A review of train delay prediction approaches

Arshad, 2019, Train delay estimation in Indian railways by including weather factors through machine learning techniques, Recent Adv. Comput. Sci. Commun., 12 Arshad, 2021, Train delay estimation in Indian railways by including weather factors through machine learning techniques, Recent Adv. Comput. Sci. Commun., 14, 1300, 10.2174/2666255813666190912095739 Banerjee, 2019, Passenger demand forecasting in scheduled transportation, Eur. J. Oper. Res., 286, 797, 10.1016/j.ejor.2019.10.032 Bao, 2021, Prediction of train arrival delay using hybrid ELM-PSO approach, J. Adv. Transport., 2021 Barbour, 2018, Prediction of arrival times of freight traffic on US railroads using support vector regression, Transport. Res. C Emerg. Technol., 93, 211, 10.1016/j.trc.2018.05.019 Barta, 2012, Statistical modelling of delays in a rail freight transportation network, 1 Berger, 2011, Passenger flow-oriented train disposition, 6942 LNCS, 227 Berger, 2011, Stochastic delay prediction in large train networks Bešinović, 2020, Resilience in railway transport systems: a literature review and research agenda, Transport Rev., 40, 457, 10.1080/01441647.2020.1728419 Büker, 2012, Stochastic modelling of delay propagation in large networks, J. Rail Trans. Plann. Manag., 2, 34 Cacchiani, 2010, Scheduling extra freight trains on railway networks, Transp. Res. Part B Methodol., 44, 215, 10.1016/j.trb.2009.07.007 Cacchiani, 2014, An overview of recovery models and algorithms for real-time railway rescheduling, Transp. Res. Part B Methodol., 63, 15, 10.1016/j.trb.2014.01.009 Carey, 1994, Stochastic approximation to the effects of headways on knock-on delays of trains, Transport. Res. Part B, 28, 251, 10.1016/0191-2615(94)90001-9 Chen, 1990, Two moments estimation of the delay on single-track rail lines with scheduled traffic, Transport. Sci., 24, 261, 10.1287/trsc.24.4.261 Chen, 2021, Predicting weather-induced delays of high-speed rail and aviation in China, Transport Pol., 101, 1, 10.1016/j.tranpol.2020.11.008 Corman, 2018, Stochastic prediction of train delays in real-time using Bayesian networks, Transport. Res. C Emerg. Technol., 95, 599, 10.1016/j.trc.2018.08.003 D'Ariano, 2009, An advanced real-time train dispatching system for minimizing the propagation of delays in a dispatching area under severe disturbances, Network. Spatial Econ., 9, 63, 10.1007/s11067-008-9088-1 Davydov, 2017, Online train traffic adjustments: probabilistic modeling and estimating, Sci. Tech. Conf. Trans. Syst. Theor. Pract., 55–60 Davydov, 2016, Prediction of the train traffic in a transport corridor, Procedia Eng., 165, 1430, 10.1016/j.proeng.2016.11.875 Dekker, 2019, Predicting transitions across macroscopic states for railway systems, PLoS One, 14, 1, 10.1371/journal.pone.0217710 Gao, 2020, A data-driven two-stage prediction model for train primary-delay recovery time, Int. J. Software Eng. Knowl. Eng., 30, 921, 10.1142/S0218194020400124 Gaurav, 2018, Estimating train delays in a large rail network using a zero shot Markov model, 1221 Gestrelius, 2015, On the uniqueness of operation days and delivery commitment generation for train timetables Ghofrani, 2018, Recent applications of big data analytics in railway transportation systems: a survey, Transport. Res. C Emerg. Technol., 90, 226, 10.1016/j.trc.2018.03.010 Gorman, 2009, Statistical estimation of railroad congestion delay, Transport. Res. E Logist. Transport. Rev., 45, 446, 10.1016/j.tre.2008.08.004 Goverde, 2010, A delay propagation algorithm for large-scale railway traffic networks, Transport. Res. C Emerg. Technol., 18, 269, 10.1016/j.trc.2010.01.002 Goverde, 2000, TNV-prepare: analysis of Dutch railway operations based on train detection data, Adv. Trans., 50, 779 Goverde, 2011, Advanced monitoring and management information of railway operations, J. Rail Trans. Plann. Manag., 1, 69 Greenberg, 1988, Predicting dispatching delays on a low speed, single track railroad, Transport. Sci., 22, 31, 10.1287/trsc.22.1.31 Hallowell, 1996, Predicting on-time line-haul performance in scheduled railroad operations, Transport. Sci., 30, 364, 10.1287/trsc.30.4.364 