Conference Proceeding

Capturing Driver Response to In-Vehicle Human-Machine Interface Technologies Using Facial Thermography

  • Michelle L Reyes (University of Iowa, Iowa City)
  • Jeffrey D Lee (University of Iowa, Iowa City)
  • Yulan Liang (University of Iowa, Iowa City)
  • Joshua D Hoffman (University of Iowa, Iowa City)
  • Ritchie W Huang (Honda R&D Americas, Inc., Torrance, CA)


Measuring driver response to in-vehicle human-machine interface (HMI) systems is critical for the automotive design and evaluation process. Physiological measures provide a useful complement to performance-based and subjective measures because they promise an estimate of the affective response of drivers to an in-vehicle system in a way that requires no overt response by the driver. This research explored how facial temperature might reflect the drivers’ response to the demands they confront when interacting with in-vehicle systems. Sixteen drivers completed a series of in-vehicle tasks while driving in a simulator. Facial temperature was measured using an infrared camera. The analyses focus on how the thermal data, aggregated over four facial regions, correlated with both measures of driving performance and subjective ratings of workload and frustration. Facial temperature measures correlated with more driving performance measures of longitudinal control than lateral control, suggesting that thermal measures are sensitive to different cognitive processes than are typically assessed by measures of steering and lane position. Thermal measures aggregated over a 15-second window correlated with subjective ratings. Unlike other measures typically used to evaluate in-vehicle systems that are aggregated over long time windows, thermal measures have temporal specificity and might be able to identify specific interactions that increase workload and frustration. No single facial area or summary measure emerged as the best indicator of driver response; rather, composite measures of facial temperature could be developed that offer a more complete profile of driver response.

How to Cite:

Reyes, M. & Lee, J. & Liang, Y. & Hoffman, J. & Huang, R., (2009) “Capturing Driver Response to In-Vehicle Human-Machine Interface Technologies Using Facial Thermography”, Driving Assessment Conference 5(2009), 536-542. doi:

Rights: Copyright © 2009 the author(s)

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Published on
25 Jun 2009
Peer Reviewed