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[1] Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L. & Wagenaar, J., An overview of recovery models and algorithms for real-time railway rescheduling. Transportation Research Part B, 63, pp. 15–37, 2014. [Crossref]
[2] D’Ariano, A. & Albrecht, T., Running time re-optimization during real-time timetable perturbations. WIT Transactions on the Built Environment, 88, pp. 531–540, 2006. [Crossref]
[3] D’Ariano, A., Pranzo, M. & Hansen, I.A., Conflict resolution and train speed coordi-nation for solving real-time timetable perturbations. IEEE Transactions on Intelligent Transportation Systems, 8(2), pp. 208–222, 2007. [Crossref]
[4] D’Ariano, A., Improving Real-Time Train Dispatching: Models, Algorithms and Applications. PhD thesis, Delft University of Technology, The Netherlands, 2008.
[5] Goverde, R.M.P., Railway timetable stability analysis using max-plus system theory. Transportation Research Part B, 41(2), pp. 179–201, 2007. [Crossref]
[6] Goverde, R.M.P., A delay propagation algorithm for large-scale railway traffic networks. Transportation Research Part C, 18(3), pp. 269–287, 2010. [Crossref]
[7] Corman, F., D’Ariano, A., Pacciarelli, D. & Pranzo, M., Evaluation of a green wave policy in real-time railway traffic management. Transportation Research Part C, 17(6), pp. 607–616, 2009. [Crossref]
[8] Corman, F., D’Ariano, A., Pacciarelli, D. & Pranzo, M., A tabu search algorithm for rerouting trains during rail operations. Transportation Research Part B, 44(1), pp. 175–192, 2010. [Crossref]
[9] Corman, F., D’Ariano, A., Pranzo, M. & Hansen, I.A., Effectiveness of dynamic reordering and rerouting of trains in a complicated and densely occupied station area. Transportation Planning and Technology, 34(4), pp. 341–362, 2011. [Crossref]
[10] D’Ariano, A., Pacciarelli, D. & Pranzo, M., A branch and bound algorithm for schedul-ing trains on a railway network. European Journal of Operational Research, 183(2), pp. 643–657, 2007. [Crossref]
[11] D’Ariano, A., Corman, F., Pacciarelli, D. & Pranzo, M., Reordering and local rerouting strategies to manage train traffic in real time. Transportation Science, 42(4), pp. 405–419, 2008. [Crossref]
[12] Mascis, A. & Pacciarelli, D., Job-shop scheduling with blocking and no-wait con-straints. European Journal of Operational Research, 143(3), pp. 498–517, 2002. [Crossref]
[13] Quaglietta, E. Corman, F. & Goverde, R.M.P., Impact of a stochastic and dynamic set-ting on the stability of railway dispatching solutions. Proceedings of the 14th IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1035–1040, 2013.
[14] Canca, D., Zarzo, A., Algaba, E. & Barrena, E., Confrontation of different objectives in the determination of train scheduling. Procedia – Social and Behavioral Sciences, 20,pp. 302–312, 2011. [Crossref]
[15] Canca, D., Barrena, E., Zarzo, A., Ortega, F. & Algaba, E., Optimal train reallocation strategies under service disruptions. Procedia – Social and Behavioral Sciences, 54, pp. 402–413, 2012. [Crossref]
[16] D’Acierno, L., Gallo, M., Montella, B. & Placido, A., Analysis of the interaction between travel demand and rail capacity constraints. WIT Transactions on the Built Environment, 128, pp. 197–207, 2012. [Crossref]
[17] Hamdouch, Y., Ho, H.W., Sumalee, A. & Wang, G., Schedule-based transit assignment model with vehicle capacity and seat availability. Transportation Research Part B, 45(10), pp. 1805–1830, 2011. [Crossref]
[18] Kanai, S., Shiina, K., Harada, S. & Tomii, N., An optimal delay management algo-rithm from passengers’ viewpoints considering the whole railway network. Journal of Rail Transport Planning & Management, 1(1), pp. 25–37, 2011. jrtpm.2011.09.003. [Crossref]
[19] Zheng, Y., Zhang, Z., Xu, B. & Wang, L., Carrying capacity reliability of railway net-works. Journal of Transportation Systems Engineering and Information Technology, 11(4), pp. 16–21, 2011. [Crossref]
[20] Bifulco, G.N., Cantarella, G.E., De Luca, S. & Di Pace, R., Analysis and modelling the effects of information accuracy on travellers’ behaviour. Proceedings of the 14th IEEE Conference on Intelligent Transportation Systems (ITSC), Washington, DC, pp. 2098–2105, 2011.
