Driven to discussion: engaging drivers in conversation with a digital assistant as a countermeasure to passive task‐related fatigue. Issue 6 (14th March 2018)

• Record Type: Journal Article
• Authors: Large, David R.; Burnett, Gary; Antrobus, Vicki; Skrypchuk, Lee
• Is Part Of: IET intelligent transport systems. Volume 12:Issue 6(2018)
• Page Start: 420
• Page End: 426
• Publication Date: 2018-03-14
• Subjects: driver information systems -- natural language interfaces; Wizard‐of‐Oz approach -- digital assistant -- passive task‐related fatigue -- in‐vehicle natural language interfaces -- driver fatigue; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2017.0201
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : Using a Wizard‐of‐Oz approach, the authors explored the effectiveness of engaging drivers in conversation with a digital assistant as an operational strategy to combat the symptoms of passive task‐related fatigue. Twenty participants undertook two 30 min drives in a medium‐fidelity driving simulator between 13:00 and 16:30 when circadian and homeostatic influences naturally reduce alertness. Participants were asked to follow a lead‐car travelling at a constant speed of 68 mph, in a sparsely populated UK motorway scenario. During one of the counterbalanced drives, participants were engaged in conversation by a digital assistant ('Vid'). Results show that interacting with Vid had a positive effect on driving performance and arousal, evidenced by better lane‐keeping, earlier response to a potential hazard situation, larger pupil diameter, and an increased spread of attention to the road‐scene (i.e. fewer fixations concentrated on the road‐centre indicating a lower incidence of 'cognitive tunnelling'). Drivers also reported higher levels of alertness and lower sleepiness following the Vid drive. Subjective workload ratings suggest that drivers exerted less effort to 'stay awake' when engaged with Vid. The findings support the development and application of in‐vehicle natural language interfaces and can be used to inform the design of novel countermeasures for driver fatigue.