The less-than-perfect driver: A model of collision-inclusive car-following behavior

Unlike traditional car-following models that preclude vehicle collisions, a proposed model aims to emulate less-than-perfect everyday driving while capturing both safe and unsafe driver behavior. Most important, a realistic perception-response process is incorporated into the model on the basis of developments from visual perception studies. Driver inattention is characterized by a driver-specific variable called the scanning interval. This variable, when coupled with the driver's visual perception-response process, results in variable reaction times that are dependent not only on each driver's individual characteristics but also on instantaneous traffic conditions such as speed and density. This allows closer emulation of real-life human driving and its interactions with surrounding vehicles. Both inter- and intradriver variations in reaction time are captured in a plausible and coherent manner; in earlier studies, reaction time either was presumed fixed or was of limited variability. Furthermore, parameters of this model have a direct physical and behavioral meaning; this implies that vehicle collisions, if any, can be analyzed for behavioral patterns rather than simply being treated as numerical artifacts. In all, 54 detailed and accurate vehicle trajectories extracted from 10 real-life crashes were used to test the model's capability of replicating freeway rear-end collisions. High-resolution crash-free trajectory data were used to validate the model against normal driving behavior. Test results indicate that the proposed model is able to replicate both normal and unsafe driving behavior that could lead to vehicle collisions. The feasibility of integrating the proposed model with existing microsimulators is discussed. The outcome of this work could facilitate studying crash mechanisms at a high-definition microscopic level and could enable safety-related system design improvements and evaluation through microsimulation software.