Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Objective We aim to bridge the gap between naturalistic studies of driver behavior and
modern cognitive and neuroscientific accounts of decision making by modeling the cognitive …

Introduction: The final failure in the causal chain of events in 94% of crashes is driver error. It
is assumed most crashes will be prevented by autonomous vehicles (AVs), but AVs will still …

This article presents a systematic literature review documenting how technical investigations
have been adapted in value sensitive design (VSD) studies from 1996 to 2023. We present …

Automated driving systems (ADSs) are becoming ubiquitous to reduce the workload of
drivers and improve road safety. However, present-day ADS lacks accurate and effective …

This paper illustrates a 10-year research endeavor on collective learning, a paradigm for
tackling tragedy of the commons problems in socio-technical systems using human-centered …

Laboratory studies of abstract, highly controlled tasks point towards noisy evidence
accumulation as a key mechanism governing decision making. Yet it is unclear whether the …

Much of the debate on the ethics of self-driving cars has revolved around trolley scenarios.
This paper instead takes up the political or institutional question of who should decide how a …

The safety of automated vehicles is principally a question of ethics. As a result, an
understanding of the ethical frameworks that underlie different regulatory, legal and …

Reinforcement Learning (RL) has been widely used to create generalizable autonomous
vehicles. However, they rely on fixed reward functions that struggle to balance values like …