Predictability of public transport usage: A study of bus rides in Lisbon, Portugal

Stefan Foell*, Santi Phithakkitnukoon, Gerd Kortuem, Marco Veloso, Carlos Bento

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)

Abstract

This paper presents a study of the predictability of bus usage based on massive bus ride data collected from Lisbon, Portugal. An understanding of public bus usage behavior is important for future development of personalized transport information systems that are equipped with proactive capabilities such as predictive travel recommender systems. In this study, we show that there exists a regularity in the bus usage and that daily bus rides can be predicted with a high degree of accuracy. In addition, we show that there are spatial and temporal factors that influence bus usage predictability. These influential factors include bus usage frequency, number of different bus lines and stops used, and time of rides.

Original languageEnglish
Article number7110372
Pages (from-to)2955-2960
Number of pages6
JournalIEEE Transactions on Intelligent Transportation Systems
Volume16
Issue number5
DOIs
Publication statusPublished - Oct 2015
Externally publishedYes

Keywords

  • data mining
  • Public transport
  • smart card data
  • transport usage patterns
  • travel prediction
  • urban computing

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