Train drivers are challenged to stay alert during train driving, for a big part due to the limited amount of tasks, and monotony of tasks. Driver condition monitoring (DCM) is a technology that involves measuring the driver’s alertness state in real-time, in which use of eye-based measurements is considered. Since DCM’s are upcoming in car and truck industry, train operators are now also showing interest in this technology to improve alertness. New technologies however are often resisted in railway operator companies, shown by strikes and works council involvement, and currently, it is unknown how drivers recognize and deal with alertness in the first place. Also for implementing DCM’s in the future, it is unknown what is required for such DCM feedback designs for acceptance to be promoted. This research thus aims to investigate how acceptance of train drivers can be promoted in a DCM feedback system. Considering a DCM system that can measure eye-directions, blinking behavior and gaze fixations, theoretical insights propose that you can use these measurements to infer driver distraction, sleepiness and mind-wandering. Theoretical approaches towards acceptance of technologies are generally focused on influencing the in-tention to use a technology. Generally used is Technology Acceptance model for evaluating acceptance of various technologies, proposing that the perceived usefulness and perceived ease of use are important to model an intention to use, and actual use of such DCM technology.
An explorative, qualitative approach led to conducting focus groups with train drivers and office employees to investigate the sensitive topic of alertness. In total, four train drivers and four office employees participated. To analyze the results qualitatively, thematic analysis was performed by coding iteratively. For current alertness strategies, the results showed that drivers recognize sleepiness the most, while fatigue and mind-wandering (task-related tiredness) are perceived as similar to sleepiness. Distraction was not recognized, as they are occupied more with a ’distributing’ and ’prioritizing’ their attention. Designing DCM feedback in a way that promotes acceptance is proposed to consider how drivers find a device useful, how their perceptions of autonomy and competence are influenced, and how to foster the trust towards the organization with respect to data use. The conclusions call for considering both rational factors (perceived usefulness) and affective factors (as a feeling of competence and autonomy might be related to intrinsic motivation) in the design of alertness feedback systems for train drivers.