Arrival Time Based Traffic Signal Optimization for Intelligent Transportation Systems

Road Transportation is a crucial component of today´s society, which drives several facets of our lives. The goal of intelligent transportation systems (ITS) is to improve the effectiveness, efficiency, and safety of the transportation system. Traffic signals are an elementary component of all road transportation systems. In order to maximize the productivity of a city, traffic signals must be able to efficiently control the flow of vehicles. Traditionally, current traffic signal optimization is based on traffic arrival rates, either estimated or forecasted. In this paper, we illustrate that arrival time based solutions can outperform arrival rate based approaches. To the best of our knowledge, this is the first work that exploits arrival times of vehicles to improve traffic signal efficiency in order to reduce stopped delays and fuel consumptions, thus in turn reducing greenhouse gases and emissions. We show that arrival time knowledge can be utilized in realizing drastic gains in sparse load scenarios and significant gains in moderate load scenarios. The performance improvement translates to reducing stopped delays by over 40,000 hours daily and in reducing fuel consumption by over 650 gallons/signal/day.