Modelling driver behaviour: a rationale for multivariate statistics

Abstract

This article provides a discussion of driver behaviour models. Based on a literature survey and using experimental driving simulator data, three types of driver behaviour models are evaluated: motivational models, adaptive control models and trait models. It is shown that motivational models are comprehensive but lack specificity. Many adaptive control models yield precise results but tend to be overly specific and psychologically implausible. Trait models have not been successful in the past and have been criticised for providing post hoc explanations and for the absence of a multifactorial structural approach. We demonstrate that if the right multivariate statistical techniques are used, trait models are suitable for the parsimonious modelling of predictive-valid driver characteristics, thereby taking an intermediate position on a dimension ranging from specific to unspecific models.