With increasing urban populations (Boyd 2015), also comes higher land resource demands and more concentrated pollution levels. Increasing the efficiency of transportation systems is key to fostering sustainable urban development because it can decrease urban pollution levels, better meet the social demands of its residents, and decrease vehicle fuel consumption – encompassing the three pillars of sustainability: social, environment, and economic. This study aims to better understand the environmental impact of traffic light coordination and their timing policies in a randomly generated traffic network on an urban area. We focus on the effect of three different stoplight policies on emission and congestion.

Transportation is a basic human need and an area of sustainable development with great potential. The United Nations states that achieving sustainable transportation is a key component in the development of sustainable cities across the world (United Nations 2016). The number of vehicles on the roads are increasing, as are their emission levels (Environmental Protection Agency 2017). In the United States alone, over 263 million vehicles were registered by 2015 (Bureau Of Transportation Statistics 2015).

The coordination of stoplight timing has the potential to mitigate not only traffic-related congestion, but also traffic-related emissions. An acceleration following either a deceleration or a complete stop due to a red light that has turned green is responsible for significantly more carbon dioxide (CO2) emissions than cruising at a constant speed when approaching a green light (Ericsson 2001). Congestion decreases the fuel efficiency of all vehicle types on the road (Bigazzi, Clifton and Gregor 2014). With decreased fuel efficiency comes increased CO2 emissions (Barth et al. 2007). Stoplights are responsible for much of vehicles’ halts and changes in acceleration. Depending on the sequences of the traffic lights and the flow of traffic, the lights can both cause and relieve congestion, especially in large cities because of the high concentration of intersections with traffic lights. Just in New York City there were 12,460 recorded intersections that were stoplight-regulated (NYC DOT 2012), and out of the 3,360 intersections found in the Manhattan borough (Howe 2010), 2,820 of them are operated by traffic lights (NYC DOT 2012).

In this study, three stoplight timing policies are assessed for their effect on vehicle emissions for random traffic scenarios on a given downtown area. Without loss of generality, vehicle emissions are assumed to be primarily caused by acceleration and deceleration. Traffic is modeled using a variation of a cell transition model to capture traffic as density-dependent flows (Daganzo 1995). To block any secondary effects in the system, all vehicles are assumed to have identical characteristics. This study assumes 100% penetration of vehicle autonomy, or in other words driver-less vehicles. It also assumes vehicle-to-infrastructure (V2X) technology, which includes vehicle-to-vehicle (V2V) communication of the vehicles’ locations and speeds as well as communication with other network infrastructure such as traffic lights. These vehicle assumptions aid in the simplicity and accuracy of the cell transmission model application. V2X is also known for its potential to improve traffic safety and decrease idling time (Abboud, Omar and Zhuang 2016). We compare the performance, as captured on the total emission levels of traffic controlled by three stoplight timing policies: a conventionally timed traffic light system, a system with traffic flow-dependent lights, and a light-less system.

Library of Congress Subject Headings

Traffic signs and signals--Control systems--Government policy; City traffic--Planning; Air--Pollution; Automobiles--Environmental aspects; Motor fuels--Environmental aspects

Publication Date


Document Type


Student Type


Degree Name

Sustainable Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)


Ruben Proaño

Advisor/Committee Member

Brian Thorn


RIT – Main Campus

Plan Codes