A spatially disaggregated model for the technology selection and design of a transit line

Luigi Moccia, Duncan W. Allen, Gilbert Laporte

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)

Abstract

Our research question is the usefulness of a high level of spatial granularity for the travel demand when planning a transit line. We formulate a new optimization model for the technology selection and design of a transit line where the spatial attributes of the travel demand can be finely set. The solution method relies on approximated formulae, and we establish relationships with a classic result for the optimal stop spacing. We also present a refinement of the in-vehicle passenger crowding for an existing transit design model where demand spatial attributes are set synthetically. We call “spatially disaggregate” and “spatially aggregate” the former and the latter model, respectively. These two models are compared by numerical experiments on a scenario for three semi-rapid transit technologies where two variants consider opposite demand profiles in terms of spatial distribution. We conclude that the spatially aggregated model is sufficient when the main goal is technology selection, whereas the spatially disaggregate model is better for design and benchmarking purposes.

Original languageEnglish
Pages (from-to)647-691
Number of pages45
JournalPublic Transport
Volume12
Issue number3
Early online date9 Sept 2020
DOIs
Publication statusPublished - 1 Oct 2020

Bibliographical note

Funding Information:
Luigi Moccia was partly supported by CNR (Italy) under project ?Smart data and models?. Gilbert Laporte was funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189. These supports are gratefully acknowledged. Luigi Moccia and Duncan W. Allen thank Eric C. Bruun for fruitful discussions on transit planning and operations. We thank the Editor and the referees for their valuable comments.

Funding Information:
Luigi Moccia was partly supported by CNR (Italy) under project “Smart data and models”. Gilbert Laporte was funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189. These supports are gratefully acknowledged. Luigi Moccia and Duncan W. Allen thank Eric C. Bruun for fruitful discussions on transit planning and operations. We thank the Editor and the referees for their valuable comments.

Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Public transport optimization
  • Semi-rapid transit
  • Transit Line design
  • Transit technology assessment
  • Mass transport
  • Sustainability

ASJC Scopus subject areas

  • Information Systems
  • Transportation
  • Mechanical Engineering
  • Management Science and Operations Research

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