No human drives a car in a vacuum; she/he must negotiate with other road users to achieve their goals in social traffic scenes. A rational human driver can interact with other road users in a socially-compatible way through implicit communications to complete their driving tasks smoothly in interaction-intensive, safety-critical environments. This paper aims to review the existing approaches and theories to help understand and rethink the interactions among human drivers toward social autonomous driving. We take this survey to seek the answers to a series of fundamental questions: 1) What is social interaction in road traffic scenes? 2) How to measure and evaluate social interaction? 3) How to model and reveal the process of social interaction? 4) How do human drivers reach an implicit agreement and negotiate smoothly in social interaction? This paper reviews various approaches to modeling and learning the social interactions between human drivers, ranging from optimization theory and graphical models to social force theory and behavioral & cognitive science. We also highlight some new directions, critical challenges, and opening questions for future research.
翻译:人类不能在真空中驾驶汽车; 人类不能在真空中驾驶汽车; 他/ 他必须与其他道路使用者谈判,以实现其在社会交通场景中的目标; 理性的人类驾驶者可以通过隐含的交流,以社会兼容的方式与其他道路使用者互动,在互动密集、安全危急的环境中顺利地完成驾驶任务; 本文旨在审查现有的方法和理论,以帮助理解和重新思考人类驾驶者之间在社会自主驾驶方面的相互作用; 我们通过这次调查寻求一系列基本问题的答案:1) 道路交通场的社会互动是什么? 2) 如何衡量和评价社会互动? 3) 如何建模和揭示社会互动进程? 4) 人类驾驶者如何在社会互动中达成隐含的协议并顺利地进行谈判? 本文回顾了模拟和学习人类驾驶者之间社会互动的各种方法,从优化理论和图形模型到社会力量理论以及行为和认知科学。 我们还强调了一些新的方向、关键挑战,并为未来研究提出问题。