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 language | English |
---|---|
Title of host publication | Mobility Patterns, Big Data and Transport Analytics |
Subtitle of host publication | Tools and Applications for Modeling |
Editors | Constantinos Antoniou, Loukas Dimitriou, Francisco Pereira |
Place of Publication | Amsterdam Netherlands |
Publisher | Elsevier |
Chapter | 10 |
Pages | 229-261 |
Number of pages | 33 |
ISBN (Electronic) | 9780128129708 |
ISBN (Print) | 9780128129715 |
DOIs | |
Publication status | Published - 2019 |
Externally published | Yes |
Keywords
- AFC
- AVL
- Transit
- Operations planning
- Control
- Assignment
- Predictive analytics
- Information
- Transit demand management