EAI Endorsed Transactions on Future Internet 17(12): e5

Research Article

Evaluation of a Traffic-Aware Smart Highway Lighting System

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  • @ARTICLE{10.4108/eai.21-12-2017.153508,
        author={Ahmad M. Mustafa and Omar M. Abubakr and Ahmed H. Derbala and Essam Ahmed and Bassem Mokhtar},
        title={Evaluation of a Traffic-Aware Smart Highway Lighting System},
        journal={EAI Endorsed Transactions on Future Internet},
        volume={17},
        number={12},
        publisher={EAI},
        journal_a={UE},
        year={2017},
        month={12},
        keywords={Smart Highway Lighting, Energy Saving, Wireless Sensor Network, Traffic Modeling, Traffic Simulation.},
        doi={10.4108/eai.21-12-2017.153508}
    }
    
  • Ahmad M. Mustafa
    Omar M. Abubakr
    Ahmed H. Derbala
    Essam Ahmed
    Bassem Mokhtar
    Year: 2017
    Evaluation of a Traffic-Aware Smart Highway Lighting System
    UE
    EAI
    DOI: 10.4108/eai.21-12-2017.153508
Ahmad M. Mustafa1, Omar M. Abubakr1, Ahmed H. Derbala1, Essam Ahmed1, Bassem Mokhtar1,*
  • 1: Department of Electrical Engineering, Faculty of Engineering, Alexandria University, Egypt
*Contact email: bmokhtar@alexu.edu.eg

Abstract

Highway lighting consumes considerable amounts of energy, yet smart lighting techniques provide significant potential for reducing this consumption. This paper introduces a preliminary algorithm, simulation studies and a small-scale hardware prototype for a smart highway lighting management system based on road occupancy. Wireless Sensor Network (WSN) detects the presence of vehicles along the road, and controls lighting accordingly. The system is evaluated through two different simulation studies: using a realistic model for vehicles traffic based on cellular automata (Nagel-Shreckenberg model), and using state-of-the-art Simulation of Urban Mobility (SUMO) traffic simulator. Simulations provide estimation for expected energy saving rates at different cases and scenarios. According to simulation results, the proposed system can save up to 57.4% of power consumption compared to conventional lighting systems.