A Link-Based Stochastic Traffic Assignment Model for Travel Time Reliability Estimation

Chong Wei (), Yasuo Asakura () and Takamasa Iryo ()
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Chong Wei: Tokyo Institute of Technology
Yasuo Asakura: Tokyo Institute of Technology
Takamasa Iryo: Kobe University

Chapter Chapter 12 in Network Reliability in Practice, 2012, pp 209-221 from Springer

Abstract: Abstract This study proposes a link-based stochastic traffic assignment model that aims to capture the stochastic nature of link traffic flow, and the output of the model is the probability distribution of link traffic flows. We consider the link traffic flow variables as random variables. The distribution of the random variables is formulated as a conditional probability distribution for a given assumption: the traffic network is in stochastic user equilibrium. The conditional probability distribution is deduced from a Bayesian theorem, referred to as posterior probability distribution. A Markov chain Monte Carlo(MCMC) method is applied to simulate samples from the posterior distribution. Characteristics such as the means and variances of link traffic flows as well as travel time reliability are estimated from the simulated samples.

Keywords: Travel Time; Traffic Flow; Route Choice; Markov Chain Monte Carlo Method; Proposal Distribution (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:trachp:978-1-4614-0947-2_12

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DOI: 10.1007/978-1-4614-0947-2_12

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