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Driving is a complex task that mainly requires visual perception and manual control. The performance of this task is influenced by the driver’s ability to perceive and adapt to different environmental demands, which in turn is influenced by driver’s state. Distraction, a driver state that is defined as “the diversion of attention away from activities critical for safe driving toward a competing activity” by Regan, Lee, and Young (2008, p. 34), has been shown to be prevalent among drivers (Dingus et al., 2016; Young & Lenné, 2010), to impair driving performance (Caird, Willness, Steel, & Scialfa, 2008; Horrey & Wickens, 2006; Regan et al., 2008), and to increase crash risk (Dingus et al., 2016; National Highway Traffic Safety Administration, 2018).
Technological advances are generating smarter vehicles that aim to enhance traffic safety and the experience of driving by detecting driver state (McCall & Trivedi, 2004; Pentland & Liu, 1999; Yang, Lin, & Bhattacharya, 2010), the state of the driving environment (Fridman et al., 2016), and driver intent (Jain, Koppula, Raghavan, Soh, & Saxena, 2015; Martin, Vora, Yuen, & Trivedi, 2018). These technologies that are mainly still in development are promising for distraction mitigation. For example, upon predicting driving impairment due to distraction, the vehicle may provide feedback to the driver that could help direct the driver’s attention back to the driving task (Donmez, Boyle, & Lee, 2007, 2008) or may take over lateral and/or longitudinal control (e.g. Stanton & Young, 2005). Further, when high levels of driver distraction are detected, the vehicle can adapt user interfaces that are built-in or brought into the vehicle, such as by filtering information content, delaying notifications, and blocking access to certain actions. For example, Tchankue, Wesson, and Vogts (2011) developed a prototype adaptive user interface for an in-car communication system that blocked incoming phone calls and prevented drivers from sending text messages when distraction was detected. Such a system can also block phone calls when environmental demands are predicted to be high. In general, better system awareness of the driving environment can lead to more effective and intelligent distraction mitigation strategies.