most citedAdvancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap

3 citations · 6 across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO2024

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…

cs.HC20243 cited

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…

cs.CY20242 cited

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…

eess.IV2023

LROC-PANGU-GAN: Closing the Simulation Gap in Learning Crater Segmentation with Planetary Simulators

Jaewon La, Jaime Phadke, Matt Hutton +5

It is critical for probes landing on foreign planetary bodies to be able to robustly identify and avoid hazards - as, for example, steep cliffs or deep craters can pose significant…

cs.RO2023

Towards Probabilistic Causal Discovery, Inference & Explanations for Autonomous Drones in Mine Surveying Tasks

Ricardo Cannizzaro, Rhys Howard, Paulina Lewinska +1

Causal modelling offers great potential to provide autonomous agents the ability to understand the data-generation process that governs their interactions with the world. Such mode…

cs.RO2023

Towards a Causal Probabilistic Framework for Prediction, Action-Selection & Explanations for Robot Block-Stacking Tasks

Ricardo Cannizzaro, Jonathan Routley, Lars Kunze

Uncertainties in the real world mean that is impossible for system designers to anticipate and explicitly design for all scenarios that a robot might encounter. Thus, robots design…