Search Results for author: John Redford

Found 7 papers, 2 papers with code

Comparison of Pedestrian Prediction Models from Trajectory and Appearance Data for Autonomous Driving

no code implementations25 May 2023 Anthony Knittel, Morris Antonello, John Redford, Subramanian Ramamoorthy

Typical predictors use the trajectory history to predict future motion, however in cases of motion initiation, motion in the trajectory may only be clearly visible after a delay, which can result in the pedestrian has entered the road area before an accurate prediction can be made.

Autonomous Driving Trajectory Prediction

An Active Learning Reliability Method for Systems with Partially Defined Performance Functions

1 code implementation5 Oct 2022 Jonathan Sadeghi, Romain Mueller, John Redford

This enables active learning Gaussian process methods to be applied to problems where the performance of the system is sometimes undefined, and we demonstrate the effectiveness of our approach by testing our methodology on synthetic numerical examples for the autonomous driving domain.

Active Learning Autonomous Driving

Query-based Hard-Image Retrieval for Object Detection at Test Time

1 code implementation23 Sep 2022 Edward Ayers, Jonathan Sadeghi, John Redford, Romain Mueller, Puneet K. Dokania

There is a longstanding interest in capturing the error behaviour of object detectors by finding images where their performance is likely to be unsatisfactory.

Autonomous Driving Image Retrieval +2

Beyond RMSE: Do machine-learned models of road user interaction produce human-like behavior?

no code implementations22 Jun 2022 Aravinda Ramakrishnan Srinivasan, Yi-Shin Lin, Morris Antonello, Anthony Knittel, Mohamed Hasan, Majd Hawasly, John Redford, Subramanian Ramamoorthy, Matteo Leonetti, Jac Billington, Richard Romano, Gustav Markkula

Even though the models' RMSE value differed, all the models captured the kinematic-dependent merging behavior but struggled at varying degrees to capture the more nuanced courtesy lane change and highway lane change behavior.

Autonomous Vehicles

A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation

no code implementations28 Sep 2021 Jonathan Sadeghi, Blaine Rogers, James Gunn, Thomas Saunders, Sina Samangooei, Puneet Kumar Dokania, John Redford

There has been increasing interest in characterising the error behaviour of systems which contain deep learning models before deploying them into any safety-critical scenario.

Autonomous Driving

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