research-article

Eliciting Driver Stress Using Naturalistic Driving Scenarios on Real Roads

Authors:

Sonia Baltodano,

Jesus Garcia-Mancilla,

Wendy JuAuthors Info & Claims

AutomotiveUI '18: Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 298 - 309

https://doi.org/10.1145/3239060.3239090

Published: 23 September 2018 Publication History

Abstract

We propose a novel method for reliably inducing stress in drivers for the purpose of generating real-world participant data for machine learning, using both scripted in-vehicle stressor events and unscripted on-road stressors such as pedestrians and construction zones. On-road drives took place in a vehicle outfitted with an experimental display that lead drivers to believe they had prematurely ran out of charge on an isolated road. We describe the elicitation method, course design, instrumentation, data collection procedure and the post-hoc labeling of unplanned road events to illustrate how rich data about a variety of stress-related events can be elicited from study participants on-road. We validate this method with data including psychophysiological measurements, video, voice, and GPS data from (N=20) participants. Results from algorithmic psychophysiological stress analysis were validated using participant self-reports. Results of stress elicitation analysis show that our method elicited a stress-state in 89% of participants.

References

[1]

Ahmad Alipour, Hossein Zare, Hamid Poursharifi, Khadijeh Aerab Sheibani, and Mohammad Afkhami Ardekani. 2012. The Intermediary Role of Self-Efficacy in Relation with Stress, Glycosylated Haemoglobin and Health-Related Quality of Life in Patients with Type2 Diabetes. 41, 12 (2012), 76. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3646785/

[2]

American Diabetes Association. 2011. American Diabetes Association Complete Guide to Diabetes: The Ultimate Home Reference from the Diabetes Experts (fifth edition edition ed.). American Diabetes Association.

[3]

Sonia Baltodano, Srinath Sibi, Nikolas Martelaro, Nikhil Gowda, and Wendy Ju. 2015. The RRADS platform: a real road autonomous driving simulator. In Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. ACM, 281--288.

Digital Library

[4]

Myra Blanco, Jeffrey S Hickman, Rebecca L Olson, Joseph L Bocanegra, Mike Greening, Phillip Madison, G Thomas Holbrook, Richard J Hanowski, Akiko Nakata, Darrell S Bowman, and others. 2016. Investigating critical incidents, driver restart period, sleep quantity, and crash countermeasures in commercial vehicle operations using naturalistic data collection. Technical Report. United States. Federal Motor Carrier Safety Administration.

[5]

John T Cacioppo, Gary G Berntson, Jeff T Larsen, Kirsten M Poehlmann, Tiffany A Ito, and others. 2000. The psychophysiology of emotion. Handbook of emotions 2 (2000), 173--191.

[6]

Chenyi Chen, Ari Seff, Alain Kornhauser, and Jianxiong Xiao. 2015. Deepdriving: Learning affordance for direct perception in autonomous driving. In Computer Vision (ICCV), 2015 IEEE International Conference on. IEEE, 2722--2730.

Digital Library

[7]

Joannes El Chliaoutakis, Panayotis Demakakos, Georgia Tzamalouka, Vassiliki Bakou, Malamatenia Koumaki, and Christina Darviri. 2002. Aggressive behavior while driving as predictor of self-reported car crashes. Journal of safety Research 33, 4 (2002), 431--443.

[8]

Minho Choi, Gyogwon Koo, Minseok Seo, and Sang Woo Kim. 2018. Wearable Device-Based System to Monitor a Driver's Stress, Fatigue, and Drowsiness. IEEE Transactions on Instrumentation and Measurement 67, 3 (March 2018), 634--645.

[9]

Thi-Hai-Ha Dang and Adriana Tapus. 2014. Physiological Signals in Driving Scenario: How heart rate and skin conductance reveal different aspects of driver's cognitive load. In Proceedings of the. 378--384.

[10]

Anita DeLongis, Susan Folkman, and Richard S. Lazarus. 1988. The impact of daily stress on health and mood: psychological and social resources as mediators. 54, 3 (1988), 486. http://psycnet.apa.org/journals/psp/54/3/486/

[11]

Paul Ekman. 1970. Universal facial expressions of emotion. 8, 4 (1970), 151--158.

