Using data from the web to predict public transport arrivals under special events scenarios
Authors
Abstract
The Internet has become the preferred resource to announce, search and comment about social events such as concerts, sports games, parades, demonstrations, sales or any other public event that potentially gathers a large group of people. These \emph{planned special events} often carry a potential disruptive impact to the transportation system, because they correspond to non-habitual behavior patterns that are hard to predict and plan for.Except for very large and mega events (e.g. olympic games, football world cup), operators seldom apply special planning measures for two major reasons: the task of manually tracking which events are happening in large cities is labour-intensive; and, even with a list of events, their impact is hard to estimate, especially when more than one event happens simultaneously.
In this paper, we utilize the Internet as a resource for contextual information about special events and develop a model that predicts public transport arrivals in event areas. In order to demonstrate the feasibility
of this solution for practitioners, we apply off-the-shelf techniques both for Internet data collection and for the prediction model development. We demonstrate the results with a case study from the city-state of Singapore using public transport tap-in/tap-out data and local event information obtained from the Internet.
Keywords
Intelligent Transportation Systems, machine learning, demand prediction, context miningSubject
Intelligent Transportation Systems, machine learning, demand prediction, context miningRelated Project
Crowds - Understanding urban land use from digital footprints of crowdsJournal
Journal of Intelligent Transportation Systems: Technology, Planning, and Operations (JITS), Asad Khattak, November 2013PDF File
DOI
Cited by
Year 2015 : 4 citations
WY Szeto, J YEUNG, RCP WONGâ?¦, Trip Attraction, Trip Distribution, and Modal Split for Columbarium Trips, Journal of the Eastern Asia …, 2015
K Gkiotsalitis, A Stathopoulos, Optimizing Leisure Travel: Is BigData Ready to Improve the Joint Leisure Activities Efficiency?, Engineering and Applied Sciences …, 2015
E Chaniotakis, C Antoniou, Use of Geotagged Social Media in Urban Settings: Empirical Evidence on Its Potential from Twitter, Intelligent Transportation Systems …, 2015
WY Szeto, RCP Wong, J Yeungâ?¦, Mixed logit approach to modeling arrival time choice behavior of cemetery and columbarium visitors during grave-sweeping festivals, … A: Transport Science, 2015
Year 2014 : 1 citations
S Gowrishankar, ER Stern, DB Work, Including the social component in smart transportation systems, National Workshop on …, 2014