Autonomous vehicles need the ability to predict the trajectory of surrounding vehicles, so as
to make a rational decision planning, improve driving safety and ride comfort. In this paper, a …

Autonomous driving decision-making is a challenging task due to the inherent complexity
and uncertainty in traffic. For example, adjacent vehicles may change their lane or overtake …

This work examines the hypothesis that partially observable Markov decision process
(POMDP) planning with human driver internal states can significantly improve both safety …

As pedestrians are one of the most vulnerable traffic participants, their motion prediction is of
utmost importance for intelligent transportation systems. Predicting motions of pedestrians is …

To reduce the number of collision fatalities at crossroads intersections, many countries have
started replacing intersections with non-signalized roundabouts, forcing the drivers to be …

It is essential for autonomous vehicles at level 3 or higher to have the ability to predict the
trajectories of surrounding vehicles to safely and effectively plan and drive along trajectories …

Accurate and robust recognition and prediction of traffic situation plays an important role in
autonomous driving, which is a prerequisite for risk assessment and effective decision …

Autonomous driving vehicles can reduce congestion and improve safety while increasing
traffic efficiency. To reflect the quality of driving more comprehensively, the driving safety …

Turning behaviour is one of the most challenging driving manoeuvres that take place at
intersections. Autonomous vehicles (AVs) are often overly conservative in these scenarios …

When modeling decision-making in autonomous vehicles (AVs), only a fraction of the
required information is usually available at the start due to the presence of uncertainty in the …