Advanced Sensor Technologies in CAVs for Traditional and Smart Road Condition Monitoring: A Review

Masoud Khanmohamadi and Marco Guerrieri ()
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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

Sustainability, 2024, vol. 16, issue 19, 1-27

Abstract: This paper explores new sensor technologies and their integration within Connected Autonomous Vehicles (CAVs) for real-time road condition monitoring. Sensors like accelerometers, gyroscopes, LiDAR, cameras, and radar that have been made available on CAVs are able to detect anomalies on roads, including potholes, surface cracks, or roughness. This paper also describes advanced data processing techniques of data detected with sensors, including machine learning algorithms, sensor fusion, and edge computing, which enhance accuracy and reliability in road condition assessment. Together, these technologies support instant road safety and long-term maintenance cost reduction with proactive maintenance strategies. Finally, this article provides a comprehensive review of the state-of-the-art future directions of condition monitoring systems for traditional and smart roads.

Keywords: advanced sensors; Automated Connected Vehicles (CAVs); road monitoring systems; pavement defects; smart roads (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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