Santos, A.J.D.,
Soares, A.R.,
de Almeida Redondo, F.M.,
Carvalho, N.B.,
Tracking Trains via Radio Frequency Systems,
ITS(6), No. 2, June 2005, pp. 244-258.
IEEE Abstract.
0506
BibRef
Khan, M.B.,
Zhou, X.,
Stochastic Optimization Model and Solution Algorithm for Robust
Double-Track Train-Timetabling Problem,
ITS(11), No. 1, March 2010, pp. 81-89.
IEEE DOI
1003
BibRef
Shafiullah, G.M.,
Ali, A.B.M.S.,
Thompson, A.,
Wolfs, P.J.,
Predicting Vertical Acceleration of Railway Wagons Using Regression
Algorithms,
ITS(11), No. 2, June 2010, pp. 290-299.
IEEE DOI
1007
BibRef
Song, Q.,
Song, Y.,
Tang, T.,
Ning, B.,
Computationally Inexpensive Tracking Control of High-Speed Trains With
Traction/Braking Saturation,
ITS(12), No. 4, December 2011, pp. 1116-1125.
IEEE DOI
1112
BibRef
Shafia, M.A.,
Pourseyed Aghaee, M.,
Sadjadi, S.J.,
Jamili, A.,
Robust Train Timetabling Problem:
Mathematical Model and Branch and Bound Algorithm,
ITS(13), No. 1, March 2012, pp. 307-317.
IEEE DOI
1203
BibRef
Su, S.[Shuai],
Li, X.[Xiang],
Tang, T.[Tao],
Gao, Z.Y.[Zi-You],
A Subway Train Timetable Optimization Approach Based on
Energy-Efficient Operation Strategy,
ITS(14), No. 2, 2013, pp. 883-893.
IEEE DOI
1307
automatic train operation system
BibRef
Caballini, C.,
Pasquale, C.,
Sacone, S.,
Siri, S.,
An Event-Triggered Receding-Horizon Scheme for Planning Rail
Operations in Maritime Terminals,
ITS(15), No. 1, February 2014, pp. 365-375.
IEEE DOI
1403
discrete time systems
BibRef
Albrecht, T.,
Binder, A.,
Gassel, C.,
Applications of real-time speed control in rail-bound public
transportation systems,
IET-ITS(7), No. 3, September 2013, pp. 305-314.
DOI Link
1402
energy consumption
BibRef
Wang, Y.B.[Yi-Bing],
Guo, J.Q.[Jing-Qiu],
Currie, G.,
Ceder, A.,
Dong, W.[Wei],
Pender, B.,
Bus Bridging Disruption in Rail Services With Frustrated and
Impatient Passengers,
ITS(15), No. 5, October 2014, pp. 2014-2023.
IEEE DOI
1410
Monte Carlo methods
BibRef
Bai, Y.,
Ho, T.K.,
Mao, B.,
Ding, Y.,
Chen, S.,
Energy-Efficient Locomotive Operation for Chinese Mainline Railways
by Fuzzy Predictive Control,
ITS(15), No. 3, June 2014, pp. 938-948.
IEEE DOI
1407
Energy consumption
BibRef
Zhu, L.[Li],
Yu, F.R.,
Ning, B.[Bin],
Tang, T.[Tao],
Handoff Performance Improvements in MIMO-Enabled Communication-Based
Train Control Systems,
ITS(13), No. 2, June 2012, pp. 582-593.
IEEE DOI
1206
BibRef
Sun, W.,
Yu, F.R.,
Tang, T.,
Bu, B.,
Energy-Efficient Communication-Based Train Control Systems With
Packet Delay and Loss,
ITS(17), No. 2, February 2016, pp. 452-468.
IEEE DOI
1602
Delays
BibRef
Wang, X.,
Liu, L.,
Tang, T.,
Sun, W.,
Enhancing Communication-Based Train Control Systems Through
Train-to-Train Communications,
ITS(20), No. 4, April 2019, pp. 1544-1561.
