Abstract

Continuous growth in transportation demand in recent years has led to many traffic issues in urban areas. Among the most challenging are traffic congestion and the associated vehicular emissions. Efficient design of traffic signal control systems is a promising approach for addressing these problems. This research developed a real-time signal control system that optimizes signal timings at an undersaturated isolated intersection by minimizing total vehicular emissions. A combination of previously introduced analytical models based on traffic flow theory was used. These models estimated time spent per operating mode (i.e., time spent accelerating, decelerating, cruising, and idling) as functions of demand, vehicle arrival times, saturation flow, and signal control parameters. Information on vehicle activity was used along with the vehicle-specific power approach that provided emission rates per time spent in each operating mode to estimate the total emissions per cycle. For the evaluation of the proposed method, data from the intersection of Mesogeion and Katechaki Avenues in Athens, Greece, were used. The evaluation was performed through deterministic arrival tests under the assumption of perfect information of vehicle arrival demand and times, as well as through stochastic arrival tests in a microsimulation environment. The results reveal that the proposed emission-based optimization can substantially reduce total emissions at signalized intersections and can also lead to reduced person delay compared with the commonly used vehicle-based optimization for most cases, even under the uncertainty of stochastic arrivals.

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