Multi-Agent Autonomous Control Framework for Intelligent Transportation Infrastructure

  • Authors

    • N. Seshagiri Information Technology Pioneer, National Informatics Centre, India. Author

    DOI:

    https://doi.org/10.67228/30716357/IJMRSE-2024PI9E4Q

    Published 04-05-2024

  • Multi-Agent Systems, Autonomous Transportation, Intelligent Infrastructure, Reinforcement Learning, Edge Computing, V2X Communication

    Issue

    Vol. 7 No. 1 (2024)

    Section

    Articles

    How to Cite

    Multi-Agent Autonomous Control Framework for Intelligent Transportation Infrastructure. (2024). International Journal of Modern Research in Science & Engineering, 7(1), 01-17. https://doi.org/10.67228/30716357/IJMRSE-2024PI9E4Q

  • Abstract

    Rapid urbanization and increasing traffic demand require intelligent transportation systems that can adapt in real time. Traditional centralized traffic management is limited in handling dynamic traffic conditions, leading to congestion, delays, higher fuel consumption, and reduced road safety. This study proposes a Multi-Agent Autonomous Control Framework that integrates Multi-Agent Systems (MAS), Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), Graph Neural Networks (GNN), Internet of Things (IoT), Vehicle-to-Everything (V2X) communication, and edge-cloud computing. The framework enables traffic signals, vehicles, roadside units, and other transportation entities to operate as autonomous, cooperative agents that exchange real-time information and make distributed decisions. By analyzing traffic, environmental, and infrastructure data, the proposed architecture dynamically optimizes signal control, routing, and emergency response. Simulation results demonstrate improvements in traffic flow, congestion reduction, travel time, fuel efficiency, road safety, scalability, and system resilience. The framework provides a scalable and intelligent foundation for future smart cities, connected autonomous transportation, and sustainable urban mobility.

  • References

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