IEEE DOI
1904
Rails, Resilience, Wireless communication, Delays,
Quality of service, Rail transportation, Control systems, CBTC,
cognitive control
BibRef
Gao, S.,
Dong, H.,
Chen, Y.,
Ning, B.,
Chen, G.,
Yang, X.,
Approximation-Based Robust Adaptive Automatic Train Control:
An Approach for Actuator Saturation,
ITS(14), No. 4, 2013, pp. 1733-1742.
IEEE DOI
1312
Actuators
BibRef
Wang, H.,
Yu, F.R.,
Zhu, L.,
Tang, T.,
Ning, B.,
A Cognitive Control Approach to Communication-Based Train Control
Systems,
ITS(16), No. 4, August 2015, pp. 1676-1689.
IEEE DOI
1508
Channel models
BibRef
Sun, W.,
Yu, F.R.,
Tang, T.,
You, S.,
A Cognitive Control Method for Cost-Efficient CBTC Systems With Smart
Grids,
ITS(18), No. 3, March 2017, pp. 568-582.
IEEE DOI
1703
Control systems
BibRef
Bu, B.,
Yu, F.R.,
Tang, T.,
Performance Improved Methods for Communication-Based Train Control
Systems With Random Packet Drops,
ITS(15), No. 3, June 2014, pp. 1179-1192.
IEEE DOI
1407
Computers
BibRef
Zhu, L.,
Yu, F.R.,
Ning, B.,
Tang, T.,
Design and Performance Enhancements in Communication-Based Train
Control Systems With Coordinated Multipoint Transmission and
Reception,
ITS(15), No. 3, June 2014, pp. 1258-1272.
IEEE DOI
1407
Rail transportation
BibRef
Gu, Q.,
Tang, T.,
Cao, F.,
Song, Y.,
Energy-Efficient Train Operation in Urban Rail Transit Using
Real-Time Traffic Information,
ITS(15), No. 3, June 2014, pp. 1216-1233.
IEEE DOI
1407
Acceleration
BibRef
Yang, X.,
Li, X.,
Ning, B.,
Tang, T.,
A Survey on Energy-Efficient Train Operation for Urban Rail Transit,
ITS(17), No. 1, January 2016, pp. 2-13.
IEEE DOI
1601
Acceleration
BibRef
Yang, X.,
Chen, A.,
Ning, B.,
Tang, T.,
Measuring Route Diversity for Urban Rail Transit Networks:
A Case Study of the Beijing Metro Network,
ITS(18), No. 2, February 2017, pp. 259-268.
IEEE DOI
1702
Algorithm design and analysis
BibRef
Wang, Y.,
Ning, B.,
Tang, T.,
van den Boom, T.J.J.,
de Schutter, B.,
Efficient Real-Time Train Scheduling for Urban Rail Transit Systems
Using Iterative Convex Programming,
ITS(16), No. 6, December 2015, pp. 3337-3352.
IEEE DOI
1512
Energy consumption
BibRef
Yin, J.T.[Jia-Teng],
Chen, D.W.[De-Wang],
Li, L.X.[Ling-Xi],
Intelligent Train Operation Algorithms for Subway by Expert System
and Reinforcement Learning,
ITS(15), No. 6, December 2014, pp. 2561-2571.
IEEE DOI
1412
control engineering computing
BibRef
Zheng, W.[Wei],
Liang, C.[Ci],
Wang, R.[Rui],
Kong, W.J.[Wei-Jie],
Automated Test Approach Based on All Paths Covered Optimal Algorithm
and Sequence Priority Selected Algorithm,
ITS(15), No. 6, December 2014, pp. 2551-2560.
IEEE DOI
1412
Petri nets. Rail system tests.
BibRef
Zheng, Y.,
Zhang, M.,
Ling, H.,
Chen, S.,
Emergency Railway Transportation Planning Using a Hyper-Heuristic
Approach,
ITS(16), No. 1, February 2015, pp. 321-329.
