7 citations · 13 across the 8 of their papers we have counts for
8 papers
A Simulation Study of Passing Drivers' Responses to the Autonomous Truck-Mounted Attenuator System in Road Maintenance
Yu Li, Bill Wang, William Li +1
The Autonomous Truck-Mounted Attenuator (ATMA) system is a lead-follower vehicle system based on autonomous driving and connected vehicle technologies. The lead truck performs main…
A Multi-tasking Model of Speaker-Keyword Classification for Keeping Human in the Loop of Drone-assisted Inspection
Yu Li, Anisha Parsan, Bill Wang +3
Audio commands are a preferred communication medium to keep inspectors in the loop of civil infrastructure inspection performed by a semi-autonomous drone. To understand job-specif…
Crash Report Data Analysis for Creating Scenario-Wise, Spatio-Temporal Attention Guidance to Support Computer Vision-based Perception of Fatal Crash Risks
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Reducing traffic fatalities and serious injuries is a top priority of the US Department of Transportation. The computer vision (CV)-based crash anticipation in the near-crash phase…
A Virtual Reality-based Training and Assessment System for Bridge Inspectors with an Assistant Drone
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Over 600,000 bridges in the U.S. must be inspected every two years to identify flaws, defects, or potential problems that may need follow-up maintenance. Bridge inspection has adop…
A Gaze Data-based Comparative Study to Build a Trustworthy Human-AI Collaboration in Crash Anticipation
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Vehicles with a safety function for anticipating crashes in advance can enhance drivers' ability to avoid crashes. As dashboard cameras have become a low-cost sensor device accessi…
Towards explainable artificial intelligence (XAI) for early anticipation of traffic accidents
Muhammad Monjurul Karim, Yu Li, Ruwen Qin
Traffic accident anticipation is a vital function of Automated Driving Systems (ADSs) for providing a safety-guaranteed driving experience. An accident anticipation model aims to p…
A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention
Muhammad Monjurul Karim, Yu Li, Ruwen Qin +1
To assist human drivers and autonomous vehicles in assessing crash risks, driving scene analysis using dash cameras on vehicles and deep learning algorithms is of paramount importa…
A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents
Muhammad Monjurul Karim, Yu Li, Ruwen Qin +1
The rapid advancement of sensor technologies and artificial intelligence are creating new opportunities for traffic safety enhancement. Dashboard cameras (dashcams) have been widel…