ABSTRACT
The number of systems in commercially available vehicles that assist or automate driving tasks is rapidly increasing. At least for the next decade, using such systems remains up to the discretion of the user. In this paper, different reasons why drivers may disengage the autopilot are investigated. This was done through a simulator study in which the system could drive fully automated, but where participants could also disengage the system. Qualitative data were collected about why participants disengaged the autopilot. The analysis of the data revealed six themes covering the reasons why participants disabled the autopilot: The speed maintained by the autopilot, the behavior of the autopilot in relation to overtaking other vehicles, onset of boredom, onset of sleepiness, lack of trust in the autopilot, and enjoyment of manual driving. On the basis of the results, design opportunities are proposed to counteract the tendency to not use automated driving systems.
- David Abbink and Mark Mulder. 2010. Neuromuscular Analysis as a Guideline in designing Shared Control. In Advances in Haptics. InTech.Google Scholar
- Bart van Arem, Cornelie J. G. van Driel, and Ruben Visser. 2006. The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics. IEEE Transactions on Intelligent Transportation Systems 7, 4: 429--436. Google ScholarDigital Library
- Johannes Beller, Matthias Heesen, and Mark Vollrath. 2013. Improving the Driver--Automation Interaction. Human Factors: The Journal of the Human Factors and Ergonomics Society 55, 6: 1130--1141.Google ScholarCross Ref
- Arie P. van den Beukel, Mascha C. van der Voort, and Arthur O. Eger. 2016. Supporting the changing driver's task: Exploration of interface designs for supervision and intervention in automated driving. Transportation Research Part F: Traffic Psychology and Behaviour 43: 279--301.Google ScholarCross Ref
- Mike Blommer, Reates Curry, Dev Kochhar, Rads Swaminathan, Walter Talamonti, and Louis Tijerina. 2015. The Effects of a Scheduled Driver Engagement Strategy in Automated Driving. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 59, 1: 1681--1685.Google ScholarCross Ref
- Barry Brown and Eric Laurier. 2017. The Trouble with Autopilots: Assisted and Autonomous Driving on the Social Road. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17, 416--429. Google ScholarDigital Library
- Stephen M. Casner, Edwin L. Hutchins, and Don Norman. 2016. The challenges of partially automated driving. Communications of the ACM 59, 5: 70--77. Google ScholarDigital Library
- Stefan Diewald, Andreas Möller, Luis Roalter, Tobias Stockinger, and Matthias Kranz. 2013. Gameful design in the automotive domain -- Review, Outlook and Challenges. In Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '13, 262--265. Google ScholarDigital Library
- Kai Eckoldt, Martin Knobel, Marc Hassenzahl, and Josef Schumann. 2012. An Experiential Perspective on Advanced Driver Assistance Systems. it - Information Technology 54: 165--171.Google Scholar
- James Elander, Robert West, and Davina French. 1993. Behavioral correlates of individual differences in road traffic crash risk: an examination of methods and findings. 113, 2: 279--294.Google Scholar
- Mica R. Endsley. 1995. Toward a Theory of Situation Awareness in Dynamic Systems. Human Factors: The Journal of the Human Factors and Ergonomics Society 37, 1: 32--64.Google ScholarCross Ref
- Anna-Katharina Frison, Philipp Wintersberger, Andreas Riener, and Clemens Schartmüller. 2017. Driving Hotzenplotz: A Hybrid Interface for Vehicle Control Aiming to Maximize Pleasure in Highway Driving. In Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '17, 236--244. Google ScholarDigital Library
- Pilar Tejero Gimeno, Gemma Pastor Cerezuela, and Mariano Choliz Montanes. 2006. On the concept and measurement of driver drowsiness, fatigue and inattention: implications for countermeasures. International Journal of Vehicle Design 42, 1/2: 67.Google ScholarCross Ref
