An Activity-based Travel Demand Model for London
A Sivakumar, S Le Vine, J Polak, Imperial College London, UK
In this paper, we report the first large scale empirical application of an activity-based travel demand modelling system for Greater London.
In recent years considerable interest has focused on the development of activity-based travel demand modelling techniques as an alternative to conventional trip-based approaches. Amongst the benefits claimed for these approaches are greater behavioural realism and credibility in prediction of travellers? behavioural response, especially to non-marginal policy measures. Work in North America and in some European countries has led to the development and implementation of significant activity-based demand modelling systems, which are being used for operational policy analysis. In the UK however, the practical application of activity based modelling techniques has been much slower.
In this paper, we report the first large scale empirical application of an activity-based travel demand modelling system for Greater London. The initial application focuses on the development of a household-based activity scheduling model which predicts the activities that household members engage in, and schedules the activities both temporally and spatially. The modelling approach is based on TASHA, a rule-based activity scheduling model originally developed by Roorda et al at the University of Toronto. In addition to customising TASHA to the London study area, we propose to extend the scheduling approach adopted in TASHA to align the treatment of choice behaviour more systematically with random utility theory by relaxing several of the restrictive and deterministic rules in the activity scheduling process.
The paper first presents the process of data assembly for the activity based travel demand model system, which combined time use and travel diary data. This is followed by a description of the model development and application. Initial results from the empirical application of the model are also presented, and validated against the results of the London Transportation Studies (LTS) model. Several policy scenarios are then examined, such as the congestion pricing policy and increased public transport costs, to explore the differences between the traditional trip-based LTS and the activity-based approach.
This research is part of a broader line of enquiry into understanding the ways in which people?s social and economic behaviour in cities result in aggregate energy demands, as an interim step towards developing strategies for improving urban energy efficiency.
Association for European Transport