235 citations · 850 across the 47 of their papers we have counts for
53 papers
A Rule-Based Behaviour Planner for Autonomous Driving
Bouchard Frederic, Sedwards Sean, Czarnecki Krzysztof
Autonomous vehicles require highly sophisticated decision-making to determine their motion. This paper describes how such functionality can be achieved with a practical rule engine…
Object Re-Identification from Point Clouds
Benjamin Thérien, Chengjie Huang, Adrian Chow +1
Object re-identification (ReID) from images plays a critical role in application domains of image retrieval (surveillance, retail analytics, etc.) and multi-object tracking (autono…
Revealed Multi-Objective Utility Aggregation in Human Driving
Atrisha Sarkar, Kate Larson, Krzysztof Czarnecki
A central design problem in game theoretic analysis is the estimation of the players' utilities. In many real-world interactive situations of human decision making, including human…
FJMP: Factorized Joint Multi-Agent Motion Prediction over Learned Directed Acyclic Interaction Graphs
Luke Rowe, Martin Ethier, Eli-Henry Dykhne +1
Predicting the future motion of road agents is a critical task in an autonomous driving pipeline. In this work, we address the problem of generating a set of scene-level, or joint,…
XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection
Sunsheng Gu, Vahdat Abdelzad, Krzysztof Czarnecki
Explainable AI (XAI) methods are frequently applied to obtain qualitative insights about deep models' predictions. However, such insights need to be interpreted by a human observer…
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition
Luke Rowe, Benjamin Thérien, Krzysztof Czarnecki +1
In adversarial machine learning, the popular threat model has been the focus of much previous work. While this mathematical definition of imperceptibility successfull…
Interpretable Deep Tracking
Benjamin Thérien, Krzysztof Czarnecki
Imagine experiencing a crash as the passenger of an autonomous vehicle. Wouldn't you want to know why it happened? Current end-to-end optimizable deep neural networks (DNNs) in 3D…
Out-of-Distribution Detection for LiDAR-based 3D Object Detection
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad +5
3D object detection is an essential part of automated driving, and deep neural networks (DNNs) have achieved state-of-the-art performance for this task. However, deep models are no…
A Safety Assurable Human-Inspired Perception Architecture
Rick Salay, Krzysztof Czarnecki
Although artificial intelligence-based perception (AIP) using deep neural networks (DNN) has achieved near human level performance, its well-known limitations are obstacles to the…
SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving
Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki
Self-supervised learning (SSL) is an emerging technique that has been successfully employed to train convolutional neural networks (CNNs) and graph neural networks (GNNs) for more…
A Hierarchical Pedestrian Behavior Model to Generate Realistic Human Behavior in Traffic Simulation
Scott Larter, Rodrigo Queiroz, Sean Sedwards +2
Modelling pedestrian behavior is crucial in the development and testing of autonomous vehicles. In this work, we present a hierarchical pedestrian behavior model that generates hig…
LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection
Matthew Pitropov, Chengjie Huang, Vahdat Abdelzad +2
The estimation of uncertainty in robotic vision, such as 3D object detection, is an essential component in developing safe autonomous systems aware of their own performance. Howeve…
A Driver-Vehicle Model for ADS Scenario-based Testing
Rodrigo Queiroz, Divit Sharma, Ricardo Caldas +4
Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic scenarios that rely on interactions with other vehicles. Although many languages for hig…
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components
Boyue Caroline Hu, Lina Marsso, Krzysztof Czarnecki +3
Machine Vision Components (MVC) are becoming safety-critical. Assuring their quality, including safety, is essential for their successful deployment. Assurance relies on the availa…
Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning
Jaeyoung Lee, Sean Sedwards, Krzysztof Czarnecki
We consider the challenge of finding a deterministic policy for a Markov decision process that uniformly (in all states) maximizes one reward subject to a probabilistic constraint…
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…
I Know You Can't See Me: Dynamic Occlusion-Aware Safety Validation of Strategic Planners for Autonomous Vehicles Using Hypergames
Maximilian Kahn, Atrisha Sarkar, Krzysztof Czarnecki
A particular challenge for both autonomous and human driving is dealing with risk associated with dynamic occlusion, i.e., occlusion caused by other vehicles in traffic. Based on t…
Generalized dynamic cognitive hierarchy models for strategic driving behavior
Atrisha Sarkar, Kate Larson, Krzysztof Czarnecki
While there has been an increasing focus on the use of game theoretic models for autonomous driving, empirical evidence shows that there are still open questions around dealing wit…
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…
The missing link: Developing a safety case for perception components in automated driving
Rick Salay, Krzysztof Czarnecki, Hiroshi Kuwajima +6
Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine…
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…
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…
Solution Concepts in Hierarchical Games under Bounded Rationality with Applications to Autonomous Driving
Atrisha Sarkar, Krzysztof Czarnecki
With autonomous vehicles (AV) set to integrate further into regular human traffic, there is an increasing consensus on treating AV motion planning as a multi-agent problem. However…
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…