Interactions among road, vehicle and driver risk factors for the identification of safety tolerance zone

Road safety is a complex issue influenced by a wide range of factors, including driver characteristics, environmental conditions and traffic variables. The aim of this study was to identify the interactions among road environment, vehicle state and driver behavior for the identification of the Safety Tolerance Zone (STZ). More specifically, the impact of task complexity and coping capacity on crash risk was examined.

Towards that end, a naturalistic driving experiment was conducted, involving 135 drivers and a large database of 31,954 trips was collected. Exploratory analyses, such as Generalized Linear Models (GLMs) were developed and the most appropriate variables associated to the latent variable task complexity and coping capacity were estimated from the various indicators. In addition, Structural Equation Models (SEMs) were used to explore how the model variables were inter-related, allowing for both direct and indirect relationships. Results showed positive correlation of task complexity and coping capacity that implies that driver’s coping capacity increased as the complexity of driving task increases. It was demonstrated that task complexity was positively correlated with risk, indicating that driving during nighttime or in adverse weather conditions can exacerbate the challenges posed by complex tasks, further increasing the likelihood of crashes. On the other hand, coping capacity was negatively correlated with risk, indicating that drivers with higher coping capacity are better equipped to handle challenging driving situations. The integrated treatment of task complexity, coping capacity and risk can improve behavior and safety of all travellers, through the unobtrusive and seamless monitoring of behavior.