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

Traffic Flow Models for Road Network with Intersections

Authors
Zhongwen Chen
Corresponding Author
Zhongwen Chen
Available Online April 2017.
DOI
10.2991/emim-17.2017.311How to use a DOI?
Keywords
Traffic flow model; Road network with intersections; Multi-agent
Abstract

This paper discussed the influence of the self-driving car on the traffic flow, and presented the traffic-density-velocity traffic flow (TDVTF) model and cellular automata model based on multi-agent. From the law of conservation, the single lane, multi-lane TDVTF models and TDVTF models for road network with intersections are established. As for multi-lane TDVTF model, the function of self-driving car proportion with respect to self-driving car density and human- driving car density are obtained.

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 the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
978-94-6252-356-2
ISSN
2352-538X
DOI
10.2991/emim-17.2017.311How 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  - Zhongwen Chen
PY  - 2017/04
DA  - 2017/04
TI  - Traffic Flow Models for Road Network with Intersections
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1542
EP  - 1545
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.311
DO  - 10.2991/emim-17.2017.311
ID  - Chen2017/04
ER  -