How technology commitment affects mode choice for a self-driving shuttle service

Abstract Although automation of motorized vehicles has the potential to transform public transport as we know it, prospective users are still skeptical. Trials with shared autonomous vehicles (AVs) offer an opportunity to assess future demand in a more realistic setting. In the context of an autonomous shuttle service trial operating on public road-space in Switzerland, we carried out a mode choice experiment with a random sample of 773 potential users. Study participants could choose between a rental bike, walking, and the autonomous bus at varying costs, travel time, occupation, and weather conditions. Based on attitudinal survey items on technology commitment, consisting of technology acceptance, control, and competence that were integrated into a latent variable model, we study how technology commitment affects mode choice behaviour. While results show a comparably low willingness to pay, they also indicate that technology acceptance is a robust predictor of autonomous bus usage. In line with the technology adoption life cycle argument, potential users are currently mainly technology enthusiasts. Thus, in order to also “bring on board” the less technophile parts of the population, improved communication of AV benefits will be required.

[1]  Joan L. Walker,et al.  Integration of Choice and Latent Variable Models , 1999 .

[2]  Charles Abraham,et al.  Psychological correlates of car use: A meta-analysis , 2008 .

[3]  S. Chaiken,et al.  The psychology of attitudes. , 1993 .

[4]  K. Train Discrete Choice Methods with Simulation , 2003 .

[5]  Eva M. Fraedrich,et al.  Societal and Individual Acceptance of Autonomous Driving , 2016 .

[6]  Yoram Shiftan,et al.  User preferences regarding autonomous vehicles , 2017 .

[7]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[8]  I. Ajzen,et al.  Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, and Reasoned Action , 2003 .

[9]  Iyad Rahwan,et al.  The social dilemma of autonomous vehicles , 2015, Science.

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

[11]  K. Axhausen,et al.  Income and Distance Elasticities of Values of Travel Time Savings: New Swiss Results , 2008 .

[12]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[13]  Bernd H. Schmitt,et al.  Waiting time and decision making: is time like money? , 1995 .

[14]  Johanna Zmud,et al.  Towards an Understanding of the Travel Behavior Impact of Autonomous Vehicles , 2017 .

[15]  K. Axhausen,et al.  In-store or online shopping of search and experience goods: A hybrid choice approach , 2019, Journal of Choice Modelling.

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

[17]  L. Frank,et al.  Urban form, travel time, and cost relationships with tour complexity and mode choice , 2007 .

[18]  Kara M. Kockelman,et al.  Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective , 2016 .

[19]  Yinhai Wang,et al.  Capturing ownership behavior of autonomous vehicles in Japan based on a stated preference survey and a mixed logit model with repeated choices , 2018, International Journal of Sustainable Transportation.

[20]  Edwin R. Galea,et al.  Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age , 2018 .

[21]  D. McFadden The Choice Theory Approach to Market Research , 1986 .

[22]  Bart van Arem,et al.  Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips , 2016 .

[23]  Cathy Macharis,et al.  Linking modal choice to motility: a comprehensive review , 2013 .

[24]  Rico Krueger,et al.  Preferences for shared autonomous vehicles , 2016 .

[25]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[26]  Wassim G. Najm,et al.  Frequency of Target Crashes for IntelliDrive Safety Systems , 2010 .

[27]  J. D. Winter,et al.  Acceptance of Driverless Vehicles: Results from a Large Cross-National Questionnaire Study , 2018 .

[28]  Daniel J. Fagnant,et al.  Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations , 2015 .

[29]  William Payre,et al.  Intention to use a fully automated car: attitudes and a priori acceptability , 2014 .

[30]  T. Gärling,et al.  Behaviour Theory and Soft Transport Policy Measures , 2011 .

[31]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[32]  Riender Happee,et al.  Public opinion on automated driving: results of an international questionnaire among 5000 respondents , 2015 .

[33]  Michael Siegrist,et al.  Factors influencing public acceptance of innovative food technologies and products , 2008 .

[34]  Peng Liu,et al.  Willingness to pay for self-driving vehicles: Influences of demographic and psychological factors , 2019, Transportation Research Part C: Emerging Technologies.

[35]  Zhigang Xu,et al.  Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions , 2018, Risk analysis : an official publication of the Society for Risk Analysis.

[36]  Kay W. Axhausen,et al.  Literature review on surveys investigating the acceptance of automated vehicles , 2017, Transportation.

[37]  Michael Sivak,et al.  A Survey of Public Opinion about Autonomous and Self-Driving Vehicles in the U.S., the U.K., and Australia , 2014 .

[38]  T. Schwanen,et al.  Understanding Auto Motives , 2011 .

[39]  Ricardo A. Daziano,et al.  Are Consumers Willing to Pay to Let Cars Drive for Them? Analyzing Response to Autonomous Vehicles , 2017 .

[40]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[41]  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.

[42]  S. Rice,et al.  Do gender and age affect willingness to ride in driverless vehicles: If so, then why? , 2019, Technology in Society.

