Travel time reliability versus safety: A stochastic risk-based acceleration modeling approach

This paper presents a modeling approach to linking stochastic acceleration behavior to travel time reliability on congested freeways. Individual driving behavior is represented by a prospect theory based model that takes into account uncertainty and risk-based evaluation of the gains and losses while following a lead vehicle. Given a set of stimuli (i.e. headways, relative speeds, etc.), the stochastic acceleration model generates acceleration probability distribution functions rather than simple acceleration deterministic values. Such distribution functions may be integrated across the link and across the vehicles at different time steps. Numerical results from a Monte Carlo simulation demonstrate that the proposed microscopic stochastic modeling approach produces a realistic macroscopic traffic flow pattern and can be used to generate travel time distributions. With proper experimental set-up and sensitivity analysis, the travel time distributions may be linked to the drivers' safety-based parameters.