Abstract:
Rising traffic congestion is an inescapable condition in large and growing metropolitan areas across the world. Main entities of a traffic scenario are pedestrians and vehicles. Police make different rules to control the traffic congestions and from an infrastructure development perspective, authorities take actions to construct underground and overhead pedestrian bridges, fences along pavements, islands, etc. However, most of these initiatives end up with unexpected results, mostly since traffic congestion is an emerging macro-level pattern of complex micro-level behaviors of pedestrians and drivers. The study proposes Agent-Based Modeling and Simulation (ABMS) approach, which applies computational methods to study the issues in complex systems. When considering a simulation environment, software agents interact with each other similar to the way real world vehicles and pedestrians behave. This lets us study traffic congestion emerging as a macro-level pattern. Identifying the overall impact of behaviors of drivers and pedestrians to the congestion by extending the previous work, is the aim of this research. The research uses ABMS environment called NetLogo to develop the simulator and Kiribathgoda junction in Western Province, Sri Lanka as the testbed. Coming up with an effective traffic simulator for the unordered traffic conditions in Sri Lanka, which could be used by policy makers to analyze different traffic congestion scenarios and test different solutions to reduce traffic, is the main objective of this research.
