15 citations · 43 across the 7 of their papers we have counts for
8 papers
Coupling Intent and Action for Pedestrian Crossing Behavior Prediction
Yu Yao, Ella Atkins, Matthew Johnson Roberson +2
Accurate prediction of pedestrian crossing behaviors by autonomous vehicles can significantly improve traffic safety. Existing approaches often model pedestrian behaviors using tra…
Smart Black Box 2.0: Efficient High-bandwidth Driving Data Collection based on Video Anomalies
Ryan Feng, Yu Yao, Ella Atkins
Autonomous vehicles require fleet-wide data collection for continuous algorithm development and validation. The Smart Black Box (SBB) intelligent event data recorder has been propo…
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation
Yu Yao, Ella Atkins, Matthew Johnson-Roberson +2
Pedestrian trajectory prediction is an essential task in robotic applications such as autonomous driving and robot navigation. State-of-the-art trajectory predictors use a conditio…
Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
Nan Li, Yu Yao, Ilya Kolmanovsky +2
Motivated by the need to develop simulation tools for verification and validation of autonomous driving systems operating in traffic consisting of both autonomous and human-driven…
Realtime Rooftop Landing Site Identification and Selection in Urban City Simulation
Jeremy Castagno, Yu Yao, Ella Atkins
Safe autonomous landing in urban cities is a necessity for the growing Unmanned Aircraft Systems (UAS) industry. In urgent situations, building rooftops, particularly flat rooftops…
The Smart Black Box: A Value-Driven High-Bandwidth Automotive Event Data Recorder
Yu Yao, Ella M. Atkins
Autonomous vehicles require reliable and resilient sensor suites and ongoing validation through fleet-wide data collection. This paper proposes a Smart Black Box (SBB) to augment t…
Unsupervised Traffic Accident Detection in First-Person Videos
Yu Yao, Mingze Xu, Yuchen Wang +2
Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems…
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems
Yu Yao, Mingze Xu, Chiho Choi +3
Predicting the future location of vehicles is essential for safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous driving. This paper introd…