Modeling Car-Following Behavior with Different Acceptable Safety Levels

Abstract

In normal car-following (CF) states, the minimum safe braking distance (MSBD) is virtually an unmeasurable variable, mainly due to the diversity of drivers’ reaction times and vehicles’ braking performance. The average MSBD regarding the reaction time and decelerations as constant values is sometimes greater than the distance used for safe braking of the following vehicle when the leading vehicle applies an emergency brake, which is named the short-distance CF behavior. The short-distance CF conveys that drivers adopt strategies of lower acceptable safety levels, which can be applied to intelligent connected technology (ICT). The objective of this paper was to extend the CF model to accommodate manual driving behavior on the state of different safety levels, and to analyze road traffic flow in the environment from manual driving to high-level intelligent driving with different delays. First, the cognitive bias variable was defined as the ratio of the actual braking distance available to the average MSBD to indirectly analyze different safety levels. Second, the Gipps model was extended, depending on the cognitive bias variable threshold and the duration length of the short-distance CF state, to reproduce driving behaviors with different acceptable safety levels more accurately by numerical simulation. Finally, using models to numerically simulate the impact of vehicles on road traffic flow was carried out. CF behaviors with lower acceptable safety levels under manual driving conditions increase traffic efficiency, and road capacity and safety are significantly improved due to ICT enabling a shortened reaction time. The short-distance driving applied to ICT is expected to be a strategy for traffic congestion mitigation.