A Formulation and Solution Algorithm for Fuzzy Dynamic Traffic Assignment Model

How to model traveler’s perception of travel time is always an important issue in the development of traffic assignment models. Since travelers rarely have perfect knowledge of the road network or of the traveling conditions, they choose routes based on their perceived travel times. Traditionally, travelers’ perceived travel times are treated as random variables, leading to the stochastic traffic assignment problem. However, uncertain factors are also observed in the subjective recognition of travelers for travel times, which can be illustrated as fuzzy variables. Therefore, in this paper, we propose a fuzzy dynamic traffic assignment model taking account of the imprecision and the uncertainties in the route choice process. By modeling the expressions of perceived travel times as fuzzy variables, this model makes possible a more accurate and realistic description of travelers’ route choice process than its deterministic or stochastic counterparts. We give the definition of fuzzy perceived link travel time and fuzzy perceived path travel time, and employ a fuzzy shortest path algorithm to find the group of fuzzy shortest paths and assign traffic to each of them using the so-called C-Logit method. We also compare the results of our proposed model with those from stochastic dynamic traffic assignment model, and demonstrate that the impact of Advanced Traveler Information Systems (ATIS) on the traveler’s route choice process can be readily incorporated in our proposed model.