IEEE DOI
1502
IP networks
BibRef
Li, K.,
Yao, X.,
Chen, D.,
Yuan, L.,
Zhou, D.,
HAZOP Study on the CTCS-3 Onboard System,
ITS(16), No. 1, February 2015, pp. 162-171.
IEEE DOI
1502
Hazards
BibRef
Katsuta, K.,
Cost effective railway signalling by wireless communication among
onboard controllers and switch controllers,
IET-ITS(9), No. 1, 2015, pp. 67-74.
DOI Link
1503
locomotives
BibRef
Wen, S.H.[Shu-Huan],
Yang, J.W.[Jing-Wei],
Rad, A.B.,
Hao, P.C.[Peng-Cheng],
Multi-model direct generalised predictive control for automatic train
operation system,
IET-ITS(9), No. 1, 2015, pp. 86-94.
DOI Link
1503
fuzzy set theory
BibRef
Lu, S.F.[Shao-Feng],
Weston, P.,
Hillmansen, S.,
Gooi, H.B.,
Roberts, C.,
Increasing the Regenerative Braking Energy for Railway Vehicles,
ITS(15), No. 6, December 2014, pp. 2506-2515.
IEEE DOI
1412
direct energy conversion
BibRef
Pilo, E.,
Mazumder, S.K.,
Gonzalez-Franco, I.,
Smart Electrical Infrastructure for AC-Fed Railways With Neutral
Zones,
ITS(16), No. 2, April 2015, pp. 642-652.
IEEE DOI
1504
Frequency selective surfaces
BibRef
Su, S.,
Tang, T.,
Roberts, C.,
A Cooperative Train Control Model for Energy Saving,
ITS(16), No. 2, April 2015, pp. 622-631.
IEEE DOI
1504
Acceleration
BibRef
He, R.,
Ai, B.,
Zhong, Z.,
Molisch, A.F.,
Chen, R.,
Yang, Y.,
A Measurement-Based Stochastic Model for High-Speed Railway Channels,
ITS(16), No. 3, June 2015, pp. 1120-1135.
IEEE DOI
1506
Antenna measurements
BibRef
Zhang, B.,
Zhong, Z.,
He, R.,
Dahman, G.,
Ding, J.,
Lin, S.,
Ai, B.,
Yang, M.,
Measurement-Based Markov Modeling for Multi-Link Channels in Railway
Communication Systems,
ITS(20), No. 3, March 2019, pp. 985-999.
IEEE DOI
1903
Antenna measurements, Channel models, Correlation,
Markov processes, Fading channels, Railway communication,
railway communication
BibRef
He, R.,
Zhong, Z.,
Ai, B.,
Guan, K.,
Reducing the Cost of High-Speed Railway Communications: From the
Propagation Channel View,
ITS(16), No. 4, August 2015, pp. 2050-2060.
IEEE DOI
1508
Control systems
BibRef
Corman, F.,
Meng, L.,
A Review of Online Dynamic Models and Algorithms for Railway Traffic
Management,
ITS(16), No. 3, June 2015, pp. 1274-1284.
IEEE DOI
1506
Delays
BibRef
Sun, X.,
Zhang, S.,
Dong, H.,
Chen, Y.,
Zhu, H.,
Optimization of Metro Train Schedules With a Dwell Time Model Using
the Lagrangian Duality Theory,
ITS(16), No. 3, June 2015, pp. 1285-1293.
IEEE DOI
1506
Cost function
BibRef
Ning, B.,
Xun, J.,
Gao, S.,
Zhang, L.,
An Integrated Control Model for Headway Regulation and Energy Saving
in Urban Rail Transit,
ITS(16), No. 3, June 2015, pp. 1469-1478.
IEEE DOI
1506
Acceleration
BibRef
Zhang, L.,
Zhuan, X.,
Development of an Optimal Operation Approach in the MPC Framework for
Heavy-Haul Trains,
ITS(16), No. 3, June 2015, pp. 1391-1400.
