41 citations · 47 across the 6 of their papers we have counts for
6 papers · 1 filter
Determination of building flood risk maps from LiDAR mobile mapping data
Yu Feng, Qing Xiao, Claus Brenner +4
With increasing urbanization, flooding is a major challenge for many cities today. Based on forecast precipitation, topography, and pipe networks, flood simulations can provide ear…
Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention
Hao Cheng, Li Feng, Hailong Liu +3
Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for…
Exploring Dynamic Context for Multi-path Trajectory Prediction
Hao Cheng, Wentong Liao, Xuejiao Tang +3
To accurately predict future positions of different agents in traffic scenarios is crucial for safely deploying intelligent autonomous systems in the real-world environment. Howeve…
Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: a case study of Hurricane Harvey
Yu Feng, Claus Brenner, Monika Sester
With increasing urbanization, in recent years there has been a growing interest and need in monitoring and analyzing urban flood events. Social media, as a new data source, can pro…
AMENet: Attentive Maps Encoder Network for Trajectory Prediction
Hao Cheng, Wentong Liao, Michael Ying Yang +2
Trajectory prediction is critical for applications of planning safe future movements and remains challenging even for the next few seconds in urban mixed traffic. How an agent move…
MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic
Hao Cheng, Wentong Liao, Michael Ying Yang +2
Trajectory prediction in urban mixed-traffic zones (a.k.a. shared spaces) is critical for many intelligent transportation systems, such as intent detection for autonomous driving.…