IET-ITS(11), No. 6, August 2017, pp. 349-357.
DOI Link 1707
BibRef

Cheng, R., Song, Y., Chen, D., Chen, L.,
Intelligent Localization of a High-Speed Train Using LSSVM and the Online Sparse Optimization Approach,
ITS(18), No. 8, August 2017, pp. 2071-2084.
IEEE DOI 1708
Adaptation models, Computational modeling, Data models, Mathematical model, Rail transportation, Real-time systems, Support vector machines, High-speed train, L0-norm minimization, LSSVM, iterative pruning error minimization, location error, online, sparse, optimization BibRef

Wandelt, S., Wang, Z., Sun, X.,
Worldwide Railway Skeleton Network: Extraction Methodology and Preliminary Analysis,
ITS(18), No. 8, August 2017, pp. 2206-2216.
IEEE DOI 1708
Data mining, Estimation, Planets, Rail transportation, Skeleton, Urban areas, OpenStreetMap, Worldwide railway network, global, mobility BibRef

Liu, Y., Neri, A., Ruggeri, A., Vegni, A.M.,
A MPTCP-Based Network Architecture for Intelligent Train Control and Traffic Management Operations,
ITS(18), No. 9, September 2017, pp. 2290-2302.
IEEE DOI 1709
control engineering computing, intelligent control, quality of service, rail traffic control, railway communication, traffic engineering computing, transport protocols, MPTCP-based network architecture, QoS, add and drop subflow policies, communication system architecture, data control, multipath transmission control protocol, priority handling logics, public land mobile networks, quality-of-service, traffic management operations, Long Term Evolution, Network architecture, Satellite broadcasting, Satellites, ERTMS/ETCS, MPTCP, PLMNs. BibRef

Arboleya, P.,
Heterogeneous Multiscale Method for Multirate Railway Traction Systems Analysis,
ITS(18), No. 9, September 2017, pp. 2575-2580.
IEEE DOI 1709
mechanical variables, Hidden Markov models, heterogeneous multiscale method, multirate analysis, BibRef

Marais, J., Beugin, J., Berbineau, M.,
A Survey of GNSS-Based Research and Developments for the European Railway Signaling,
ITS(18), No. 10, October 2017, pp. 2602-2618.
IEEE DOI 1710
Rail transportation, Safety, Localization, railway safety, signaling BibRef

Ghazel, M.,
A Control Scheme for Automatic Level Crossings Under the ERTMS/ETCS Level 2/3 Operation,
ITS(18), No. 10, October 2017, pp. 2667-2680.
IEEE DOI 1710
Context, Control systems, Rail transportation, Roads, Safety, ERTMS/ETCS, GSM-R, Level crossing, formal methods, railway control, railway safety, time, Petri, net BibRef

de Aguiar, E.P.[Eduardo P.], de A. Nogueira, F.M.[Fernando M.], Vellasco, M.M.B.R.[Marley M.B.R.], Ribeiro, M.V.[Moisés V.],
Set-Membership Type-1 Fuzzy Logic System Applied to Fault Classification in a Switch Machine,
ITS(18), No. 10, October 2017, pp. 2703-2712.
IEEE DOI 1710
Computational complexity, Convergence, Fuzzy logic, Monitoring, Rail transportation, Switches, Training, Fuzzy logic systems, adaptive algorithms, computational complexity reduction, set-membership BibRef

Eaton, J., Yang, S., Gongora, M.,
Ant Colony Optimization for Simulated Dynamic Multi-Objective Railway Junction Rescheduling,
ITS(18), No. 11, November 2017, pp. 2980-2992.
IEEE DOI 1711
Delays, Dynamic scheduling, Energy consumption, Heuristic algorithms, Junctions, Linear programming, Rail transportation, Train rescheduling, U.K. railway network, ant colony optimisation, dynamic multi-objective optimization, rail, transportation BibRef

Hua, W.[Wen], Ong, G.P.[Ghim Ping],
Network survivability and recoverability in urban rail transit systems under disruption,
IET-ITS(11), No. 10, December 2017, pp. 641-648.
DOI Link 1711
BibRef

Li, W.J.[Wen-Jun], Nie, L.[Lei],
Coordinated optimisation problem integrating EMU circulation and timetabling for high-speed railway,
IET-ITS(11), No. 10, December 2017, pp. 695-704.
DOI Link 1711
BibRef

Fu, Y.[Yating], Yang, H.[Hui], Ding, J.L.[Jin-Liang],
Multiple operating mode ANFIS modelling for speed control of HSEMU,
IET-ITS(12), No. 1, February 2018, pp. 31-40.
DOI Link 1801
High-speed electric multiple unit. BibRef

Tang, H., Wang, Q., Feng, X.,
Robust Stochastic Control for High-Speed Trains With Nonlinearity, Parametric Uncertainty, and Multiple Time-Varying Delays,
ITS(19), No. 4, April 2018, pp. 1027-1037.
IEEE DOI 1804
Adaptation models, Aerodynamics, Automobiles, Delays, Robustness, Stochastic processes, Time-varying systems, velocity tracking control BibRef

Carboni, A.[Angela], Deflorio, F.[Francesco],
Performance indicators and automatic identification systems in inland freight terminals for intermodal transport,
IET-ITS(12), No. 4, May 2018, pp. 309-318.
DOI Link 1804
BibRef

Liu, F.B.[Feng-Bo], Xu, R.H.[Rui-Hua], Fan, W.[Wei], Jiang, Z.B.[Zhi-Bin],
Data analytics approach for train timetable performance measures using automatic train supervision data,
IET-ITS(12), No. 7, September 2018, pp. 568-577.
DOI Link 1808
BibRef

Zheng, H.[Han], Cui, Z.Y.[Zan-Yang], Zhang, X.C.[Xing-Chen],
Identifying Modes of Driving Railway Trains from GPS Trajectory Data: An Ensemble Classifier-Based Approach,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Huang, Y.P.[Ya-Ping], Lu, S.[Shiwei], Yang, X.P.[Xi-Ping], Zhao, Z.Y.[Zhi-Yuan],
Exploring Railway Network Dynamics in China from 2008 to 2017,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Feng, F.L.[Fen-Ling], Li, W.[Wan], Jiang, Q.W.[Qi-Wei],
Railway freight volume forecast using an ensemble model with optimised deep belief network,
IET-ITS(12), No. 8, October 2018, pp. 851-859.
DOI Link 1809
BibRef

Ferlin, A., Qiu, S., Bon, P., Sallak, M., Collart Dutilleul, S., Schön, W., Cherfi-Boulanger, Z.,
An Automated Method for the Study of Human Reliability in Railway Supervision Systems,
ITS(19), No. 10, October 2018, pp. 3360-3375.
IEEE DOI 1810
Reliability, Task analysis, Rail transportation, Context modeling, Accidents, Analytical models, Human factors, railway/ERTMS BibRef

Liu, H., Yang, H., Cai, B.,
Optimization for the Following Operation of a High-Speed Train Under the Moving Block System,
ITS(19), No. 10, October 2018, pp. 3406-3413.
IEEE DOI 1810
Optimization, Convergence, Safety, Resistance, Rail transportation, Measurement, Algorithm design and analysis, High-speed train, PSO algorithm BibRef

Liu, P., Yang, L., Gao, Z., Huang, Y., Li, S., Gao, Y.,
Energy-Efficient Train Timetable Optimization in the Subway System with Energy Storage Devices,
ITS(19), No. 12, December 2018, pp. 3947-3963.
IEEE DOI 1812
Acceleration, Public transportation, Energy consumption, Optimization, Linear programming, Supercapacitors, Subway system, regenerative braking energy BibRef