IEEE DOI
1506
Cost function
BibRef
Coviello, N.,
Bruno, F.,
Energy performance in railway services:
A calculation methodology and the influence of operation parameters,
IET-ITS(9), No. 5, 2015, pp. 530-538.
DOI Link
1507
digital simulation
BibRef
Li, Z.,
He, Q.,
Prediction of Railcar Remaining Useful Life by Multiple Data Source
Fusion,
ITS(16), No. 4, August 2015, pp. 2226-2235.
IEEE DOI
1508
Axles
BibRef
Wei, S.[Shang_Guan],
Yan, X.H.[Xi-Hui],
Cai, B.G.[Bai-Gen],
Wang, J.[Jian],
Multiobjective Optimization for Train Speed Trajectory in CTCS
High-Speed Railway With Hybrid Evolutionary Algorithm,
ITS(16), No. 4, August 2015, pp. 2215-2225.
IEEE DOI
1508
Energy consumption
BibRef
Yan, X.H.[Xi-Hui],
Cai, B.G.[Bai-Gen],
Ning, B.[Bin],
Wei, S.[Shang_Guan],
Moving Horizon Optimization of Dynamic Trajectory Planning for
High-Speed Train Operation,
ITS(17), No. 5, May 2016, pp. 1258-1270.
IEEE DOI
1605
Energy consumption
BibRef
Chen, L.,
Roberts, C.,
Schmid, F.,
Stewart, E.,
Modeling and Solving Real-Time Train Rescheduling Problems in Railway
Bottleneck Sections,
ITS(16), No. 4, August 2015, pp. 1896-1904.
IEEE DOI
1508
Delays
BibRef
Fernandez-Rodriguez, A.,
Fernandez-Cardador, A.,
Cucala, A.P.,
Dominguez, M.,
Gonsalves, T.,
Design of Robust and Energy-Efficient ATO Speed Profiles of
Metropolitan Lines Considering Train Load Variations and Delays,
ITS(16), No. 4, August 2015, pp. 2061-2071.
IEEE DOI
1508
Delays
BibRef
Zhao, N.[Ning],
Roberts, C.,
Hillmansen, S.,
Nicholson, G.,
A Multiple Train Trajectory Optimization to Minimize Energy
Consumption and Delay,
ITS(16), No. 5, October 2015, pp. 2363-2372.
IEEE DOI
1511
ant colony optimisation
BibRef
Li, D.Y.[Dan-Yong],
Song, Y.D.[Yong-Duan],
Cai, W.C.[Wen-Chuan],
Neuro-Adaptive Fault-Tolerant Approach for Active Suspension Control
of High-Speed Trains,
ITS(16), No. 5, October 2015, pp. 2446-2456.
IEEE DOI
1511
adaptive control
BibRef
Cai, W.C.[Wen-Chuan],
Li, D.Y.[Dan-Yong],
Liu, B.,
Song, Y.D.[Yong-Duan],
Uniform Rolling-Wear-Based Robust Adaptive Control of High-Speed
Trains in the Presence of Actuator Differences,
ITS(17), No. 12, December 2016, pp. 3591-3601.
IEEE DOI
1612
Actuators
BibRef
Cai, W.C.[Wen-Chuan],
Li, D.Y.[Dan-Yong],
Song, Y.D.[Yong-Duan],
A Novel Approach for Active Adhesion Control of High-Speed Trains
Under Antiskid Constraints,
ITS(16), No. 6, December 2015, pp. 3213-3222.
IEEE DOI
1512
Control design
BibRef
Niu, H.M.[Hui-Min],
Tian, X.P.[Xiao-Peng],
Zhou, X.S.[Xue-Song],
Demand-Driven Train Schedule Synchronization for High-Speed Rail
Lines,
ITS(16), No. 5, October 2015, pp. 2642-2652.
