Cooperatively planning for multiple agents has been proposed as a promising method for
strategic and motion planning for automated vehicles. By taking into account the intent of …

The actions of an autonomous vehicle on the road affect and are affected by those of other
drivers, whether overtaking, negotiating a merge, or avoiding an accident. This mutual …

In this article, we propose a nonlinear receding horizon game-theoretic planner for
autonomous cars in competitive scenarios with other cars. The online planner is specifically …

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, a major challenge in the field of trajectory planning for autonomous on-road
vehicles is addressed: to calculate trajectories efficiently and reliably. The proposed method …

This paper considers the problem of cooperative trajectory planning for multiple,
communicating, automated vehicles in general non-hazardous on-road scenarios …

This paper considers the problem of planning reference trajectories for cooperating
autonomous vehicles. Our previous work [1] relied on mixed-integer quadratic programming …

With the adoption of autonomous vehicles on our roads, we will witness a mixed-autonomy
environment where autonomous and human-driven vehicles must learn to co-exist by …

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 …

This paper presents a real-time game theoretic planning algorithm for a robotic vehicle (eg a
drone or a car) to race competitively against multiple opponents on a racecourse. Our …