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Smart Intersections and Connected Autonomous Vehicles for Sustainable Smart Cities: A Brief Review

Author

Listed:
  • Masoud Khanmohamadi

    (Department of Civil, Environmental and Mechanical Engineering (DICAM), University of Trento, Via Mesiano 77, 3812 Trento, Italy)

  • Marco Guerrieri

    (Department of Civil, Environmental and Mechanical Engineering (DICAM), University of Trento, Via Mesiano 77, 3812 Trento, Italy)

Abstract

As the importance of safety, efficiency, and sustainability in urban transportation becomes more apparent, intelligent transportation systems are changing and growing. Smart intersections play a crucial role in different parts of this context. Technologies such as Vehicle-to-Everything (V2X) communication, artificial intelligence, multi-sensor data fusion, and more are incorporated into these intersections to improve capacity and safety and reduce damage to the environment. This literature review aims to merge various recent works on advancing smart intersection technologies, their thematic application, methodological approach, and regional implementations. Highlighting adaptive traffic signal control, real-time data processing, and connected autonomous vehicle (CAV) integrations sheds light on the way the effectiveness of transportation in cities can be improved. At the same time, this study tackles questions of cybersecurity and standardization. This review provides insights for researchers, policymakers, and practitioners who aim to improve transportation systems’ sustainability, fairness, and operability.

Suggested Citation

  • Masoud Khanmohamadi & Marco Guerrieri, 2025. "Smart Intersections and Connected Autonomous Vehicles for Sustainable Smart Cities: A Brief Review," Sustainability, MDPI, vol. 17(7), pages 1-32, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3254-:d:1628788
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    References listed on IDEAS

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    1. Saša Zdravković & Filip Dobrić & Zoran Injac & Violeta Lukić-Vujadinović & Milinko Veličković & Branka Bursać Vranješ & Srđan Marinković, 2025. "AI-Driven Safety Evaluation in Public Transport: A Case Study from Belgrade’s Closed Transit Systems," Sustainability, MDPI, vol. 17(18), pages 1-36, September.
    2. Silvia Baeva & Nikolay Hinov & Plamen Nakov, 2025. "Comparative Analysis of Some Methods and Algorithms for Traffic Optimization in Urban Environments Based on Maximum Flow and Deep Reinforcement Learning," Mathematics, MDPI, vol. 13(14), pages 1-40, July.

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