Becker, M., Schreckenberg, M.,
Analytical Method for the Precise and Fast Prediction of Railway Running Times and its Applications,
ITS(19), No. 11, November 2018, pp. 3560-3569.
IEEE DOI 1812
railways, standard commuter train, railway management, railway running time prediction, rail transportation BibRef

Khayyam, S., Berr, N., Razik, L., Fleck, M., Ponci, F., Monti, A.,
Railway System Energy Management Optimization Demonstrated at Offline and Online Case Studies,
ITS(19), No. 11, November 2018, pp. 3570-3583.
IEEE DOI 1812
energy consumption, energy management systems, optimisation, railway electrification, integrated mainline railway system, smart grids BibRef

Yuan, Z., Chen, X., Liu, J., Yu, Y., Sun, H., Zhou, T., Jin, Z.,
Simplifying the Formal Verification of Safety Requirements in Zone Controllers Through Problem Frames and Constraint-Based Projection,
ITS(19), No. 11, November 2018, pp. 3517-3528.
IEEE DOI 1812
control engineering computing, formal verification, rail traffic control, railway safety, formal verification BibRef

Goya, J., de Miguel, G., Arrizabalaga, S., Zamora-Cadenas, L., Adin, I., Mendizabal, J.,
Methodology and Key Performance Indicators (KPIs) for Railway On-Board Positioning Systems,
ITS(19), No. 12, December 2018, pp. 4035-4042.
IEEE DOI 1812
Global navigation satellite system, Rail transportation, Standardization, Random access memory, Safety, Europe, Reliability, on-board position BibRef

Dong, H.R.[Hai-Rong], Zhu, H.N.[Hai-Nan], Li, Y.D.[Yi-Dong], Lv, Y.S.[Yi-Sheng], Gao, S.G.[Shi-Gen], Zhang, Q.[Qi], Ning, B.[Bin],
Parallel Intelligent Systems for Integrated High-Speed Railway Operation Control and Dynamic Scheduling,
Cyber(48), No. 12, December 2018, pp. 3381-3389.
IEEE DOI 1812
parallel processing, rail traffic, railway engineering, railways, traffic engineering computing, dynamic scheduling, parallel intelligent system BibRef

Dai, X.W.[Xue-Wu], Zhao, H.[Hui], Yu, S.P.[Sheng-Ping], Cui, D.L.[Dong-Liang], Zhang, Q.[Qi], Dong, H.R.[Hai-Rong], Chai, T.Y.[Tian-You],
Dynamic Scheduling, Operation Control and Their Integration in High-Speed Railways: A Review of Recent Research,
ITS(23), No. 9, September 2022, pp. 13994-14010.
IEEE DOI 2209
Dynamic scheduling, Rail transportation, Control systems, Scheduling, Safety, Dispatching, Delays, High-speed trains, integration BibRef

Zhang, X., Ludwig, A., Sood, N., Sarris, C.D.,
Physics-Based Optimization of Access Point Placement for Train Communication Systems,
ITS(19), No. 9, September 2018, pp. 3028-3038.
IEEE DOI 1809
Cost function, Receivers, Mathematical model, Wireless communication, Rails, wireless access point BibRef

Hwang, K., Cho, J., Park, J., Har, D., Ahn, S.,
Ferrite Position Identification System Operating With Wireless Power Transfer for Intelligent Train Position Detection,
ITS(20), No. 1, January 2019, pp. 374-382.
IEEE DOI 1901
Ferrites, Rail transportation, Magnetic cores, Insulation life, Degradation, Detectors, Wheels, Wireless power transfer (WPT), ferrite device BibRef

Meng, J., Xu, R., Li, D., Chen, X.,
Combining the Matter-Element Model With the Associated Function of Performance Indices for Automatic Train Operation Algorithm,
ITS(20), No. 1, January 2019, pp. 253-263.
IEEE DOI 1901
Optimization, Process control, Safety, Intelligent control, PI control, PD control, Automatic train operation, performance indices BibRef

Sun, H., Wu, J., Ma, H., Yang, X., Gao, Z.,
A Bi-Objective Timetable Optimization Model for Urban Rail Transit Based on the Time-Dependent Passenger Volume,
ITS(20), No. 2, February 2019, pp. 604-615.
IEEE DOI 1902
Energy consumption, Optimization, Rails, Numerical models, Safety, Sun, Rail transportation, Timetable, passenger waiting time, AFC data BibRef

Khadilkar, H.,
A Scalable Reinforcement Learning Algorithm for Scheduling Railway Lines,
ITS(20), No. 2, February 2019, pp. 727-736.
IEEE DOI 1902
Rail transportation, Tracking, Learning (artificial intelligence), Delays, Processor scheduling, rail transportation BibRef

Song, H.F.[Hai-Feng], Schnieder, E.[Eckehard],
Development and Validation of a Distance Measurement System in Metro Lines,
ITS(20), No. 2, February 2019, pp. 441-456.
IEEE DOI 1902
Train-to-train distance. Unified modeling language, Software, Distance measurement, Analytical models, Safety, Petri nets, Metro transport, model validation BibRef

Li, S., Yang, L., Gao, Z.,
Efficient Real-Time Control Design for Automatic Train Regulation of Metro Loop Lines,
ITS(20), No. 2, February 2019, pp. 485-496.
IEEE DOI 1902
Real-time systems, Mathematical model, Optimal control, Safety, Predictive control, Quadratic programming, Metro loop lines, quadratic programming BibRef

Yazhemsky, D., Rashid, M., Sirouspour, S.,
An On-Line Optimal Controller for a Commuter Train,
ITS(20), No. 3, March 2019, pp. 1112-1125.
IEEE DOI 1903
Optimal control, Real-time systems, Optimization, Computational modeling, Numerical models, Vehicle dynamics, sparse optimization BibRef

Zou, L., Wen, T., Wang, Z., Chen, L., Roberts, C.,
State Estimation for Communication-Based Train Control Systems With CSMA Protocol,
ITS(20), No. 3, March 2019, pp. 843-854.
IEEE DOI 1903
Protocols, Multiaccess communication, State estimation, Control systems, Wireless communication, Scheduling, linear matrix inequalities BibRef

Zhang, Y., Wang, H., Yuan, T., Lv, J., Xu, T.,
Hybrid Online Safety Observer for CTCS-3 Train Control System On-Board Equipment,
ITS(20), No. 3, March 2019, pp. 925-934.
IEEE DOI 1903
Safety, Brakes, Monitoring, Observers, Rail transportation, Runtime, CTCS-3, on-board equipment, reachability analysis, safety, online verification BibRef

Li, D., Li, P., Cai, W., Ma, X., Liu, B., Dong, H.,
Neural Adaptive Fault Tolerant Control for High Speed Trains Considering Actuation Notches and Antiskid Constraints,
ITS(20), No. 5, May 2019, pp. 1706-1718.
IEEE DOI 1905
Aerodynamics, Force, Adaptation models, Artificial neural networks, Fault tolerant control, Safety, High speed train, adaptive control, fault tolerant control BibRef

Song, H., Liu, H., Schnieder, E.,
A Train-Centric Communication-Based New Movement Authority Proposal for ETCS-2,
ITS(20), No. 6, June 2019, pp. 2328-2338.
IEEE DOI 1906
Safety, Switches, Rail transportation, Accidents, Tracking, Estimation, Movement authority, European Train Control System (ETCS), minimum train headway distance BibRef

