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     Research Journal of Applied Sciences, Engineering and Technology


Equilibrium Assignment Model with Uncertainties in Traffic Demands

Aiwu Kuang and Zhongxiang Huang
Department of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha 410004, China
Research Journal of Applied Sciences, Engineering and Technology  2013  3:773-777
http://dx.doi.org/10.19026/rjaset.5.5021  |  © The Author(s) 2013
Received: June 07, 2012  |  Accepted: July 04, 2012  |  Published: January 21, 2013

Abstract

In this study, we present an equilibrium traffic assignment model considering uncertainties in traffic demands. The link and route travel time distributions are derived based on the assumption that OD traffic demand follows a log-normal distribution. We postulate that travelers can acquire the variability of route travel times from past experiences and factor such variability into their route choice considerations in the form of mean route travel time. Furthermore, all travelers want to minimize their mean route travel times. We formulate the assignment problem as a variational inequality, which can be solved by a route-based heuristic solution algorithm. Some numerical studies on a small test road network are carried out to validate the proposed model and algorithm, at the same time, some reasonable results are obtained.

Keywords:

Log-normal distribution, stochastic demand, traffic assignment, user equilibrium,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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