Measuring user responses to driving simulators: A galvanic skin response based study

Atiqul Islam, Jinshuai Ma, Tom Gedeon, Md Zakir Hossain, Ying Hsang Liu

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

2 Citations (Scopus)

Abstract

The use of simulator technology has become popular in providing training, investigating driving activity and performing research as it is a suitable alternative to actual field study. The transferability of the achieved result from driving simulators to the real world is a critical issue considering later real-world risks, and important to the ethics of experiments. Moreover, researchers have to trade-off between simulator sophistication and the cost it incurs to achieve a given level of realism. This study will be the first step towards investigating the plausibility of different driving simulator configurations of varying verisimilitude, from drivers' galvanic skin response (GSR) signals. GSR is the widely used indicator of behavioural response. By analyzing GSR signals in a simulation environment, our results are aimed to support or contradict the use of simple low-level driving simulators. We investigate GSR signals of 23 participants doing virtual driving tasks in 5 different configurations of simulation environments. A number of features are extracted from the GSR signals after data preprocessing. With a simple neural network classifier, the prediction accuracy of different simulator configurations reaches up to 90% during driving. Our results suggest that participants are more engaged when realistic controls are used in normal driving, and are less affected by visible context during driving in emergency situations. The implications for future research are that for emergency situations realistic controls are important and research can be conducted with simple simulators in lab settings, whereas for normal driving the research should be conducted with full context in a real driving setting.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages33-40
Number of pages8
ISBN (Electronic)9781728156040
DOIs
Publication statusPublished - Dec 1 2019
Event2nd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019 - San Diego, United States
Duration: Dec 9 2019Dec 11 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019

Conference

Conference2nd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
CountryUnited States
CitySan Diego
Period12/9/1912/11/19

Keywords

  • Classification
  • Driving simulator
  • Galvanic skin response
  • Physiological signal
  • Verisimilitude

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Media Technology
  • Modelling and Simulation

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