Novak, H., Lešic, V., Vašak, M.,
Hierarchical Model Predictive Control for Coordinated Electric Railway Traction System Energy Management,
ITS(20), No. 7, July 2019, pp. 2715-2727.
IEEE DOI 1907
Rail transportation, Energy consumption, Optimization, Force, Resistance, Energy management, Power grids, hierarchical model predictive control BibRef

Felez, J., Kim, Y., Borrelli, F.,
A Model Predictive Control Approach for Virtual Coupling in Railways,
ITS(20), No. 7, July 2019, pp. 2728-2739.
IEEE DOI 1907
Couplings, Rail transportation, Control systems, Aerodynamics, Safety, Predictive control, CBTC, ERTMS, virtual coupling BibRef

Gao, S., Dong, H., Ning, B., Zhang, Q.,
Cooperative Prescribed Performance Tracking Control for Multiple High-Speed Trains in Moving Block Signaling System,
ITS(20), No. 7, July 2019, pp. 2740-2749.
IEEE DOI 1907
Trajectory, Tracking, Rails, Safety, Moving block signaling system, high-speed train, cooperative control, prescribed performance control BibRef

Bai, W., Lin, Z., Dong, H., Ning, B.,
Distributed Cooperative Cruise Control of Multiple High-Speed Trains Under a State-Dependent Information Transmission Topology,
ITS(20), No. 7, July 2019, pp. 2750-2763.
IEEE DOI 1907
Automobiles, Safety, Topology, Couplers, Decentralized control, Information processing, Rail transportation, High-speed train, train-to-train communication BibRef

Tian, Z., Zhao, N., Hillmansen, S., Roberts, C., Dowens, T., Kerr, C.,
SmartDrive: Traction Energy Optimization and Applications in Rail Systems,
ITS(20), No. 7, July 2019, pp. 2764-2773.
IEEE DOI 1907
Optimization, Rails, Rail transportation, Vehicles, Energy consumption, Trajectory, Genetic algorithms, driver practical training BibRef

Wen, T., Constantinou, C., Chen, L., Li, Z., Roberts, C.,
A Practical Access Point Deployment Optimization Strategy in Communication-Based Train Control Systems,
ITS(20), No. 8, August 2019, pp. 3156-3167.
IEEE DOI 1908
Planning, Wireless communication, Wireless LAN, Optimization, Power system reliability, Probability, Shadow mapping, integrated simulation platform BibRef

Zheng, H.[Han], Cui, Z.Y.[Zan-Yang], Zhang, X.C.[Xing-Chen],
Automatic Discovery of Railway Train Driving Modes Using Unsupervised Deep Learning,
IJGI(8), No. 7, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Umiliacchi, S.[Silvia], Bhatia, D.[Davinder], Brownlee, A.[Andrew], Brown, C.[Colin],
Enterprise architecture within railway systems engineering,
IET-ITS(13), No. 10, October 2019, pp. 1461-1467.
DOI Link 1909
BibRef

Cheng, R., Song, Y., Chen, D., Ma, X.,
Intelligent Positioning Approach for High Speed Trains Based on Ant Colony Optimization and Machine Learning Algorithms,
ITS(20), No. 10, October 2019, pp. 3737-3746.
IEEE DOI 1910
Data models, Clustering algorithms, Adaptation models, Real-time systems, Mathematical model, Prediction algorithms, online learning algorithm BibRef

Liu, J.[Jin], Chen, L.[Lei], Roberts, C.[Clive], Nicholson, G.[Gemma], Ai, B.[Bo],
Algorithm and peer-to-peer negotiation strategies for train dispatching problems in railway bottleneck sections,
IET-ITS(13), No. 11, November 2019, pp. 1717-1725.
DOI Link 1911
BibRef

Wu, C., Zhang, W., Lu, S., Tan, Z., Xue, F., Yang, J.,
Train Speed Trajectory Optimization With On-Board Energy Storage Device,
ITS(20), No. 11, November 2019, pp. 4092-4102.
IEEE DOI 1911
Electrostatic discharges, Traction motors, Trajectory, Energy storage, Rail transportation, Acceleration, on-board energy storage device (ESD) BibRef

Zhang, Y.[Yong], Wang, H.F.[Hai-Feng],
Topological manifold-based monitoring method for train-centric virtual coupling control systems,
IET-ITS(14), No. 2, February 2020, pp. 91-102.
DOI Link 2002
BibRef

Zhang, Y.[Yong], Wang, H.F.[Hai-Feng], James, P.[Phillip], Roggenbach, M.[Markus], Tian, D.X.[Da-Xin],
A Train Protection Logic Based on Topological Manifolds for Virtual Coupling,
ITS(23), No. 8, August 2022, pp. 11930-11945.
IEEE DOI 2208
Couplings, Control systems, Safety, Rail transportation, Manifolds, Tracking, Process control, Virtual coupling control, formal verification BibRef

Saki, M., Abolhasan, M., Lipman, J.,
A Novel Approach for Big Data Classification and Transportation in Rail Networks,
ITS(21), No. 3, March 2020, pp. 1239-1249.
IEEE DOI 2003
Rail transportation, Data communication, Rails, Big Data, Real-time systems, Data analysis, Railway condition monitoring, online data classification BibRef

Zhou, T., Tao, C., Salous, S., Liu, L.,
Geometry-Based Multi-Link Channel Modeling for High-Speed Train Communication Networks,
ITS(21), No. 3, March 2020, pp. 1229-1238.
IEEE DOI 2003
High-speed train communication, distributed systems, multi-link channel, channel modeling, cross-correlation BibRef

Xu, Z., Zhang, Q., Chen, D., He, Y.,
Characterizing the Connectivity of Railway Networks,
ITS(21), No. 4, April 2020, pp. 1491-1502.
IEEE DOI 2004
Rail transportation, Measurement, Urban areas, Roads, Rails, Complex network, railway systems, simulation BibRef

Yao, X., Wu, L., Guo, L.,
Disturbance-Observer-Based Fault Tolerant Control of High-Speed Trains: A Markovian Jump System Model Approach,
SMCS(50), No. 4, April 2020, pp. 1476-1485.
IEEE DOI 2004
Force, Circuit faults, Sensors, Aerodynamics, Load modeling, Resistance, Analytical models, Disturbance observer, velocity tracking BibRef

Bai, Y., Cao, Y., Yu, Z., Ho, T.K., Roberts, C., Mao, B.,
Cooperative Control of Metro Trains to Minimize Net Energy Consumption,
ITS(21), No. 5, May 2020, pp. 2063-2077.
IEEE DOI 2005
Energy consumption, Optimization, Optimal control, Delays, Switches, Energy storage, Metro train, cooperative control, energy saving, co-evolutionary algorithm BibRef

Muniandi, G.[Ganesan],
Blockchain-enabled virtual coupling of automatic train operation fitted mainline trains for railway traffic conflict control,
IET-ITS(14), No. 6, June 2020, pp. 611-619.
DOI Link 2005
BibRef

Hamid, H.A.[Hassan Abdulsalam], Nicholson, G.L.[Gemma L.], Roberts, C.[Clive],
Impact of train positioning inaccuracies on railway traffic management systems: framework development and impacts on TMS functions,
IET-ITS(14), No. 6, June 2020, pp. 534-544.
DOI Link 2005
BibRef

Guilliard, I.[Iain], Trevizan, F.[Felipe], Sanner, S.[Scott],
Mitigating the impact of light rail on urban traffic networks using mixed-integer linear programming,
IET-ITS(14), No. 6, June 2020, pp. 523-533.
DOI Link 2005
BibRef

