4 papers
Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions
Henggang Cui, Thi Nguyen, Fang-Chieh Chou +4
Self-driving vehicles (SDVs) hold great potential for improving traffic safety and are poised to positively affect the quality of life of millions of people. To unlock this potenti…
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui +6
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to…
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou +5
Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potentia…
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
Nemanja Djuric, Vladan Radosavljevic, Henggang Cui +5
We address one of the crucial aspects necessary for safe and efficient operations of autonomous vehicles, namely predicting future state of traffic actors in the autonomous vehicle…