Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)

Weibull Distribution Based Multi-class Stochastic User Equilibrium Model

Authors
Yuan Xu, Jing Zhou, Chaoyu Huang, Ke Lu
Corresponding Author
Yuan Xu
Available Online December 2016.
DOI
https://doi.org/10.2991/msota-16.2016.53How to use a DOI?
Keywords
multi-class user; logit model; weibit model; stochastic user equilibrium; network cognitive level
Abstract

This paper aims to develop a multi-class Weibull distribution based route choice model (MWM) to alleviate the drawback from conventional logit model meanwhile take multi-class users into consideration. Specially, this paper distinguishes the user categories according to different cognitive levels of the network based on weibit model. The equivalent mathematical programming formulation for multi-class stochastic user equilibrium (MSUE) is provided and the solution algorithm is given. Numerical examples are also presented to illustrate the equilibrium traffic assignment.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-284-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/msota-16.2016.53How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuan Xu
AU  - Jing Zhou
AU  - Chaoyu Huang
AU  - Ke Lu
PY  - 2016/12
DA  - 2016/12
TI  - Weibull Distribution Based Multi-class Stochastic User Equilibrium Model
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 244
EP  - 248
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.53
DO  - https://doi.org/10.2991/msota-16.2016.53
ID  - Xu2016/12
ER  -