Use of Drivers’ Jerk Profiles in Computer Vision–Based Traffic Safety Evaluations

Abstract

A traffic conflict is usually composed of a chain of events in which at least one of the involved road users performs some sort of evasive action to avoid a collision. An evasive action usually involves powerful braking, which leads to sudden, negative change in acceleration (deceleration). The temporal dynamics (variation over time) of the acceleration of a vehicle is represented by the jerk profile. More formally, jerk is the derivative of the acceleration. In the case of an evasive action by braking, the jerk profile is characterized by strong, negative values. This study examined two issues in the quest to understand the benefits of evasive action analysis. The first issue was whether jerk profiles can be used to identify critical traffic events (conflicts). The second issue addressed the validity of the assumption that the deceleration profile is inadequate as a stand-alone measure for conflict identification. Automated video analysis was used to collect traffic data and analysis was applied on two data sets with distinct traffic patterns. The study revealed a significant difference between the jerk behavior of the groups of drivers involved in conflictive and normal traffic interactions. It also showed instances in which automated jerk evaluation was successful in finding conflicts undetected by conventional conflict indicators. The same could not be demonstrated for the road users’ deceleration behavior. These findings support earlier studies on the shortcomings of the use of deceleration data for conflict identification.