Ai, B., Molisch, A.F., Rupp, M., Zhong, Z.,
5G Key Technologies for Smart Railways,
PIEEE(108), No. 6, June 2020, pp. 856-893.
IEEE DOI 2006
5G mobile communication, Rail transportation, Wireless communication, Artificial intelligence, ultrareliable low latency communication (URLLC) BibRef

Mao, Z.H.[Ze-Hui], Yan, X.G.[Xing-Gang], Jiang, B.[Bin], Chen, M.[Mou],
Adaptive Fault-Tolerant Sliding-Mode Control for High-Speed Trains with Actuator Faults and Uncertainties,
ITS(21), No. 6, June 2020, pp. 2449-2460.
IEEE DOI 2006
Uncertainty, Actuators, Fault tolerance, Fault tolerant systems, Mathematical model, Force, Adaptation models, Actuator faults, high-speed train BibRef

di Meo, C., di Vaio, M., Flammini, F., Nardone, R., Santini, S., Vittorini, V.,
ERTMS/ETCS Virtual Coupling: Proof of Concept and Numerical Analysis,
ITS(21), No. 6, June 2020, pp. 2545-2556.
IEEE DOI 2006
Couplings, Safety, Europe, Numerical analysis, Reliability, Block signalling, Railways, ERTMS/ETCS, automatic train control, numerical analysis BibRef

Ji, Y., Tang, Y., Shen, Y., Du, Y., Wang, W.,
An Integrated Approach for Tram Prioritization in Signalized Corridors,
ITS(21), No. 6, June 2020, pp. 2386-2395.
IEEE DOI 2006
Bandwidth, Timing, Reliability, Schedules, Real-time systems, Trajectory, Intelligent transportation systems, Tram, microsimulation BibRef

López Díez, P., Gabilondo, I., Alarcón, E., Moll, F.,
Mechanical Energy Harvesting Taxonomy for Industrial Environments: Application to the Railway Industry,
ITS(21), No. 7, July 2020, pp. 2696-2706.
IEEE DOI 2007
Magnetic domains, Magnetostriction, Amorphous magnetic materials, Energy harvesting, Mechanical energy, Industries, railway industry BibRef

Jin, B.[Bo], Sun, P.F.[Peng-Fei], Wang, Q.Y.[Qing-Yuan], Feng, X.Y.[Xiao-Yun],
Two-step method to reduce metro transit energy consumption by optimising speed profile and timetable,
IET-ITS(14), No. 9, September 2020, pp. 1097-1107.
DOI Link 2008
BibRef

Mo, P., Yang, L., d'Ariano, A., Yin, J., Yao, Y., Gao, Z.,
Energy-Efficient Train Scheduling and Rolling Stock Circulation Planning in a Metro Line: A Linear Programming Approach,
ITS(21), No. 9, September 2020, pp. 3621-3633.
IEEE DOI 2008
Schedules, Load modeling, Dynamic scheduling, Numerical models, Energy consumption, Optimization, Metro train scheduling, dynamic passenger demands BibRef

Ghasempour, T., Nicholson, G.L., Kirkwood, D., Fujiyama, T., Heydecker, B.,
Distributed Approximate Dynamic Control for Traffic Management of Busy Railway Networks,
ITS(21), No. 9, September 2020, pp. 3788-3798.
IEEE DOI 2008
Rail transportation, Real-time systems, Delays, Dynamic programming, Rails, Aerospace electronics, Tools, reinforcement learning BibRef

Ge, M., Song, Q., Hu, X., Zhang, H.,
RBFNN-Based Fractional-Order Control of High-Speed Train With Uncertain Model and Actuator Failures,
ITS(21), No. 9, September 2020, pp. 3883-3892.
IEEE DOI 2008
Actuators, Force, Aerodynamics, Reliability, Uncertainty, Resistance, Fractional-order control, high speed train, actuator failures BibRef

Ge, M.[Meng], Song, Q.[Qi],
Fractional-Order Control of High Speed Train With Actuator Complete Failure,
ITS(23), No. 11, November 2022, pp. 21665-21674.
IEEE DOI 2212
Actuators, Force, Robustness, Uncertainty, Fault tolerant systems, Termination of employment, Resistance, Actuator complete failure, fault-tolerant control BibRef

Su, S., Wang, X., Cao, Y., Yin, J.,
An Energy-Efficient Train Operation Approach by Integrating the Metro Timetabling and Eco-Driving,
ITS(21), No. 10, October 2020, pp. 4252-4268.
IEEE DOI 2010
Energy consumption, Optimization, Acceleration, Switches, Dynamic programming, Rails, Mathematical model, regenerative energy BibRef

Wang, X., Liu, L., Zhu, L., Tang, T.,
Train-Centric CBTC Meets Age of Information in Train-to-Train Communications,
ITS(21), No. 10, October 2020, pp. 4072-4085.
IEEE DOI 2010
Wireless communication, Rails, Quality of service, Control systems, Public transportation, Resource management, Wireless LAN, DS-SPS BibRef

Liu, J., Zhang, Y., Han, J., He, J., Sun, J., Zhou, T.,
Intelligent Hazard-Risk Prediction Model for Train Control Systems,
ITS(21), No. 11, November 2020, pp. 4693-4704.
IEEE DOI 2011
Predictive models, Hazards, Control systems, Rails, Neural networks, Systems architecture, Risk prediction, deep learning, statistical model checking BibRef

Wang, X., Zhu, L., Wang, H., Tang, T., Li, K.,
Robust Distributed Cruise Control of Multiple High-Speed Trains Based on Disturbance Observer,
ITS(22), No. 1, January 2021, pp. 267-279.
IEEE DOI 2012
Cruise control, Safety, Automobiles, Disturbance observers, Rail transportation, Decentralized control, High-speed train, disturbance observer BibRef

Zhang, Q.[Qi], Wang, T.[Tao], Huang, K.[Kang], Chen, F.[Feng],
Efficient dispatching system of railway vehicles based on internet of things technology,
PRL(143), 2021, pp. 14-18.
Elsevier DOI 2102
Vehicle dispatching system, Internet of things technology, Information management, Transportation management, Railway transportation BibRef

Pichlík, P., Bauer, J.,
Analysis of the Locomotive Wheel Slip Controller Operation During Low Velocity,
ITS(22), No. 3, March 2021, pp. 1543-1552.
IEEE DOI 2103
Adhesives, Wheels, Force, Velocity measurement, Rails, Estimation, Kalman filters, Adhesion, digital control, unscented Kalman filter, velocity control BibRef

Liu, G.F.[Gen-Feng], Hou, Z.S.[Zhong-Sheng],
Adaptive Iterative Learning Control for Subway Trains Using Multiple-Point-Mass Dynamic Model Under Speed Constraint,
ITS(22), No. 3, March 2021, pp. 1388-1400.
IEEE DOI 2103
Public transportation, Vehicle dynamics, Adaptation models, Iterative learning control, Heuristic algorithms, Resistance, barrier composite energy function (BCEF) BibRef

Liu, G.F.[Gen-Feng], Hou, Z.S.[Zhong-Sheng],
Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains,
Cyber(52), No. 2, February 2022, pp. 1098-1111.
IEEE DOI 2202
Public transportation, Actuators, Vehicle dynamics, Heuristic algorithms, Adaptation models, Fault tolerance, radial basis function neural network (RBFNN) BibRef

