Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4968475 | Transportation Research Part C: Emerging Technologies | 2017 | 19 Pages |
Abstract
This paper explores how we can use smart card data for bus passengers to reveal individual and aggregate travel behaviour. More specifically, we measure the extent to which both individual and bus routes exhibit habitual behaviour. To achieve this, we introduce a metric called Stickiness Index to quantify the range of preferences of users that always select to travel on the same route (high stickiness) to those with a more varied patterns of route selection (low stickiness). Adopting a visual analytic and modelling approach using a suite of regression models we find evidence to suggest that stickiness varies across the metropolitan area and over a 24-h period wherein higher stickiness is associated with high frequency users where there is substantial variability of route travel times across all alternatives. We argue that our findings are important in their capacity to contribute to a new evidence base with the potential to inform the (re)-design and scheduling of a public transit systems through unveiling the complexities of transit behaviour.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Jiwon Kim, Jonathan Corcoran, Marty Papamanolis,