A dynamic stochastic model for evaluating congestion and crowding effects in transit systems
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
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.
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
Transport Systems and Logistics
IdentifiersURN: 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
QC 201605162016-05-162016-05-162016-08-25Bibliographically approved