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Evaluating the added-value of online bus arrival prediction schemes
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0002-4506-0459
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
2016 (English)In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 86, 35-55 p.Article in journal (Refereed) PublishedText
Abstract [en]

Online predictions of bus arrival times have the potential to reduce the uncertainty associated with bus operations. By better anticipating future conditions, online predictions can reduce perceived and actual passenger travel times as well as facilitate more proactive decision making by service providers. Even though considerable research efforts were devoted to the development of computationally expensive bus arrival prediction schemes, real-world real-time information (RTI) systems are typically based on very simple prediction rules. This paper narrows down the gap between the state-of-the-art and the state-of-the-practice in generating RTI for public transport systems by evaluating the added-value of schemes that integrate instantaneous data and dwell time predictions. The evaluation considers static information and a commonly deployed scheme as a benchmark. The RTI generation algorithms were applied and analyzed for a trunk bus network in Stockholm, Sweden. The schemes are assessed and compared based on their accuracy, reliability, robustness and potential waiting time savings. The impact of RTI on passengers waiting times are compared with those attained by service frequency and regularity improvements. A method which incorporates information on downstream travel conditions outperforms the commonly deployed scheme, leading to a 25% reduction in the mean absolute error. Furthermore, the incorporation of instantaneous travel times improves the prediction accuracy and reliability, and contributes to more robust predictions. The potential waiting time gains associated with the prediction scheme are equivalent to the gains expected when introducing a 60% increase in service frequency, and are not attainable by service regularity improvements.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 86, 35-55 p.
Keyword [en]
Public transport, Real-time information, Reliability, Travel time prediction, Waiting times
National Category
Transport Systems and Logistics
URN: urn:nbn:se:kth:diva-187096DOI: 10.1016/j.tra.2016.02.004ISI: 000374354800003ScopusID: 2-s2.0-84959143493OAI: diva2:928907

QC 20160517

Available from: 2016-05-17 Created: 2016-05-17 Last updated: 2016-06-08Bibliographically approved

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