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Intelligent Pavement Damage Monitoring Research in China [PDF]

IEEE Access, 2019
The development of artificial intelligence technology is of vital significance to the progress of human civilization. Through the development of this aspect in recent years, China has achieved unprecedented gains in equipment and software technology ...
Bing Zhang, Xianlin Liu
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An Exploration of Recent Intelligent Image Analysis Techniques for Visual Pavement Surface Condition Assessment

Sensors, 2022
Road pavement condition assessment is essential for maintenance, asset management, and budgeting for pavement infrastructure. Countries allocate a substantial annual budget to maintain and improve local, regional, and national highways.
Waqar S. Qureshi, Syed Ibrahim Hassan, Susan McKeever, David Power, Brian Mulry, Kieran Feighan, Dympna O’Sullivan   +6 more
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Intelligent pavement condition survey: Overview of current researches and practices

Journal of Road Engineering
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)
Allen A. Zhang, Jing Shang, Baoxian Li, Bing Hui, Hongren Gong, Lin Li, You Zhan, Changfa Ai, Haoran Niu, Xu Chu, Zilong Nie, Zishuo Dong, Anzheng He, Hang Zhang, Dingfeng Wang, Yi Peng, Yifan Wei, Huixuan Cheng   +17 more
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YOLO11-WLBS: an efficient model for pavement defect detection [PDF]

Scientific Reports
Pavement defects pose serious threats to traffic safety, pavement durability, and operational efficiency. To achieve accurate and real-time identification of pavement defects, this study proposes an enhanced lightweight model, YOLO11-WLBS, which ...
Junqi Lin, Pinxin Wang, Yunkai Ruan, Yunqiang Sun   +3 more
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Intelligent identification of pavement cracks based on PSA-Net

Frontiers in Environmental Science, 2023
The identification of pavement cracks is critical for ensuring road safety. Currently, manual crack detection is quite time-consuming. To address this issue, automated pavement crack-detecting technology is required.
Xuan Lin, Jian Zhang, Daifeng Wu, Enhong Meng, Maoyi Liu, Meng Li, Fuliu Gao   +6 more
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Transformer–CNN Hybrid Framework for Pavement Pothole Segmentation [PDF]

Sensors
Pavement surface defects such as potholes pose significant safety risks and accelerate infrastructure deterioration. Accurate and automated detection of such defects requires both advanced sensing technologies and robust deep learning models.
Tianjie Zhang, Zhen Liu, Bingyan Cui, Xingyu Gu, Yang Lu   +4 more
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Piezoelectric Energy Harvesting from Roadways under Open-Traffic Conditions: Analysis and Optimization with Scaling Law Method

Energies, 2022
Piezoelectric energy harvesting from roadways, which converts ambient vibration energy of roads into electric energy, has a wide range of potential applications in intelligent transportation systems.
Yangyang Zhang, Qi Lai, Ji Wang, Chaofeng Lü   +3 more
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A pavement distresses identification method optimized for YOLOv5s

Scientific Reports, 2022
Automatic detection and recognition of pavement distresses is the key to timely repair of pavement. Repairing the pavement distresses in time can prevent the destruction of road structure and the occurrence of traffic accidents.
Keyou Guo, Chengbo He, Min Yang, Sudong Wang   +3 more
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Research on Feature Identification and Trajectory Planning of Pavement Cracks

Applied Sciences, 2023
As the most common method to detect pavement cracks, manual detection has uncontrollable factors such as low efficiency, inconsistent standards and easy to be interfered with by external forces, so it is not suitable for pavement crack detection in today’
Zhaomeng Zhou, Sijie Cai, Bingjing Lin, Jianchun Lin   +3 more
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Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

Buildings, 2021
With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction.
Ziyuan Ma, Jingxiao Zhang, Simon P. Philbin, Hui Li, Jie Yang, Yunlong Feng, Pablo Ballesteros-Pérez, Martin Skitmore   +7 more
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