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Journal Article

Citation

Kim M, Kim HK. Transp. Res. D Trans. Environ. 2020; 85: e102464.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.trd.2020.102464

PMID

unavailable

Abstract

The traffic demands in major cities are increasing, causing significant congestion and greenhouse gas (GHG) emissions around signalized intersections. Many researchers have attempted to mitigate these effects by optimizing traffic signal systems, but this study introduces a red time traffic signal countdown timer (TSCT) to help drivers decide to control vehicle idling and investigates its environmental benefits. The research framework consists of three modules: the development of a drivers' behavior model; implementation of vehicle idling control; and the estimation of GHG emissions. This framework has been materialized in Haeundae-gu in Busan, Korea as a case study. The results revealed reductions of GHG emissions by 10.9% and 56.8% of the stationary and idling vehicles, respectively, proving the environmental benefit of the red time TSCT with the drivers' voluntary involvement. This study presents a logical basis for the assertive deployment of the red time TSCT in major cities suffering from GHG emissions.


Language: en

Keywords

Binary logistic regression model; Greenhouse gas emission; Microscopic simulation model; Motor vehicle emission simulator; Traffic signal countdown timer; Vehicle idling

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