Being watched over by a conversation robot may enhance safety in simulated driving

J Safety Res. 2019 Dec:71:207-218. doi: 10.1016/j.jsr.2019.09.010. Epub 2019 Nov 21.

Abstract

Introduction: In an aging society that is more and more information-oriented, being able to replace human passengers' protective effects on vehicle drivers with those of social robots is both essential and promising. However, the effects of a social robot's presence on drivers have not yet been fully explored. Thus, using a driving simulator and a conversation robot, this experimental study had two main goals: (a) to find out whether social robots' anthropomorphic qualities (i.e., not the practical information the robot provides drivers) have protective effects by promoting attentive driving and alleviating crash risks; and (b) by what psychological processes such effects emerge.

Method: Participants were recruited from young (n = 38), the middle-aged (n = 39), and the elderly (n = 49) age groups. They were assigned to either the treatment group (simulated driving in a conversation robot's presence) or the control group (simulated driving alone), and their driving performance was measured. Mental states (peaceful, concentrating, and reflective) also were assessed in a post-driving questionnaire using our original scales.

Results: Although the group of older participants did not experience protective effects (perhaps due to motion sickness), the young participants drove attentively, with the robot enhancing peace of mind. The protective effect was also observed among the middle-aged participants, and the verbal data analysis ascribed this to the robot's role of expressing sympathy, especially when the middle-aged drivers nearly had not-at-fault crashes, which caused them to be stressed. In conclusion, we discuss the practical implications of the results.

Keywords: Passenger effects on drivers; Social robots; Weak AI stance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adult
  • Age Factors
  • Aged
  • Attention*
  • Automobile Driving / psychology*
  • Communication*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Robotics*
  • Young Adult