Public Transport

, Volume 10, Issue 3, pp 455–497 | Cite as

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

  • Luigi MocciaEmail author
  • Duncan W. Allen
  • Eric C. Bruun
Original Paper


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.


Semi-rapid transit Bus rapid transit Light rail transit Transit line optimization 



This work was partly supported by CNR (Italy) under project “Smart data and models”. This support is gratefully acknowledged. Luigi Moccia and Eric Bruun also show their appreciation to IBI Group for permitting Duncan Allen to share his dataset and expertise. Thanks are also due to the reviewers for their valuable comments.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Consiglio Nazionale delle Ricerche, Istituto di Calcolo e Reti ad Alte PrestazioniRendeItaly
  2. 2.Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT)MontrealCanada
  3. 3.IBI GroupBostonUSA
  4. 4.Kyyti Group Ltd.HelsinkiFinland

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