[12]

Paul Ekman, Robert W. Levenson, and Wallace V. Friesen. 1983. Autonomic Nervous System Activity Distiguishes Among Emotions. 221, 4616 (1983), 1208--1210.

[13]

Paul Ekman and Harriet Oster. 1979. Facial expressions of emotion. 30, 1 (1979), 527--554.

[14]

Haluk Eren, Semiha Makinist, Erhan Akin, and Alper Yilmaz. 2012. Estimating driving behavior by a smartphone. In Intelligent Vehicles Symposium (IV), 2012 IEEE. IEEE, 234--239.

[15]

Raul Fernandez and Rosalind W Picard. 2003. Modeling drivers' speech under stress. Speech communication 40, 1-2 (2003), 145--159.

Digital Library

[16]

National Center for Statistics {and} Analysis. 2018. Police-reported motor vehicle traffic crashes in 2016. Traffic safety facts research note 2018 (2018), 1--9.

[17]

Jesus Garcia-Mancilla and Victor M. Gonzalez. 2016. Stress Quantification Using a Wearable Device for Daily Feedback to Improve Stress Management. In Smart Health, Xiaolong Zheng, Daniel Dajun Zeng, Hsinchun Chen, and Scott J. Leischow (Eds.). Vol. 9545. Springer International Publishing, 204--209.

Digital Library

[18]

Khadidja Gouizi, Fethi Bereksi Reguig, and Choubeila Maaoui. 2011. Emotion recognition from physiological signals. 35, 6 (2011), 300--307.

[19]

James J Gross and Robert W Levenson. 1995. Emotion elicitation using films. Cognition & emotion 9, 1 (1995), 87--108.

[20]

Richard J Hanowski, Walter W Wierwille, Andrew G Gellatly, Nancy Early, and Thomas A Dingus. 1998. Impact of Local/Short Haul Operations on Driver Fatigue. Task 1: Focus Group Summary and Analysis. Technical Report.

[21]

Jennifer Healey, Lama Nachman, Sushmita Subramanian, Junaith Shahabdeen, and Margaret Morris. 2010. Out of the lab and into the fray: towards modeling emotion in everyday life. In International Conference on Pervasive Computing. Springer, 156--173.

Digital Library

[22]

Jennifer A. Healey and Rosalind W. Picard. 2005-06. Detecting stress during real-world driving tasks using physiological sensors. 6, 2 (2005-06), 156--166.

Digital Library

[23]

Dwight A Hennessy and David L Wiesenthal. 1999. Traffic congestion, driver stress, and driver aggression. Aggressive Behavior: Official Journal of the International Society for Research on Aggression 25, 6 (1999), 409--423.

[24]

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.

Digital Library

[25]

Changhyun Jeong, Y. Lee, S. Choi, Dohyun Jung, and K. Lee. 2013. Comparison of driving characteristics between drivers in Korea and in the united states of America based on driver-vehicle interaction field database. International Journal of Automotive Technology 14, 1 (jan 2013), 123--132.

[26]

Malte F Jung, David Sirkin, Turgut M Gür, and Martin Steinert. 2015. Displayed uncertainty improves driving experience and behavior: The case of range anxiety in an electric car. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2201--2210.

Digital Library

[27]

Inna Z. Khazan. 2013. The clinical handbook of biofeedback: a step-by-step guide for training and practice with mindfulness. Wiley.

[28]

Ronald R Knipling. 2015. Naturalistic driving events: No harm, no foul, no validity. (2015).

[29]

Annemarie Künn-Nelen. 2016. Does commuting affect health? Health economics 25, 8 (2016), 984--1004.

[30]

Martin Kusserow, Oliver Amft, and Gerhard Troster. 2013. Monitoring stress arousal in the wild. 2 (2013), 28--37. http://www.computer.org/csdl/mags/pc/2013/02/mpc2013020028-abs.html

Digital Library

[31]

Dae Seok Lee, Teak Wei Chong, and Boon Giin Lee. 2017. Stress Events Detection of Driver by Wearable Glove System. IEEE Sensors Journal 17, 1 (2017), 194--204.

