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 autonomous vehicle 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 in this work. Commencing with an examination of terminology, attention is drawn to challenges and existing models employed for modelling the behaviour of drivers and pedestrians. Next, a comprehensive review is conducted on various techniques proposed for interaction modelling, 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.

翻译：交互感知的自主驾驶（IAAD）是一个快速发展的研究领域，主要关注能够与人类道路使用者安全高效交互的自主车辆（AV）的开发。这是一项具有挑战性的任务，要求自主车辆能够理解并预测人类道路使用者的行为。本综述对IAAD的研究现状进行了全面梳理。首先从术语辨析入手，重点探讨了驾驶员和行人行为建模所面临的挑战与现有模型；随后系统综述了交互建模领域的多样化技术方法，涵盖认知方法、机器学习方法与博弈论方法。最后，通过讨论IAAD的潜在优势与风险，并明确指出了未来亟需探索的关键研究问题。