Luo, P., Li, Q., Zhou, Y., Ma, Q., Zhang, Y., Peng, Y., Sun, J.,
Multi-Application Strategy Based on Railway Static Power Conditioner With Energy Storage System,
ITS(22), No. 4, April 2021, pp. 2140-2152.
IEEE DOI 2104
Rail transportation, Economics, Energy storage, Traction power supplies, Maintenance engineering, Load modeling, multi-application strategy BibRef

Schanzenbächer, F.[Florian], Farhi, N.[Nadir], Leurent, F.[Fabien], Gabriel, G.[Gérard],
Feedback Control for Metro Lines With a Junction,
ITS(22), No. 5, May 2021, pp. 2741-2750.
IEEE DOI 2105
Junctions, Feedback control, Mathematical model, Frequency control, Rail transportation, Time-frequency analysis, Physics. BibRef

Tan, P.[Ping], Li, X.F.[Xu-Feng], Wu, Z.G.[Zheng-Guang], Ding, J.[Jin], Ma, J.[Jien], Chen, Y.F.[Ying-Feng], Fang, Y.T.[You-Tong], Ning, Y.[Yong],
Multialgorithm Fusion Image Processing for High Speed Railway Dropper Failure-Defect Detection,
SMCS(51), No. 7, July 2021, pp. 4466-4478.
IEEE DOI 2106
Rail transportation, Inspection, Maintenance engineering, Wires, Deep learning, Feature extraction, Deep learning, multialgorithm fusion BibRef

Huang, D.Q.[De-Qing], Chen, Y.[Yong], Meng, D.[Deyuan], Sun, P.F.[Peng-Fei],
Adaptive Iterative Learning Control for High-Speed Train: A Multi-Agent Approach,
SMCS(51), No. 7, July 2021, pp. 4067-4077.
IEEE DOI 2106
Automobiles, Multi-agent systems, Aerodynamics, Resistance, Force, Couplers, Sun, High-speed train, iterative learning control (ILC), tracking control BibRef

Huang, S.Z.[Shi-Ze], Yang, L.Y.[Ling-Yu], Chen, W.[Wei], Tao, T.[Ting], Zhang, B.J.[Bing-Jie],
A specific perspective: Subway driver behaviour recognition using CNN and time-series diagram,
IET-ITS(15), No. 3, 2021, pp. 387-395.
DOI Link 2106
BibRef

Ying, P.R.[Pei-Ran], Zeng, X.Q.[Xiao-Qing], Song, H.F.[Hai-Feng], Shen, T.[Tuo], Yuan, T.F.[Teng-Fei],
Energy-efficient train operation with steep track and speed limits: A novel Pontryagin's maximum principle-based approach for adjoint variable discontinuity cases,
IET-ITS(15), No. 9, 2021, pp. 1183-1202.
DOI Link 2108
BibRef

Dong, H.X.[Han-Xuan], Ding, F.[Fan], Tan, H.C.[Hua-Chun], Wu, Y.K.[Yuan-Kai], Li, Q.[Qin], Ran, B.[Bin],
Rail transit OD-matrix completion via manifold regularized tensor factorisation,
IET-ITS(15), No. 10, 2021, pp. 1304-1317.
DOI Link 2109
BibRef

Grandhi, B.S.[Bhagya Shrithi], Chaniotakis, E.[Emmanouil], Thomann, S.[Stephan], Laube, F.[Felix], Antoniou, C.[Constantinos],
An estimation framework to quantify railway disruption parameters,
IET-ITS(15), No. 10, 2021, pp. 1256-1268.
DOI Link 2109
BibRef

Guo, X.G.[Xiang-Gui], Ahn, C.K.[Choon Ki],
Adaptive Fault-Tolerant Pseudo-PID Sliding-Mode Control for High-Speed Train With Integral Quadratic Constraints and Actuator Saturation,
ITS(22), No. 12, December 2021, pp. 7421-7431.
IEEE DOI 2112
Actuators, Adaptive systems, Fault tolerance, Fault tolerant systems, Adaptation models, Resistance, high-speed train (HST) BibRef

Zhou, P.[Ping], Chen, L.[Lefang], Dai, X.[Xuewu], Li, B.[Baoxu], Chai, T.Y.[Tian-You],
Intelligent Prediction of Train Delay Changes and Propagation Using RVFLNs With Improved Transfer Learning and Ensemble Learning,
ITS(22), No. 12, December 2021, pp. 7432-7444.
IEEE DOI 2112
Delays, Rail transportation, Predictive models, Data models, Dispatching, Stacking, Prediction algorithms, Train delays, RVFLNs BibRef

Yuan, Z.M.[Zhi-Ming], Yan, L.[Lu], Gao, Y.[Ying], Zhang, T.[Tao], Gao, S.[Shigen],
Virtual Parameter Learning-Based Adaptive Control for Protective Automatic Train Operation,
ITS(22), No. 12, December 2021, pp. 7943-7954.
IEEE DOI 2112
Rail transportation, Adaptive control, Resistance, Mathematical model, Target tracking, Real-time systems, learning based adaptive control BibRef

Albrecht, A.[Amie], Howlett, P.[Phil], Pudney, P.[Peter],
Optimal Driving Strategies for Two Successive Trains on Level Track With Safe Separation,
ITS(23), No. 1, January 2022, pp. 280-295.
IEEE DOI 2201
Australia, Schedules, Indexes, Standards, Time factors, Fuels, Intelligent transportation systems, Train control, optimal driving strategies BibRef

Leng, K.J.[Kai-Jun], Li, S.H.[Shang-Hong],
Distribution Path Optimization for Intelligent Logistics Vehicles of Urban Rail Transportation Using VRP Optimization Model,
ITS(23), No. 2, February 2022, pp. 1661-1669.
IEEE DOI 2202
Logistics, Optimization, Transportation, Rail transportation, Rails, Mathematical model, Routing, Vehicle routing problem, immune algorithm particle swarm optimization (IAPSO) BibRef

Rao, Y.[Yu], Feng, X.Y.[Xiao-Yun], Wang, Q.Y.[Qing-Yuan], Sun, P.F.[Peng-Fei], Xiao, Z.[Zhuang], Chen, H.H.[Hong-Hui],
Energy-efficient control of a train considering multi-trains power flow,
IET-ITS(16), No. 3, 2022, pp. 380-393.
DOI Link 2202
BibRef

Rao, Y.[Yu], Sun, P.F.[Peng-Fei], Wang, Q.Y.[Qing-Yuan], Feng, X.Y.[Xiao-Yun], Wang, C.[Chuanru], Wei, M.[Mi],
Energy-efficient train control considering the traction system efficiency,
IET-ITS(16), No. 11, 2022, pp. 1633-1647.
DOI Link 2210
BibRef

Wen, T.[Tao], Xie, G.[Guo], Cao, Y.[Yuan], Cai, B.[Baigen],
A DNN-Based Channel Model for Network Planning in Train Control Systems,
ITS(23), No. 3, March 2022, pp. 2392-2399.
IEEE DOI 2203
Wireless communication, Control systems, Optimization, Planning, Channel models, Probability, Power system reliability, DNN BibRef

Deng, L.[Lianbo], Jing, E.[Enwei], Xu, J.[Jing], Chen, C.[Chen],
The accumulation cost of relaxed fixed time accumulation mode,
IET-ITS(16), No. 4, 2022, pp. 445-458.
DOI Link 2203
BibRef

Rao, Y.[Yu], Sun, P.F.[Peng-Fei], Wang, Q.Y.[Qing-Yuan], Bai, B.[Baoxue], Feng, X.Y.[Xiao-Yun],
Optimal running time supplement for the energy-efficient train control considering the section running time constraint,
IET-ITS(16), No. 5, 2022, pp. 661-674.
DOI Link 2204
BibRef

