A stochastic process traffic assignment model considering stochastic traffic demand

• Main Authors: Han, Linghui, Sun, Huijun, Wang, David Zhi Wei, Zhu, Chengjuan
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2017
• Subjects: Stochastic process; Day-to-day dynamical model
• Online Access: https://hdl.handle.net/10356/83022; http://hdl.handle.net/10220/43820
• Institution: Nanyang Technological University

In real traffic network, both link capacity and traffic demand are subject to stochastic fluctuations. These random fluctuations are major sources of travel time uncertainty. All existing stochastic process traffic assignment model models considering the uncertainty of travel time are presented with fixed traffic demand. In this study, a stochastic process traffic assignment model is presented to consider stochastic traffic demand. The traffic demand is assumed to be comprised of two groups of travelers: commuters with fixed traffic demand and irregular travelers with discrete random demand. With mild conditions, it is proved that our stochastic process traffic assignment model is ergodic and has a unique stable distribution. An algorithm is given to describe the stochastic process model. By conducting numerical test, we analyze the effect of commuters' memory length, irregular travelers' demand and commuters' perception error on the stable distribution of our model.