Exploring Personalised Autonomous Vehicles to Influence User Trust

Trust is a major determinant of acceptance of an autonomous vehicle (AV), and a lack of appropriate trust could prevent drivers and society in general from taking advantage of such technology. This paper makes a new attempt to explore the effects of personalised AVs as a novel approach to the cognitive underpinnings of drivers’ trust in AVs. The personalised AV system is able to identify the driving behaviours of users and thus adapt the driving style of the AV accordingly. A prototype of a personalised AV was designed and evaluated in a lab-based experimental study of 36 human drivers, which investigated the impact of the personalised AV on user trust when compared with manual human driving and non-personalised AVs. The findings show that a personalised AV appears to be significantly more reliable through accepting and understanding each driver’s behaviour, which could thereby increase a user’s willingness to trust the system. Furthermore, a personalised AV brings a sense of familiarity by making the system more recognisable and easier for users to estimate the quality of the automated system. Personalisation parameters were also explored and discussed to support the design of AV systems to be more socially acceptable and trustworthy.

[1]  Klaus Bengler,et al.  Why Do I Have to Drive Now? Post Hoc Explanations of Takeover Requests , 2018, Hum. Factors.

[2]  R. M. Taylor,et al.  Multi-Modal Cockpit Warnings: Pictures. Words. or Both? , 1992 .

[3]  Ward Vanlaar,et al.  Fatigued and drowsy driving: a survey of attitudes, opinions and behaviors. , 2008, Journal of safety research.

[4]  Joseph B. Lyons,et al.  Human–Human Reliance in the Context of Automation , 2012, Hum. Factors.

[5]  Masooda Bashir,et al.  Trust in Automation , 2015, Hum. Factors.

[6]  N. Epley,et al.  The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle , 2014 .

[7]  Mukesh Singhal,et al.  Do You Want Your Autonomous Car to Drive Like You? , 2015, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

[8]  Ellen Enkel,et al.  Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices , 2016 .

[9]  Ann M. Bisantz,et al.  Assessment of operator trust in and utilization of automated decision-aids under different framing conditions , 2001 .

[10]  Kanwaldeep Kaur,et al.  Trust in driverless cars: Investigating key factors influencing the adoption of driverless cars , 2018 .

[11]  John Zimmerman,et al.  A fieldwork of the future with user enactments , 2012, DIS '12.

[12]  Francesco Borrelli,et al.  Autonomous car following: A learning-based approach , 2015, 2015 IEEE Intelligent Vehicles Symposium (IV).

[13]  Peter A. M. Ruijten,et al.  Enhancing Trust in Autonomous Vehicles through Intelligent User Interfaces That Mimic Human Behavior , 2018, Multimodal Technol. Interact..

[14]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[15]  Barry Smyth,et al.  Personalized Route Planning: A Case-Based Approach , 2000, EWCBR.

[16]  Fredrick Ekman,et al.  Creating Appropriate Trust for Autonomous Vehicle Systems: A Framework for HMI Design , 2016 .

[17]  Lionel P. Robert,et al.  Monitoring and Trust in Virtual Teams , 2016, CSCW.

[18]  M. Hoedemaeker,et al.  Driving behaviour with ACC and the acceptance by individual drivers , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[19]  Antti Oulasvirta,et al.  Understanding mobile contexts , 2003, Personal and Ubiquitous Computing.

[20]  L. Eboli,et al.  How drivers' characteristics can affect driving style , 2017 .

[21]  Mette Møller,et al.  Keep on cruising: Changes in lifestyle and driving style among male drivers between the age of 18 and 23 , 2013 .

[22]  M. König,et al.  Users’ resistance towards radical innovations: The case of the self-driving car , 2017 .

[23]  G. Kilduff,et al.  From Glue to Gasoline , 2013, Psychological science.

[24]  F. Cushman Crime and punishment: Distinguishing the roles of causal and intentional analyses in moral judgment , 2008, Cognition.

[25]  Yong Jie Zhao,et al.  Damage behaviors of unidirectional CFRP in orthogonal cutting: A comparison between single- and multiple-pass strategies , 2020 .

[26]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[27]  Serge P. Hoogendoorn,et al.  Heterogeneity In Car-Following Behavior: Theory And Empirics , 2011 .

[28]  Mark Stevenson,et al.  Accuracy of self-report of on-road crashes and traffic offences in a cohort of young drivers: the DRIVE study , 2010, Injury Prevention.

[29]  Heiko Wersing,et al.  Personalization in advanced driver assistance systems and autonomous vehicles: A review , 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).

[30]  Andrew May,et al.  The impact of user- and system-initiated personalization on the user experience at large sports events. , 2016, Applied ergonomics.

[31]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004 .

[32]  Tal Oron-Gilad,et al.  The effect of system aesthetics on trust, cooperation, satisfaction and annoyance in an imperfect automated system. , 2012, Work.

[33]  MariAnne Karlsson,et al.  Exploring automated vehicle driving styles as a source of trust information , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[34]  Linda Ng Boyle,et al.  Extending the Technology Acceptance Model to assess automation , 2011, Cognition, Technology & Work.

[35]  Petros A. Ioannou,et al.  Personalized Driver/Vehicle Lane Change Models for ADAS , 2015, IEEE Transactions on Vehicular Technology.

