Pougala, Janody;
Hillel, Tim;
Bierlaire, Michel;
(2023)
OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions.
Transportation Research Part C: Emerging Technologies
, 155
, Article 104291. 10.1016/j.trc.2023.104291.
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Abstract
Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between subsequent choices, oversimplifying the scheduling process. In this paper we introduce OASIS, an integrated framework to simulate activity schedules by considering all choice dimensions simultaneously. We present a methodology for the estimation of the parameters of an activity-based model from historic data, allowing for the generation of realistic and consistent daily mobility schedules. The estimation process has two main elements: (i) choice set generation, using the Metropolis-Hasting algorithm, and (ii) estimation of the maximum likelihood estimators of the parameters. We test our approach by estimating parameters of multiple utility specifications for a sample of individuals from a Swiss nationwide travel survey, and evaluating the output of the OASIS model against realised schedules from the data. The results demonstrate the ability of the new framework to simulate realistic distributions of activity schedules, and estimate stable and significant parameters from historic data that are consistent with behavioural theory. This work opens the way for future developments of activity-based models, where a great deal of constraints can be explicitly included in the modelling framework, and all choice dimensions are handled simultaneously.
| Type: | Article |
|---|---|
| Title: | OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.trc.2023.104291 |
| Publisher version: | https://doi.org/10.1016/j.trc.2023.104291 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Activity-based modelling, discrete choice modelling, parameter estimation, choice set generation, maximum likelihood estimation, simulation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10176178 |
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