Connecting e-hailing to mass transit platform: Analysis of relative spatial position

Peng (Will) Chen, Yu (Marco) Nie*

*Corresponding author for this work

Research output: Contribution to journalArticle

27 Scopus citations

Abstract

This paper analyzes and compares two different relative spatial position (RSP) designs in an integrated e-hailing/fixed-route transit system: a zone-based design that operates e-hailing vehicles within a zone, and a line-based design that operates e-hailing vehicles along a fixed-route transit line and with a stable headway. To conduct a meaningful comparison, the optimal design problems for both systems are formulated using a same analytical framework based on the continuous approximation approach. A comprehensive numerical experiment is performed to compare various cost components corresponding to the optimal designs, and a discrete-event simulation model is developed to validate the analysis. The analytical and simulation results agree with each other well, with a discrepancy in the total system cost less than 5% in most test scenarios. These results also suggest that the line-based system consistently outperforms the zone-based system in terms of both agency and user costs, for all scenarios tested. Compared to the zone-based design, the line-based design features a sparser fixed-route network (resulting in larger stop spacing) but a higher dispatching frequency. It is concluded that the higher efficiency of the line-based design is likely derived from the strategy of operating e-hailing vehicles with a more regular route/headway structure and allowing ride-sharing.

Original languageEnglish (US)
Pages (from-to)444-461
Number of pages18
JournalTransportation Research Part C: Emerging Technologies
Volume77
DOIs
StatePublished - Apr 1 2017

Keywords

  • Continuous approximation
  • Discrete-event simulation
  • E-hailing service
  • Fixed-route service
  • Relative spatial position

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

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