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Capturing correlation with a mixed recursive logit model for activity-travel scheduling
Univ Montreal, Dept Comp Sci & Operat Res, Montreal, PQ, Canada.;CIRRELT Interuniv Res Ctr Entreprise Networks Log, Montreal, PQ, Canada..
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Univ Montreal, Dept Comp Sci & Operat Res, Montreal, PQ, Canada.;CIRRELT Interuniv Res Ctr Entreprise Networks Log, Montreal, PQ, Canada..
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.ORCID iD: 0000-0001-5290-6101
2018 (English)In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 93, p. 273-291Article in journal (Refereed) Published
Abstract [en]

Representing activity-travel scheduling decisions as path choices in a time-space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Vastberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.

Place, publisher, year, edition, pages
Pergamon Press, 2018. Vol. 93, p. 273-291
Keywords [en]
Travel demand modeling, Activity-travel scheduling, Mixed recursive logic, Activity network, Mode choice
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-234636DOI: 10.1016/j.trc.2018.05.032ISI: 000442173400016Scopus ID: 2-s2.0-85048520868OAI: oai:DiVA.org:kth-234636DiVA, id: diva2:1247456
Funder
Swedish National Infrastructure for Computing (SNIC)National Supercomputer Centre (NSC), Sweden
Note

QC 20180912

Available from: 2018-09-12 Created: 2018-09-12 Last updated: 2018-09-12Bibliographically approved

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Västberg, Oskar BlomKarlström, Anders

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