- Hanneke Hooft van Huysduynen, Jacques Terken, and Berry Eggen. 2016. Encouraging the Use of ADAS through Personalized Persuasion. In Adjunct Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - Automotive 'UI 16, 105--110. Google ScholarDigital Library
- Hanneke Hooft van Huysduynen, Jacques Terken, Jean Bernard Martens, and Berry Eggen. 2015. Measuring driving styles: a validation of the multidimensional driving style inventory. In Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '15, 257--264. Google ScholarDigital Library
- Mishel Johns, Brian Mok, David Sirkin, Nikhil Gowda, Catherine Smith, Walter Talamonti, and Wendy Ju. 2016. Exploring shared control in automated driving. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 91--98. Google ScholarDigital Library
- Miltos Kyriakidis, Riender Happee, and Joost C.F. de Winter. 2015. Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation Research Part F: Traffic Psychology and Behaviour 32: 127--140.Google ScholarCross Ref
- Timo Lajunen and Heikki Summala. 1995. Driving experience, personality, and skill and safety-motive dimensions in drivers' self-assessments. Personality and Individual Differences 19, 3: 307--318.Google ScholarCross Ref
- John D. Lee and Katrina A. See. 2004. Trust in Automation: Designing for Appropriate Reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society 46, 1: 50--80.Google ScholarCross Ref
- Robert E Llaneras, Jeremy Salinger, and Charles A Green. 2013. Human Factors Issues Associated with Limited Ability Autonomous Driving Systems: Driver' Allocation of Visual Attention to the Forward Roadway. In the Seventh International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, 92--98. Retrieved December 8, 2015 from http://trid.trb.org/view.aspx?id=1363482Google ScholarCross Ref
- Bella. Martin and Bruce M. Hanington. 2012. Universal methods of design: 100 ways to research complex problems, develop innovative ideas, and design effective solutions. Rockport Publishers.Google Scholar
- Jennifer F. May and Carryl L. Baldwin. 2009. Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies. Transportation Research Part F: Traffic Psychology and Behaviour 12, 3: 218--224.Google ScholarCross Ref
- William L Mikulas and Stephen J Vodanovich. 1993. The essence of boredom. The Psychological Record 43, 1.Google Scholar
- David Miller, Annabel Sun, Mishel Johns, Hillary Ive, David Sirkin, Sudipto Aich, and Wendy Ju. 2015. Distraction Becomes Engagement in Automated Driving. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 59, 1: 1676--1680.Google ScholarCross Ref
- Armen A. Mkrtchyan, Jamie C. Macbeth, Erin T. Solovey, Jason C. Ryan, and M. L. Cummings. 2012. Using Variable-Rate Alerting to Counter Boredom in Human Supervisory Control. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 56, 1: 1441--1445.Google ScholarCross Ref
- Brian Mok, Mishel Johns, David Miller, and Wendy Ju. 2017. Tunneled In: Drivers with Active Secondary Tasks Need More Time to Transition from Automation. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17, 2840--2844. Google ScholarDigital Library
- Sina Nordhoff, Bart van Arem, and Riender Happee. 2016. Conceptual Model to Explain, Predict, and Improve User Acceptance of Driverless Podlike Vehicles. Transportation Research Record: Journal of the Transportation Research Board 2602: 60--67.Google ScholarCross Ref
- Raja Parasuraman and Victor Riley. 1997. Humans and Automation: Use, Misuse, Disuse, Abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society 39, 2: 230--253.Google ScholarCross Ref
- Jean-François Petiot, Bjørn G. Kristensen, and Anja M. Maier. 2013. How Should an Electric Vehicle Sound? User and Expert Perception. In Volume 5: 25th International Conference on Design Theory and Methodology; ASME 2013 Power Transmission and Gearing Conference.Google Scholar
- SAE International. J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems - SAE International. Retrieved March 1, 2018 from https://www.sae.org/standards/content/j3016_201401/Google Scholar