[21] Dziekan, K. & Kottenhoff, K., Dynamic at-stop real-time information displays for pub-lic transport: effects on customers. Transportation Research Part A, 41(6), pp. 489–501, 2007. [Crossref]
[22] Molina, E.J.E. & Timmermans, H.J.P., Traveler expectations and willingness-to-pay for web-enabled public transport information services. Transportation Research Part C, 14(2), pp. 57–67, 2006. [Crossref]
[23] Paulley, N., Balcombe, R., Mackett, R., Titheridge, H., Preston, J. Wardman, M., Shires, J. & White, P., The demand for public transport: The effects of fares, quality of service, income and car ownership. Transport Policy, 13(4), pp. 295–306, 2006. [Crossref]
[24] Hansen, I.A., & Pachl. J., Railway Timetable and Traffic: Analysis, Modelling, Simula-tion, Eurail Press: Hamburg, Germany, 2008.
[25] Nash, A. & Huerlimann, D., Railroad simulation using OpenTrack. Computers in Rail-ways, 9, pp. 45–54, 2004. [Crossref]
[26] D’Acierno, L., Gallo, M., Montella, B. & Placido, A., The definition of a model frame-work for managing rail systems in the case of breakdowns. Proceedings of the 16th IEEE Conference on Intelligent Transportation Systems (ITSC), The Hague, pp. 1059–1064, 2013.
[27] MVA Consultancy, Understanding the Passenger: Valuation of Overcrowding on Rail Services. Report for Department of Transport, London, 2008.
[28] CENELEC, Railway Applications – Specification and Demonstration of Reliability, Availability, Maintainability and Safety (RAMS). EN50126, 1999.
[29] Pachl, J., Railway Operation and Control. VTD Rail Publishing: Mountlake Terrace, WA, 2009.
[30] Cascetta, E., Transportation Systems Analysis: Models and Applications. Springer: New York, 2009.
[31] Wardman, M. & Whelan, G., Twenty years of rail crowding valuation studies: Evidence and lessons from British experience. Transport Reviews, 31(3), pp. 379–398, 2011. [Crossref]
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Acadlore takes over the publication of IJTDI from 2025 Vol. 9, No. 4. The preceding volumes were published under a CC BY 4.0 license by the previous owner, and displayed here as agreed between Acadlore and the previous owner. ✯ : This issue/volume is not published by Acadlore.

Open Access
Research article

Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study

A. Placido1,
C. Petito2,
M. Gallo3,
L. D’Acierno4
1
D’Appolonia S.p.A., Italy
2
Rete Ferroviaria Italiana (Italian Railway Network), Italy
3
Department of Engineering, University of Sannio (Benevento), Italy
4
Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Italy
International Journal of Transport Development and Integration
|
Volume 1, Issue 4, 2017
|
Pages 695-710
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: 09-01-2017
View Full Article|Download PDF

Abstract:

In the case of conventional rail lines, when disruptions occur, dispatchers have the difficult task of finding feasible rescheduling solutions rapidly so as to re-establish ordinary conditions as soon as possible. Despite the numerous contributions for automatic rescheduling proposed in the literature, this process is still totally controlled by dispatchers who decide according to their personal experience and under their own responsibility. Indeed, in many cases, it can be more advantageous to let the system revert to ordinary conditions without implementing any strategy rather than look for solutions which can reduce the discomfort perceived by passengers. In this article we propose a system of models for managing the rail system, combining a microscopic simulation model with an assignment tool which is able to consider passenger flows on the network. as a result, the disutility experienced by users during their trip can be evaluated and feasible intervention strategies can be assessed, taking into account the passengers’ perspective. an application on a real regional line in campania (Italy) shows the benefits of the proposed approach for performing off-line analyses of intervention solutions and helping dispatchers make decisions during critical events to increase service quality.

