|
Abstract
|
As the progression from partial to fully autonomous vehicles (AVs) accelerates, the driver's role will eventually change from that of active operator to that of passenger (Kyriakidis et al., 2019). It is argued that this change will lead to improved traffic safety, as well as increased comfort (Litman, 2017). Instead of focusing on the driving task, drivers will be able to occupy themselves with what were previously regarded as secondary tasks; relaxing, reading or indeed working while commuting to and from work (Fagnant & Kockelman, 2015). However, to utilise this greater freedom, drivers must first trust the AV. Research into automation has shown that trust is an important prerequisite to using automation systems (Parasuraman & Riley, 1997), since it plays an important role in creating user acceptance (Ghazizadeh, Lee, & Boyle, 2012) and in generating a positive user experience. Moreover, for the purposes of safe AV operation, it is important that the user's trust in the automation is appropriate to the actual capabilities of the system (Lee & See, 2004).
One important aspect that can build trust is vehicle capability (Lee & See, 2004), something which is commonly communicated via displays located in the cockpit of the vehicle (Helldin et al., 2013, Seppelt and Lee, 2007, Stockert et al., 2015). However, parameters such as lateral steering also provide the driver with an understanding of the vehicle's capability (Price, Venkatraman, Gibson, Lee, & Mutlu, 2016). It has been shown that driving styles, or how the act of driving an AV should be conducted, may affect a user's trust. In one study, Lee et al. (2016) found that perceived improper lane positioning (not keeping to an expected lane positioning) of an AV led to distrust. This is further supported by Sonoda and Wada (2016) who argue that the distance to a traffic object when passing affects the user's trust in the AV. Another, more recent, experimental study by Ekman and colleagues (Ekman, Johansson, Bligård, Karlsson, & Strömberg, 2019) concluded that driving style affects a user's trust by communicating information important for the user to be able to predict future actions of the AV.
However, to the authors' knowledge, the impact of driving styles in AVs has not been studied in everyday traffic situations; that is, situations often encountered in a day-to-day driving context, such as stopping for a pedestrian at a zebra crossing or overtaking a moving vehicle. Earlier research, in the area of automation, has shown the importance of also taking context into account, this since even though an automated system may in general be regarded as trustworthy, a user may not trust it in certain situations or under certain conditions (Marsh & Dibben, 2003). External situational aspects that may directly influence a user's trust include task difficulty and perceived risks (Hoff & Bashir, 2015). Task difficulty correlates to how easy or hard a task is perceived to be and, if automation fails an easy task, it is likely that the user's trust in it will decrease (Madhavan, Wiegmann, & Lacson, 2006). Perceived risks correlate with trust such that, if the situation presents excessively high risks, users may reduce their reliance on automation (Hoff and Bashir, 2015, Satterfield et al., 2017). Hence, it may be argued that trust is affected not only by the automation itself but also by contextual aspects and, further, that these need to be considered when studying and designing for appropriate trust...
Language: en |