Mitigating the Impact of Congestion Minimization on Vehicles' Emissions in a Transportation Road Network.

Traffic optimization normally improves flow conditions at the expense of increased vehicles' emissions. This paper proposes a bi-objective optimization approach to address this situation. In contrast to existing literature, this study considers environmental and congestion impacts of Network Design Problems (NDPs) using the Markov chain traffic assignment approach instead of user equilibrium. The NDP model selectively reverses roads' directions to improve network performance. The model is optimized by simultaneously minimizing maximum traffic density and total vehicles' emissions cost using non-dominated sorting genetic algorithm. A realistic city example was used to demonstrate the approach's efficiency. Results showed that a compromise solution between the two objectives is more practical than single-objective optimization solutions. Nomenclature BPR Bureau of public roads CO Carbon Monoxide GA Genetic algorithm GHG Greenhouse gas MCTA Markov chain traffic assignment NDP Network Design Problem NOx Nitrogen oxides TEC Total emissions cost UE User equilibrium VOC Volatile organic compounds NSGA-II Non-dominated sorting genetic algorithm [ABSTRACT FROM AUTHOR]