Traffic Congestion Modeling and Simulation in Front of the University of North Sumatra (USU) Campus Using an Agent-Based Modeling Approach

Abstract

Traffic congestion around the entrance of the University of North Sumatra (USU) campus represents a major issue influenced by several factors, including the presence of street vendors, illegal vehicle parking, public transport (angkot) that frequently stops without proper order, and the movement of both vehicles and pedestrians crossing the road. This research aims to construct and simulate the traffic situation in that area using an Agent-Based Modeling (ABM) approach, which was manually developed through the Python programming language. Each type of vehicle motorcycle, car, public transport, and pedicab is modeled as an individual agent that exhibits specific behaviors such as varying speed, stopping probability, and pause duration, based on observational data obtained from CCTV recordings of the Medan City Transportation Agency’s ATCS system. The simulation covers two main traffic directions, namely Jalan Setia Budi and Jalan Jamin Ginting, and evaluates several intervention scenarios such as adding designated bus stops, organizing street vendors, and managing pedestrian crossings. The outcomes demonstrate that applying a combination of these interventions increases the average vehicle speed by approximately 15-20% compared to the initial condition, implying that the proper management of roadside activities and environmental control significantly reduce traffic congestion. The ABM method proves capable of realistically illustrating traffic dynamics and can serve as a valuable analytical tool for evaluating transportation policies within campus zones and other urban areas.