AutoPreview: A Framework for Autopilot Behavior Understanding

Yuan Shen, Niviru Wijayaratne, Peter Du, Shanduojiao Jiang, Katherine Driggs-Campbell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The behavior of self-driving cars may differ from people's expectations (e.g. an autopilot may unexpectedly relinquish control). This expectation mismatch can cause potential and existing users to distrust self-driving technology and can increase the likelihood of accidents. We propose a simple but effective framework, AutoPreview, to enable consumers to preview a target autopilot's potential actions in the real-world driving context before deployment. For a given target autopilot, we design a delegate policy that replicates the target autopilot behavior with explainable action representations, which can then be queried online for comparison and to build an accurate mental model. To demonstrate its practicality, we present a prototype of AutoPreview integrated with the CARLA simulator along with two potential use cases of the framework. We conduct a pilot study to investigate whether or not AutoPreview provides deeper understanding about autopilot behavior when experiencing a new autopilot policy for the first time. Our results suggest that the AutoPreview method helps users understand autopilot behavior in terms of driving style comprehension, deployment preference, and exact action timing prediction.

Original languageEnglish (US)
Title of host publicationExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450380959
DOIs
StatePublished - May 8 2021
Event2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021 - Virtual, Online, Japan
Duration: May 8 2021May 13 2021

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021
Country/TerritoryJapan
CityVirtual, Online
Period5/8/215/13/21

Keywords

  • Agent Behavior Understanding
  • Autonomous Vehicle
  • Human Robot Interaction
  • Imitation Learning
  • Mental Model
  • Preview

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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