Instrumentation and testing for road condition monitoring – A state-of-the-art review

Barbieri, Diego Maria; Lou, Baowen

doi:10.1016/j.ndteint.2024.103161

NDT & E International

2024

DOI: 10.1016/j.ndteint.2024.103161

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Instrumentation and testing for road condition monitoring – A state-of-the-art review

Diego Maria Barbieri,

Baowen Lou

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2024

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Cited by 3 publications

References 142 publications

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Non-destructive evaluation of rigid pavements using surface wave tests

Gohil,

Samu,

Kumar

2024

Construction and Building Materials

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Non-destructive evaluation of rigid pavements using surface wave tests

Gohil,

Samu,

Kumar

2024

Construction and Building Materials

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Integración de IMU y GNSS. Estimación del estado del firme

Díaz-Cacho Medina,

Chaves,

García Rivera

2024

JA-CEA

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Este trabajo presenta un sistema de integración de sensores proporcionada por un dispositivo móvil para entornos vehículares. Los sensores integrados son un IMU y un receptor GNSS, que permiten crear un sistema de estimación del estado del firme basado en la variación de la aceleración vertical detectada por el IMU y asociarlo a unas coordenadas geodésicas. Para dotar al sistema técnico de un marco teórico se definen unidades específicas de rugosidad basándose en las muestras de la aceleración medida e inspiradas en las técnicas tradicionales de medida de rugosidad de superficies. El sistema se sirve de una topología ITS tradicional, donde el dispositivo móvil es la OBU con capacidad de transmisión de datos al servidor C-ITS en la nube para ser procesados y determinar los parámetros resultantes. Se realizaron pruebas del sistema en un entorno viario real con resultados satisfactorios, donde se detectaron diferencias en los tipos de firme y hendiduras en la calzada.

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

Khanmohamadi,

Guerrieri

2024

Sustainability

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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.

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Instrumentation and testing for road condition monitoring – A state-of-the-art review

Cited by 3 publications

References 142 publications

Non-destructive evaluation of rigid pavements using surface wave tests

Non-destructive evaluation of rigid pavements using surface wave tests

Integración de IMU y GNSS. Estimación del estado del firme

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

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