Model for determining the optimal number of lanes in toll stations

DOI

10.2991/fmsmt-17.2017.208How to use a DOI?

Keywords

BP-Neural Networks , Queuing Theory , Goal programming

Abstract

I design a rational toll plaza layout and the congestion problem of the vehicle passing through the toll station is optimized reasonably.By analyzing the behavior process, the arrival distribution and the distribution model of the vehicles at the toll station,we get a reasonable number of conventional lanes, toll stations In the export confluence area, the traffic volume is large and the road is complex. Vehicles in accelerated lane will have a common merger behavior, it often causes the trunk line of traffic flowing disorder, reduces the traveling speed of traffic flow, causes the severe delay, and causes the traffic accident .So the confluence area is the accident-prone areas of the highway. Based on the research on the layout and design of toll station, we use the BP-neural network method to simulate the driver in the confluence of the highway entrance and line decision-making process. By comparing the capacity of the conventional toll plaza with the same conditions, and then comparing the results of the model forecast with the actual situation, the results are more consistent. Thus I obtain a more reasonable merging model.

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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TY  - CONF
AU  - Fei Zheng
PY  - 2017/04
DA  - 2017/04
TI  - Model for determining the optimal number of lanes in toll stations
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 1063
EP  - 1066
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.208
DO  - 10.2991/fmsmt-17.2017.208
ID  - Zheng2017/04
ER  -