Cii, S.[Stefano], Tomasini, G.[Gisella], Bacci, M.L.[Maria Laura], Tarsitano, D.[Davide],
Solar Wireless Sensor Nodes for Condition Monitoring of Freight Trains,
ITS(23), No. 5, May 2022, pp. 3995-4007.
IEEE DOI 2205
Wireless sensor networks, Wireless communication, Monitoring, Batteries, Temperature sensors, Temperature measurement, Rails, on-field tests BibRef

Wang, J.X.[Jia-Xi], Zhao, Y.[Yinan], Gronalt, M.[Manfred], Lin, B.[Boliang], Wu, J.P.[Jian-Ping],
Synchronized Optimization for Service Scheduling, Train Parking and Routing at High-Speed Rail Maintenance Depot,
ITS(23), No. 5, May 2022, pp. 4525-4540.
IEEE DOI 2205
Routing, Computational modeling, Rail transportation, Tracking, Maintenance engineering, Cleaning, Optimization, Maintenance depot, integer linear programming BibRef

Zhong, W.F.[Wei-Feng], Li, S.[Shukai], Xu, H.Z.[Hong-Ze], Zhang, W.J.[Wen-Jing],
On-Line Train Speed Profile Generation of High-Speed Railway With Energy-Saving: A Model Predictive Control Method,
ITS(23), No. 5, May 2022, pp. 4063-4074.
IEEE DOI 2205
Rail transportation, Optimal control, Heuristic algorithms, Genetic algorithms, Resistance, Real-time systems, Delays, pseudospectral method BibRef

Wei, S.G.[Shang-Guan], Luo, R.[Rui], Song, H.Y.[Hong-Yu], Sun, J.[Jing],
High-Speed Train Platoon Dynamic Interval Optimization Based on Resilience Adjustment Strategy,
ITS(23), No. 5, May 2022, pp. 4402-4414.
IEEE DOI 2205
Resilience, Optimization, Safety, Rail transportation, Trajectory, Biological system modeling, Rails, High-speed train, multi-objective optimization BibRef

Wang, Z.Y.[Zhang-Yu], Yu, G.Z.[Gui-Zhen], Zhou, B.[Bin], Wang, P.C.[Peng-Cheng], Wu, X.[Xinkai],
A Train Positioning Method Based-On Vision and Millimeter-Wave Radar Data Fusion,
ITS(23), No. 5, May 2022, pp. 4603-4613.
IEEE DOI 2205
Feature extraction, Rail transportation, Millimeter wave radar, Databases, Sensor fusion, Radar tracking, millimeter-wave radar BibRef

Vujanic, R.[Robin], Hill, A.J.[Andrew J.],
Computationally Efficient Dynamic Traffic Optimization of Railway Systems,
ITS(23), No. 5, May 2022, pp. 4706-4719.
IEEE DOI 2205
Optimization, Rail transportation, Computational modeling, System recovery, Schedules, Numerical models, Robots, railway systems BibRef

Bai, W.Q.[Wei-Qi], Dong, H.R.[Hai-Rong], Zhang, Z.X.[Zi-Xuan], Li, Y.D.[Yi-Dong],
Coordinated Time-Varying Low Gain Feedback Control of High-Speed Trains Under a Delayed Communication Network,
ITS(23), No. 5, May 2022, pp. 4331-4341.
IEEE DOI 2205
Delays, Resistance, Communication networks, Feedback control, Time-varying systems, Servomotors, Safety, High-speed train, low gain feedback BibRef

Arboleya, P.[Pablo], Mayet, C.[Clément], Bouscayrol, A.[Alain], Mohamed, B.[Bassam], Delarue, P.[Philippe], El-Sayed, I.[Islam],
Electrical Railway Dynamical Versus Static Models for Infrastructure Planning and Operation,
ITS(23), No. 6, June 2022, pp. 5514-5525.
IEEE DOI 2206
Computational modeling, Rail transportation, Substations, Voltage control, Analytical models, Estimation, dc traction networks BibRef

Ju, Y.[Yanni], Yuan, H.H.[Hai-Hua], Li, Z.[Zongping], Gan, M.[Mi], Chen, Y.F.[Yu-Fan],
Multilayer structures and resilience evaluation for multimode regional rail transit system,
IET-ITS(16), No. 7, 2022, pp. 843-859.
DOI Link 2206
BibRef

Cai, X.[Xiao], Shi, K.[Kaibo], Zhong, S.M.[Shou-Ming], Pang, X.R.[Xuan-Rong],
Dissipative Sampled-Data Control for High-Speed Train Systems With Quantized Measurements,
ITS(23), No. 6, June 2022, pp. 5314-5325.
IEEE DOI 2206
Stability criteria, Asymptotic stability, Mathematical model, Force, Delays, Reliability, Adaptive control, high-speed train systems BibRef

Wang, K.M.[Ke-Ming], Wang, X.[Xia], Wang, Z.[Zheng], Wu, G.F.[Guan-Feng], Xu, Y.[Yang],
Logical consistency verification of state sensing in safety-critical decision: A case study of train routing selection,
IET-ITS(16), No. 8, 2022, pp. 1042-1057.
DOI Link 2207
BibRef

Sheng, Z.[Zhao], Wei, S.G.[Shang-Guan], Cai, B.G.[Bai-Gen], Song, H.Y.[Hong-Yu],
Energy-optimal study integrated speed trajectories, timetable and the layout of neutral sections for high-speed railway,
IET-ITS(16), No. 8, 2022, pp. 1026-1041.
DOI Link 2207
BibRef

Ying, C.S.[Cheng-Shuo], Chow, A.H.F.[Andy H. F.], Wang, Y.H.[Yi-Hui], Chin, K.S.[Kwai-Sang],
Adaptive Metro Service Schedule and Train Composition With a Proximal Policy Optimization Approach Based on Deep Reinforcement Learning,
ITS(23), No. 7, July 2022, pp. 6895-6906.
IEEE DOI 2207
Schedules, Scheduling, Dynamic scheduling, Training, Urban areas, Reinforcement learning, Processor scheduling, proximal policy optimization BibRef

Wu, D.[Daohua], Lu, D.[Debiao], Tang, T.[Tao],
Qualitative and Quantitative Safety Evaluation of Train Control Systems (CTCS) With Stochastic Colored Petri Nets,
ITS(23), No. 8, August 2022, pp. 10223-10238.
IEEE DOI 2208
Control systems, Analytical models, Unified modeling language, Petri nets, Numerical models, Data models, Rail transportation, CTCS, Coloured Petri Nets BibRef

Ning, L.B.[Ling-Bin], Zhou, M.[Min], Hou, Z.[Zhuopu], Goverde, R.M.P.[Rob M.P.], Wang, F.Y.[Fei-Yue], Dong, H.R.[Hai-Rong],
Deep Deterministic Policy Gradient for High-Speed Train Trajectory Optimization,
ITS(23), No. 8, August 2022, pp. 11562-11574.
IEEE DOI 2208
Rail transportation, Training, Heuristic algorithms, Resistance, Optimal control, Trajectory optimization, Switches, energy efficiency BibRef

Luo, J.C.[Jian-Chao], Zhou, M.C.[Meng-Chu], Wang, J.Q.[Jun-Qiang],
A Place-Timed Petri Net-Based Method to Avoid Deadlock and Conflict in Railway Networks,
ITS(23), No. 8, August 2022, pp. 10763-10772.
IEEE DOI 2208
Rail transportation, System recovery, Sensors, Safety, Petri nets, Layout, Schedules, Railway network, Petri net (PN), safety BibRef

