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Social Interactions for Autonomous Driving: A Review and Perspectives

  • Wenshuo Wang
  • , Letian Wang
  • , Chengyuan Zhang
  • , Changliu Liu
  • , Lijun Sun
  • McGill University
  • University of Toronto
  • Carnegie Mellon University

科研成果: 期刊稿件文献综述同行评审

摘要

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 monograph 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 monograph reviews various approaches to modeling and learning the social interactions between human drivers, ranging from optimization theory, deep learning, 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.

源语言英语
页(从-至)198-377
页数180
期刊Foundations and Trends in Robotics
10
3-4
DOI
出版状态已出版 - 2022
已对外发布

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