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This chapter explores a descriptive theory of multidimensional travel behaviour, estimation of quantitative models and demonstration in an agent-based microsimulation.

A descriptive theory on multidimensional travel behaviour is conceptualised. It theorizes multidimensional knowledge updating, search start/stopping criteria and search/decision heuristics. These components are formulated or empirically modelled and integrated in a unified and coherent approach.

The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network.

Based on artificially intelligent agents, learning and search theory and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based micro-simulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.

We review what is known and what is still unknown about the process of revealing the impact of unreliability on travel choices. We do this from the perspective of a demand-modelling practitioner who wishes to allow for the benefits from improved reliability in the assessment of a transport scheme. We discuss the travel responses affected by unreliability, the requirements from the data used to model these responses, the explanatory variables used in these models and the additional information required as input when applying them. One of our findings is that there is a conflict between existing studies in their conclusions about the aversion to early arrival. Another notion is that it is unclear whether the common simplified treatment of the distribution of preferred arrival times is acceptable. We also suggest that the dominance of departure time shifting as a primary response to unreliability might refute the common assumptions about travellers' choice hierarchy, which was established without considering the impact of unreliability; this raises questions about the robustness of assignment models that do not allow time shifting.