Investigating the Effects of Mental Workload on Highway Safety

Abstract

The majority of vehicle collisions occur because of human error; in fact, studies have shown that approximately 95% of collisions are caused, at least in part, as a result of human mistakes. Therefore, it is important to study the main causes of human mistakes and develop mitigation strategies to reduce, if not eliminate, these errors from occurring. In this respect, designing highways that balance mental workload is a crucial task that ensures drivers have sufficient time to make appropriate decisions. However, the quantitative relationship between mental workload and collisions is not well documented in the safety literature. Enough evidence exists to support the reasonable conclusion that safety is affected by changes in workload, but there is no quantitative evidence of this effect. Consequently, this paper tries to investigate the relation between mental workload ratings and collisions on highways using data from Alberta, Canada. Horizontal and vertical curve parameters on two-lane, two-way highways were first extracted from LiDAR and GPS data using MATLAB algorithms, and the resulting features were summarized using Civil 3D. The mental workload ratings were assigned based on the presence of four major geometric features, namely, intersections, horizontal curves, vertical curves, and changes in cross-section. The results show that mental workload has a significant effect on safety for two-way, two-lane highways. Furthermore, the findings strongly indicated the need to integrate mental workload into the design process, to not only meet the operational needs of the highway, but also ensure that the geometric layout does not mentally overwhelm drivers.