The environmental effects of the traffic are highly dependent on the driving modes, which is mainly observed at signalized intersections (Rakha and Ahn, 2004, Rakha et al., 2000). Pandian et al., 2009, Marsden et al., 2001 reported that the emissions from idling vehicles at signalized intersections can have fatal health effects for pedestrians and can deteriorate the air quality in urban areas. Section snippets Review of existing research
These three modules are integrated and implemented centered on Module 2.
#Traffic light countdown timers simulator
This study developed a novel research framework consisted of three modules: modeling drivers’ behavior model regarding the TSCTs with a stated preference survey (SP survey) (Module 1), implementation of controlling vehicle idling in the mobility simulator (i.e., VISSIM) coupled with the drivers’ behavior model (Module 2), and estimation of the reduced GHG emissions with the emission simulator (i.e., MOVES) (Module 3). Their decision to control vehicle idling can be affected by their socioeconomic characteristics, the distance to the stop line, and the remaining red time.
#Traffic light countdown timers drivers
In other words, drivers informed of the remaining red time through the TSCT are expected to control vehicle idling, resulting in the reduction of GHG emissions. While most research into the TSCTs has been focused on their effect on traffic safety (e.g., a reduction in the number of red-light violations) and traffic efficiency (e.g., improved intersection capacity) (Ma et al., 2010, Islam et al., 2016, Fu et al., 2016, Jou et al., 2011), this study investigates their environmental effect on the reduction of GHGs emitted by idling vehicles. Considering this, this study introduces one specific traffic signal countdown timer (TSCT) particularly for red traffic signal during a signal cycle as a means to inform drivers of the amount of remaining red time. One of the most effective ways to reduce GHG emissions from idling vehicles may be to enable drivers to voluntarily control vehicle idling while waiting in the queue at signalized intersections. To address this, several sophisticated technologies and research efforts such as stop-start techniques and traffic signal optimization (Rakha and Ahn, 2004, Rakha et al., 2000, Lv et al., 2013, Shen, 2018) have been attempted and fuel economy and emission regulations have been implemented as well. However, vehicle idling is inevitable as vehicles have to wait for the green time at signalized intersections. generates approximately 30 million tons of CO 2 every year from idling vehicles which would be equivalent to taking 5 million vehicles off the road (U.S.
Most developed countries are striving to reduce the amount of greenhouse gas (GHG) emitted by vehicles in major cities. This study presents a logical basis for the assertive deployment of the red time TSCT in major cities suffering from GHG emissions. 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 framework has been materialized in Haeundae-gu in Busan, Korea as a case study. 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. 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 traffic demands in major cities are increasing, causing significant congestion and greenhouse gas (GHG) emissions around signalized intersections.
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