Center for Traffic Simulation Studies

Traffic assignment has received much attention since the 1950s. Stochasticity, dynamics and fuzziness are three characteristics of traffic assignment. Since drivers usually do not have perfect information about traffic conditions, they choose their route based on perceived travel time. Traditional traffic assignment models can only capture the stochastic and dynamic features of traffic assignment and cannot represent the fuzziness of drivers' perceptions over travel time. In this paper, we present a new fuzzy dynamic traffic assignment model. We use a fuzzy shortest path algorithm to find the group of fuzzy shortest paths and assign traffic to each of them using the C-logit method. We also compare results of our proposed model with those from a traditional stochastic dynamic traffic assignment (SDTA) model.