Abstract:
Traffic congestion in urban areas is a major challenge for city management today. It not only compromises the efficiency and sustainability of transport systems, but also affects citizens' quality of life and the environment. The aim of this thesis is to provide an in-depth analysis of the complex dynamics of urban congestion, its main causes - in particular the intensive use of private cars - and its many negative impacts, with a view to proposing sustainable solutions. The city of Skikda chosen as a case study because of the heavy use of private vehicles, identified as one of the main factors causing congestion. A field survey carried out to gain a better understanding of the reasons why users prefer to use cars, with a view to proposing viable alternatives. Particular
attention paid to promoting public transport as a strategic solution for reducing the use of private cars and, consequently, mitigating the harmful effects of congestion, particularly air pollution and noise pollution. To achieve our objectives, a simulation of the Skikda transport network carried out using SUMO software, enabling a detailed and realistic analysis of traffic conditions. The results highlight the need for integrated and coherent strategies to combat congestion, while underlining the crucial importance of developing efficient and attractive public transport infrastructure. This work also highlights the fundamental role of urban planning in promoting sustainable mobility. Innovative approaches, such as Spatio-Temporal causality trees and fuzzy logic, have used to identify congestion patterns and guide planning decisions based on critical areas of the network.
