Investigating Emission Reduction Benefit From Intersection Signal Optimization

Abstract

Most existing intersection signals are timed based on delay minimization. However, minimizing delay does not necessarily lead to the minimization of emissions at an intersection. No study has focused on the difference or the trade-off between delay based and emissions based signal optimization. Delay-based optimization typically uses macroscopic flow conditions such as traffic demands, saturation flow rates, and average delay. However, the latest emission model, MOVES (Motor Vehicle Emission Simulation), requires second-by-second individual vehicle speed profiles, which makes the model difficult to formulate directly in an emission-based signal optimization problem. This study first develops a methodology to derive vehicle profiles given macroscopic inputs so that MOVES can be applied to estimating emissions. Then an optimization methodology of signal timing is developed and solved with a genetic algorithm. The objective function of the optimization problem considers both delay and emissions, with the signal timing elements being the decision variables. Through a case study, the air quality benefit by reducing vehicle emissions through intersection signal control is demonstrated, and thetrade-off between operational and emission performance measures is investigated. Furthermore, the air quality benefit from intersection signal control is discussed under different scenarios of cycle lengths, percentages of turning vehicles, and traffic demands on major/minor roads.

Multi-objective optimization of traffic signal timing using non-dominated sorting artificial bee colony algorithm for unsaturated intersections

“…A large value will affect the breadth search capabilities of the algorithm, and a small value will affect the depth search capabilities of the algorithm. At the employed bee stage, each food source will be exploited by all the employed bees, and the ABC algorithm is expressed as follows: 12 { , , , (-1,1)…”

“…The onlooker bee searches for the new food source from the selected food sources in accordance with Eq. (12). Greedy rules are also used to decide whether to retain new food sources or not.…”

An optimisation method for train scheduling with minimum energy consumption and travel time in metro rail systems

“…It was first initiated by Holland (1975) and developed by other researches (Chootinan, Chen, and Yang 2005;Sumalee 2007;Sáez et al 2012;Kirchlera and Calvo 2013;Shen et al 2013). Due to its extensive generality, strong robustness, high efficiency and practical applicability, the genetic algorithm has been widely applied to the solution to integer programming problems (Menon 2009;Wu, Close, and Lonardi 2011;Özgüven, Yavuz, and Özbakır 2012) and the research on transportation system Lv, Zhang, and Zietsman 2013;Sharma and Mishra 2013;Li and Lo 2014) .…”

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing

“…For the signal timing optimization, the typical methods of TRRL and ARRP are widely applied, which mainly focus on determining an optimal cycle length and green-time split to reduce delay and stops (Lv, Zhang, and Zietsman 2013;Sun, Benekohal, and Waller 2003). As air pollution has attracted more attentions around the world, more signal control policies were proposed under the consideration of the environmental factors (Rouphail et al 2001;Frey et al 2001;Horiguchi et al 1994;Stevanovic et al 2009;Rakha and Ahn 2004).…”