Abstract In-vehicle information systems (IVIS) aimed at supporting green driving have increased in both number and complexity over the past decade. However, this added information available to the driver raises significant ergonomic concerns for mental workload, distraction and ultimately driving task performance. Adaptive interfaces offer a potential solution to this problem. The Smart driving system evaluated in this study (which provided in-vehicle, real-time feedback to the driver on both green driving and safety related parameters via a Smartphone application) offers a comparatively simple workload algorithm, while offering complexity in its levels of adaptively on the display, with the theoretical aim to limit driver visual interaction and workload with the system during complex driving environments. Experimental results presented in this paper have shown that using the Smart driving system modulates workload towards manageable levels, by allowing an increase in driver workload when under low task demands (motorway and inter-urban driving) but not increasing workload when it is already at moderate levels (urban driving). Thus suggesting that any increase in workload can be integrated within the driving task using the spare attentional resource the driver has available.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Using Adaptive Interfaces to Encourage Smart Driving and Their Effect on Driver Workload


    Contributors:


    Publication date :

    2016-07-07


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Driver workload during differing driving maneuvers

    Hancock, P.A. / Wulf, G. / Thom, D. et al. | Elsevier | 1989


    Fatigue, workload and adaptive driver systems

    Hancock, P.A. | Online Contents | 1997


    Fatigue, workload and adaptive driver systems

    Hancock, P. A. / Verwey, W. B. / Western Australia; Traffic Board | British Library Conference Proceedings | 1996


    Highly reliable driving workload analysis using driver electroencephalogram (EEG) activities during driving

    Kim, J. Y. / Jeong, C. H. / Jung, M. J. et al. | British Library Online Contents | 2013


    Personalized Driver Workload Estimation in Real-World Driving

    Kochhar, Dev S. / Murphey, Yi / Xie, Yongquan | SAE Technical Papers | 2018