[43]  Zhen Wang,et al.  What drives people to accept automated vehicles? Findings from a field experiment , 2018, Transportation Research Part C: Emerging Technologies.

[44]  P. Bentler,et al.  Models of attitude–behavior relations. , 1979 .

[45]  M. Siegrist The Influence of Trust and Perceptions of Risks and Benefits on the Acceptance of Gene Technology , 2000, Risk analysis : an official publication of the Society for Risk Analysis.

[46]  M. Dijst,et al.  Impact of Everyday Weather on Individual Daily Travel Behaviours in Perspective: A Literature Review , 2013 .

[47]  Jan C Zoellick,et al.  Assessing acceptance of electric automated vehicles after exposure in a realistic traffic environment , 2019, PloS one.

[48]  T. Bernauer,et al.  Public Opinion on Route 12: Interim report on the second survey on the pilot experiment of an automated bus service in Neuhausen am Rheinfall , 2018 .

[49]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[50]  K. Axhausen,et al.  The social aspect of residential location choice: on the trade-off between proximity to social contacts and commuting , 2018, Journal of Transport Geography.

[51]  Erfassung von Technikbereitschaft,et al.  Entwicklung und Validierung einer Kurzskala zur Erfassung von Technikbereitschaft , 2012 .

[52]  Felix Becker,et al.  mixl: An open-source R package for estimating complex choice models on large datasets , 2021, Journal of Choice Modelling.

[53]  Joshua D. Greene Our driverless dilemma , 2016, Science.

[54]  Natasha Merat,et al.  User acceptance of automated shuttles in Berlin-Schöneberg: A questionnaire study , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.

[55]  Isabell M. Welpe,et al.  How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups , 2016 .

[56]  J. Jacoby,et al.  Time and Consumer Behavior: An Interdisciplinary Overview , 1976 .

[57]  Emily C. Anania,et al.  Do Americans differ in their willingness to ride in a driverless bus? , 2018, Journal of Unmanned Vehicle Systems.

[58]  K. Kockelman,et al.  Are we ready to embrace connected and self-driving vehicles? A case study of Texans , 2016, Transportation.

[59]  Riender Happee,et al.  Conceptual Model to Explain, Predict, and Improve User Acceptance of Driverless Podlike Vehicles , 2016 .

[60]  Phillip T. Meade,et al.  The technology adoption life cycle attractor: Understanding the dynamics of high-tech markets , 2004 .

[61]  H. Arkes,et al.  The sunk cost and Concorde effects: Are humans less rational than lower animals? , 1999 .

[62]  D. McFadden,et al.  URBAN TRAVEL DEMAND - A BEHAVIORAL ANALYSIS , 1977 .

[63]  William Payre,et al.  What impressions do users have after a ride in an automated shuttle? An interview study , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[64]  Johanna Zmud,et al.  Self-Driving Vehicles: Determinants of Adoption and Conditions of Usage , 2016 .

[65]  C. Bhat,et al.  Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types , 2015 .

[66]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[67]  W. F. V. Raaij,et al.  How Consumers Trade Off Behavioural Costs and Benefits , 1986 .

[68]  I. Ajzen The theory of planned behavior , 1991 .

[69]  B. Orme Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research , 2005 .

[70]  Franz J. Neyer,et al.  Kurzskala Technikbereitschaft (TB, technology commitment) , 2016 .

[71]  K. Axhausen,et al.  Does variation in residents’ spatial mobility affect their preferences concerning local governance? , 2019, Political Geography.

[72]  Ali Shamshiripour,et al.  Eliciting preferences for adoption of fully automated vehicles using best-worst analysis , 2018, Transportation Research Part C: Emerging Technologies.

[73]  S. Chaiken,et al.  The advantages of an inclusive definition of attitude , 2007 .

[74]  C. Abraham,et al.  What cognitive mechanisms predict travel mode choice? A systematic review with meta-analysis , 2017 .

[75]  Luca Persia,et al.  Automated Vehicles and the Rethinking of Mobility and Cities , 2015 .

[76]  M. Givoni,et al.  The autonomous car—a blessing or a curse for the future of low carbon mobility? An exploration of likely vs. desirable outcomes , 2015 .

[77]  D. Soman The mental accounting of sunk time costs: Why time is not like money. , 2001 .

[78]  Danielle Dai,et al.  Public Perceptions of Self-Driving Cars: The Case of Berkeley, California , 2014 .

[79]  Urbano Nunes,et al.  Platooning With IVC-Enabled Autonomous Vehicles: Strategies to Mitigate Communication Delays, Improve Safety and Traffic Flow , 2012, IEEE Transactions on Intelligent Transportation Systems.

[80]  George Dimitrakopoulos,et al.  An empirical investigation on consumers’ intentions towards autonomous driving , 2018, Transportation Research Part C: Emerging Technologies.

[81]  Nick Hanley,et al.  The value of familiarity: Effects of knowledge and objective signals on willingness to pay for a public good , 2014 .

[82]  Andras Varhelyi,et al.  Modelling Acceptance of Driver Assistance Systems: Application of the Unified Theory of Acceptance and Use of Technology. , 2014 .