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A dynamic stochastic model for evaluating congestion and crowding effects in transit systems
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. Delft University of Technology, Netherlands.ORCID iD: 0000-0002-4506-0459
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0003-3043-8145
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0003-1789-9238
2016 (English)In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 89, 43-57 p.Article in journal (Refereed) PublishedText
Abstract [en]

One of the most common motivations for public transport investments is to reduce congestion and increase capacity. Public transport congestion leads to crowding discomfort, denied boardings and lower service reliability. However, transit assignment models and appraisal methodologies usually do not account for the dynamics of public transport congestion and crowding and thus potentially underestimate the related benefits. This study develops a method to capture the benefits of increased capacity by using a dynamic and stochastic transit assignment model. Using an agent-based public transport simulation model, we dynamically model the evolution of network reliability and on-board crowding. The model is embedded in a comprehensive framework for project appraisal.A case study of a metro extension that partially replaces an overloaded bus network in Stockholm demonstrates that congestion effects may account for a substantial share of the expected benefits. A cost-benefit analysis based on a conventional static model will miss more than a third of the benefits. This suggests that failure to represent dynamic congestion effects may substantially underestimate the benefits of projects, especially if they are primarily intended to increase capacity rather than to reduce travel times.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 89, 43-57 p.
Keyword [en]
Agent-based simulation, Capacity, Cost-benefit analysis, Dynamic congestion, Transit assignment, Cost benefit analysis, Cost effectiveness, Mass transportation, Stochastic systems, Travel time, Agent based simulation, Crowding effects, Network reliability, Public transport, Service reliability, Transit systems, Stochastic models
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-186912DOI: 10.1016/j.trb.2016.04.001ISI: 000379281900003ScopusID: 2-s2.0-84963517880OAI: oai:DiVA.org:kth-186912DiVA: diva2:928829
Note

QC 20160516

Available from: 2016-05-16 Created: 2016-05-16 Last updated: 2016-08-25Bibliographically approved
In thesis
1. Modelling and Appraisal in Congested Transport Networks
Open this publication in new window or tab >>Modelling and Appraisal in Congested Transport Networks
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Appraisal methodologies for congestion mitigation projects are relatively less well developed compared to methodologies for projects reducing free flow travel times. For instance, static assignment models are incapable of representing the build-up and dissipation of traffic queues, or capturing the experienced crowding caused by uneven on-board passenger loads. Despite the availability of dynamic traffic assignment, only few model systems have been developed for cost-benefit analysis of real applications. The six included papers present approaches and tools for analysing traffic and transit projects where congestion relief is the main target.

In the transit case studies, we use an agent-based simulation model to analyse congestion and crowding effects and to conduct cost-benefit analyses. In the case study of a metro extension in Stockholm, we demonstrate that congestion and crowding effects constitute more than a third of the total benefits and that a conventional static model underestimates these effects vastly. In another case study, we analyse various operational measures and find that the three main measures (boarding through all doors, headway-based holding and bus lanes) had an overall positive impact on service performance and that synergetic effects exist.

For the congestion charging system in Gothenburg, we demonstrate that a hierarchal route choice model with a continuous value of time distribution gives realistic predictions of route choice effects although the assignment is static. We use the model to show that the net social benefit of the charging system in Gothenburg is positive, but that low income groups pay a larger share of their income than high income groups. To analyse congestion charges in Stockholm however, integration of dynamic traffic assignment with the demand model is necessary, and we demonstrate that this is fully possible.

Models able to correctly predict these effects highlight the surprisingly large travel time savings of pricing policies and small operational measures. These measures are cheap compared to investments in new infrastructure and their implementation can therefore lead to large societal gains.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016
Series
TRITA-TSC-PHD, 16:007
Keyword
Transport modelling, Transit Assignment, Appraisal, Congestion, Crowding, Cost-benefit analysis, Value of time, Congestion charge, Dynamic traffic assignment
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
urn:nbn:se:kth:diva-190866 (URN)978-91-87353-92-5 (ISBN)
External cooperation:
Public defence
2016-09-30, L1, KTH, Drottning Kristinas väg 30, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20160829

Available from: 2016-08-29 Created: 2016-08-17 Last updated: 2016-08-30Bibliographically approved

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