342 citations · 578 across the 39 of their papers we have counts for
16 papers · 1 filter
A risk model and analysis method for the psychological safety of human and autonomous vehicles interaction
Yandika Sirgabsou, Benjamin Hardin, François Leblanc +5
The rapid advancement of artificial intelligence and autonomous driving technologies has significantly propelled the development of autonomous vehicles (AVs). However, psychologica…
GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation
Efimia Panagiotaki, Georgi Pramatarov, Lars Kunze +1
Testing and validating Autonomous Vehicle (AV) performance in safety-critical and diverse scenarios is crucial before real-world deployment. However, manually creating such scenari…
NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
Efimia Panagiotaki, Daniele De Martini, Lars Kunze +2
This study explores the intersection of neural networks and classical robotics algorithms through the Neural Algorithmic Reasoning (NAR) blueprint, enabling the training of neural…
A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers
Daniel Omeiza, Raunak Bhattacharyya, Marina Jirotka +2
Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (suc…
S-RAF: A Simulation-Based Robustness Assessment Framework for Responsible Autonomous Driving
Daniel Omeiza, Pratik Somaiya, Jo-Ann Pattinson +4
As artificial intelligence (AI) technology advances, ensuring the robustness and safety of AI-driven systems has become paramount. However, varying perceptions of robustness among…
From Feature Importance to Natural Language Explanations Using LLMs with RAG
Sule Tekkesinoglu, Lars Kunze
As machine learning becomes increasingly integral to autonomous decision-making processes involving human interaction, the necessity of comprehending the model's outputs through co…
Risk-aware Trajectory Prediction by Incorporating Spatio-temporal Traffic Interaction Analysis
Divya Thuremella, Lewis Ince, Lars Kunze
To operate in open-ended environments where humans interact in complex, diverse ways, autonomous robots must learn to predict their behaviour, especially when that behavior is pote…
Learning Run-time Safety Monitors for Machine Learning Components
Ozan Vardal, Richard Hawkins, Colin Paterson +4
For machine learning components used as part of autonomous systems (AS) in carrying out critical tasks it is crucial that assurance of the models can be maintained in the face of p…
Extending Structural Causal Models for Autonomous Vehicles to Simplify Temporal System Construction & Enable Dynamic Interactions Between Agents
Rhys Howard, Lars Kunze
In this work we aim to bridge the divide between autonomous vehicles and causal reasoning. Autonomous vehicles have come to increasingly interact with human drivers, and in many ca…
RobotCycle: Assessing Cycling Safety in Urban Environments
Efimia Panagiotaki, Tyler Reinmund, Stephan Mouton +9
This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how road infrastructure influences cyclist behaviour and sa…
Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap
Sule Tekkesinoglu, Azra Habibovic, Lars Kunze
Given the uncertainty surrounding how existing explainability methods for autonomous vehicles (AVs) meet the diverse needs of stakeholders, a thorough investigation is imperative t…
COBRA-PPM: A Causal Bayesian Reasoning Architecture Using Probabilistic Programming for Robot Manipulation Under Uncertainty
Ricardo Cannizzaro, Michael Groom, Jonathan Routley +2
Manipulation tasks require robots to reason about cause and effect when interacting with objects. Yet, many data-driven approaches lack causal semantics and thus only consider corr…
Real-time 3D semantic occupancy prediction for autonomous vehicles using memory-efficient sparse convolution
Samuel Sze, Lars Kunze
In autonomous vehicles, understanding the surrounding 3D environment of the ego vehicle in real-time is essential. A compact way to represent scenes while encoding geometric distan…
OORD: The Oxford Offroad Radar Dataset
Matthew Gadd, Daniele De Martini, Oliver Bartlett +11
There is a growing academic interest as well as commercial exploitation of millimetre-wave scanning radar for autonomous vehicle localisation and scene understanding. Although seve…
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
David Fernández Llorca, Ronan Hamon, Henrik Junklewitz +9
This study explores the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and the impact…
RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model
Jianhao Yuan, Shuyang Sun, Daniel Omeiza +4
We need to trust robots that use often opaque AI methods. They need to explain themselves to us, and we need to trust their explanation. In this regard, explainability plays a crit…