Abstract
This study explores how multi-agent interaction enhances autonomous vehicle (AV) decision-making in dynamic traffic environments. While traditional AV models focus on individual autonomy, real-world traffic scenarios often require collective behavior through inter-agent communication and coordination. To investigate this, we developed a graph-based simulation environment that enables vehicle agents to exchange information and reroute in real time in response to road obstacles. Our findings demonstrate that communication and adaptive rerouting significantly reduce average wait times and improve travel efficiency. Furthermore, we introduce a lightweight memory mechanism—Object Memory Management (OMM)—which allows agents to retain knowledge of previously encountered obstacles. This feature proved critical in avoiding routing loops and redundant decisions. Together, these results highlight the potential of communication- and memory-enhanced agents in creating resilient, cooperative AV systems capable of navigating complex and unpredictable traffic networks.
Advisor
Palmer, Daniel
Department
Computer Science
Recommended Citation
Saifullah, KM Khalid, "Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation Based Study" (2025). Senior Independent Study Theses. Paper 11341.
https://openworks.wooster.edu/independentstudy/11341
Disciplines
Artificial Intelligence and Robotics
Keywords
Multi-Agent Systems, Autonomous Vehicles, V2V Communication, Decentralized Control, Object Memory Management (OMM), Graph-Based Simulation, Adaptive Rerouting, Intelligent Transportation Systems, Agent Coordination
Publication Date
2025
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2025 KM Khalid Saifullah