342 citations · 578 across the 39 of their papers we have counts for
6 papers · 1 filter
Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profiles
Rhys Howard, Nick Hawes, Lars Kunze
Transparency and explainability are important features that responsible autonomous vehicles should possess, particularly when interacting with humans, and causal reasoning offers a…
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…
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…
Generating and Explaining Corner Cases Using Learnt Probabilistic Lane Graphs
Enrik Maci, Rhys Howard, Lars Kunze
Validating the safety of Autonomous Vehicles (AVs) operating in open-ended, dynamic environments is challenging as vehicles will eventually encounter safety-critical situations for…
Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour
Rhys Howard, Lars Kunze
Autonomous robots are required to reason about the behaviour of dynamic agents in their environment. The creation of models to describe these relationships is typically accomplishe…
From Spoken Thoughts to Automated Driving Commentary: Predicting and Explaining Intelligent Vehicles' Actions
Daniel Omeiza, Sule Anjomshoae, Helena Webb +2
In commentary driving, drivers verbalise their observations, assessments and intentions. By speaking out their thoughts, both learning and expert drivers are able to create a bette…