Stephanie Balters
ABSTRACT
This paper focuses on the larger question of when to administer in-car just-in-time stress management interventions. We look at the influence of driving-related stress to find the right time to provide personalized and contextually-aware interventions. We address this challenge with a data driven approach that takes into consideration driving-induced stress, driver (cognitive) availability, and indicators of risky driving behavior such as lane departures and high steering reversal rates. We ran a study with sixteen commuters during morning and evening traffic while applying an in-situ experience sampling. During 45 minutes of driving through various scenarios including city, highway, and neighborhood roads we captured physiological measurements, video of participants and surroundings, and CAN bus driving data. Initial review of the data shows that stress levels changed greatly between 2 and 9 (out of a 0-min to 10-max scale). We conclude with a discussion on how to prepare the data to train supervised algorithms to find the right time to intervene stress while driving.
Supplemental Material
- Stephanie Balters, Elizabeth Murnane, James A. Landay, and Pablo E. Paredes. 2018. Breath Booster! Exploring In-car, Fast-paced Breathing Interventions to Enhance Driver Arousal State. Proceedings of the PervasiveHealth Conference (2018). Google Scholar
Digital Library
- Sonia Baltodano, Jesus Garcia-Mancilla, and Wendy Ju. 2018. Eliciting Driver Stress Using Naturalistic Driving Scenarios on Real Roads. In Proceedings of Automotive User Interfaces and Interactive Vehicular Applications. ACM, 298--309. Google ScholarDigital Library
- Mihaly Csikszentmihalyi and Reed Larson. 2014. Validity and reliability of the experience-sampling method. In Flow and the Foundations of Positive Psychology. Springer, 35--54.Google Scholar
- Lex Fridman, Bryan Reimer, Bruce Mehler, and William T. Freeman. 2018. Cognitive Load Estimation in the Wild. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 652. Google ScholarDigital Library
- Javier Hernandez, Daniel McDuff, Xavier Benavides, Judith Amores, Pattie Maes, and Rosalind Picard. 2014. AutoEmotive: bringing empathy to the driving experience to manage stress. In Proceedings of the 2014 Companion Publication on Designing Interactive Systems. ACM, 53--56. Google ScholarDigital Library
- Robert R. McCrae. 1984. Situational determinants of coping responses: Loss, threat, and challenge. Journal of Personality and Social Psychology 46, 4 (1984), 919.Google ScholarCross Ref
- Brian McKenzie. 2015. Who drives to work? Commuting by automobile in the United States: 2013. American Community Survey Reports (2015).Google Scholar
- Pablo E. Paredes, Ran Gilad-Bachrach, Mary Czerwinski, Asta Roseway, Kael Rowan, and Javier Hernandez. 2014. PopTherapy: coping with stress through pop-culture. In Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare. 109--117. Google ScholarDigital Library
- Pablo E. Paredes, Nur Hamdan, Dav Clark, Carrie Cai, Wendy Ju, and James A. Landay. 2017. Evaluating in-car movements in the design of mindful commute interventions: exploratory study. Journal of medical Internet research 19, 12 (2017).Google ScholarCross Ref
- Pablo E. Paredes, Francisco Ordonez, Wendy Ju, and James A. Landay. 2018. Fast & Furious: Detecting Stress with a Car Steering Wheel. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 665. Google ScholarDigital Library
- Pablo E. Paredes, Yijun Zhou, Nur Al-Huda Hamdan, Stephanie Balters, Elizabeth Murnane, Wendy Ju, and James A. Landay. 2018. Just Breathe: In-Car Interventions for Guided Slow Breathing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 28. Google ScholarDigital Library
- Matthew P. Reed and Paul A. Green. 1999. Comparison of driving performance on-road and in a low-cost simulator using a concurrent telephone dialling task. Ergonomics 42, 8 (1999), 1015--1037.Google ScholarCross Ref
- Jonathan W. Roberti, Lisa N. Harrington, and Eric A. Storch. 2006. Further psychometric support for the 10-item version of the perceived stress scale. Journal of College Counseling 9, 2 (2006), 135--147.Google ScholarCross Ref
- James A. Russell, Anna Weiss, and Gerald A. Mendelsohn. 1989. Affect grid: a single-item scale of pleasure and arousal. Journal of Personality and Social Psychology 57, 3 (1989), 493.Google ScholarCross Ref
- SAE ISO Standards. 2015. Operational Definitions of Driving Performance Measures and Statistics. Society of Automotive Engineers.Google Scholar
- Mark Vollrath, Tobias Meilinger, and Hans-Peter Krüger. 2002. How the presence of passengers influences the risk of a collision with another vehicle. Accident Analysis & Prevention 34, 5 (2002), 649--654.Google ScholarCross Ref
Index Terms
- On-road Stress Analysis for In-car Interventions During the Commute
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