Different level automation technology acceptance: Older adult driver opinion. (July 2021)

• Record Type: Journal Article
• Authors: Motamedi, Sanaz; Masrahi, Alaa; Bopp, Tobias; Wang, Jyh-Hone
• Is Part Of: Transportation research. Volume 80(2021)
• Page Start: 1
• Page End: 13
• Publication Date: 2021-07
• Subjects: Driving safety -- Challenging driving situation -- Automated driver assistant systems -- Full driving automation -- Level-1 of automation -- Older adult drivers, Technology acceptance; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2021.03.010
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: The USEA Model predicts user behavioral intention to use of level-1 automation better than level-5 automation. Perceived usefulness was found to be the strongest predictor of behavioral intention to use in both level of technologies. Perceived safety is significant predictor of behavioral intention to use, which impacts perceived usefulness. Perceived anxiety has limited impact than in the acceptance model of both level technologies. Abstract: The increase in the number of older adult drivers in developed countries has raised safety concerns due to the decline in their sensory, motor, perceptual, and cognitive abilities which can limit their driving capabilities. Their driving safety could be enhanced by the use of modern Automated Driver Assistance Systems (ADASs) and might totally resolved by full driving automation. However, the acceptance of these technologies by older adult drivers is not yet well understood. Thus, this study investigated older adult drivers' intention to use six ADASs and full driving automation through two questionnaires with 115 and 132 participants respectively in Rhode Island, USA. A four-dimensional model referred to as the USEA model was used for exploring older adult drivers' technology acceptance. The USEA model included perceived usefulness, perceived safety, perceived ease of use, and perceived anxiety. Path Analysis was applied to evaluate the proposed model. The results of this study identified the important factors in older adult drivers' intention to use ADASs and full driving automation, which could assist stakeholders in improving technologies for use by older drivers.