Investigating the decision to travel more in a partially automated electric vehicle

Abstract Partially automated battery electric vehicles (BEVs) are already being sold to and used by consumers. Estimates indicate that as of the end of 2019, there were over 1.2 million Partially Automated Tesla Vehicles—the subject of this study—on the roads globally. Despite this, little research has been done to understand how partially automated vehicles may be changing travel behaviour. In this study we conduct qualitative interviews with 35 owners of Tesla BEVs with Autopilot. The focus was to determine whether partially automated BEVs could cause or are causing an increase in travel. Results show that partial automation and electrification leads to interviewees driving more and choosing to drive rather than fly. These changes are due to increased comfort and reduced stress due to the partial automation system, and because of the lower running costs of a BEV. The results show how partially automated BEVs could increase vehicle miles travelled.

[1]  K. Roulston,et al.  Reconceptualizing Bias in Teaching Qualitative Research Methods , 2015 .

[2]  Christos Gkartzonikas,et al.  What have we learned? A review of stated preference and choice studies on autonomous vehicles , 2019, Transportation Research Part C: Emerging Technologies.

[3]  Kenneth A. Perrine,et al.  Anticipating long-distance travel shifts due to self-driving vehicles , 2020, Journal of Transport Geography.

[4]  Bryan Reimer,et al.  Learning to Use In-Vehicle Technologies: Consumer Preferences and Effects on Understanding , 2018, Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

[5]  Elias Boutros Khalil,et al.  The impact of private autonomous vehicles on vehicle ownership and unoccupied VMT generation , 2018 .

[6]  F. Asdrubali,et al.  Carbon Footprint of autonomous vehicles at the urban mobility system level: A traffic simulation-based approach , 2019, Transportation Research Part D: Transport and Environment.

[7]  Bryan Reimer,et al.  Consumer Comfort with Vehicle Automation: Changes Over Time , 2019, Proceedings of the 10th International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design: driving assessment 2019.

[8]  Dorothy Watson,et al.  Correcting for Acquiescent Response Bias in the Absence of a Balanced Scale , 1992 .

[9]  Bryan Reimer,et al.  What's in a Name: Vehicle Technology Branding & Consumer Expectations for Automation , 2017, AutomotiveUI.

[10]  Graham R. Gibbs,et al.  Thematic Coding and Categorizing , 2007 .

[11]  J. Zmud,et al.  Consumer acceptance and travel behavior : impacts of automated vehicles : final report. , 2016 .

[12]  Bart van Arem,et al.  Policy and society related implications of automated driving: A review of literature and directions for future research , 2017, J. Intell. Transp. Syst..

[13]  Y. Trope,et al.  Construal-level theory of psychological distance. , 2010, Psychological review.

[14]  Francesco Ciari,et al.  Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies , 2018, Transport Reviews.

[15]  Viktoriya Kolarova,et al.  Assessing the effect of autonomous driving on value of travel time savings: A comparison between current and future preferences , 2019, Transportation Research Part A: Policy and Practice.

[16]  M. Sivak,et al.  Potential impact of self-driving vehicles on household vehicle demand and usage , 2015 .

[17]  Ming Xu,et al.  A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehicles , 2018, Environmental science & technology.

[18]  Wei Zhang,et al.  An interview study exploring Tesla drivers' behavioural adaptation. , 2018, Applied ergonomics.

[19]  Catherine M. Burns,et al.  Trust in autonomous vehicles: The case of Tesla Autopilot and Summon , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[20]  Suzanne Childress,et al.  Using an Activity-Based Model to Explore the Potential Impacts of Automated Vehicles , 2015 .

[21]  Don MacKenzie,et al.  Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles , 2016 .

[22]  Patricia L. Mokhtarian,et al.  Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment , 2018, Transportation.

[23]  Gil Tal,et al.  Who is buying electric vehicles in California? Characterising early adopter heterogeneity and forecasting market diffusion , 2019, Energy Research & Social Science.

[24]  Anthony J. Ries,et al.  Trust and Distrust of Automated Parking in a Tesla Model X , 2020, Hum. Factors.

[25]  Gonçalo Homem de Almeida Correia,et al.  On the impact of vehicle automation on the value of travel time while performing work and leisure activities in a car: Theoretical insights and results from a stated preference survey , 2019, Transportation Research Part A: Policy and Practice.

[26]  Caspar G. Chorus,et al.  How will automated vehicles shape users’ daily activities? Insights from focus groups with commuters in the Netherlands , 2019, Transportation Research Part D: Transport and Environment.

[27]  Ching-Yao Chan Advancements, prospects, and impacts of automated driving systems , 2017 .

[28]  A. Furnham Response bias, social desirability and dissimulation , 1986 .

[29]  M. Endsley Autonomous Driving Systems: A Preliminary Naturalistic Study of the Tesla Model S , 2017 .

[30]  P. Galdas Revisiting Bias in Qualitative Research , 2017 .

[31]  Don MacKenzie,et al.  Would being driven by others affect the value of travel time? Ridehailing as an analogy for automated vehicles , 2019, Transportation.

[32]  Scott Hardman,et al.  How do drivers use automation? Insights from a survey of partially automated vehicle owners in the United States , 2019, Transportation Research Part A: Policy and Practice.