B. Davydov | V. Chebotarev | K. Kablukova
OPEN ACCESS
The article explores the problem of train rescheduling based on the actual situation. The proposed stochastic model uses specific distributions of operating times which are dependent on the current traffic conditions. The arrival time distribution is considered as a result of adjusting the train trajectory by speed control. The results of modelled arrival distributions correspond well with the experimental data received at the russian railways. The proposed model is used for prevention of sequence-of-trains conflicts and violations of connections. The basis of deviation prediction is two-train model of mesa-level which uses actual features of scattering of the operation times both at sites and at stations. The article also proposed a new measure of arrival delay which considers the share of satisfied passengers.
local adjustments, online rescheduling, stochastic mesa-mode, train traffic
[1] Berger, A., Gebhardt, A., Müller-Hannemann, M. & Ostrowski, M., Stochastic DelayPrediction in Large Train Networks. Proceedings of 11th Workshop on Algorithmic Approachesfor Transportation Modelling, Optimization, and Systems (ATMOS’11), eds.A. Caprara & S. Kontogiannis, pp. 100–111, 2011.
[2] Büker, T. & Seybold, B., Stochastic modelling of delay propagation in large networks.Journal of Rail Transport Planning & Management, 2, pp. 34–50, 2012. DOI: 10.1016/j.jrtpm.2012.10.001.
[3] Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L. & Wagenaar,J., Overview of recovery models and algorithms for real-time railway rescheduling.Transportation Research, Part B, 63, pp. 15–37, 2014. DOI: 10.1016/j.trb.2014.01.009.
[4] Törnquist, J., Computer-based decision support for railway traffic scheduling and dispatching:A review of models and algorithms. Proceedings of the 5th Workshop onAlgorithmic Methods and Models for Optimization of Railways, (ATMOS’05), eds.L. Kroon & H. Rolf, 23 p., 2005.
[5] Muhlhans, E., Berechnung der verspatungsentwicklung bei zugfahrten. Eisenbahntechn.Rundschau ETR, 39(7/8), pp. 465–468, 1990.
[6] Carey, M. & Kwiecin´ski, A., Stochastic approximation to the effects of headways onknock-on delays of trains. Transportation Research, Part B, 28, pp. 251–267, 1994.DOI: 10.1016/0191-2615(94)90001-9.
[7] Meester, L.E. & Muns, S., Stochastic delay propagation in railway networks and phasetypedistributions. Transportation Research, Part B, 41, pp. 218–230, 2007. DOI:10.1016/j.trb.2006.02.007.
[8] Huisman, T. & Boucherie, R.J., Running times on railway sections with heterogeneoustrain traffic. Transportation Research, Part B, 35, pp. 271–292, 2001. DOI: 10.1016/S0191-2615(99)00051-X.
[9] Wendler, E., The scheduled waiting time on railway lines. Transportation Research,Part B, 41(2), pp. 148–158, 2007. DOI: 10.1016/j.trb.2006.02.009.
[10] Yuan, J., Stochastic Modelling of Train Delays and Delay Propagation in Stations, PhDThesis, TRAIL Thesis Series no. T2006/6, the Netherlands, 142p., 2006.
[11] Kroon, L.G., Dekker, R. & Vromans, M., Cyclic Railway Timetabling: A StochasticOptimization Approach. Proceedings of the 4th Workshop on Algorithmic Methods andModels for Optimization of Railways (ATMOS’04), eds. F. Geraets, L. Kroon, A. Schoebel,D. Wagner & C. Zaroliagiis, pp. 41–66, 2004.
[12] Vromans, M., Reliability of Railway Systems, PhD Thesis. TRAIL Thesis series no.T2005/7, The Netherlands TRAIL Research School, 244p., 2005.
[13] Chebotarev, V., Davydov, B. & Godyaev, A., Stochastic Traffic Models for the AdaptiveTrain Dispatching. Proceedings of the 1st International Scientific Conference on “IntelligentInformation Technologies for Industry” (IITI’16), Rostov-on-Don, Russia, May16–21, 2016.
[14] Goverde, R.P.M., A delay propagation algorithm for large-scale railway traffic networks.Transportation Research, Part C, 18(3), pp. 269–287, 2010. DOI: 10.1016/j.trc.2010.01.002
[15] Beck, A., Bente, H. & Schilling, M., Railway Efficiency: An Overview and a Look atOpportunities for Improvement. The International Transport Forum, Discussion paperno. 2013–12, 44p., 2013.
[16] Shapkin, I.N., Yusipov, R.A. & Kozhanov, E.M., Modelling train traffic based on multifactorsetting technological operations. Vestnik VNIIZhT, 4, pp. 30–36, 2006.
[17] Törnquist Krasemann, J., Design of an effective algorithm for fast response to the reschedulingof railway traffic during disturbances. Transportation Research, Part C,20(6), pp. 62–78, 2012. DOI: 10.1016/j.trc.2010.12.004.