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Results of traffic assignment models are the main output of transportation planning studies and decision making for future developments is based on these results. Therefore, accuracy of these models is very important. Despite the mentioned importance, comparing the models and their solving methods to estimate actual traffic volume and network performance measures is rarely considered in previous studies. The traffic assignment process has started from the simplest methods like All-or-Nothing, then it has developed using the rules and supplement assumptions such as Wardrop principles and finally it has evolved by concepts such as Fuzzy theory. Traffic assignment models can be categorized by various factors into several groups: deterministic vs. stochastic, congestion considering vs. unconstrained capacity and being equilibrium or not. The main goal of this paper is a comparative and quantitative analysis of various traffic assignment methods to estimate the observed traffic volumes. In this regard, the main questions that this study seeks to answer is as follows: 1- Do the results of various traffic assignment methods have a significant difference in terms of overall network indices? 2- Is there a significant difference in the accuracy of traffic volume estimation in various traffic assignment methods? In this study various traffic assignment methods such as All-or-Nothing, Incremental, Stochastic, User Equilibrium, Stochastic User Equilibrium and System Optimum have been examined. To compare the results of traffic assignment methods, in addition to estimated link volumes, various performance measures such as vehicle-kilometers traveled, vehicle-hours traveled, fuel consumption and air pollutants emission are also used. In this regard the city of Qazvin is selected as a case study. This city has more than 400 thousands inhabitant, near 46 square kilometers area, 113 traffic analysis zone (TAZ) and its network has 2300 directional links and 1200 nodes. The results of applying these methods in Qazvin city network show that various traffic assignment methods based on User Equilibrium, despite different assumptions, have no significant difference in estimating the overall network performance measures as well as estimating traffic volume in links (correlation between estimated and actual link volumes using all of these models is approximately 0.88). But the other methods, which do not consider equilibrium assumption and volume-delay functions, produce different results (correlation between estimated and actual link volumes using all of these models is approximately 0.70). Although estimated link volumes in some of traffic assignment models are significantly different, overall network performance measures are approximately the same. In all of assignment models the differences between estimated and actual link volumes in average are high which are not negligible (approximately 20 percent). In addition to high average error in estimating link volumes, the distribution of these errors has significantly high standard deviation (approximately 20 percent). In spite of different and complicated assumptions, models and solving algorithms in various traffic assignment methods, on basis of Kolmogorov-Smirnov (K-S) test results, the distribution of links volume estimation error is not significantly different. According to this fact, it seems that should be careful in using the results of traffic assignment models to compare and assess minor network improvement alternatives, such as changing conventional streets function to pedestrian streets, upgrading intersections to interchanges, cross section widening, traffic signals optimization and changing traffic direction in streets.

Keywords: Deterministic Traffic Assignment Methods, Stochastic Traffic Assignment Methods, Route Choice, Discrete Choice, Logit Model

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