Krzysztof Czarnecki

A taxonomy of strategic human interactions in traffic conflicts

In order to enable autonomous vehicles (AV) to navigate busy traffic sit...
09/27/2021 ∙ by Atrisha Sarkar, et al. ∙ 0 ∙ share

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Generalized dynamic cognitive hierarchy models for strategic driving behavior

While there has been an increasing focus on the use of game theoretic mo...
09/20/2021 ∙ by Atrisha Sarkar, et al. ∙ 0 ∙ share

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I Know You Can't See Me: Dynamic Occlusion-Aware Safety Validation of Strategic Planners for Autonomous Vehicles Using Hypergames

A particular challenge for both autonomous and human driving is dealing ...
09/20/2021 ∙ by Maximilian Kahn, et al. ∙ 0 ∙ share

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The missing link: Developing a safety case for perception components in automated driving

Safety assurance is a central concern for the development and societal a...
08/30/2021 ∙ by Rick Salay, et al. ∙ 5 ∙ share

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Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual Uncertainty

Formal reasoning on the safety of controller systems interacting with pl...
08/17/2021 ∙ by Tsutomu Kobayashi, et al. ∙ 0 ∙ share

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Self-Attention Based Context-Aware 3D Object Detection

Most existing point-cloud based 3D object detectors use convolution-like...
01/07/2021 ∙ by Prarthana Bhattacharyya, et al. ∙ 9 ∙ share

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Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations

Autonomous Vehicles (AV) will transform transportation, but also the int...
10/10/2020 ∙ by Henry Chen, et al. ∙ 0 ∙ share

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Solution Concepts in Hierarchical Games with Applications to Autonomous Driving

With autonomous vehicles (AV) set to integrate further into regular huma...
09/21/2020 ∙ by Atrisha Sarkar, et al. ∙ 3 ∙ share

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

We present Deformable PV-RCNN, a high-performing point-cloud based 3D ob...
08/20/2020 ∙ by Prarthana Bhattacharyya, et al. ∙ 0 ∙ share

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

Deep neural networks (DNNs) have become the de facto learning mechanism ...
06/25/2020 ∙ by Vahdat Abdelzad, et al. ∙ 35 ∙ share

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Universally Safe Swerve Manoeuvres for Autonomous Driving

This paper characterizes safe following distances for on-road driving wh...
01/30/2020 ∙ by Ryan De Iaco, et al. ∙ 0 ∙ share

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Canadian Adverse Driving Conditions Dataset

The Canadian Adverse Driving Conditions (CADC) dataset was collected wit...
01/27/2020 ∙ by Matthew Pitropov, et al. ∙ 22 ∙ share

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Efficacy of Pixel-Level OOD Detection for Semantic Segmentation

The detection of out of distribution samples for image classification ha...
11/07/2019 ∙ by Matt Angus, et al. ∙ 58 ∙ share

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Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output

Deep neural networks achieve superior performance in challenging tasks s...
10/23/2019 ∙ by Vahdat Abdelzad, et al. ∙ 0 ∙ share

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Out-of-distribution Detection in Classifiers via Generation

By design, discriminatively trained neural network classifiers produce r...
10/09/2019 ∙ by Sachin Vernekar, et al. ∙ 0 ∙ share

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TruPercept: Trust Modelling for Autonomous Vehicle Cooperative Perception from Synthetic Data

Inter-vehicle communication for autonomous vehicles (AVs) stands to prov...
09/17/2019 ∙ by Braden Hurl, et al. ∙ 0 ∙ share

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MLOD: A multi-view 3D object detection based on robust feature fusion method

This paper presents Multi-view Labelling Object Detector (MLOD). The det...
09/09/2019 ∙ by Jian Deng, et al. ∙ 0 ∙ share

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Design Space of Behaviour Planning for Autonomous Driving

We explore the complex design space of behaviour planning for autonomous...
08/21/2019 ∙ by Marko Ilievski, et al. ∙ 0 ∙ share

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Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective

The standard reinforcement learning (RL) formulation considers the expec...
05/24/2019 ∙ by Changjian Li, et al. ∙ 0 ∙ share

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FANTrack: 3D Multi-Object Tracking with Feature Association Network

We propose a data-driven approach to online multi-object tracking (MOT) ...
05/07/2019 ∙ by Erkan Baser, et al. ∙ 0 ∙ share

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Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception

We introduce the Precise Synthetic Image and LiDAR (PreSIL) dataset for ...
05/01/2019 ∙ by Braden Hurl, et al. ∙ 0 ∙ share

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Analysis of Confident-Classifiers for Out-of-distribution Detection

Discriminatively trained neural classifiers can be trusted, only when th...
04/27/2019 ∙ by Sachin Vernekar, et al. ∙ 0 ∙ share

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Learning a Lattice Planner Control Set for Autonomous Vehicles

In this paper, we introduce a method to compute a sparse lattice planner...
03/05/2019 ∙ by Ryan De Iaco, et al. ∙ 0 ∙ share

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A behavior driven approach for sampling rare event situations for autonomous vehicles

Performance evaluation of urban autonomous vehicles requires a realistic...
03/04/2019 ∙ by Atrisha Sarkar, et al. ∙ 0 ∙ share

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Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving

Perception is a safety-critical function of autonomous vehicles and mach...
03/03/2019 ∙ by Krzysztof Czarnecki, et al. ∙ 0 ∙ share

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WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving

Machine learning can provide efficient solutions to the complex problems...
02/11/2019 ∙ by Jaeyoung Lee, et al. ∙ 0 ∙ share

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Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

There is an increasingly apparent need for validating the classification...
12/06/2018 ∙ by Taylor Denouden, et al. ∙ 0 ∙ share

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Calibrating Uncertainties in Object Localization Task

In many safety-critical applications such as autonomous driving and surg...
11/27/2018 ∙ by Buu Phan, et al. ∙ 0 ∙ share

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Urban Driving with Multi-Objective Deep Reinforcement Learning

Autonomous driving is a challenging domain that entails multiple aspects...
11/21/2018 ∙ by Changjian Li, et al. ∙ 8 ∙ share

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Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262

The use of machine learning (ML) is on the rise in many sectors of softw...
08/05/2018 ∙ by Rick Salay, et al. ∙ 0 ∙ share

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Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to int...
07/23/2018 ∙ by Paulius Juodisius, et al. ∙ 0 ∙ share

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Unlimited Road-scene Synthetic Annotation (URSA) Dataset

In training deep neural networks for semantic segmentation, the main lim...
07/16/2018 ∙ by Matt Angus, et al. ∙ 0 ∙ share

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An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software

Machine learning (ML) plays an ever-increasing role in advanced automoti...
09/07/2017 ∙ by Rick Salay, et al. ∙ 0 ∙ share

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Relating Complexity-theoretic Parameters with SAT Solver Performance

Over the years complexity theorists have proposed many structural parame...
06/26/2017 ∙ by Edward Zulkoski, et al. ∙ 0 ∙ share

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SAT-based Analysis of Large Real-world Feature Models is Easy

Modern conflict-driven clause-learning (CDCL) Boolean SAT solvers provid...
06/17/2015 ∙ by Jia Hui Liang, et al. ∙ 0 ∙ share

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Krzysztof Czarnecki

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