19 citations · 31 across the 4 of their papers we have counts for
4 papers
Comparison of Pedestrian Prediction Models from Trajectory and Appearance Data for Autonomous Driving
Anthony Knittel, Morris Antonello, John Redford +1
The ability to anticipate pedestrian motion changes is a critical capability for autonomous vehicles. In urban environments, pedestrians may enter the road area and create a high r…
DiPA: Probabilistic Multi-Modal Interactive Prediction for Autonomous Driving
Anthony Knittel, Majd Hawasly, Stefano V. Albrecht +2
Accurate prediction is important for operating an autonomous vehicle in interactive scenarios. Prediction must be fast, to support multiple requests from a planner exploring a rang…
Beyond RMSE: Do machine-learned models of road user interaction produce human-like behavior?
Aravinda Ramakrishnan Srinivasan, Yi-Shin Lin, Morris Antonello +9
Autonomous vehicles use a variety of sensors and machine-learned models to predict the behavior of surrounding road users. Most of the machine-learned models in the literature focu…
Sparse, guided feature connections in an Abstract Deep Network
Anthony Knittel, Alan Blair
We present a technique for developing a network of re-used features, where the topology is formed using a coarse learning method, that allows gradient-descent fine tuning, known as…