[36]  Josef F. Krems,et al.  Objective Metrics of Comfort: Developing a Driving Style for Highly Automated Vehicles , 2016 .

[37]  Han Huang,et al.  Deformation mechanism and force modelling of the grinding of YAG single crystals , 2019, International Journal of Machine Tools and Manufacture.

[38]  Dapeng Tan,et al.  Cavitation-based soft abrasive flow processing method , 2020, The International Journal of Advanced Manufacturing Technology.

[39]  Mark Vollrath,et al.  Improving the Driver–Automation Interaction , 2013, Hum. Factors.

[40]  Matthias Rauterberg,et al.  The Exploration of Autonomous Vehicle Driving Styles: Preferred Longitudinal, Lateral, and Vertical Accelerations , 2016, AutomotiveUI.

[41]  J. Freeman,et al.  Comparison of self-report and objective measures of driving behavior and road safety: A systematic review. , 2018, Journal of safety research.

[42]  Hans-Rüdiger Pfister,et al.  The influence of time headway on subjective driver states in adaptive cruise control , 2014 .

[43]  Berry Eggen,et al.  The relation between self-reported driving style and driving behaviour. A simulator study , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.

[44]  Jaap Ham,et al.  Trust in Smart Systems , 2012, Hum. Factors.

[45]  Hesham A Rakha,et al.  Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions. , 2015, Accident; analysis and prevention.

[46]  Mohammed A. Quddus,et al.  Examining lane change gap acceptance, duration and impact using naturalistic driving data , 2019, Transportation Research Part C: Emerging Technologies.

[47]  Andrew F. Monk,et al.  Theory of Personalization of Appearance: Why Users Personalize Their PCs and Mobile Phones , 2003, Hum. Comput. Interact..

[48]  Stefania Serafin,et al.  Volvo intelligent news: A context aware multi modal proactive recommender system for in-vehicle use , 2014, Pervasive Mob. Comput..

[49]  O. Taubman–Ben-Ari,et al.  The value of self-report measures as indicators of driving behaviors among young drivers , 2016 .

[50]  G. Currie,et al.  Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy , 2019, Journal of Transport and Land Use.

[51]  James L. Szalma,et al.  A Meta-Analysis of Factors Influencing the Development of Trust in Automation , 2016, Hum. Factors.

[52]  Joerg J Meerpohl,et al.  Authors report lack of time as main reason for unpublished research presented at biomedical conferences: a systematic review. , 2015, Journal of clinical epidemiology.

[53]  Josef F. Krems,et al.  Driving comfort, enjoyment and acceptance of automated driving – effects of drivers’ age and driving style familiarity , 2018, Ergonomics.

[54]  Andrew McGordon,et al.  Development of a driver model to study the effects of real-world driver behaviour on the fuel consumption , 2011 .

[55]  M. Alicke Culpable control and the psychology of blame. , 2000, Psychological bulletin.

[56]  Fridulv Sagberg,et al.  A Review of Research on Driving Styles and Road Safety , 2015, Hum. Factors.

[57]  Klaus Bengler,et al.  Trust in Automation – Before and After the Experience of Take-over Scenarios in a Highly Automated Vehicle☆ , 2015 .

[58]  Francis T. Durso,et al.  Individual Differences in the Calibration of Trust in Automation , 2015, Hum. Factors.

[59]  Jessie Y. C. Chen,et al.  A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction , 2011, Hum. Factors.

[60]  Alexandra Neukum,et al.  Increasing anthropomorphism and trust in automated driving functions by adding speech output , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

[61]  M. Mikulincer,et al.  The multidimensional driving style inventory--scale construct and validation. , 2004, Accident; analysis and prevention.

[62]  Martin Ingvar,et al.  A History of Psychosis in Bipolar Disorder is Associated With Gray Matter Volume Reduction , 2017, Schizophrenia bulletin.

[63]  Yong Gu Ji,et al.  Investigating the Importance of Trust on Adopting an Autonomous Vehicle , 2015, Int. J. Hum. Comput. Interact..

[64]  I. C. MariAnne Karlsson,et al.  Setting the stage for autonomous cars: a pilot study of future autonomous driving experiences , 2015 .

[65]  Dawn M. Tilbury,et al.  Situational Awareness, Drivers Trust in Automated Driving Systems and Secondary Task Performance , 2019, SAE International Journal of Connected and Automated Vehicles.

[66]  Dariusz G. Mikulski,et al.  Trust-based controller for convoy string stability , 2014, 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS).

[67]  Dragos Axinte,et al.  Textured grinding wheels: A review , 2016 .

[68]  Catherine M. Burns,et al.  Autonomous Driving in the Real World: Experiences with Tesla Autopilot and Summon , 2016, AutomotiveUI.

[69]  Göran Falkman,et al.  Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving , 2013, AutomotiveUI.

[70]  Alan R. Dennis,et al.  Individual Swift Trust and Knowledge-Based Trust in Face-to-Face and Virtual Team Members , 2009, J. Manag. Inf. Syst..

[71]  Andrew J. May,et al.  Mobile Personalization at Large Sports Events User Experience and Mobile Device Personalization , 2007, HCI.

[72]  Anthony Gerald King,et al.  Autonomous Driving - A Practical Roadmap , 2010 .