Modeling Driver Visual Demand on Complex Horizontal Alignments

Abstract

Visual information is one of the vital elements that affect driver workload. Previous studies have modeled driver visual demand on simple horizontal curves and have found that it is significantly affected by the curve radius. This paper models driver visual demand on complex horizontal alignments that may include simple, compound, and reverse curves. Two sets of visual demand models were developed (curve models and tangent models) using visual demand data collected on 18 highway alignments on a driving simulator. The results show that visual demand is affected by the characteristics of not only the current element but also the preceding element. The characteristics of the preceding element included curve radius, curve direction (right or left), deflection angle, and lane width. As such, the developed models represent important tools for accurately evaluating driver workload on complex horizontal alignments.