Search

This paper proposes a conceptual framework that can be used to assess to what extent the findings of road safety evaluation research make sense from a theoretical point of view. The effects of road safety measures are modelled as passing through two causal chains. One of these, termed the engineering effect, refers to the intended effects of a road safety measure on a set of risk factors related to accident occurrence or injury severity. The engineering effect of road safety measures is modelled in terms of nine basic risk factors, one or more of which any road safety measure needs to influence in order to have the intended effect on accidents or injuries. The other causal chain producing the effects of road safety measures is termed the behavioural effect, and refers to road user behavioural adaptations to road safety measures. The behavioural effect is related to the engineering effect, in the sense that certain properties of the engineering effect of a road safety measure influence the likelihood that behavioural adaptation will occur. The behavioural effect of a road safety measure is modelled in terms of six factors that influence the likelihood that behavioural adaptation will occur. The nine basic risk factors representing the engineering effect of a road safety measure, and the six factors influencing the likelihood of behavioural adaptation can be used as checklists in assessing whether or not the findings of road safety evaluation studies make sense from a theoretical point of view. At the current state of knowledge, a more stringent evaluation of the extent to which theory can explain the findings of road safety evaluation studies is, in most cases, not possible.

This paper discusses how the validity of road safety evaluation studies can be assessed by analysing causal chains. A causal chain denotes the path through which a road safety measure influences the number of accidents. Two cases are examined. One involves chemical de-icing of roads (salting). The intended causal chain of this measure is: spread of salt --> removal of snow and ice from the road surface --> improved friction --> shorter stopping distance --> fewer accidents. A Norwegian study that evaluated the effects of salting on accident rate provides information that describes this causal chain. This information indicates that the study overestimated the effect of salting on accident rate, and suggests that this estimate is influenced by confounding variables the study did not control for. The other case involves a traffic club for children. The intended causal chain in this study was: join the club --> improve knowledge --> improve behaviour --> reduce accident rate. In this case, results are rather messy, which suggests that the observed difference in accident rate between members and non-members of the traffic club is not primarily attributable to membership in the club. The two cases show that by analysing causal chains, one may uncover confounding factors that were not adequately controlled in a study. Lack of control for confounding factors remains the most serious threat to the validity of road safety evaluation studies.