[32]

Haet Bit Lee, Jung Soo Kim, Yun Seong Kim, Hyun Jae Baek, Myung Suk Ryu, and Kwang Suk Park. 2007. The relationship between HRV parameters and stressful driving situation in the real road. In Information Technology Applications in Biomedicine, 2007. ITAB 2007. 6th International Special Topic Conference on. IEEE, 198--200.

[33]

Robert W. Levenson, Paul Ekman, and Wallace V. Friesen. 1990. Voluntary Facial Action Generates Emotion-Specific Autonomic Nervous System Activity. 27, 4 (1990), 636--384.

[34]

Christine Lætitia Lisetti and Fatma Nasoz. 2004. Using noninvasive wearable computers to recognize human emotions from physiological signals. EURASIP journal on applied signal processing 2004 (2004), 1672--1687.

Digital Library

[35]

Nikolas Martelaro and Wendy Ju. 2017. WoZ Way: Enabling real-time interaction prototyping and on-road observation. In Proceedings of the 2017 Conference on Computer Supported Cooperative Work.

Digital Library

[36]

Adam Martin, Yevgeniy Goryakin, and Marc Suhrcke. 2014. Does active commuting improve psychological wellbeing? Longitudinal evidence from eighteen waves of the British Household Panel Survey. Preventive Medicine 69 (2014), 296--303.

[37]

Gerald Matthews, Lisa Dorn, Thomas W Hoyes, D Roy Davies, A Ian Glendon, and Ray G Taylor. 1998. Driver stress and performance on a driving simulator. Human Factors 40, 1 (1998), 136--149.

[38]

Jeremy Morton, Tim A Wheeler, and Mykel J Kochenderfer. 2017. Analysis of recurrent neural networks for probabilistic modeling of driver behavior. IEEE Transactions on Intelligent Transportation Systems 18, 5 (2017), 1289--1298.

Digital Library

[39]

Fatma Nasoz, Christine L Lisetti, and Athanasios V Vasilakos. 2010. Affectively intelligent and adaptive car interfaces. Information Sciences 180, 20 (2010), 3817--3836.

Digital Library

[40]

Eshed Ohn-Bar and Mohan Manubhai Trivedi. 2016. Looking at humans in the age of self-driving and highly automated vehicles. IEEE Transactions on Intelligent Vehicles 1, 1 (2016), 90--104.

[41]

Pablo E. Paredes, Nur Al-Huda 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. 19, 12 (2017), e372.

[42]

Pablo E. Paredes, Francisco Ordonez, Wendy Ju, and James A. Landay. 2018a. Fast & Furious: Detecting Stress with a Car Steering Wheel. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM Press, 1--12.

Digital Library

[43]

Pablo E. Paredes, Yijun Zhou, Nur Al-Huda Hamdan, Stephanie Balters, Elizabeth Murnane, Wendy Ju, and James A. Landay. 2018b. Just Breathe: In-Car Interventions for Guided Slow Breathing. 2, 1 (2018), 1--23.

[44]

Juha Pärkkä, Juho Merilahti, Elina M Mattila, Esko Malm, Kari Antila, Martti T Tuomisto, Ari Viljam Saarinen, Mark van Gils, and Ilkka Korhonen. 2009. Relationship of psychological and physiological variables in long-term self-monitored data during work ability rehabilitation program. IEEE Transactions on Information Technology in Biomedicine 13, 2 (2009), 141--151.

Digital Library

[45]

Rosalind W Picard and Jocelyn Scheirer. 2001. The galvactivator: A glove that senses and communicates skin conductivity. In Proceedings 9th Int. Conf. on HCI.

[46]

Jeanne L. Tsai, Nnamdi Pole, Robert W. Levenson, and Ricardo F. Muñoz. 2003. The effects of depression on the emotional responses of Spanish-speaking Latinas. 9, 1 (2003), 49--63.

[47]

Gary R VandenBos. 2007. APA dictionary of psychology. American Psychological Association.

[48]

Nai Chi Jonathan Yeung and Courtney von Hippel. 2008. Stereotype threat increases the likelihood that female drivers in a simulator run over jaywalkers. Accident Analysis & Prevention 40, 2 (2008), 667--674.

