Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Intelligent pavement condition survey: Overview of current researches and practices
Automated pavement condition survey is of critical importance to road network management. There are three primary tasks involved in pavement condition surveys, namely data collection, data processing and condition evaluation. Artificial intelligence (AI) has achieved many breakthroughs in almost every aspect of modern technology over the past decade, and undoubtedly offers a more robust approach to automated pavement condition survey. This article aims to provide a comprehensive review on data collection systems, data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey. In particular, the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles. The AI-driven hardware devices including right-of-way (ROW) cameras, ground penetrating radar (GPR) devices, light detection and ranging (LiDAR) devices, and advanced laser imaging systems, etc. These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement. In addition, this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses, measuring pavement roughness, identifying pavement rutting, analyzing skid resistance and evaluating structural strength of pavements. Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies, remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.
Intelligent pavement condition survey: Overview of current researches and practices
Automated pavement condition survey is of critical importance to road network management. There are three primary tasks involved in pavement condition surveys, namely data collection, data processing and condition evaluation. Artificial intelligence (AI) has achieved many breakthroughs in almost every aspect of modern technology over the past decade, and undoubtedly offers a more robust approach to automated pavement condition survey. This article aims to provide a comprehensive review on data collection systems, data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey. In particular, the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles. The AI-driven hardware devices including right-of-way (ROW) cameras, ground penetrating radar (GPR) devices, light detection and ranging (LiDAR) devices, and advanced laser imaging systems, etc. These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement. In addition, this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses, measuring pavement roughness, identifying pavement rutting, analyzing skid resistance and evaluating structural strength of pavements. Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies, remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.
Intelligent pavement condition survey: Overview of current researches and practices
Allen A. Zhang (Autor:in) / Jing Shang (Autor:in) / Baoxian Li (Autor:in) / Bing Hui (Autor:in) / Hongren Gong (Autor:in) / Lin Li (Autor:in) / You Zhan (Autor:in) / Changfa Ai (Autor:in) / Haoran Niu (Autor:in) / Xu Chu (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Pavement Design Reinforced Base Researches
| British Library Conference Proceedings | 2016
Current practices for pavement condition monitoring of road infrastructure in India
| British Library Conference Proceedings | 2010
Precast Concrete Pavement Current Practices—2019
| ASCE | 2019
Precast Concrete Pavement Current Practices — 2019
| TIBKAT | 2019