Psycho-spacing models and adverse conditions: A close look at incidents

Abstract

Adverse conditions have been shown to have a substantial impact on traffic flow operations with a substantial impact on network performance. In order to quantify adaptation effects in driving behavior underlying this impact car-following models can be used. In this contribution it was examined to what extent the position of action points in the relative speed — spacing plane as well as acceleration and ‘jumps’ in acceleration in psycho-spacing models is influenced by perception of an incident in the other driving lane. Using two datasets and a new data analysis technique in order to determine the position of the action points, it was concluded that perception of an incident in the other driving lane significantly influences this position. Furthermore it was concluded that acceleration as well as the ‘jumps’ in acceleration at the action points differed substantially between the two datasets. Drivers reacted with smaller accelerations and larger jumps in acceleration to relative speed at the incident site. The fact that the positions of action points in the relative speed-spacing plane as well as the relationship between relative speed, spacing and (jumps in) acceleration differ substantially between the datasets leads to the conclusion that deterministic perceptual thresholds in the original formulation of psycho-spacing models do not hold in reality. It is recommended to develop a data-driven stochastic model based on the principles of psycho-spacing theory, able to describe adaptation effects in case of adverse conditions.