Longitudinal Driving Behavior under Adverse Conditions: A Close Look at Psycho-spacing Models

Abstract

Adverse weather conditions have been shown to have a substantial impact on traffic flow operations following substantial adaptation effects in driving behavior. In quantifying these effects psycho-spacing models may be used. In this contribution it was examined to what extend adverse weather conditions influence the position of action points in the relative speed-spacing plane in these models, the relationship between speed of the lead vehicle and relative speed at the action points and acceleration as well as jumps in acceleration. In this regard a driving simulator experiment with a Repeated Measures design was performed in which fog was simulated in the experimental condition. Using a new data analysis technique followed from the results that substantial differences were present with regard to the position of action points. Furthermore a substantial influence of fog on the relationship between speed of the lead vehicle and relative speed at the action points was found. Finally, a substantial influence of this adverse weather condition on acceleration and jumps in acceleration was established. Furthermore, a large degree of driver heterogeneity was observed with regard to the position of action points as with regard to (jumps in) acceleration at the action points. It is recommended to develop a data driver stochastic car-following model based on psycho-spacing theory.