Human drivers use nonverbal communication and anticipation of other drivers' actions to
master conflicts occurring in everyday driving situations. Without a high penetration of …

Automated driving with human-like driving behavior requires the capability of cooperative
decision making. In this paper, we present a novel method of cooperative decision making in …

Urban traffic scenarios often require a high degree of cooperation between traffic
participants to ensure safety and efficiency. Observing the behavior of others, humans infer …

While motion planning techniques for automated vehicles in a reactive and anticipatory
manner have already been widely presented, cooperative motion planning has only been …

Today's automated vehicles lack the ability to cooperate implicitly with others. This work
presents a Monte Carlo Tree Search (MCTS) based approach for decentralized cooperative …

Automated cooperative collision avoidance of multiple vehicles is a promising approach to
increase road safety in the future. This approach requires a real-time motion planner which …

In order to determine a cooperative driving strategy, it is beneficial for an autonomous
vehicle to incorporate the intended motion of surrounding vehicles within its own motion …

This paper presents a novel cooperative-driving prediction and planning framework for
dynamic environments based on the methods of game theory. The proposed algorithm can …

Planning an interactive and cooperative behavior in the vicinity of multiple decision-makers
is a challenging task. The game-theoretic perspective provides a suitable framework to …

In this paper, we propose a new cooperative driving strategy for connected and automated
vehicles (CAVs) at unsignalized intersections. Based on the tree representation of the …