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Pedestrian Group Activity Recognition for Autonomous Vehicles and Robots: A Survey and Perspectives

  • Beijing Institute of Technology
  • Tongji University
  • Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction
  • Tsinghua University

Research output: Contribution to journalArticlepeer-review

Abstract

In human-machine (autonomous vehicles and robots) interaction scenarios, pedestrians often appear in groups. Pedestrian groups provide richer information compared to individuals, which helps address occlusion problems in pedestrian-machine interactions. However, the randomness and spatiotemporal complexity of pedestrian activity make pedestrian group activity recognition (PGAR) a highly challenging task. This article provides a detailed description of the PGAR task. For the first time, a definition of pedestrian group and activity for autonomous vehicles and robots is provided. Existing datasets and methods are systematically summarized. Furthermore, the unique challenges and trends in PGAR for autonomous vehicles and robots are outlined. Although some related surveys have been published, there has not yet been a survey specifically focused on PGAR in autonomous driving and robotics scenarios. Therefore, the goal of this article is to narrow the gap in this topic and provide a comprehensive reference for researchers in this field.

Original languageEnglish
Pages (from-to)1515-1528
Number of pages14
JournalIEEE Transactions on Cybernetics
Volume56
Issue number3
DOIs
Publication statusPublished - 2026
Externally publishedYes

Keywords

  • Autonomous vehicles and robots
  • pedestrian group activity recognition (PGAR)
  • pedestrian-machine interaction

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