16 citations · 28 across the 5 of their papers we have counts for
5 papers
Modeling mandatory and discretionary lane changes using dynamic interaction networks
Yue Zhang, Yajie Zou, Yuanchang Xie +1
A quantitative understanding of dynamic lane-changing (LC) interaction patterns is indispensable for improving the decision-making of autonomous vehicles, especially in mixed traff…
Fundamental Diagrams of Commercial Adaptive Cruise Control: Worldwide Experimental Evidence
Tienan Li, Danjue Chen, Hao Zhou +2
Experimental measurements on commercial adaptive cruise control (ACC) vehicles \RoundTwo{are} becoming increasingly available from around the world, providing an unprecedented oppo…
Dampen the Stop-and-Go Traffic with Connected and Automated Vehicles -- A Deep Reinforcement Learning Approach
Liming Jiang, Yuanchang Xie, Danjue Chen +2
Stop-and-go traffic poses many challenges to tranportation system, but its formation and mechanism are still under exploration.however, it has been proved that by introducing Conne…
Cooperative Highway Work Zone Merge Control based on Reinforcement Learning in A Connected and Automated Environment
Tianzhu Ren, Yuanchang Xie, Liming Jiang
Given the aging infrastructure and the anticipated growing number of highway work zones in the United States, it is important to investigate work zone merge control, which is criti…
A Deep Neural Networks Approach for Pixel-Level Runway Pavement Crack Segmentation Using Drone-Captured Images
Liming Jiang, Yuanchang Xie, Tianzhu Ren
Pavement conditions are a critical aspect of asset management and directly affect safety. This study introduces a deep neural network method called U-Net for pavement crack segment…