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Dey DGoedicke DYang CSirkin DCurrano RJu W(2024)GrokWalks: A Portable Virtual Reality Platform to Facilitate Studying Driver-Pedestrian InteractionsAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685013(284-288)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685013
Barka RPolitis I(2024)Driving into the future: A scoping review of smartwatch use for real-time driver monitoringTransportation Research Interdisciplinary Perspectives10.1016/j.trip.2024.10109825(101098)Online publication date: May-2024
https://doi.org/10.1016/j.trip.2024.101098
Venkatachalapathy ARahman MRaj AMerickel JSharma AWang JVelipasalar S(2023)Deep Insight: A Cloud Based Big Data Analytics Platform For Naturalistic Driving StudiesInternational Journal of Automotive Engineering10.20485/jsaeijae.14.3_6614:3(66-76)Online publication date: 2023
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Index Terms

Eliciting Driver Stress Using Naturalistic Driving Scenarios on Real Roads
1. Human-centered computing
  1. Interaction design
    1. Empirical studies in interaction design
    2. Systems and tools for interaction design

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cover image ACM Conferences

AutomotiveUI '18: Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2018

374 pages

ISBN:9781450359467

DOI:10.1145/3239060

Copyright © 2018 ACM.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Publication History

Published: 23 September 2018

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AutomotiveUI '18

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AutomotiveUI '18: 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 23 - 25, 2018

ON, Toronto, Canada

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Overall Acceptance Rate 248 of 566 submissions, 44%

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https://dl.acm.org/doi/10.1145/3641308.3685013
Barka RPolitis I(2024)Driving into the future: A scoping review of smartwatch use for real-time driver monitoringTransportation Research Interdisciplinary Perspectives10.1016/j.trip.2024.10109825(101098)Online publication date: May-2024
https://doi.org/10.1016/j.trip.2024.101098
Venkatachalapathy ARahman MRaj AMerickel JSharma AWang JVelipasalar S(2023)Deep Insight: A Cloud Based Big Data Analytics Platform For Naturalistic Driving StudiesInternational Journal of Automotive Engineering10.20485/jsaeijae.14.3_6614:3(66-76)Online publication date: 2023
https://doi.org/10.20485/jsaeijae.14.3_66
Pabst ATabb TStewart KDanielescu A(2023)A Qualitative Study on the Expectations and Concerns Around Voice and Gesture Interactions in VehiclesProceedings of the 2023 ACM Designing Interactive Systems Conference10.1145/3563657.3596040(2155-2171)Online publication date: 10-Jul-2023
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Hirsh TSahar YMusicant OBotzer AShoval S(2023)Relationship between braking intensity and driver heart rate as a function of the size of the measurement window and its positionTransportation Research Part F: Traffic Psychology and Behaviour10.1016/j.trf.2023.03.01394(528-540)Online publication date: Apr-2023
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Yang LSong YHu ZWang ZLi X(2022)Recognition of typical driving stressors and driver stress level in a Chinese sampleJournal of Transportation Safety & Security10.1080/19439962.2022.212895915:8(774-794)Online publication date: 12-Oct-2022
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Venkatachalapathy ASharma AVanajakshi L(2022)A Naturalistic Data-Driven Study of Indian Traffic Conditions and Driver’s Physiological StressTransportation in Developing Economies10.1007/s40890-022-00158-38:2Online publication date: 12-Apr-2022
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Zontone PAffanni ABernardini RDel Linz LPiras ARinaldo R(2020)Stress Evaluation in Simulated Autonomous and Manual Driving through the Analysis of Skin Potential Response and Electrocardiogram SignalsSensors10.3390/s2009249420:9(2494)Online publication date: 28-Apr-2020
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Ju WYavo-Ayalon SMandel ISaldarini FFriedman NSibi SZamfirescu-Pereira JOrtiz J(2020)Tracking Urban Mobility and Occupancy under Social Distancing PolicyDigital Government: Research and Practice10.1145/34179911:4(1-12)Online publication date: 15-Oct-2020
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