To meet the requirements of scenario-based testing for Autonomous Vehicles (AVs), driving
scenario characterization has become a critical issue. Existing studies have concluded that …

While partially automated vehicles can provide a range of benefits, they also bring about
new Human Machine Interface (HMI) challenges around ensuring the driver remains alert …

The aim of this research is to investigate whether visual feedback alone can affect a driver's
trust in an autonomous vehicle, and in particular, what level of feedback (no feedback vs …

Partially automated vehicles present interface design challenges in ensuring the driver
remains alert should the vehicle need to hand back control at short notice, but without …

Partially automated vehicles present a large range of information to the driver in order to
keep them in-the-loop and engaged with monitoring the vehicle's actions. However, existing …

The primary goal of the paper is to explore the human-vehicle-road interaction mechanism
in the traffic environment and evaluate the traffic environment complexity for unmanned …

This paper proposes a sampling-based multi-dimensional entropy hierarchical evaluation
method to evaluate the environmental complexity for measuring autonomous capabilities of …

Complexity is a key measure of driving scenario significance for scenario-based
autonomous driving tests. However, current methods for quantifying scenario complexity …

Objective At present, most research on driver mental load identification is based on a single
driving scene. However, the driver mental load model established in a road traffic scene is …

Understanding how best to present information inside a partially automated vehicle is a
prevalent challenge in Human–Machine Interface (HMI) design. This chapter contributes to a …