Latest revision as of 11:32, 16 February 2021

Abstract

Driving a vehicle is a task affected by an increasing number and a rising complexity of Driver Assistance Systems (DAS) resulting in a raised cognitive load of the driver, and in consequence to the distraction from the main activity of driving. A number of potential solutions have been proposed so far, however, although these techniques broaden the perception horizon (e. g. the introduction of the sense of touch as additional information modality or the utilization of multimodal instead of unimodal interfaces), they demand the attention of the driver too. In order to cope with the issues of workload and/or distraction, it would be essential to find a non-distracting and noninvasive solution for the emergence of information. In this work we have investigated the application of heart rate variability (HRV) analysis to electrocardiography (ECG) data for identifying driving situations of possible threat by monitoring and recording the autonomic arousal states of the driver. For verification we have collected ECG and global positioning system (GPS) data in more than 20 test journeys on two regularly driven routes during a period of two weeks. The first results have shown that an indicated difference of the arousal state of the driver for a dedicated point on a route, compared to its usual state, can be interpreted as a warning sign and used to notify the driver about this, perhaps safety critical, change. To provide evidence for this hypothesis it would be essential in the next step to conduct a large number of journeys on different times of the day, using different drivers and various roadways.

Original document

The different versions of the original document can be found in:

• http://dl.acm.org/citation.cfm?id=1620529

• https://www.auto-ui.org/09/docs/p99-riener.pdf,

https://www.pervasive.jku.at/Research/Publications/_Documents/2009_Heart%20on%20the%20road%20-%20HRV%20analysis%20for%20monitoring%20a%20drivers%20affective%20state_Riener.pdf,

https://dl.acm.org/citation.cfm?id=1620529,

http://portal.acm.org/citation.cfm?doid=1620509.1620529,

https://dblp.uni-trier.de/db/conf/automotiveUI/automotiveUI2009.html#RienerFA09,

https://doi.acm.org/10.1145/1620509.1620529,

https://academic.microsoft.com/#/detail/2110019901

• http://dl.acm.org/ft_gateway.cfm?id=1620529&ftid=691359&dwn=1,

http://dx.doi.org/10.1145/1620509.1620529