Action-Point in Human Driving

Abstract

When following a vehicle, drivers often change their acceleration at so called action-points (AP), and keep it constant in between them. By investigating a large data-set of car-following data, the state- and time-distributions of the APs is analyzed. In the state-space spanned by speed-difference and distance to the lead vehicle, this distribution is mostly proportional to the distribution of all data-points, with small deviations from this. Therefore, the APs are not concentrated around certain thresholds as is claimed by psycho-physical car-following models. Instead, small distances indicate a slightly higher probability of finding an AP than is the case for large distances. The time-differences between subsequent action-points follow a one-humped distribution that is comparable with a log-normal-distribution. Both results lend support to the hypothesis that APs are not triggered by the crossing of certain perception thresholds.