Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)

Travel Time Estimation Model Based on Markov Queuing Model

Authors
Zhijian Wang, Zhengying Hou, Haoran Liu
Corresponding Author
Zhijian Wang
Available Online December 2016.
DOI
10.2991/icseee-16.2016.43How to use a DOI?
Keywords
Markov chain; travel time estimation; traffic wave theory; stochastic arrivals
Abstract

To overcome the limitation of the existing models intersection queuing models in which vehicle arrivals are assumed to meet some specific traffic distribution, a new model which based on markov chain and traffic wave theory is proposed to estimate the travel time of vehicles. This model fits the signalized intersection with fixed signal cycle and stochastic vehicle arrivals. At last, the model has experimented on a road of Beijing and the results shows that it has high estimation precision.

Copyright
© 2016, 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 the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
10.2991/icseee-16.2016.43
ISSN
2352-5401
DOI
10.2991/icseee-16.2016.43How to use a DOI?
Copyright
© 2016, 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  - Zhijian Wang
AU  - Zhengying Hou
AU  - Haoran Liu
PY  - 2016/12
DA  - 2016/12
TI  - Travel Time Estimation Model Based on Markov Queuing Model
BT  - Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)
PB  - Atlantis Press
SP  - 232
EP  - 240
SN  - 2352-5401
UR  - https://doi.org/10.2991/icseee-16.2016.43
DO  - 10.2991/icseee-16.2016.43
ID  - Wang2016/12
ER  -