A fuzzy traffic assignment algorithm based on driver perceived travel time of network links

Traffic assignment is a step of travel demand estimation. Given a trip origin–destination demand matrix, this step determines traffic flow in each link, according to assumptions based on the behavior of drivers. Conventional assignment algorithms, which are mostly based on the Wardrop first principle of user equilibrium, assume that all drivers choose the shortest path to the destination, based on the same travel time computed by travel time functions. However, in reality, driver perception of travel time varies for a specific route. This paper presents a traffic assignment algorithm which assumes that driver perception of travel time affects route choices. Fuzzy set theory is used to define travel time perceived by drivers. A fuzzy equilibrium is suggested for the prediction of network flows. Next, a Fuzzy Incremental Traffic Assignment algorithm (FITA) is developed to utilize route Perceived Travel Time (PTT) for reaching the suggested fuzzy equilibrium. The FITA is used for a real network traffic assignment in Mashhad, which is large city in Iran. Traffic flow that is estimated by a FITA and by conventional algorithms is compared to real observed volumes, which indicate that a FITA is more accurate than conventional traffic flow estimation algorithms.