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A technology selection and design model of a semi-rapid transit line

Author

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  • Luigi Moccia

    (Consiglio Nazionale delle Ricerche, Istituto di Calcolo e Reti ad Alte Prestazioni
    Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT))

  • Duncan W. Allen

    (IBI Group)

  • Eric C. Bruun

    (Kyyti Group Ltd.)

Abstract

We present a new optimization model for technology selection and design of a semi-rapid transit line. With respect to previous studies, we improve the synthetic representation of the temporal and spatial variability of demand, and of several operational and design aspects. We apply the model to two scenarios offering comparable performance by commercially available technologies in terms of service, rather than assuming that service quality is strongly associated with technology. The model is validated by comparing some computed performance indices with best practices. We show that planning for a faster technology can be more important than the choice between bus and rail per se, except at very low demand density, and that differences of total cost, sum of passengers’ time value and operator’s cost, between the technologies are smaller than commonly held across a wide range of higher demands. At high demand density multiple-unit rail offers the most cost-effective way to achieve high capacities under many conditions. A scenario variation analysis shows the relevance of differences between value of time components, the bias of averaging vehicle load ratios when assessing the crowding disutility, the usefulness of a demand index abstracting from some specific parameter choices, and the high impact of the project discount rate.

Suggested Citation

  • Luigi Moccia & Duncan W. Allen & Eric C. Bruun, 2018. "A technology selection and design model of a semi-rapid transit line," Public Transport, Springer, vol. 10(3), pages 455-497, December.
    • Handle: RePEc:spr:pubtra:v:10:y:2018:i:3:d:10.1007_s12469-018-0187-1
    DOI: 10.1007/s12469-018-0187-1
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    References listed on IDEAS

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    1. Akçelik, Rahmi & Rouphail, Nagui M., 1993. "Estimation of delays at traffic signals for variable demand conditions," Transportation Research Part B: Methodological, Elsevier, vol. 27(2), pages 109-131, April.
    2. Tirachini, Alejandro & Hensher, David A., 2011. "Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 828-844, June.
    3. N. Oort, 2016. "Incorporating enhanced service reliability of public transport in cost-benefit analyses," Public Transport, Springer, vol. 8(1), pages 143-160, March.
    4. Tirachini, Alejandro & Hensher, David A. & Jara-Díaz, Sergio R., 2010. "Restating modal investment priority with an improved model for public transport analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1148-1168, November.
    5. Newman, Peter & Davies-Slate, Sebastian & Jones, Evan, 2018. "The Entrepreneur Rail Model: Funding urban rail through majority private investment in urban regeneration," Research in Transportation Economics, Elsevier, vol. 67(C), pages 19-28.
    6. Haywood, Luke & Koning, Martin & Monchambert, Guillaume, 2017. "Crowding in public transport: Who cares and why?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 215-227.
    7. Daganzo, Carlos F., 2012. "On the design of public infrastructure systems with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1288-1293.
    8. Moccia, Luigi & Laporte, Gilbert, 2016. "Improved models for technology choice in a transit corridor with fixed demand," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 245-270.
    9. David Verbich & Ehab Diab & Ahmed El-Geneidy, 2016. "Have they bunched yet? An exploratory study of the impacts of bus bunching on dwell and running times," Public Transport, Springer, vol. 8(2), pages 225-242, September.
    10. Vukan R. Vuchic, 1969. "Rapid Transit Interstation Spacings for Maximum Number of Passengers," Transportation Science, INFORMS, vol. 3(3), pages 214-232, August.
    11. Shinya Kikuchi & Vukan R. Vuchic, 1982. "Transit Vehicle Stopping Regimes and Spacings," Transportation Science, INFORMS, vol. 16(3), pages 311-331, August.
    12. W. Klumpenhouwer & S. C. Wirasinghe, 2016. "Cost-of-crowding model for light rail train and platform length," Public Transport, Springer, vol. 8(1), pages 85-101, March.
    13. Daganzo, Carlos F., 2009. "A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 913-921, December.
    14. Bartholdi, John J. & Eisenstein, Donald D., 2012. "A self-coördinating bus route to resist bus bunching," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 481-491.
    15. Hörcher, Daniel & Graham, Daniel J. & Anderson, Richard J., 2017. "Crowding cost estimation with large scale smart card and vehicle location data," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 105-125.
    16. Tirachini, Alejandro & Sun, Lijun & Erath, Alexander & Chakirov, Artem, 2016. "Valuation of sitting and standing in metro trains using revealed preferences," Transport Policy, Elsevier, vol. 47(C), pages 94-104.
    17. Moccia, Luigi & Giallombardo, Giovanni & Laporte, Gilbert, 2017. "Models for technology choice in a transit corridor with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 733-756.
    18. Vukan R. Vuchic & Gordon F. Newell, 1968. "Rapid Transit Interstation Spacings for Minimum Travel Time," Transportation Science, INFORMS, vol. 2(4), pages 303-339, November.
    19. Rodrigo Fernandez & Rosemarie Planzer, 2002. "On the capacity of bus transit systems," Transport Reviews, Taylor & Francis Journals, vol. 22(3), pages 267-293, January.
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    Cited by:

    1. Philipp Heyken Soares & Christine L. Mumford & Kwabena Amponsah & Yong Mao, 2019. "An adaptive scaled network for public transport route optimisation," Public Transport, Springer, vol. 11(2), pages 379-412, August.
    2. Gülçin Canbulut & Erkan Köse & Oğuzhan Ahmet Arik, 2022. "Public transportation vehicle selection by the grey relational analysis method," Public Transport, Springer, vol. 14(2), pages 367-384, June.
    3. Philipp Heyken Soares, 2021. "Zone-based public transport route optimisation in an urban network," Public Transport, Springer, vol. 13(1), pages 197-231, March.
    4. Luigi Moccia & Duncan W. Allen & Gilbert Laporte & Andrea Spinosa, 2022. "Mode boundaries of automated metro and semi-rapid rail in urban transit," Public Transport, Springer, vol. 14(3), pages 739-802, October.
    5. Luigi Moccia & Duncan W. Allen & Gilbert Laporte, 2020. "A spatially disaggregated model for the technology selection and design of a transit line," Public Transport, Springer, vol. 12(3), pages 647-691, October.
    6. Nir Sharav & Yoram Shiftan, 2021. "Optimal Urban Transit Investment Model and Its Application," Sustainability, MDPI, vol. 13(16), pages 1-29, August.

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