The study aimed to systematically determine key human issues related to automated driving by utilising selected theoretical approaches applied in road traffic and work environments. The aim was also to compare the descriptive power of theoretical approaches to automated driving. Three approaches were applied to partial and high automation scenarios: (1) motivational theories, (2) model for the human as an information processor, and (3) core-task analysis. A descriptive analysis using the terms of theoretical approaches was conducted for automated driving in the contexts of urban and highway driving. In all, the qualitative data provided encompassed 13 subtasks of a trip made by car (e.g. choosing the route, entering a highway, driving in an urban intersection) in several contextual circumstances (traffic situation, environment, weather etc.). The study resulted in a list of 20 human issues related to automated driving. The issues were categorised in four groups highlighting the common aspects identified. These were: strategic decisions related to personal mobility; road safety; the role of information in automated driving; and communication and interaction in traffic. Each theoretical approach appeared useful in defining the issues, and the views were found to complement each other. Increasing automation in road transport calls for reforming the theoretical background and developing new models. The core-task analysis, not earlier applied in road transport, emerged as a promising model and is suggested to be applied in more detailed analysis of automated driving, specifically regarding information and communication aspects.

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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.32040/2242-122x.2019.t356
Licence: CC BY-NC-SA license

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