Li, Z.X.[Zhen-Xuan], Yin, C.K.[Chen-Kun], Ji, H.H.[Hong-Hai], Hou, Z.S.[Zhong-Sheng],
Constrained Spatial Adaptive Iterative Learning Control for Trajectory Tracking of High Speed Train,
ITS(23), No. 8, August 2022, pp. 11720-11728.
IEEE DOI 2208
Resistance, Trajectory, Convergence, Adaptation models, Iterative learning control, Aerodynamics, Uncertainty, automatic train control (ATC) BibRef

Xu, K.[Kai], Tu, Y.C.[Yong-Chao], Xu, W.X.[Wen-Xuan], Wu, S.[Shixun],
Intelligent train operation based on deep learning from excellent driver manipulation patterns,
IET-ITS(16), No. 9, 2022, pp. 1177-1192.
DOI Link 2208
BibRef

Zhang, B.J.[Bing-Jie], Huang, S.[Shize], Zhang, L.[Lei], Liu, X.W.[Xiao-Wen], Song, G.Q.[Guan-Qun], Qin, J.Z.[Jin-Zhe], Li, M.[Man],
Method of railway shunting operation sheet information extraction guided by table header,
IET-ITS(16), No. 10, 2022, pp. 1391-1403.
DOI Link 2209
BibRef

Bešinovic, N.[Nikola], de Donato, L.[Lorenzo], Flammini, F.[Francesco], Goverde, R.M.P.[Rob M. P.], Lin, Z.Y.[Zhi-Yuan], Liu, R.H.[Rong-Hui], Marrone, S.[Stefano], Nardone, R.[Roberto], Tang, T.L.[Tian-Li], Vittorini, V.[Valeria],
Artificial Intelligence in Railway Transport: Taxonomy, Regulations, and Applications,
ITS(23), No. 9, September 2022, pp. 14011-14024.
IEEE DOI 2209
Rail transportation, Artificial intelligence, Taxonomy, Rails, Maintenance engineering, Software, Safety, Artificial intelligence, predictive maintenance BibRef

Huang, P.[Ping], Spanninger, T.[Thomas], Corman, F.[Francesco],
Enhancing the Understanding of Train Delays With Delay Evolution Pattern Discovery: A Clustering and Bayesian Network Approach,
ITS(23), No. 9, September 2022, pp. 15367-15381.
IEEE DOI 2209
Delays, Predictive models, Markov processes, Data models, Bayes methods, Rail transportation, Clustering algorithms, Bayesian network BibRef

Wang, P.L.[Peng-Ling], Bešinovic, N.[Nikola], Goverde, R.M.P.[Rob M. P.], Corman, F.[Francesco],
Improving the Utilization of Regenerative Energy and Shaving Power Peaks by Railway Timetable Adjustment,
ITS(23), No. 9, September 2022, pp. 15742-15754.
IEEE DOI 2209
Rail transportation, Robustness, Synchronization, Optimization, Energy consumption, Delays, Planning, Railway timetabling, power peak shaving BibRef

Jing, Y.[Yun], Guo, S.[Siye], Chen, F.Q.[Fang-Qiu], Wang, X.[Xuan], Li, K.X.[Kai-Xuan],
Dynamic Differential Pricing of High-Speed Railway Based on Improved GBDT Train Classification and Bootstrap Time Node Determination,
ITS(23), No. 9, September 2022, pp. 16854-16866.
IEEE DOI 2209
Pricing, Rail transportation, Transportation, Markov processes, Machine learning algorithms, Heuristic algorithms, Markov stochastic process BibRef

Yang, S.P.[Song-Po], Liao, F.X.[Fei-Xiong], Wu, J.J.[Jian-Jun], Chen, Y.Y.[Yan-Yan],
An Efficient Train Timetable Scheduling Approach With Regenerative-Energy Supplementation Strategy Responding to Potential Power Interruptions,
ITS(23), No. 9, September 2022, pp. 14267-14282.
IEEE DOI 2209
Substations, Optimization, Reliability, Energy consumption, Safety, Heuristic algorithms, Genetic algorithms, multi-objective optimization BibRef

Ko, K.J.[Kyeong-Jun], Byun, I.[Ilmu], Ahn, W.[Woojin], Shin, W.[Wonjae],
High-Speed Train Positioning Using Deep Kalman Filter With 5G NR Signals,
ITS(23), No. 9, September 2022, pp. 15993-16004.
IEEE DOI 2209
Kalman filters, 5G mobile communication, Safety, Global navigation satellite system, Fading channels, OFDM, TDOA BibRef

Deleplanque, S.[Samuel], Hosteins, P.[Pierre], Pellegrini, P.[Paola], Rodriguez, J.[Joaquin],
Train management in freight shunting yards: Formalisation and literature review,
IET-ITS(16), No. 10, 2022, pp. 1286-1305.
DOI Link 2209
BibRef

Wang, Q.[Qian], Jin, S.[Shangtai], Hou, Z.S.[Zhong-Sheng],
Data-Driven Event-Triggered Cooperative Control for Multiple Subway Trains With Switching Topologies,
ITS(23), No. 9, September 2022, pp. 14702-14711.
IEEE DOI 2209
Topology, Switches, Public transportation, Control systems, Resistance, Data models, Aerodynamics, multiple subway trains BibRef

Liu, H.[Hongen], Yang, L.J.[Luo-Jun], Yang, H.[Hui],
Cooperative Optimal Control of the Following Operation of High-Speed Trains,
ITS(23), No. 10, October 2022, pp. 17744-17755.
IEEE DOI 2210
Optimization, Safety, Rail transportation, Optimal control, Couplings, Task analysis, Force, High-speed train, consensus stability BibRef

Gao, S.[Shigen], Li, M.J.[Ming-Jun], Zheng, Y.[Yue], Zhao, N.[Ning], Dong, H.R.[Hai-Rong],
Fuzzy Adaptive Protective Control for High-Speed Trains: An Outstretched Error Feedback Approach,
ITS(23), No. 10, October 2022, pp. 17966-17975.
IEEE DOI 2210
Rail transportation, Resistance, Aerodynamics, Safety, Nonlinear systems, Rails, Cruise control, High-speed train control, outstretched error feedback BibRef

Choi, J.S.[Jun-Sung], Marojevic, V.[Vuk], Dietrich, C.B.[Carl B.], Ahn, S.[Seungyoung],
DSRC-Enabled Train Safety Communication System at Unmanned Crossings,
ITS(23), No. 10, October 2022, pp. 18210-18223.
IEEE DOI 2210
Safety, Communication systems, Receivers, Vehicles, Long Term Evolution, Antenna measurements, Alarm systems, train-to-vehicle (T2V) communication BibRef

Cao, Y.[Yuan], Zhang, Z.X.[Zi-Xuan], Cheng, F.L.[Fang-Lin], Su, S.[Shuai],
Trajectory Optimization for High-Speed Trains via a Mixed Integer Linear Programming Approach,
ITS(23), No. 10, October 2022, pp. 17666-17676.
IEEE DOI 2210
Rail transportation, Control systems, Optimization, Mathematical models, Switches, Trajectory optimization, high-speed railway BibRef

Li, Z.J.[Zheng-Jiao], Cai, B.[Baigen], Liu, J.[Jiang], Lu, D.[Debiao],
Modelling and performance analysis of Balise under dynamic energy harvesting in high-speed railway,
IET-ITS(16), No. 11, 2022, pp. 1504-1520.
DOI Link 2210
BibRef

