UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Choice set generation for activity-based models

Pougala, Janody; Hillel, Tim; Bierlaire, Michel; (2021) Choice set generation for activity-based models. In: Proceedings of the 21st Swiss Transport Research Conference. (pp. pp. 1-26). : Swiss Transport Research Conference. Green open access

[thumbnail of Hillel_ Choice set generation for activity-based models_VoR.pdf]
Preview
Text
Hillel_ Choice set generation for activity-based models_VoR.pdf

Download (809kB) | Preview

Abstract

Activity-based models have seen a significant increase in research focus in the past decade. Based on the fundamental assumption that travel demand is derived from the need to do activities and time and space constraints (Hägerstraand, 1970, Chapin, 1974). ABM offer a more flexible and behaviourally centred alternative to traditional trip-based approaches. Econometric — or utility-based — activity-based models (e.g., Adler and Ben-Akiva, 1979, Bowman and BenAkiva, 2001) postulate that the process of activity generation and scheduling can be modelled as discrete choices. Individuals derive a utility from performing activities, and they schedule them as to maximise the total utility of the schedule. In classical discrete choice model applications, the parameters of the utility functions can be estimated by deriving their maximum likelihood estimators. As the likelihood function is defined over a full enumeration of the alternatives in the choice set, this approach is limited for activity-based applications: the set of possible activities and their spatio-temporal sequence is combinatorial and not fully observed by either the decision-maker or the modeller. While discrete choice models can be estimated over samples of alternatives (e.g., Guevara and Ben-Akiva, 2013) an appropriate definition of such sample is as crucial as it is challenging. This paper presents a methodology to sample a choice set of full daily schedules for a given individual and a list of activities. The Metropolis-Hastings algorithm allows us to explore the space efficiently and draw both high and lower probability alternatives for consistent estimation of the parameters. The methodology is tested on a sample of individuals from the 2015 Swiss Mobility and Transport Microcensus (Office fédéral de la statistique and Office fédéral du développement Territorial, 2017).

Type: Proceedings paper
Title: Choice set generation for activity-based models
Event: 21st Swiss Transport Research Conference
Location: Ascona, Switzerland
Dates: 12 Sep 2021 - 14 Sep 2021
Open access status: An open access version is available from UCL Discovery
Publisher version: https://www.strc.ch/2021.php
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Activity-based modelling, Metropolis-Hastings, choice set, simulation, sampling
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.ucl.ac.uk/id/eprint/10174122
Downloads since deposit
0Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item