Connected Automated Vehicles (CAV) are completely self-driving cars that are equipped with tools to communicate and share data with other devices both inside and outside the car, such as other cars, and public transport systems. The driver has the role of a passenger inside CAV. CAV is not available on the market right now, but they may dominate the road environment in the future. Many car manufacturers have already incorporated some degrees of automation into their cars, such as parking assist, and adaptive cruise control. Some manufacturers are now pilot testing vehicles with high or full automation in designated areas.
CAV may play an important role to solve several societal problems, such as increasing traffic safety, reducing traffic jams, enhancing mobility for those unable to drive, and reducing traffic CO2 emissions.
In the SUaaVE project (Horizons 2020 project funded by the EU) we examine the acceptability and acceptance of CAV. Acceptability is an attitude people have towards CAV before they have experienced it. Acceptance is related to if people want to use or buy CAV after they have experienced it. We want to find out what drives the acceptability and acceptance of CAV, and what we can do to increase acceptability and acceptance for both potential users, as well as for other road users. SUaaVE aims to make a change in the current situation of public acceptance of CAV by focusing on the human side to improve more “intangible” aspects as safety perception, attitudes, and in general, emotional appraisal of CAV. First, we have examined what factors predict the acceptability of CAV. Based on an extensive literature review and several focus groups conducted in Italy, Spain, France, and the Netherlands, we proposed a psychological model that can predict acceptability of CAV.
Large Scale Survey in 6 European Countries
To test our psychological model that predicts the acceptability of CAV, we conducted a large scale survey. The survey was conducted online in 6 European countries: the United Kingdom, the Netherlands, Germany, France, Spain, and Italy. In total, almost 3800 people filled out the survey in April 2020. The sample was relatively evenly spread in terms of age (about 20% was between 18 and 30 years old, and about 20% was older than 55), gender, and country (about 630 participants per country). In the survey we explained what CAV is, and measured acceptability, how they perceived different aspects of CAV, and also measured various individual differences such as interest in technology and personal values.
Predicting Acceptability of CAV
We found that acceptability of CAV is predicted by its attributes, the perceived adoption norm, and the perceived behavioral control. The perceived adoption norm is the extent to which someone believes close others (such as friends, family, and coworkers) will adopt CAV in the future. The perceived behavioral control is the extent to which someone believes they will be capable of using CAV. Both of these positively predicted acceptability of CAV. As for CAV’s attributes, we found 7 distinct characteristics of CAV that influence acceptability: perceived safety (is CAV safe?), perceived convenience (is CAV useful?), perceived control (can I control CAV’s behavior?), perceived pleasure (is driving CAV enjoyable?), trust in CAV technology (is CAV’s computer system trustworthy?), perceived environmental sustainability (is CAV environmentally friendly?), and perceived status-enhancement (is CAV a status product?). Out of these, perceived safety, perceived convenience, and perceived environmental sustainability had the strongest positive effects on acceptability of CAV. Based on these results, we formulated some initial guidelines to enhance public acceptability.
Aside from the direct predictors of acceptability, we have examined other factors that could influence acceptability of CAV. For example, we have examined differences between drivers and non-drivers, and effects of personal values, the need for control, and experience with car technology. The full results are available as open access on www.suaave.eu/results. On this website you can read more about the SUaaVE project in general, as well as read all currently published open access deliverables.