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Modeling cyclist acceleration process for bicycle traffic simulation using naturalistic data
KTH, School of Architecture and the Built Environment (ABE), Transport Science. (System Simulation & Control)
(System Simulation & Control)
2016 (English)In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 40, 130-144 p., doi:10.1016/j.trf.2016.04.009Article in journal (Refereed) Published
Abstract [en]

Cycling is a healthy and sustainable form of transportation. The recent increase of daily cyclists in Sweden has triggered broad interest in finding how policies and measures may facilitate the planning of bicycle traffic in the urban area. However, in comparison to car traffic, bicycle traffic is still far from well understood. This study is part of the research effort to investigate microscopic cyclist behavior, model bicycle traffic and finally build a simulation tool for applications in transport planning. In particular, the paper focuses on representing bicycle movements when the cyclist doesn’t interact with others. The cyclist acceleration behavior is modeled using naturalistic GPS data collected by eleven recruited commuter cyclists. After filtering the large amount of data, cyclist trajectories are obtained and acceleration profiles are abstracted. A mathematical model is proposed based on the dataset, and three model forms are estimated using the maximum likelihood method with Laplace and Normal error terms. While the model with more parameters shows superior performance, the simplified ones are still capable of capturing the trends in the acceleration profiles. On the other hand, the study also introduces social economic characteristics of cyclists to explain the model parameters and they show significant effects. However, the cyclist population being investigated in the study is still limited, and more convincing results can be obtained when the data collection effort is extended to larger population with more variable cyclist characteristics.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 40, 130-144 p., doi:10.1016/j.trf.2016.04.009
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
URN: urn:nbn:se:kth:diva-189206ISI: 000378458200012Scopus ID: 2-s2.0-84968853473OAI: oai:DiVA.org:kth-189206DiVA: diva2:944319
Funder
Länsförsäkringar AB, P13-12
Note

QC 20160811

Available from: 2016-06-29 Created: 2016-06-29 Last updated: 2017-11-28Bibliographically approved

Open Access in DiVA

fulltext(17312 kB)