Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles

Interaction-aware autonomous driving (IAAD) is a rapidly growing field of research that focuses on the development of autonomous vehicles (AVs) that are capable of interacting safely and efficiently with human road users. This is a challenging task, as it requires the AV to be able to understand and predict the behaviour of human road users. In this literature review, the current state of IAAD research is surveyed. Commencing with an examination of terminology, attention is drawn to challenges and existing models employed for modeling the behaviour of drivers and pedestrians. Next, a comprehensive review is conducted on various techniques proposed for interaction modeling, encompassing cognitive methods, machine-learning approaches, and game-theoretic methods. The conclusion is reached through a discussion of potential advantages and risks associated with IAAD, along with the illumination of pivotal research inquiries necessitating future exploration. Interaction-aware autonomous driving (IAAD) is a growing research field, focusing on autonomous vehicles (AVs) safely interacting with human road users. Understanding and predicting human behavior is crucial. This review assesses current IAAD research, examining terminology, challenges, and existing models for human road user interaction. Interaction modeling techniques, including cognitive, machine learning, and game theory methods, and potential advantages are discussed.image (c) 2023 WILEY-VCH GmbH