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 better …

One way to increase user acceptance in automated vehicles is to explain their driving
decisions, but current methods still involve human interpretations and are thus prone to …

The safe deployment of autonomous vehicles (AV s) in real world scenarios requires that AV
s are accountable. One way of ensuring accountability is through the provision of …

Explanations in automated vehicles help passengers understand the vehicle's state and
capabilities, leading to increased trust in the technology. Specifically, for passengers of SAE …

The provision of natural language explanations for the predictions of deep-learning-based
vehicle controllers is critical as it enhances transparency and easy audit. In this work, a state …

Inscrutable AI systems are difficult to trust, especially if they operate in safety-critical settings
like autonomous driving. Therefore, there is a need to build transparent and queryable …

The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …

Humans, interacting with automated machines, expect certain behaviors: either because
they have experienced this behavior (eg, driving) or because they build such expectations …

As unmanned vehicles become more autonomous, it is important to maintain a high level of
transparency regarding their behaviour and how they operate. This is particularly important …

The end-to-end learning ability of self-driving vehicles has achieved significant milestones
over the last decade owing to rapid advances in deep learning and computer vision …