Stochastic User Equilibrium Traffic Assignment Model Based on Travel Time Budget
Aiwu Kuang, Zhongxiang Huang, Wai Kin Victor Chan
Abstract
Aiwu Kuang, Zhongxiang Huang, Wai Kin Victor Chan
Abstract
This paper first analyzes link and route travel time distributions in a degradable road network by assuming a uniform distribution on the capacity of each link. It is postulated that travelers, by acquiring route travel time variability from past experiences, make route decisions based on a travel time budget, which is the summation of the mean route travel time and the safety margin of the travel time. This paper then formulates a novel travel time budget-based stochastic user equilibrium traffic assignment model with multiple user classes and elastic demand as a variational inequality problem. Finally, a numerical example of a small road network is presented to illustrate the properties of the proposed model.
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This paper first analyzes link and route travel time distributions in a degradable road network by assuming a uniform distribution on the capacity of each link. It is postulated that travelers, by acquiring route travel time variability from past experiences, make route decisions based on a travel time budget, which is the summation of the mean route travel time and the safety margin of the travel time. This paper then formulates a novel travel time budget-based stochastic user equilibrium traffic assignment model with multiple user classes and elastic demand as a variational inequality problem. Finally, a numerical example of a small road network is presented to illustrate the properties of the proposed model.
Key concepts: Variational inequality, Travel time, Computer science, Margin (machine learning), Time budget, Mathematical optimization, Distribution (mathematics), Operations research