IEEE DOI
1511
dynamic programming
BibRef
Yin, X.F.[Xue-Feng],
Cai, X.S.[Xue-Song],
Cheng, X.[Xiang],
Chen, J.J.[Jia-Jing],
Tian, M.[Meng],
Empirical Geometry-Based Random-Cluster Model for High-Speed-Train
Channels in UMTS Networks,
ITS(16), No. 5, October 2015, pp. 2850-2861.
IEEE DOI
1511
3G mobile communication
BibRef
Soler, M.,
Lopez, J.,
Mera Sanchez de Pedro, J.M.,
Maroto, J.,
Methodology for Multiobjective Optimization of the AC Railway Power
Supply System,
ITS(16), No. 5, October 2015, pp. 2531-2542.
IEEE DOI
1511
Pareto analysis
BibRef
Pellegrini, P.,
Marliere, G.,
Pesenti, R.,
Rodriguez, J.,
RECIFE-MILP: An Effective MILP-Based Heuristic for the Real-Time
Railway Traffic Management Problem,
ITS(16), No. 5, October 2015, pp. 2609-2619.
IEEE DOI
1511
integer programming
BibRef
Kim, K.,
Kong, S.,
Jeon, S.,
Slip and Slide Detection and Adaptive Information Sharing Algorithms
for High-Speed Train Navigation Systems,
ITS(16), No. 6, December 2015, pp. 3193-3203.
IEEE DOI
1512
Detection algorithms
BibRef
Zhao, Y.,
Ioannou, P.,
Positive Train Control With Dynamic Headway Based on an Active
Communication System,
ITS(16), No. 6, December 2015, pp. 3095-3103.
IEEE DOI
1512
Communication systems
BibRef
Allotta, B.,
d'Adamio, P.,
Marini, L.,
Meli, E.,
Pugi, L.,
Rindi, A.,
A New Strategy for Dynamic Weighing in Motion of Railway Vehicles,
ITS(16), No. 6, December 2015, pp. 3520-3533.
IEEE DOI
1512
Intelligent systems
BibRef
Fang, W.,
Yang, S.,
Yao, X.,
A Survey on Problem Models and Solution Approaches to Rescheduling in
Railway Networks,
ITS(16), No. 6, December 2015, pp. 2997-3016.
IEEE DOI
1512
Delays
BibRef
Lei, L.,
Lu, J.,
Jiang, Y.,
Shen, X.S.,
Li, Y.,
Zhong, Z.,
Lin, C.,
Stochastic Delay Analysis for Train Control Services in
Next-Generation High-Speed Railway Communications System,
ITS(17), No. 1, January 2016, pp. 48-64.
IEEE DOI
1601
Analytical models
BibRef
Karadimou, E.,
Armstrong, R.,
Test of rolling stock electromagnetic compatibility for cross-domain
interoperability,
IET-ITS(10), No. 1, 2016, pp. 10-16.
DOI Link
1602
electromagnetic compatibility
BibRef
Umiliacchi, S.,
Nicholson, G.,
Zhao, N.[Ning],
Schmid, F.,
Roberts, C.,
Delay management and energy consumption minimisation on a
single-track railway,
IET-ITS(10), No. 1, 2016, pp. 50-57.
DOI Link
1602
freight handling
BibRef
Hasegawa, D.,
Nicholson, G.,
Roberts, C.,
Schmid, F.,
Analysis of the robustness of terminal turnaround arrangements for
railways,
IET-ITS(10), No. 1, 2016, pp. 41-49.
DOI Link
1602
Monte Carlo methods
BibRef
Liu, B.,
Ghazel, M.,
Toguyeni, A.,
Model-Based Diagnosis of Multi-Track Level Crossing Plants,
ITS(17), No. 2, February 2016, pp. 546-556.
IEEE DOI
1602
Accidents
BibRef
Brown, D.E.,
Text Mining the Contributors to Rail Accidents,
ITS(17), No. 2, February 2016, pp. 346-355.
