Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

<Previous Article In Volume
Next Article In Volume>

Determine the Optimal Merging Pattern of Toll Plaza

Authors
Yanhao Wang
Corresponding Author
Yanhao Wang
Available Online April 2017.
DOI
10.2991/emim-17.2017.270How to use a DOI?
Keywords
Traffic capacity; Cellular automaton; Queuing theory; Merging pattern
Abstract

With the travel rate increasing, Congestion problems have become more prominent. Thus it's essential to enhance traffic capacity, especially for a toll plaza. This paper tries to optimize the merging pattern of vehicles entering into a certain toll plaza .By using cellular automaton and queuing theory finally draw a conclusion of merging pattern. Cellular automaton is used for entering part of toll plaza while queuing theory is used leaving part of toll plaza.

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/).

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
10.2991/emim-17.2017.270
ISSN
2352-538X
DOI
10.2991/emim-17.2017.270How 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

risenwbib
TY  - CONF
AU  - Yanhao Wang
PY  - 2017/04
DA  - 2017/04
TI  - Determine the Optimal Merging Pattern of Toll Plaza
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1340
EP  - 1344
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.270
DO  - 10.2991/emim-17.2017.270
ID  - Wang2017/04
ER  -