- Wouter J Schakel, Bart Van Arem, and Bart D Netten. 2010. Effects of Cooperative Adaptive Cruise Control on Traffic Flow Stability. Intelligent Transportation Systems (ITSC), 2010 13th International IEEE Conference on, Idm: 759--764.Google ScholarCross Ref
- Ronald Schroeter, Jim Oxtoby, and Daniel Johnson. 2014. AR and Gamification Concepts to Reduce Driver Boredom and Risk Taking Behaviours. In Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '14, 1--8. Google ScholarDigital Library
- Neville A. Stanton, Mark S. Young, and B. McCaulder. 1997. Drive-by-wire: The case of driver workload and reclaiming control with adaptive cruise control. Safety Science 27, 2--3: 149--159.Google ScholarCross Ref
- Sonja Stockert, Natalie Tara Richardson, and Markus Lienkamp. 2015. Driving in an Increasingly Automated World -- Approaches to Improve the Driver-automation Interaction. Procedia Manufacturing 3: 2889--2896.Google ScholarCross Ref
- Niklas Strand, Josef Nilsson, I.C. MariAnne Karlsson, and Lena Nilsson. 2014. Semi-automated versus highly automated driving in critical situations caused by automation failures. Transportation Research Part F: Traffic Psychology and Behaviour 27: 218--228.Google ScholarCross Ref
- Heikki Summala. 2007. Towards understanding motivational and emotional factors in driver behaviour: Comfort through satisficing. In Modelling Driver Behaviour in Automotive Environments: Critical Issues in Driver Interactions with Intelligent Transport Systems. 189--207.Google Scholar
- Orit Taubman-Ben-Ari, Mario Mikulincer, and Omri Gillath. 2004. The multidimensional driving style inventory--scale construct and validation. Accident Analysis & Prevention 36, 3: 323--332.Google ScholarCross Ref
- Frank M. F. Verberne, Jaap Ham, and Cees J. H. Midden. 2012. Trust in Smart Systems: Sharing Driving Goals and Giving Information to Increase Trustworthiness and Acceptability of Smart Systems in Cars. Human Factors: The Journal of the Human Factors and Ergonomics Society 54, 5: 799--810.Google ScholarCross Ref
- Volvo. Overtaking assistance with the Adaptive Cruise control*. Retrieved September 14, 2017 from http://support.volvocars.com/hk/cars/Pages/owners-manual.aspx?mc=v526&my=2016&sw=15w46&article=0a55ef938975ba62c0a8015148dad001Google Scholar
- Robert West and Jane Hall. 1997. The Role of Personality and Attitudes in Traffic Accident Risk. Applied Psychology 46, 3: 253--264.Google ScholarCross Ref
- Joost C.F. de Winter, Riender Happee, Marieke H. Martens, and Neville A. Stanton. 2014. Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence. Transportation Research Part F: Traffic Psychology and Behaviour 27: 196--217.Google ScholarCross Ref
- Nidzamuddin Md. Yusof, Juffrizal Karjanto, Jacques Terken, Frank Delbressine, Muhammad Zahir Hassan, and Matthias Rauterberg. 2016. The Exploration of Autonomous Vehicle Driving Styles. In Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - Automotive 'UI 16, 245--252. Google ScholarDigital Library
- Autopilot | Tesla. Retrieved August 31, 2017 from https://www.tesla.com/autopilot?redirect=noGoogle Scholar
- The new Audi A8 -- conditional automated at level 3 | Audi MediaCenter. Retrieved March 2, 2018 from https://www.audi-mediacenter.com/en/on-autopilot-into-the-future-the-audi-vision-of-autonomous-driving-9305/the-new-audi-a8-conditional-automated-at-level-3-9307Google Scholar
- Drive Me -- the self-driving car in action | Volvo Cars. Retrieved August 30, 2017 from http://www.volvocars.com/intl/about/our-innovation-brands/intellisafe/autonomous-driving/drive-meGoogle Scholar
- Waymso. Retrieved September 4, 2017 from https://waymo.com/Google Scholar
- Here's how Daimler is evolving its tiny Smart car for self-driving - The Verge. Retrieved August 31, 2017 from https://www.theverge.com/2017/8/30/16226514/smart-vision-eq-electric-future-car2goGoogle Scholar
Index Terms
- Why Disable the Autopilot?
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