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：交互感知自动驾驶（IAAD）是一个快速发展的研究领域，旨在开发能够与人类道路使用者安全高效交互的自动驾驶车辆（AVs）。由于要求自动驾驶车辆能够理解并预测人类道路使用者的行为，这一任务具有挑战性。本文通过文献综述形式，系统梳理了IAAD研究的当前进展。首先从术语辨析入手，聚焦驾驶员与行人行为建模面临的挑战及现有模型；继而全面评述了交互建模领域的各类技术方法，涵盖认知方法、机器学习方法和博弈论方法。最后通过探讨IAAD的潜在优势与风险，阐明了未来亟需探索的关键研究问题。