Dynamic travel behaviour modelling
Advances in activity generation and scheduling with dynamic discrete choice models
Time: Thu 2024-12-05 09.00
Location: F3 (Flodis), Lindstedtsvägen 26 & 28, Stockholm
Video link: https://kth-se.zoom.us/j/65604479123
Language: English
Subject area: Transport Science, Transport Systems
Doctoral student: Stephen McCarthy , Transport och systemanalys
Opponent: Professor Jeppe Rich, Danmarks Tekniske Universitet
Supervisor: Professor, avd chef Anders Karlström, Centrum för transportstudier, CTS, Transport och systemanalys
QC 20241114
Abstract
Travel behaviour models are key decision support tools for transport planning that point the way to more sustainable and equitable transport systems and land use. Activity generation and scheduling models are a type of travel behaviour model which consider both travel and activity participation in a temporal context, reflecting the importance of time to understanding daily travel decisions. This thesis dynamically models individuals’ activity schedules, with emphasis on reflecting the inherent complexity of travel behaviour and the influences and constraints of space-time contexts.
The thesis applies and extends a dynamic discrete choice model for activity generation and scheduling. Discrete choice models have a well-developed theory encompassing behaviourally-consistent models with estimable, meaningful parameters and microeconomic welfare metrics. Dynamic models endogenously represent time, allowing them to represent interdependencies across time and making their outputs time dependent. The model used in the thesis, Scaper, started from the work of Karlström (2005). Its agents make chronological joint choices of activity purpose, location and timing. They are forward looking, making decisions which maximize their expected future utility. The model generates full-day activity schedules consistent with an agent's space-time constraints.
Within activity generation and scheduling, two papers in the thesis focus on representing the inherent complexity in people's daily travel behaviour patterns. Paper 3 establishes that trip chaining behaviour can be seen as an emergent property of a dynamic decision problem and shows how the resulting dynamic model accurately predicts several facets of trip chaining behaviour including activity purposes, locations, timings and durations. Paper 4 addresses the heterogeneity of individual behaviour using a latent class approach, demonstrating the value of the method and finding evidence for several distinct travel behaviour lifestyles primarily but not solely differentiated by travel mode preferences.
In recognition of the central role of time in activity scheduling, another two papers aim to improve the allocation and valuation of time in the dynamic scheduling context. Paper 1 concentrates on time allocation, improving the dynamic model's predictions of activity duration by making the utility rate of participating in an activity dependent on its elapsed duration. Paper 5 derives two measures of the value of travel time savings in the dynamic context, one dependent on time of day and the other reflecting the expected value of time savings to an individual at the start of the day.
Finally, the thesis focuses on understanding how people's spatial context relates to their travel behaviour. Paper 2 evaluates urban development patterns of centralization vs. dispersion with respect to travel behaviour. The paper uses a work location model developed by Naqavi et al. (2023) paired with Scaper to establish agents' spatial contexts across three scenarios, and analyses different aspects of their predicted travel behaviour. It reveals a tension between planning goals, where centralization leads to more sustainable mode choices while dispersion may help reduce residential segregation.