Keywords: Public Transport Management, Rail Network Micro-Simulation, Real-Scale Network Analysis, Travel Demand Estimation
References
[1] Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L. & Wagenaar, J., An overview of recovery models and algorithms for real-time railway rescheduling. Transportation Research Part B, 63, pp. 15–37, 2014. [Crossref]
[2] D’Ariano, A. & Albrecht, T., Running time re-optimization during real-time timetable perturbations. WIT Transactions on the Built Environment, 88, pp. 531–540, 2006. [Crossref]
[3] D’Ariano, A., Pranzo, M. & Hansen, I.A., Conflict resolution and train speed coordi-nation for solving real-time timetable perturbations. IEEE Transactions on Intelligent Transportation Systems, 8(2), pp. 208–222, 2007. [Crossref]
[4] D’Ariano, A., Improving Real-Time Train Dispatching: Models, Algorithms and Applications. PhD thesis, Delft University of Technology, The Netherlands, 2008.
[5] Goverde, R.M.P., Railway timetable stability analysis using max-plus system theory. Transportation Research Part B, 41(2), pp. 179–201, 2007. [Crossref]
[6] Goverde, R.M.P., A delay propagation algorithm for large-scale railway traffic networks. Transportation Research Part C, 18(3), pp. 269–287, 2010. [Crossref]
[7] Corman, F., D’Ariano, A., Pacciarelli, D. & Pranzo, M., Evaluation of a green wave policy in real-time railway traffic management. Transportation Research Part C, 17(6), pp. 607–616, 2009. [Crossref]
[8] Corman, F., D’Ariano, A., Pacciarelli, D. & Pranzo, M., A tabu search algorithm for rerouting trains during rail operations. Transportation Research Part B, 44(1), pp. 175–192, 2010. [Crossref]
[9] Corman, F., D’Ariano, A., Pranzo, M. & Hansen, I.A., Effectiveness of dynamic reordering and rerouting of trains in a complicated and densely occupied station area. Transportation Planning and Technology, 34(4), pp. 341–362, 2011. [Crossref]
[10] D’Ariano, A., Pacciarelli, D. & Pranzo, M., A branch and bound algorithm for schedul-ing trains on a railway network. European Journal of Operational Research, 183(2), pp. 643–657, 2007. [Crossref]
[11] D’Ariano, A., Corman, F., Pacciarelli, D. & Pranzo, M., Reordering and local rerouting strategies to manage train traffic in real time. Transportation Science, 42(4), pp. 405–419, 2008. [Crossref]
[12] Mascis, A. & Pacciarelli, D., Job-shop scheduling with blocking and no-wait con-straints. European Journal of Operational Research, 143(3), pp. 498–517, 2002. [Crossref]
[13] Quaglietta, E. Corman, F. & Goverde, R.M.P., Impact of a stochastic and dynamic set-ting on the stability of railway dispatching solutions. Proceedings of the 14th IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1035–1040, 2013.
[14] Canca, D., Zarzo, A., Algaba, E. & Barrena, E., Confrontation of different objectives in the determination of train scheduling. Procedia – Social and Behavioral Sciences, 20,pp. 302–312, 2011. [Crossref]
[15] Canca, D., Barrena, E., Zarzo, A., Ortega, F. & Algaba, E., Optimal train reallocation strategies under service disruptions. Procedia – Social and Behavioral Sciences, 54, pp. 402–413, 2012. [Crossref]
[16] D’Acierno, L., Gallo, M., Montella, B. & Placido, A., Analysis of the interaction between travel demand and rail capacity constraints. WIT Transactions on the Built Environment, 128, pp. 197–207, 2012. [Crossref]
[17] Hamdouch, Y., Ho, H.W., Sumalee, A. & Wang, G., Schedule-based transit assignment model with vehicle capacity and seat availability. Transportation Research Part B, 45(10), pp. 1805–1830, 2011. [Crossref]
[18] Kanai, S., Shiina, K., Harada, S. & Tomii, N., An optimal delay management algo-rithm from passengers’ viewpoints considering the whole railway network. Journal of Rail Transport Planning & Management, 1(1), pp. 25–37, 2011. jrtpm.2011.09.003. [Crossref]
[19] Zheng, Y., Zhang, Z., Xu, B. & Wang, L., Carrying capacity reliability of railway net-works. Journal of Transportation Systems Engineering and Information Technology, 11(4), pp. 16–21, 2011. [Crossref]
[20] Bifulco, G.N., Cantarella, G.E., De Luca, S. & Di Pace, R., Analysis and modelling the effects of information accuracy on travellers’ behaviour. Proceedings of the 14th IEEE Conference on Intelligent Transportation Systems (ITSC), Washington, DC, pp. 2098–2105, 2011.