IEEE DOI
1602
Accidents
BibRef
Sadler, J.,
Griffin, D.,
Gilchrist, A.,
Austin, J.,
Kit, O.,
Heavisides, J.,
GeoSRM- Online geospatial safety risk model for the GB rail network,
IET-ITS(10), No. 1, 2016, pp. 17-24.
DOI Link
1602
Big Data
BibRef
Wang, P.,
Ma, L.,
Goverde, R.M.P.,
Wang, Q.,
Rescheduling Trains Using Petri Nets and Heuristic Search,
ITS(17), No. 3, March 2016, pp. 726-735.
IEEE DOI
1603
Color
BibRef
Gu, Q.,
Tang, T.,
Ma, F.,
Energy-Efficient Train Tracking Operation Based on Multiple
Optimization Models,
ITS(17), No. 3, March 2016, pp. 882-892.
IEEE DOI
1603
Delays
BibRef
Song, Y.,
Song, W.,
A Novel Dual Speed-Curve Optimization Based Approach for
Energy-Saving Operation of High-Speed Trains,
ITS(17), No. 6, June 2016, pp. 1564-1575.
IEEE DOI
1606
Acceleration
BibRef
Yang, H.,
Zhang, K.P.,
Liu, H.E.,
Online Regulation of High Speed Train Trajectory Control Based on T-S
Fuzzy Bilinear Model,
ITS(17), No. 6, June 2016, pp. 1496-1508.
IEEE DOI
1606
Adaptation models
BibRef
Wang, J.F.[Jun-Feng],
Li, Y.J.[Yuan-Jing],
Zhang, Y.[Yong],
Wang, J.,
Li, Y.,
Zhang, Y.,
Research on Parallel Control Mechanism and Its Implementation in ATP,
ITS(17), No. 6, June 2016, pp. 1652-1662.
IEEE DOI
1606
Train control.
BibRef
Yin, J.,
Chen, D.,
Yang, L.,
Tang, T.,
Ran, B.,
Efficient Real-Time Train Operation Algorithms With Uncertain
Passenger Demands,
ITS(17), No. 9, September 2016, pp. 2600-2612.
IEEE DOI
1609
Algorithm design and analysis
BibRef
Lejeune, A.,
Chevrier, R.,
Vandanjon, P.O.,
Rodriguez, J.,
Towards eco-aware timetabling: evolutionary approach and cascading
initialisation strategy for the bi-objective optimisation of train
running times,
IET-ITS(10), No. 7, 2016, pp. 483-494.
DOI Link
1609
Pareto optimisation
BibRef
Dong, H.,
Gao, S.,
Ning, B.,
Cooperative Control Synthesis and Stability Analysis of Multiple
Trains Under Moving Signaling Systems,
ITS(17), No. 10, October 2016, pp. 2730-2738.
IEEE DOI
1610
Aerodynamics
BibRef
Li, S.K.[Shu-Kai],
Yang, L.X.[Li-Xing],
Gao, Z.Y.[Zi-You],
Li, K.P.[Ke-Ping],
Optimal Guaranteed Cost Cruise Control for High-Speed Train Movement,
ITS(17), No. 10, October 2016, pp. 2879-2887.
IEEE DOI
1610
Aerodynamics
BibRef
Lu, S.,
Wang, M.Q.,
Weston, P.,
Chen, S.,
Yang, J.,
Partial Train Speed Trajectory Optimization Using Mixed-Integer
Linear Programming,
ITS(17), No. 10, October 2016, pp. 2911-2920.
IEEE DOI
1610
Acceleration
BibRef
Chen, Y.,
Dong, H.,
Lü, J.,
Sun, X.,
Guo, L.,
A Super-Twisting-Like Algorithm and Its Application to Train
Operation Control With Optimal Utilization of Adhesion Force,
ITS(17), No. 11, November 2016, pp. 3035-3044.
IEEE DOI
1609
Adhesives
BibRef
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 .