In this article, we study the problem of multiple stochastic agents interacting in a dynamic
game scenario with continuous state and action spaces. We define a new notion of …

Existing game-theoretic planning methods assume that the robot knows the objective
functions of the other agents a priori while, in practical scenarios, this is rarely the case. This …

While automated vehicles (AVs) are expected to bring a wide range of benefits to future
transportation systems, emerging AV technologies open a door for cyberattacks, where a …

Accurate calibration of car-following models is essential for understanding human driving
behaviors and implementing high-fidelity microscopic simulations. This work proposes a …

We present a review and taxonomy of 200 models from the literature on driver behavior
modeling. We begin by introducing a mathematical framework for describing the dynamics of …

Automated driving systems need to perform according to what human drivers expect in every
situation. A different behavior can be wrongly interpreted by other human drivers and cause …

This paper presents a hierarchical and game-theoretic decision-making strategy for
connected and automated vehicles (CAVs). A CAV can receive preview information using …

Autonomous vehicles need to model the behavior of surrounding human driven vehicles to
be safe and efficient traffic participants. Existing approaches to modeling human driving …

Modeling the stochastic behavior of interacting agents is key for safe motion planning. In this
paper, we study the interaction of risk-aware agents in a game-theoretical framework. Under …

Automated vehicles are expected to influence human drivers' behavior. Accordingly,
capturing such changes is critical for planning and operation purposes. With regard to car …