Multi-agent Simulation of Traffic Flow and Collision Detection Using GAMA

This research paper presents a comprehensive study on simulating traffic flow and collision detection in a multi-agent framework using the GAMA platform. The aim of the study is to check out the effectiveness of different approaches for modeling traffic behavior and assessing collision risks in a simulated road network. The simulation consists of three main parts: a multi-agent design of traffic flow, random movement of vehicles with increased collision rates, and the application of the Intelligent Driver Model (IDM) for vehicle movement. The results demonstrate the capability of the multi-agent simulation in capturing realistic traffic patterns and evaluating collision risks. The findings contribute to the understanding of traffic dynamics and provide insights for the development of efficient traffic management strategies.