Calculating dynamic thresholds for critical time to collision as a safety measure

Surrogate safety measures have been recognised as suitable tools for a warning strategy. As one such measure, the time to collision (TTC) is the time remaining to a collision if the collision course and speed remain unaltered. To apply the TTC in discriminating dangerous situations, a critical threshold (TTC*) must be determined. However, a method for calculating this threshold is yet to be presented. Previously, the critical threshold has been considered as a constant value, but the value of TTC* changes the calculated probability for a crash at each time instant. In this work, a method was developed for calculating TTC* based on driver characteristics, environmental conditions, the type of preceding object and the microscopic traffic parameters of the subject vehicle based on an adaptive neuro fuzzy inference system and motion mechanics. For this purpose, data were first collected from a driving simulator. Then, to compare the collision probability calculated based on a dynamic TTC* (DTTC*) and a static TTC* (STTC*), microscopic traffic data were obtained from Modares highway in Tehran, Iran. Assessments indicated that, statistically, there is a significant difference between DTTC* and STTC* results. This finding might help to enhance the capability of in-vehicle collision-avoidance systems to prevent rear-end collisions.