activity
20152022
most citedTowards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving

68 citations · 237 across the 20 of their papers we have counts for

collaborators

28 papers

cs.AI20211 cited

A taxonomy of strategic human interactions in traffic conflicts

Atrisha Sarkar, Kate Larson, Krzysztof Czarnecki

In order to enable autonomous vehicles (AV) to navigate busy traffic situations, in recent years there has been a focus on game-theoretic models for strategic behavior planning in…

cs.SE202110 cited

Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual Uncertainty

Tsutomu Kobayashi, Rick Salay, Ichiro Hasuo +3

Formal reasoning on the safety of controller systems interacting with plants is complex because developers need to specify behavior while taking into account perceptual uncertainty…

cs.CV2021

SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

Existing point-cloud based 3D object detectors use convolution-like operators to process information in a local neighbourhood with fixed-weight kernels and aggregate global context…

cs.AI2020

Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations

Henry Chen, Robin Cohen, Kerstin Dautenhahn +2

Autonomous Vehicles (AV) will transform transportation, but also the interaction between vehicles and pedestrians. In the absence of a driver, it is not clear how an AV can communi…

cs.CV202029 cited

Deformable PV-RCNN: Improving 3D Object Detection with Learned Deformations

Prarthana Bhattacharyya, Krzysztof Czarnecki

We present Deformable PV-RCNN, a high-performing point-cloud based 3D object detector. Currently, the proposal refinement methods used by the state-of-the-art two-stage detectors c…

cs.LG2020

The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches

Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay

Deep neural networks (DNNs) have become the de facto learning mechanism in different domains. Their tendency to perform unreliably on out-of-distribution (OOD) inputs hinders their…