Results 31 to 40 of about 288 (174)

Application of Artificial neural network technique for prediction of pavement roughness as a performance indicator

Journal of King Saud University: Engineering Sciences
One of the most important and widely accepted pavement performance and ride quality indicators is the International Roughness Index (IRI). This study investigates the combined effect of pavement distress on flexible pavement performance in two climate ...
Abdualmtalab Abdualaziz Ali, Usama Heneash, Amgad Hussein, Shahbaz Khan   +3 more
doaj   +1 more source

Evaluation and Prediction of Pavement Deflection Parameters Based on Machine Learning Methods

Buildings, 2022
The deflection measurements made using Falling Weight Deflectometers (FWDs) are widely used in the back-calculation of pavement layer moduli. Pavement structural characteristics, changes in temperature, and other related factors exert a significant ...
Xueqin Chen, Qiao Dong, Shi Dong
doaj   +1 more source

Data Driven Pavement Management: Leveraging Machine Learning for Resilient and Sustainable Pavement Condition Prediction

Journal of Engineering, Volume 2026, Issue 1, 2026.
Infrastructure construction and maintenance is very critical in supporting a robust and sustainable transportation system. The primary goal of transportation infrastructure is to ensure safe and efficient movement. However, aging, traffic loads, and environmental conditions all lead to distress on pavement that necessitates the use of predictive models
Touqeer Ali Rind, Shiraz Ahmed, Muhammad Faisal Javed, Muhammad Arsalan Khan, Natt Makul   +4 more
wiley   +1 more source

A Filter Method for Vehicle-Based Moving LiDAR Point Cloud Data for Removing IRI-Insensitive Components of Longitudinal Profile

Remote Sensing
The International Roughness Index (IRI) is calculated from elevation profiles acquired by high-speed profilers or laser scanners, but these raw data often contain measurement noise and extraneous wavelength components that can degrade the accuracy of IRI
Guoqing Zhou, Hanwen Gao, Yufu Cai, Jiahao Guo, Xuesong Zhao   +4 more
doaj   +1 more source

Intelligent Prediction of Pavement Structural Degradation Using a Multimodel Ensemble Learning Approach

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
Accurate prediction of the long‐term structural response of pavement systems is critical for performance evaluation and intelligent maintenance within the context of structural health monitoring. This study proposes an automated machine learning framework to predict the time‐dependent evolution of pavement rutting and deflection using full‐scale ...
Kaiwen Lei, Bingyan Cui, Mian Zhang, Rui Mao, Yongzuo Du, Xingyu Gu, Zhen Liu, Ka-Veng Yuen   +7 more
wiley   +1 more source

Evaluating the Complex Relationship between Environmental Factors and Pavement Friction Based on Long-Term Pavement Performance

Computation, 2022
Long-term pavement performance (LTPP) was used to investigate factors contributing to pavement skid resistance. The random effect model, with a Poisson distribution, was employed to analyze the relationship between various variables and pavement friction
Mahdi Rezapour, Marwan Hafez, Khaled Ksaibati   +2 more
doaj   +1 more source

Adaptive stochastic deterioration modeling for evaluating pavement survey schedules in relation to performance and management cost

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 31, Page 6701-6721, 29 December 2025.
Abstract Pavement performance impacts transportation mobility, safety, and comfort, with timely maintenance relying on field survey data. However, frequent surveys are costly and impractical. This study examines how survey timing and frequency influence maintenance events and pavement deterioration to optimize management strategies.
Zhe Wu, Zijun Xu, Linyi Yao, Lingxiao Shangguan, Guoyang Lu, Dawei Wang   +5 more
wiley   +1 more source

A streamlined approach for probabilistic pavement life‐cycle performance prediction via physics‐informed neural networks

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 28, Page 5136-5152, 28 November 2025.
Abstract Pavement life cycle management (LCM) is essential for assessing the long‐term environmental and economic impacts of roadway infrastructure by means of pavement life cycle assessment (LCA) and life cycle cost analysis (LCCA). However, pavement LCA and LCCA studies frequently overlook the use phase due to the limited availability of performance ...
Jin Li, Wentao He, Huailei Cheng, Haopeng Wang   +3 more
wiley   +1 more source

Shapes of Obstacles in the Longitudinal Road Profile

Shock and Vibration, 2011
A voluminous set of longitudinal road profiles gathered from the Long Term Pavement Performance (LTPP) program was processed using median filtering to separate individual large obstacles from the basic quasi-homogeneous random road unevenness. The shapes
Oldřich Kropáč, Peter Múčka
doaj   +1 more source

A Double‐T model for rutting performance prediction integrating data augmentation and periodic patterns

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 26, Page 4507-4520, 7 November 2025.
Abstract Accurate rutting prediction is crucial for traffic safety and road maintenance, enabling timely interventions and cost‐effective strategies. Such prediction remains challenging, especially with limited data across road segments. As traditional methods struggle in the case of data scarcity and complexity, in this study, a Double‐T model is ...
Xingyi Zhu, Yanan Wu, Chao Wang, Yicong Hu, Luca Rosafalco, Stefano Mariani   +5 more
wiley   +1 more source