Pavement Performance

Pavement performance research focuses on predicting and optimizing the lifespan and serviceability of road surfaces, aiming to improve maintenance strategies and reduce costs. Current research heavily utilizes machine learning, particularly deep learning architectures like LSTM and multi-task models, to predict pavement condition indices (PCI) from various data sources, including historical performance data and images. These advanced modeling techniques are integrated with causal inference approaches to better understand the long-term effects of maintenance policies, considering both economic and environmental factors. The resulting improved predictive capabilities and optimized maintenance plans offer significant potential for enhancing road infrastructure management and resource allocation.

Papers

August 4, 2024

A multi-task deep learning approach for lane-level pavement performance prediction with segment-level data
Bo Wang, Wenbo Zhang, Yunpeng LI
Segmentation Label Pavement Condition Lane Level Traffic Prediction Pavement Performance

May 6, 2024

Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements
Lingyun You, Nanning Guo, Zhengwu Long, Fusong Wang, Chundi Si, Aboelkasim Diab
System Performance Causal Inference Maintenance Planning Asphalt Pavement Pavement Challenge Long Term Effect Pavement Performance

October 12, 2023

Image2PCI -- A Multitask Learning Framework for Estimating Pavement Condition Indices Directly from Images
Neema Jakisa Owor, Hang Du, Abdulateef Daud, Armstrong Aboah, Yaw Adu-Gyamfi
Crack Detection Pavement Condition Multitask Learning Framework Pavement Image Pavement Performance

December 20, 2021

A deep reinforcement learning model for predictive maintenance planning of road assets: Integrating LCA and LCCA
Moein Latifi, Fateme Golivand Darvishvand, Omid Khandel, Mobin Latifi Nowsoud
Reinforcement Learning Deep Reinforcement Learning Road Infrastructure Pavement Performance

Pavement Performance

Papers

A multi-task deep learning approach for lane-level pavement performance prediction with segment-level data

Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements

Image2PCI -- A Multitask Learning Framework for Estimating Pavement Condition Indices Directly from Images

A deep reinforcement learning model for predictive maintenance planning of road assets: Integrating LCA and LCCA