[21] Dziekan, K. & Kottenhoff, K., Dynamic at-stop real-time information displays for pub-lic transport: effects on customers. Transportation Research Part A, 41(6), pp. 489–501, 2007. [Crossref]
[22] Molina, E.J.E. & Timmermans, H.J.P., Traveler expectations and willingness-to-pay for web-enabled public transport information services. Transportation Research Part C, 14(2), pp. 57–67, 2006. [Crossref]
[23] Paulley, N., Balcombe, R., Mackett, R., Titheridge, H., Preston, J. Wardman, M., Shires, J. & White, P., The demand for public transport: The effects of fares, quality of service, income and car ownership. Transport Policy, 13(4), pp. 295–306, 2006. [Crossref]
[24] Hansen, I.A., & Pachl. J., Railway Timetable and Traffic: Analysis, Modelling, Simula-tion, Eurail Press: Hamburg, Germany, 2008.
[25] Nash, A. & Huerlimann, D., Railroad simulation using OpenTrack. Computers in Rail-ways, 9, pp. 45–54, 2004. [Crossref]
[26] D’Acierno, L., Gallo, M., Montella, B. & Placido, A., The definition of a model frame-work for managing rail systems in the case of breakdowns. Proceedings of the 16th IEEE Conference on Intelligent Transportation Systems (ITSC), The Hague, pp. 1059–1064, 2013.
[27] MVA Consultancy, Understanding the Passenger: Valuation of Overcrowding on Rail Services. Report for Department of Transport, London, 2008.
[28] CENELEC, Railway Applications – Specification and Demonstration of Reliability, Availability, Maintainability and Safety (RAMS). EN50126, 1999.
[29] Pachl, J., Railway Operation and Control. VTD Rail Publishing: Mountlake Terrace, WA, 2009.
[30] Cascetta, E., Transportation Systems Analysis: Models and Applications. Springer: New York, 2009.
[31] Wardman, M. & Whelan, G., Twenty years of rail crowding valuation studies: Evidence and lessons from British experience. Transport Reviews, 31(3), pp. 379–398, 2011. [Crossref]
Cite this:
APA Style
IEEE Style
BibTex Style
MLA Style
Chicago Style
GB-T-7714-2015
Placido, A., Petito, C., Gallo, M., & D’Acierno, L. (2017). Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study. Int. J. Transp. Dev. Integr., 1(4), 695-710. https://doi.org/10.2495/TDI-V1-N4-695-710
A. Placido, C. Petito, M. Gallo, and L. D’Acierno, "Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study," Int. J. Transp. Dev. Integr., vol. 1, no. 4, pp. 695-710, 2017. https://doi.org/10.2495/TDI-V1-N4-695-710
@research-article{Placido2017ManagingDA,
title={Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study},
author={A. Placido and C. Petito and M. Gallo and L. D’Acierno},
journal={International Journal of Transport Development and Integration},
year={2017},
page={695-710},
doi={https://doi.org/10.2495/TDI-V1-N4-695-710}
}
A. Placido, et al. "Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study." International Journal of Transport Development and Integration, v 1, pp 695-710. doi: https://doi.org/10.2495/TDI-V1-N4-695-710
A. Placido, C. Petito, M. Gallo and L. D’Acierno. "Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study." International Journal of Transport Development and Integration, 1, (2017): 695-710. doi: https://doi.org/10.2495/TDI-V1-N4-695-710
Placido A.， Petito C.， Gallo M.， et al. Managing Disruptions and Disturbances on Railway Services: A Real-Scale Case Study[J]. International Journal of Transport Development and Integration， 2017， 1(4)： 695-710. https://doi.org/10.2495/TDI-V1-N4-695-710