Traffic Signal Optimization of Urban Arterial Network by Vehicle-to-Infrastructure

Urbanization has occasionally been linked to negative consequences. Traffic light system in urban arterial networks plays an essential role to the operation of transport systems. The availability of new Intelligent Transportation System innovations paved the way for connecting vehicles and road infrastructure. GLOSA, or the Green Light Optimal Speed Advisory, is a recent integration of vehicle-to-everything (v2x) technology. This thesis emphasized GLOSA system's potential as a tool for addressing traffic signal optimization. GLOSA serves as an advisory to drivers, informing them of the speed they must maintain to reduce waiting time. The considered study area in this thesis is the Via Aurelio Saffi – Via Emilia Ponente corridor in the Metropolitan City of Bologna which has several signalized intersections. Several simulation runs were performed in SUMOPy software on each peak-hour period (morning and afternoon) using recent actual traffic count data. GLOSA devices were placed on a 300m GLOSA distance. Considering the morning peak-hour, GLOSA outperformed the actuated traffic signal control, which is the baseline scenario, in terms of average waiting time, average speed, average fuel consumption per vehicle and average CO2 emissions. A remarkable 97% reduction on both fuel consumption and CO2 emissions were obtained. The average speed of vehicles running through the simulation was increased as well by 7% and a time saved of 25%. Same results were obtained for the afternoon peak hour with a decrease of 98% on both fuel consumption and CO2 emissions, 20% decrease on average waiting time, and an increase of 2% in average speed. In addition to previously mentioned benefits of GLOSA, a 15% and 13% decrease in time loss were obtained during morning and afternoon peak-hour, respectively. Towards the goal of sustainability, GLOSA shows a promising result of significantly lowering fuel consumption and CO2 emissions per vehicle.