Journal of Physics: Conference Series Paper • The following article is Open access Exploring the relationship between light and subjective alertness using personal lighting conditions J. van Duijnhoven1, M.P.J. Aarts1, E.R. van den Heuvel2 and H.S.M. Kort3,4 Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 2042, CISBAT 2021 Carbon-neutral cities - energy efficiency and renewables in the digital era 8-10 September 2021, EPFL Lausanne, Switzerland Citation J. van Duijnhoven et al 2021 J. Phys.: Conf. Ser. 2042 012119 Download Article PDF References Download PDF 29 Total downloads Turn on MathJax Share this article Share this content via email Share on Facebook (opens new window) Share on Twitter (opens new window) Share on Mendeley (opens new window) Hide article information Author e-mails j.v.duijnhoven1@tue.nl Author affiliations 1 Building Lighting Group, Department of the Built Environment, Eindhoven University of Technology, Eindhoven, The Netherlands 2 Stochastics, Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands 3 Research Centre Healthy and Sustainable Living, University of Applied Sciences Utrecht, Utrecht, The Netherlands 4 Building Healthy Environments for Future Users Group, Department of the Built Environment, Eindhoven University of Technology, Eindhoven, The Netherlands DOI https://doi.org/10.1088/1742-6596/2042/1/012119 Buy this article in print Journal RSS Sign up for new issue notifications Create citation alert Abstract The discovery of the ipRGCs was thought to fully explain the mechanism behind the relationship between light and effects beyond vision such as alertness. However, this relationship turned out to be more complicated. The current paper describes, by using personal lighting conditions in a field study, further exploration of the relationship between light and subjective alertness during daytime. Findings show that this relationship is highly dependent on the individual. Although nearly all dose-response curves between personal lighting conditions and subjective alertness determined in this study turned out to be not significant, the results may be of high importance in the exploration of the exact relationship.
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Health symptoms may be influenced, supported, or even controlled via a lighting control system which includes personal lighting conditions and personal factors (health characteristics). In order to be effective, this lighting control system requires both continuous information on the lighting and health conditions at the individual level. A new practical method to determine these continuous personal lighting conditions has been developed: location-bound estimations (LBE). This method was validated in the field in two case studies; comparisons were made between the LBE and location-bound measurements (LBM) in case study 1 and between the LBE and person-bound measurements (PBM) in case study 2. Overall, the relative deviation between the LBE and LBM was less than 15%, whereas the relative deviation between the LBE and PBM was 32.9% in the best-case situation. The relative deviation depends on inaccuracies in both methods (i.e., LBE and PBM) and needs further research. Adding more input parameters to the predictive model (LBE) will improve the accuracy of the LBE. The proposed first approach of the LBE is not without limitations; however, it is expected that this practical method will be a pragmatic approach of inserting personal lighting conditions into lighting control systems.
Automated driving nowadays has become reality with the help of in-vehicle (ADAS) systems. More and more of such systems are being developed by OEMs and service providers. These (partly) automated systems are intended to enhance road and traffic safety (among other benefits) by addressing human limitations such as fatigue, low vigilance/distraction, reaction time, low behavioral adaptation, etc. In other words, (partly) automated driving should relieve the driver from his/her one or more preliminary driving tasks, making the ride enjoyable, safer and more relaxing. The present in-vehicle systems, on the contrary, requires continuous vigilance/alertness and behavioral adaptation from human drivers, and may also subject them to frequent in-and-out-of-the-loop situations and warnings. The tip of the iceberg is the robotic behavior of these in-vehicle systems, contrary to human driving behavior, viz. adaptive according to road, traffic, users, laws, weather, etc. Furthermore, no two human drivers are the same, and thus, do not possess the same driving styles and preferences. So how can one design of robotic behavior of an in-vehicle system be suitable for all human drivers? To emphasize the need for HUBRIS, this project proposes quantifying the behavioral difference between human driver and two in-vehicle systems through naturalistic driving in highway conditions, and subsequently, formulating preliminary design guidelines using the quantified behavioral difference matrix. Partners are V-tron, a service provider and potential developer of in-vehicle systems, Smits Opleidingen, a driving school keen on providing state-of-the-art education and training, Dutch Autonomous Mobility (DAM) B.V., a company active in operations, testing and assessment of self-driving vehicles in the Groningen province, Goudappel Coffeng, consultants in mobility and experts in traffic psychology, and Siemens Industry Software and Services B.V. (Siemens), developers of traffic simulation environments for testing in-vehicle systems.