Hansen, 2010, Online train delay recognition and running time prediction, 1783 Hauck, 2020, Data analytics in railway operations: using machine learning to predict train delays, 741 Higgins, 1998, Modeling train delays in urban networks, Transport. Sci., 32, 346, 10.1287/trsc.32.4.346 Huang, 2020, A Bayesian network model to predict the effects of interruptions on train operations, Transport. Res. C Emerg. Technol., 114, 338, 10.1016/j.trc.2020.02.021 Huang, 2020, Modeling train operation as sequences : a study of delay prediction with operation and weather data, Transport. Res. Part E, 141, 102022, 10.1016/j.tre.2020.102022 Huang, 2020, A hybrid model to improve the train running time prediction ability during high-speed railway disruptions, Saf. Sci., 122, 104510, 10.1016/j.ssci.2019.104510 Huisman, 2001, Running times on railway sections with heterogeneous train traffic, Transp. Res. Part B Methodol., 35, 271, 10.1016/S0191-2615(99)00051-X Janecek, 2010, LUKS. Integrated tool for analysing the performance of railway junctions and lines; LUKS. Integriertes Werkzeug zur Leistungsuntersuchung von Eisenbahnknoten und -strecken, ETR. Eisenbahntechnische Rundschau, 59 Jiang, 2019, Forecasting primary delay recovery of high-speed railway using multiple linear regression, supporting vector machine, artificial neural network, and random forest regression, Can. J. Civ. Eng., 46, 353, 10.1139/cjce-2017-0642 Jiang, 2019, Punctuality prediction: combined probability approach and random forest modelling with railway delay statistics in Sweden, 2019 IEEE Intell. Trans. Syst. Conf., ITSC, 2797, 10.1109/ITSC.2019.8916892 Jordan, 2015, Machine learning: trends, perspectives, and prospects, Science, 349, 255, 10.1126/science.aaa8415 Karlaftis, 2011, Statistical methods versus neural networks in transportation research: differences, similarities and some insights, Transport. Res. C Emerg. Technol., 19, 387, 10.1016/j.trc.2010.10.004 Kecman, 2012, Process mining of train describer event data and automatic conflict identification, Comput. Railw. XIII: Comput. Syst. Design Oper. Railw. Other Trans. Syst., 127, 227, 10.2495/CR120201 Kecman, 2015 Kecman, 2015, Predictive modelling of running and dwell times in railway traffic, Publ. Trans., 7, 295, 10.1007/s12469-015-0106-7 Kecman, 2015, Online data-driven adaptive prediction of train event times, IEEE Trans. Intell. Transport. Syst., 16, 465, 10.1109/TITS.2014.2347136 Keyhani, 2012, Reliability and delay distributions of train connections Kosolsombat, 2016, Arrival time prediction and train tracking analysis, 170 Lee, 2016, A delay root cause discovery and timetable adjustment model for enhancing the punctuality of railway services, Transport. Res. C Emerg. Technol., 73, 49, 10.1016/j.trc.2016.10.009 Lee, 2016, Beyond condition-monitoring : comparing diagnostic events with word sequence Kernel for train delay prediction, 1 Lemnian, 2014, Timing of train disposition: towards early passenger rerouting in case of delays Leng, 2020, The role of information availability to passengers in public transport disruptions: an agent-based simulation approach, Transport. Res. Pol. Pract., 133, 214, 10.1016/j.tra.2020.01.007 Lessan, 2019, A hybrid Bayesian network model for predicting delays in train operations, Comput. Ind. Eng., 127, 1214, 10.1016/j.cie.2018.03.017 Li, 2020, Near-term train delay prediction in the Dutch railways network, Int. J. Real. Ther., 1 Liebchen, 2021, The ring never relieves Liu, 2017, Prediction algorithms for train arrival time in urban rail transit, 1 Ma, 2016, Forecast of train delay propagation based on max-plus algebra theory, 661 Malavasi, 2001, Simulation of stochastic elements in railway systems using self-learning processes, Eur. J. Oper. Res., 131, 262, 10.1016/S0377-2217(00)00126-0 Marković, 2015, Analyzing passenger train arrival delays with support vector regression, Transport. Res. C Emerg. Technol., 56, 251, 10.1016/j.trc.2015.04.004 Martin, 2016, Predictive reasoning and machine learning for the enhancement of reliability in railway systems, Int. Conf. Reliab., Saf. Secur. Railw. Syst., 178–188 Meester, 2007, Stochastic delay propagation in