Attitudes towards self-driving cars: A pilot study
Presentation Type
Poster
Abstract
Attitudes towards self-driving cars: A pilot study
Nadya Alzate & Marc Gentzler
University of Central Florida
Automation in transportation has helped to decrease operator workload, enhancing efficiency and safety. For example, in aviation, the autopilot has allowed pilots to fly safer in complex situations (e.g. inclement weather) and has even permitted planes to land themselves. Although there is no argument as to the helpfulness of automation in aircraft, there have been many concerns as well. For instance, automation has been a main culprit in several well publicized accidents, such as Air France 447 and Asiana 214. These accidents have brought up the issue of overreliance on automation (Parasuraman & Riley, 1997). The question is whether pilots are ready to take over when the automation fails or functions in a manner which the pilots did not expect.
These same questions and concerns arise with automation in driving, especially as vehicle automation becomes more common. The invention of cruise control in 1958 was revolutionary, with the first car containing a cruise control feature was revealed by Chrysler. Since then, automation technology in cars have expanded to several features ranging from brake assist, lane assist, and even self-park (Davis, Animashaun, Schoenheer, & McDowell, 2008). The trend in automation is predicted to lead to the development of mainstream Fully Automated Driving Vehicles (FADVs) by the year 2018 (MacIver, B, 2015). One important question that needs to be addressed is how the general public feels about FADVs, as this can affect sales and may reveal valid concerns that the transportation industry needs to address.
Several scientific articles have been published in the last few years that have investigated attitudes towards automation in driving. For instance, Payre et al. (2014) examined attitudes of French drivers towards FADVs, finding that approximately 70% of participants scored above the median of a Likert scale on acceptance of FADVs. An even more recent study by Kyriakidis et al. (2015) including over 100 countries and 5000 responses asked participants about such variables as acceptance, willingness to purchase, and level of concern regarding FADVs while correlating these responses with personality and demographic variables. Kyriakidis et al. (2015) found that only about a third of participants stated that they would highly enjoy driving a FADV. Further, participants brought up hacking, safety and legal concerns about FADVs.
The current pilot study differs from recent research by focusing on open ended/free response items rather than Likert type items to gather more rich and detailed data regarding attitudes towards FADVs. The current study will include approximately 20 participants from a variety of different ages. In addition to standard demographic items, the survey includes 10 open ended questions centering on FADVs. Content analysis will be applied to the data to determine major categories and trends in responses. The greater goal of this study is to generate an improved questionnaire with more specific items, assessing more individuals across different demographics and to aid in the creation of focus group questions.
Attitudes towards self-driving cars: A pilot study
Attitudes towards self-driving cars: A pilot study
Nadya Alzate & Marc Gentzler
University of Central Florida
Automation in transportation has helped to decrease operator workload, enhancing efficiency and safety. For example, in aviation, the autopilot has allowed pilots to fly safer in complex situations (e.g. inclement weather) and has even permitted planes to land themselves. Although there is no argument as to the helpfulness of automation in aircraft, there have been many concerns as well. For instance, automation has been a main culprit in several well publicized accidents, such as Air France 447 and Asiana 214. These accidents have brought up the issue of overreliance on automation (Parasuraman & Riley, 1997). The question is whether pilots are ready to take over when the automation fails or functions in a manner which the pilots did not expect.
These same questions and concerns arise with automation in driving, especially as vehicle automation becomes more common. The invention of cruise control in 1958 was revolutionary, with the first car containing a cruise control feature was revealed by Chrysler. Since then, automation technology in cars have expanded to several features ranging from brake assist, lane assist, and even self-park (Davis, Animashaun, Schoenheer, & McDowell, 2008). The trend in automation is predicted to lead to the development of mainstream Fully Automated Driving Vehicles (FADVs) by the year 2018 (MacIver, B, 2015). One important question that needs to be addressed is how the general public feels about FADVs, as this can affect sales and may reveal valid concerns that the transportation industry needs to address.
Several scientific articles have been published in the last few years that have investigated attitudes towards automation in driving. For instance, Payre et al. (2014) examined attitudes of French drivers towards FADVs, finding that approximately 70% of participants scored above the median of a Likert scale on acceptance of FADVs. An even more recent study by Kyriakidis et al. (2015) including over 100 countries and 5000 responses asked participants about such variables as acceptance, willingness to purchase, and level of concern regarding FADVs while correlating these responses with personality and demographic variables. Kyriakidis et al. (2015) found that only about a third of participants stated that they would highly enjoy driving a FADV. Further, participants brought up hacking, safety and legal concerns about FADVs.
The current pilot study differs from recent research by focusing on open ended/free response items rather than Likert type items to gather more rich and detailed data regarding attitudes towards FADVs. The current study will include approximately 20 participants from a variety of different ages. In addition to standard demographic items, the survey includes 10 open ended questions centering on FADVs. Content analysis will be applied to the data to determine major categories and trends in responses. The greater goal of this study is to generate an improved questionnaire with more specific items, assessing more individuals across different demographics and to aid in the creation of focus group questions.