Dynamic Traffic Assignment Model Considering Drivers' Unfamiliarity with Network Layout

摘要

Most existing dynamic traffic assignment modelsassume that drivers have sufficient knowledge on roadwaynetworks. However, past experiments have show n that drivers'familiarity with the network layout is an essential component inroute selections. In this paper, the concept of recognition level isdefined to categorize drivers based on their unfamiliarity of thenetwork and of the alternative routes between origins anddestinations. Each catalog is assigned a specific utility functionthat is dependent on travel time, length of route and recognitionparameters. Drivers' route choice behavior is determined bythese specific utility functions. A sample network is firstemployed to test the feasibility of the proposed model, and theresult complies with the specified travel patterns. After that, areal network near downtown Houston is used to further test theproposed model. An experiment is conducted based on theinformation collected from an on-site survey and the on-line real-time traffic map from Houston TranStar. In order to validate thenecessity of the proposed model, a control experiment is carriedout with all parameters being set in the same way as the designedexperiment except that drivers are assumed to be fully familiarwith the network layout and alternative routes. Test results show that the proposed model better fit the real case.