Development of Short-term Traffic Volume Prediction Models for Adaptive Traffic Control

DOI

10.2991/ameii-15.2015.132How to use a DOI?

Keywords

Short-term Traffic Volume; Prediction Method; Statistics interval; Adaptive Traffic Control

Abstract

This paper aims at establishing an accurate short-term traffic volume prediction method by introducing calculations and characteristics of triple moving average method, single exponential smoothing method, and double exponential smoothing method. Based on field data collected from intersections in Fuzhou, the prediction accuracy of three prediction methods above was calculated respectively at 5-minute, 10-minute and 15-minute statistics intervals and analyzed. Analysis results indicate that prediction methods and statistics intervals have significant impacts on the prediction accuracy. To be specific, the prediction accuracy of double exponential smoothing method is higher than other two methods; The accuracy at 10-minute statistics intervals is higher than that at other two intervals. The research results will provide an accurate volume prediction method for adaptive traffic control.

Copyright

© 2015, 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  - Yiming Bie
AU  - Menglin Yang
AU  - Yulong Pei
PY  - 2015/04
DA  - 2015/04
TI  - Development of Short-term Traffic Volume Prediction Models for Adaptive Traffic Control
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 709
EP  - 712
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.132
DO  - 10.2991/ameii-15.2015.132
ID  - Bie2015/04
ER  -