posttraumatic stress disorder (ptsd) is a common response to traumatic events. a cognitive model proposed that ptsd becomes chronic when individuals process the trauma in a way that leads to a sense of serious, current threat. the sense of threat arises as an outcome of excessively negative appraisals of the trauma and its sequel and a disturbance of autobiographical memory. variations in the n...

Models that describe the processes by which drivers follow each other in the traffic stream are generally referred to as car-following models. During the past 50 years, driver behavior within the traffic stream has been studied and models that attempt to describe this behavior have been proposed. Car-following models have frequently been developed for the purpose of incorporation with microscop...

2 1094-7167/02/$17.00 © 2002 IEEE IEEE INTELLIGENT SYSTEMS a human-piloted lead car and one autonomous following car. The lead car sends commands and information to the following car. Using this information, the following car can either mimic the lead car’s behavior (for example, steer in the same direction) or react to information (for example, activate its brakes if the lead car is going to s...

road traffic crashes (rtcs) account for great mortality and morbidity rates worldwide, resulting in substantial global burden. factors contributing to rtc generally fall into three categories: environmental, vehicle, and human, with the human factor being by far the leading determinant. obtaining an in-depth exploration of driving behavior and factors underpinning risky driving could be of part...

Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of carfollowing using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common state sequences are extracted from the model and clustered as driving patterns. The Next Generati...

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of ea...