railway networks and phase-type distributions, Transp. Res. Part B Methodol., 41, 218, 10.1016/j.trb.2006.02.007 Milinković, 2013, A fuzzy Petri net model to estimate train delays, Simulat. Model. Pract. Theor., 33, 144, 10.1016/j.simpat.2012.12.005 Mou, 2019, Predictive model of train delays in a railway system, 913 Murali, 2010, A delay estimation technique for single and double-track railroads, Transport. Res. E Logist. Transport. Rev., 46, 483, 10.1016/j.tre.2009.04.016 Nabian, 2019, Predicting near-term train schedule performance and delay using Bi-level random Forests, Transport. Res. Rec., 2673, 564, 10.1177/0361198119840339 Nair, 2019, An ensemble prediction model for train delays, Transport. Res. C Emerg. Technol., 104, 196, 10.1016/j.trc.2019.04.026 Nash, 2004, Railroad simulation using OpenTrack, WIT Trans. Built Environ., 74, 45 Oneto, 2018, Train delay prediction systems: a big data analytics perspective, Big Data Res., 11, 54, 10.1016/j.bdr.2017.05.002 Peters, 2005, Prediction of delays in public transportation using neural networks, 2, 92 Pongnumkul, 2014, Improving arrival time prediction of Thailand's passenger trains using historical travel times, 307 Pradhan, 2021, Simulating and analysing delay in Indian railways, IOP Conf. Ser. Mater. Sci. Eng., 1116, 10.1088/1757-899X/1116/1/012127 Radtke, 2004, Automated planning of timetables in large railway networks using a microscopic data basis and railway simulation techniques, WIT Trans. Built Environ., 74, 615 Roßler, 2021, Discerning primary and secondary delays in railway networks using explainable AI, Trans. Res. Procedia, 52, 171, 10.1016/j.trpro.2021.01.018 Sahin, 2017, Markov chain model for delay distribution in train schedules: assessing the effectiveness of time allowances, J. Rail Trans. Plann. Manag., 7, 101 Sara, 2020, Predict France trains delays using visualization and machine learning techniques, Procedia Comput. Sci., 175, 700, 10.1016/j.procs.2020.07.103 Shi, 2020, Arrival train delays prediction based on gradient boosting regression tress, vol. 640, 307 Shi, 2021, Prediction and analysis of train arrival delay based on XGBoost and Bayesian optimization, Appl. Soft Comput., 109, 107538, 10.1016/j.asoc.2021.107538 Shih, 2017, A parametric model of the train delay distribution based on traffic conflicts, 1549 Ulak, 2020, Analyzing network-wide patterns of rail transit delays using Bayesian network learning, Transport. Res. C Emerg. Technol., 119, 102749, 10.1016/j.trc.2020.102749 Wang, 2019, Train delay analysis and prediction based on big data fusion, Trans. Saf. Environ., 1, 79, 10.1093/tse/tdy001 Wang, 2015, Data driven approaches for passenger train delay estimation, 535 Wang, 2021, Predicting the effectiveness of supplement time on delay recoveries: a support vector regression approach, Int. J. Real. Ther., 1 Wee, 2016, How to write a literature review paper?, Transport Rev., 36, 278, 10.1080/01441647.2015.1065456 Wen, 2017, Data-driven models for predicting delay recovery in high-speed rail, 144 Wen, 2019, A predictive model of train delays on a railway line, J. Forecast., 39, 470 Yaghini, 2013, Railway passenger train delay prediction via neural network model, J. Adv. Transport., 47, 667, 10.1002/atr.193 Yuan, 2007, Dealing with stochastic dependence in the modeling of train delays and delay propagation, Int. Conf. Trans. Eng., 3908 Yuan, 2007, Optimizing capacity utilization of stations by estimating knock-on train delays, Transp. Res. Part B Methodol., 41, 202, 10.1016/j.trb.2006.02.004 Zhang, 2020, Mitigating errors of predicted delays of a train at neighbouring stops, IET Intell. Transp. Syst., 14, 873, 10.1049/iet-its.2019.0365 Zhou, 2020, Intelligent prediction of train delay changes and propagation using RVFLNs with improved transfer learning and ensemble learning, IEEE Trans. Intell. Transport. Syst., 1 Zhuang, 2016, High-speed railway train timetable conflict prediction based on fuzzy temporal knowledge reasoning, Engineering, 2, 366, 10.1016/J.ENG.2016.03.019 Zilko, 2016, Modeling railway disruption lengths with Copula Bayesian networks, Transport. Res. C Emerg. Technol., 68, 350, 10.1016/j.trc.2016.04.018