MULTI-OBJECTIVE OPTIMIZATION OF TRAFFIC SIGNAL TIMINGS FOR MINIMIZING WAITING TIME, CO2 EMISSIONS, AND FUEL CONSUMPTION AT INTERSECTIONS

Esraa Alkafaji; Husham L. Swadi

doi:10.30572/2018/KJE/150302

Authors

Esraa Alkafaji College of Engineering, University of Basrah https://orcid.org/0009-0001-8992-5215
Husham L. Swadi Department of Electrical Engineering, College of Engineering, University of Basrah,IRAQ,

DOI:

https://doi.org/10.30572/2018/KJE/150302

Keywords:

Genetic Algorithm, Optimization, Signal timing Optimization, SUMO

Abstract

In this paper, we present an optimization strategy that uses Genetic Algorithms (GA) to reduce Waiting Time, CO₂ Emissions, and fuel consumption in a transportation network. The optimization process is performed through simulations using the well-known traffic simulation tool, SUMO (Simulation of Urban MObility). The main objective is to identify the most efficient traffic light timing plan. The proposed GA uses a binary encoding method for signal timing configurations and includes a fitness function to evaluate network performance regarding fuel consumption. The algorithm iteratively builds a set of signal-timing solutions over generations until it converges on the optimal solution. Empirical results show that the GA approach significantly reduces waiting time, reducing CO₂ emissions, and reducing fuel consumption compared to standard signal timing plans. This research makes a significant contribution to the domain of traffic management and provides valuable insights for policymakers and transportation planners looking to reduce the environmental footprint of urban transportation networks.

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