Transit data analytics for planning, monitoring, control, and information

Haris N. Koutsopoulos, Zhenliang Ma, Peyman Noursalehi, Yiwen Zhu

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

Abstract

Automated data collection systems in the transit industry, such as automated fare-collection (AFC) and automated vehicle location (AVL), provide transit agencies and operators with extensive data about the state of the system and its use by passengers. The data can inform various functions of a transit agency from planning, to operations, to measuring and monitoring performance, and understanding user spatiotemporal travel patterns. We demonstrate the applicability and value of the data with examples of recent developments and applications: (a) measuring system performance from a passenger's point of view; (b) making real-time decisions to improve operations and level of service based on predictive analytics; and (c) designing transit demand management strategies to increase capacity utilization.
Original languageEnglish
Title of host publicationMobility Patterns, Big Data and Transport Analytics
Subtitle of host publicationTools and Applications for Modeling
EditorsConstantinos Antoniou, Loukas Dimitriou, Francisco Pereira
Place of PublicationAmsterdam Netherlands
PublisherElsevier
Chapter10
Pages229-261
Number of pages33
ISBN (Print)9780128129708
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • AFC
  • AVL
  • Transit
  • Operations planning
  • Control
  • Assignment
  • Predictive analytics
  • Information
  • Transit demand management

Cite this

Koutsopoulos, H. N., Ma, Z., Noursalehi, P., & Zhu, Y. (2019). Transit data analytics for planning, monitoring, control, and information. In C. Antoniou, L. Dimitriou, & F. Pereira (Eds.), Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling (pp. 229-261). Elsevier. https://doi.org/10.1016/B978-0-12-812970-8.00010-5