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      An Ontological Approach to Inform HMI Designs for Minimising Driver Distractions with ADAS


      1 , 1 , 1 , 1 , 2

      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Advanced driver assistance system, Driving distraction, Human machine interface

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          ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and efficiency as well as comfort for drivers in the driving process. Recent studies have noticed that when Human Machine Interface (HMI) is not designed properly, an ADAS can cause distraction which would affect its usage and even lead to safety issues. Current understanding of these issues is limited to the context-dependent nature of such systems. This paper reports the development of a holistic conceptualisation of how drivers interact with ADAS and how such interaction could lead to potential distraction. This is done taking an ontological approach to contextualise the potential distraction, driving tasks and user interactions centred on the use of ADAS. Example scenarios are also given to demonstrate how the developed ontology can be used to deduce rules for identifying distraction from ADAS and informing future designs.

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              Monitoring drivers' mental workload in driving simulators using physiological measures.

              Many traffic accidents are caused by, or at least related to, inadequate mental workload, when it is either too low (vigilance) or too high (stress). Creating variations in mental workload and accident-prone driving for research purposes is difficult in the real world. In driving simulators the measurement of driver mental workload is relatively easily conducted by means of physiological measures, although good research skills are required and it is time-consuming. The fact that modern driving simulator environments are laboratory-equivalent nowadays allows full control with respect to environmental conditions, scenarios and stimuli, and enables physiological measurement of parameters of mental workload such as heart rate and brain activity. Several examples are presented to illustrate the potential of modern high-standard driving simulator environments regarding the monitoring of drivers' mental workload during task performance. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

                Author and article information

                July 2018
                July 2018
                : 1-12
                [1 ] Bournemouth University

                Fern Barrow, Poole BH12 5BB
                [2 ] Coventry University

                Priory Street, Coventry CV1 5FB
                © Fan et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Electronic Workshops in Computing


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