Exploring the Effect of Explanations During Robot-Guided Emergency Evacuation

Mollik Nayyar, Zachary Zoloty, Ciera McFarland, Alan R. Wagner

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

Abstract

Humans tend to overtrust emergency robots during emergencies[12]. Here we consider how a robot’s explanations influence a person’s decision to follow the robot’s evacuation directions when those directions differ from the movement of the crowd. The experiments were conducted in a simulated emergency environment with an emergency guide robot and animated human looking Non-Player Characters (NPC). Our results show that explanations increase the tendency to follow the robot, even if these messages are uninformative. We also perform a preliminary study investigating different explanation designs for effective interventions, demonstrating that certain types of explanations can increase or decrease evacuation time. This paper contributes to our understanding of human compliance to robot instructions and methods for examining human compliance through the use of explanations during high risk, emergency situations.

Original languageEnglish (US)
Title of host publicationSocial Robotics - 12th International Conference, ICSR 2020, Proceedings
EditorsAlan R. Wagner, David Feil-Seifer, Kerstin S. Haring, Silvia Rossi, Thomas Williams, Hongsheng He, Shuzhi Sam Ge
PublisherSpringer Science and Business Media Deutschland GmbH
Pages13-22
Number of pages10
ISBN (Print)9783030620554
DOIs
StatePublished - 2020
Event12th International Conference on Social Robotics, ICSR 2020 - Golden, United States
Duration: Nov 14 2020Nov 18 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12483 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Social Robotics, ICSR 2020
CountryUnited States
CityGolden
Period11/14/2011/18/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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