@article{ref1,
title="A generalized method to extract visual time-sharing sequences from naturalistic driving data",
journal="IEEE transactions on intelligent transportation systems",
year="2017",
author="Ahlstrom, Christer and Kircher, Katja",
volume="18",
number="11",
pages="2929-2938",
abstract="Indicators based on visual time-sharing have been used to investigate drivers' visual behaviour during additional task execution. However, visual time-sharing analyses have been restricted to additional tasks with well-defined temporal start and end points and a dedicated visual target area. We introduce a method to automatically extract visual time-sharing sequences directly from eye tracking data. This facilitates investigations of systems, providing continuous information without well-defined start and end points. Furthermore, it becomes possible to investigate time-sharing behavior with other types of glance targets such as the mirrors. Time-sharing sequences are here extracted based on between-glance durations. If glances to a particular target are separated by less than a time-based threshold value, we assume that they belong to the same information intake event. Our results indicate that a 4-s threshold is appropriate. Examples derived from 12 drivers (about 100 hours of eye tracking data), collected in an on-road investigation of an in-vehicle information system, are provided to illustrate sequence-based analyses. This includes the possibility to investigate human-machine interface designs based on the number of glances in the extracted sequences, and to increase the legibility of transition matrices by deriving them from time-sharing sequences instead of single glances. More object-oriented glance behavior analyses, based on additional sensor and information fusion, are identified as the next future step. This would enable automated extraction of time-sharing sequences not only for targets fixed in the vehicle's coordinate system, but also for environmental and traffic targets that move independently of the driver's vehicle.<p /> <p>Language: en</p>",
language="en",
issn="1524-9050",
doi="10.1109/TITS.2017.2658945",
url="http://dx.doi.org/10.1109/TITS.2017.2658945"
}