  We investigate a utility-based approach for driver car-following behavioral
modeling while analyzing different aspects of the model characteristics
especially in terms of capturing different fundamental diagram regions and
safety proxy indices. The adopted model came from an elementary thought where
drivers associate subjective utilities for accelerations (i.e. gain in travel
times) and subjective dis-utilities for decelerations (i.e. loss in travel
time) with a perceived probability of being involved in rear-end collision
crashes. Following the testing of the model general structure, the authors
translate the corresponding behavioral psychology theory - prospect theory -
into an efficientmicroscopic traffic modeling with more elaborate stochastic
characteristics considered in a risk-taking environment. The formulated model
offers a better understanding of drivers behavior, particularly under
extreme/incident conditions.
