Speed and Lateral Vehicle Position Models from Controlled Nighttime Driving Experiment

Abstract

Data from a controlled nighttime driving experiment along a complex, two-lane rural highway in Pennsylvania were used to investigate participant speed and lateral vehicle position. Additionally, the association of pavement marking visibility and the roadway geometry on speed and lateral vehicle position was investigated. The modeling methodology employed considered a variety of single equation and systems methods to estimate models for speed and lateral vehicle position. These include ordinary least-squares regression models, random effects panel data models, a three-stage least-squares technique, and seemingly unrelated regression. These methods were used to determine if there was an endogenous relationship between the speed and lateral vehicle position metrics, and to account for the repeat observations on the research participants in the experiment. The results suggest that endogeneity did not exist in the speed and lateral vehicle position measures in the present experiment. A single-equation random effects panel regression model was an improvement over the ordinary least-squares regression model for the change in speed metric. However, the ordinary least-squares regression model was appropriate for the lateral vehicle position metric. A seemingly unrelated regression model was also specified to account for contemporaneous correlation across the change in speed and lateral vehicle position models. It was found that the roadside hazard rating, horizontal curve direction, vertical grade, horizontal curve radius, upstream horizontal curve radius, and approach tangent length all were associated with vehicle speed on the complex, two-lane rural highway. The horizontal curve direction, roadside hazard rating, vertical grade, horizontal curve radius, and approach tangent length all were associated with lateral vehicle position in the present experiment.