The representation of the interrelated choice of route and departure time within a discrete choice model presents important theoretical and practical problems for modellers. The model must be able to represent the nature of the choice process and it must be able to take account of the complex patterns of correlations between the available options. Such correlations involve overlapping routes and substitutability between departure times that are close together. Recent developments in behavioural modelling have established the practicality of a wide range of model forms. Several of these are based within the family of generalised logit models, such as nested logit, paired comparisons, cross-nested and ordered logit models. Other models are based on the normal distribution, such as the multinomial probit model, or on 'hybrid' forms, such as the error components logit (mixed logit) model. It is the aim of this paper to examine how this range of model forms is able to deal with the combined route and departure time problem in the context of a simulated data set. The benefit of the research lies in an improved ability to explain and predict the impact of network travel time changes and variability. Travel time variability is increasingly recognised as a key influence on both departure time and route choices. This paper is the fourth in a series of papers arising from research conducted as part of a Research Council-funded project investigating the potential of the error component logit model for the study of drivers' route and departure time choice. For the covering abstract see ITRD E124693.
Samenvatting