Ding, K.[Kui], Zhu, Q.[Quanxin], Yang, X.T.[Xue-Tao],
Intermittent Estimator-Based Mixed Passive and H8 Control for High-Speed Train With Actuator Stochastic Fault,
Cyber(52), No. 11, November 2022, pp. 11624-11638.
IEEE DOI 2211
Actuators, Switches, Safety, Resistance, Lyapunov methods, Stability criteria, Packet loss, Actuator stochastic fault, sensor channel incomplete availability BibRef

Yu, W.[Wei], Huang, D.Q.[De-Qing], Wang, Q.Y.[Qing-Yuan], Feng, X.Y.[Xiao-Yun],
Nonuniform Sampling Control for Multibody High-Speed Train Systems With Quantization Mechanisms via Stochastic Faded Channels,
ITS(23), No. 11, November 2022, pp. 20965-20977.
IEEE DOI 2212
Fading channels, Quantization (signal), Control systems, Stochastic processes, Force, Wireless communication, Safety, fading measurements BibRef

Wang, X.[Xi], Su, S.[Shuai], Cao, Y.[Yuan], Wang, X.L.[Xiao-Liang],
Robust Control for Dynamic Train Regulation in Fully Automatic Operation System Under Uncertain Wireless Transmissions,
ITS(23), No. 11, November 2022, pp. 20721-20734.
IEEE DOI 2212
Regulation, Wireless communication, Delays, Schedules, Uncertainty, Safety, Rails, Urban transit loop line, automatic train regulation, uncertain dropout probability BibRef

Chen, Q.J.[Qi-Jin], Zhou, Y.K.[Yu-Kun], Fang, B.[Bole], Zhang, Q.[Quan], Niu, X.J.[Xiao-Ji],
Experimental Study on the Potential of Vehicle's Attitude Response to Railway Track Irregularity in Precise Train Localization,
ITS(23), No. 11, November 2022, pp. 20452-20463.
IEEE DOI 2212
Location awareness, Position measurement, Rail transportation, Radar tracking, Rails, Wavelength measurement, Noise measurement, multisensory train positioning system BibRef

Chen, Y.[Yong], Huang, D.Q.[De-Qing], Xu, C.[Chao], Dong, H.R.[Hai-Rong],
Iterative Learning Tracking Control of High-Speed Trains With Nonlinearly Parameterized Uncertainties and Multiple Time-Varying Delays,
ITS(23), No. 11, November 2022, pp. 20476-20488.
IEEE DOI 2212
Delays, Aerodynamics, Automobiles, Iterative methods, Uncertainty, Resistance, Rail transportation, High-speed trains, nonlinearly parameterized uncertainties BibRef

Shihui, J.[Jiang], Dong, S.[Shen], Tianbo, Z.[Zhang], Hong-Ze, X.[Xu],
Nonlinear Robust Composite Levitation Control for High-Speed EMS Trains With Input Saturation and Track Irregularities,
ITS(23), No. 11, November 2022, pp. 20323-20336.
IEEE DOI 2212
Magnetic levitation vehicles, Air gaps, Disturbance observers, Data models, Atmospheric modeling, Structural beams, Aerodynamics, finite-time control BibRef

Gao, B.[Bing], Bu, B.[Bing], Wang, X.X.[Xiao-Xuan],
A Comprehensive Resilient Control Strategy for CBTC Systems Through Train-to-Train Communications Under Malicious Attacks,
ITS(23), No. 11, November 2022, pp. 21015-21033.
IEEE DOI 2212
Observers, Rails, Control systems, Wireless communication, Topology, Predictive models, Intelligent transportation systems, distributed leader observer BibRef

Wang, Q.[Qian], Jin, S.[Shangtai], Hou, Z.S.[Zhong-Sheng],
Compensation-Based Cooperative MFAILC for Multiple Subway Trains Under Asynchronous Data Dropouts,
ITS(23), No. 12, December 2022, pp. 23750-23760.
IEEE DOI 2212
Public transportation, Data models, Resistance, Iterative methods, Control systems, Iterative learning control, Urban areas, cooperative control BibRef

Song, Q.[Qi], Ge, M.[Meng],
Finite-Time Control of High-Speed Train With Guaranteed Steady-State and Transient Performance,
ITS(23), No. 12, December 2022, pp. 23761-23770.
IEEE DOI 2212
Transient analysis, Steady-state, Control systems, Uncertainty, Aerodynamics, Stability criteria, Robustness, Finite-time control, fractional calculus BibRef

Xu, J.P.[Jian-Peng], Ai, B.[Bo], Chen, L.Y.[Liang-Yu], Cui, Y.P.[Ya-Ping], Wang, N.[Ning],
Deep Reinforcement Learning for Computation and Communication Resource Allocation in Multiaccess MEC Assisted Railway IoT Networks,
ITS(23), No. 12, December 2022, pp. 23797-23808.
IEEE DOI 2212
Resource management, Task analysis, Delays, Rail transportation, Computational modeling, Computational efficiency, Optimization, total computational cost BibRef

Chen, J.[Jinqu], Liu, J.[Jie], Du, B.[Bo], Peng, Q.Y.[Qi-Yuan], Yin, Y.[Yong],
Resilience Assessment of an Urban Rail Transit Network Under Short-Term Operational Disturbances,
ITS(23), No. 12, December 2022, pp. 24841-24853.
IEEE DOI 2212
Resilience, Network topology, Topology, Rails, Mathematical models, Measurement, Computational modeling, Urban rail transit, time-dependent performance indicator BibRef

Huang, D.Q.[De-Qing], Yi, S.[Sha], Li, X.[Xuefang],
Accurate Parking Control for Urban Rail Trains via Robust Adaptive Backstepping Approach,
ITS(23), No. 11, November 2022, pp. 21790-21798.
IEEE DOI 2212
Resistance, Rails, Brakes, Adaptive systems, Adaptation models, Safety, Control systems, Automatic train operation, precise parking, braking system BibRef

Yao, X.M.[Xiu-Ming], Li, S.H.[Shao-Hua], Li, X.F.[Xiao-Feng],
Composite Adaptive Anti-Disturbance Fault Tolerant Control of High-Speed Trains With Multiple Disturbances,
ITS(23), No. 11, November 2022, pp. 21799-21809.
IEEE DOI 2212
Force, Resistance, Actuators, Fault tolerant systems, Fault tolerant control, Fault tolerance, Markov processes, multiple disturbances BibRef

Ragala, Z.[Zaynabe], Retbi, A.[Asmaa], Bennani, S.[Samir],
MTTR Prediction of railway rolling stock using regression algorithms,
ISCV22(1-6)
IEEE DOI 2208
Rails, Knowledge based systems, Maintenance engineering, Predictive models, Prediction algorithms, Rail transportation, Lasso Regression BibRef

Papp, A.[Adam], Wiesmeyr, C.[Christoph], Litzenberger, M.[Martin], Garn, H.[Heinrich], Kropatsch, W.[Walter],
Train Detection and Tracking in Optical Time Domain Reflectometry (OTDR) Signals,
GCPR16(320-331).
Springer DOI 1611
BibRef

Zhang, Y.Z., Yan, Y.S., Hu, Z.A.,
Optimization model of number of scheduled freight train formation cars,
IASP11(400-404).
IEEE DOI 1112
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Air Traffic Controls, Runways, Aircraft .

Last update:Nov 30, 2023 at 15:51:27