The development of automated vehicles is something most vehicle manufacturers are working on these days. Different levels of automation allow the driver to perform other tasks while traveling than focus on the dynamic driving tasks. For professional drivers where there are strict laws for the amount of driving hours that is allowed without stopping and taking a break, resting while the vehicle is in an automated driving mode can increase the transport efficiency and the comfort of the driver. With data collected from 11 professional long-haul truck drivers in the ADAS&ME project, the goal of this thesis is to investigate if it is possible to obtain rest during autonomous driving (simulated with a confederate driver). Pre- and post-drive tests, KSS and SUS ratings, HRV features obtained from ECG data and blink features obtained from vertical EOG data was used in order to evaluate if rest could be obtained during simulated autonomous driving compared to normal driving. The results show that no clear trends or statistically significant differences can be seen while comparing simulated autonomous driving with normal driving. However one of the participants showed indications in KSS and SUS ratings together with the HRV features that rest was obtained during the simulated autonomous driving. The results indicate that it could be possible to obtain rest during autonomous driving, but a larger set of participants and a more demanding study setup is needed to verify the impact of autonomous driving as a substitute for regular rest breaks in terms of obtaining rest.


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    Titel :

    A Physiological investigation of Rest in Commercial Long-Haul Truck Drivers


    Beteiligte:

    Erscheinungsdatum :

    2018-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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