Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

This paper presents a stochastic and predictive control design approach for connected and
automated vehicles (CAVs) in a mixed-autonomy traffic environment, where CAVs are able …

In order to improve the safety, stability, and efficiency of lane change operating, this paper
proposes a multivehicle‐coordinated strategy under the vehicle network environment. The …

For highly automated driving above SAE level 3, behavior generation algorithms must
reliably consider the inherent uncertainties of the traffic environment, eg arising from the …

When the number of automated vehicles (AVs) deployed in public traffic reaches a
significant level, their form of interaction with other AVs, human controlled vehicles and non …

Safe and smooth interaction between other vehicles is one of the ultimate goals of driving
automation. However, recent reports of demonstrative deployments of automated vehicles …

Explainable outcomes in autonomous navigation have become crucial for drivers, other
vehicles, as well as for pedestrians. Creating trustworthy strategies is mandatory for the …

We present a simulation-based approach to assess the safety impacts of vehicles equipped
with Automated Driving Systems (ADS) in mixed traffic with Human-driven Vehicles (HV) …

The traditional conflict resolution algorithm is designed for automated vehicles based on the
premise of the right of way, but there is an unclear road right of way at unsignalized …

Trajectory planning is one of the most important modules of the Autonomous Driving
Systems (ADSs), which aims to achieve a safe and comfortable interaction between the …