Intersection Signal Control Multi-Objective Optimization Based on Genetic Algorithm

Abstract

A signal control intersection increases not only vehicle delay, but also vehicle emissions and fuel consumption in that area. Because more and more fuel and air pollution problems have arisen recently, an intersection signal control optimization method which aims at reducing vehicle emissions, fuel consumption and vehicle delay is greatly needed. This paper proposes a signal control multi-object optimization method to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously at an intersection. The optimization method combines Paramics microscopic traffic simulation software, Comprehensive Modal Emissions Model (CMEM), and genetic algorithm. An intersection in Haizhu District, Guangzhou, is used for a case study. The result of the case study shows the optimal timing scheme obtained from this method is better than the Webster timing scheme.

Nonlinear Decision Rule Approach for Real-Time Traffic Signal Control for Congestion and Emission Mitigation

“…Zhang et al (2013) use the cell transmission model to describe traffic dynamics and vehicle emissions, and devise a signal optimization scheme that takes into account pollutant dispersion affected by weather conditions. Zhou and Cai (2014) develop a multi-objective optimization method based on microscopic traffic simulation at a single intersection, A modal emission and fuel consumption model is used in conjunction with the genetic algorithm to minimize vehicle delay, exhaust emission and fuel consumption at the same time. Osorio and Nanduri (2015) propose a meta-model, simulation-based approach to optimize fixed timing for dynamic traffic networks by incorporating dynamic traffic assignment models.…”

Signal timing optimization to minimize fuel consumption

“…Optimizacijom parametara rada svetlosnih signala primenom genetskog algoritma sa ciljem minimiziranja emisija štetnih materija, potrošnje goriva i vremenskih gubitaka su se bavili Zhou & Cai (2014). Kriterijumska funkcija optimizacije je predstavljala ukupne troškove, čije su komponente troškovi potrošnje goriva, troškovi emisije štetnih materija i troškovi vremenskih gubitaka na signalisanim raskrsnicama.…”

Multi-objective traffic signal optimization using 3D mesoscopic simulation and evolutionary algorithms

“…The authors in [35] used genetic algorithms to construct and improve the travel time prediction intervals for buses. Multi-objective optimization using GAs has also been successfully applied for road diet plans within transportation networks in [36], or to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously, in an urban intersection from China [37].…”