Methods of Reducing the Number of Effective ODs in Order to Solve Traffic Equilibrium Problem in Real Life Networks

Solving traffic equilibrium problem, or “traffic assignment”, as the last step in Transportation Planning, distributes OD trip demands of a transportation network over the network links with regard to Traffic Equilibrium Law, and estimates the link flows. In formulations of traffic equilibrium which are based on path saving, the memory consumption is considerably affected by the number of effctive OD pairs (ODs with non zero&#10demand), thus making it impossible to solve a real life transportation problem in a computer’s conventional memory. This paper attempts to present some methods to show that, reducing the number of effective OD pairs and compensating for the error, it is possible to solve a real life traffic equilibrium problem in a reasonable amount of computer memory and up to an acceptable precision. To do so, the traffic equilibrium problem of the city of Mashhad, as a case of a real life problem, is considered and The Aashtiani complementary algorithm which requires path saving is applied to solve the problem. Solving such a problem in a PC’s conventional memory is normally impossible. Nevertheless, the methods presented in this paper allow us to solve it in a conventional memory. Comparison between the results of these methods with the original answer shows that the errors generated via these methods are quite low and acceptable. A brief comparison is finally made among the different methods.&#10