DocumentCode :
659570
Title :
DriveSense: Contextual handling of large-scale route map data for the automobile
Author :
Wiehr, Frederik ; Setlur, Vidya ; Joshi, Akanksha
Author_Institution :
Saarland Univ., Saarbrucken, Germany
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
87
Lastpage :
94
Abstract :
Automakers are increasingly providing connectivity enhancements for vehicles to download navigational data, as well as to upload sensor information to the cloud. Generally, while more data may be better, for the driver on-the-go, information needs to be displayed in a manner that can be comprehended rather quickly. One of the major problems with visualizing route maps is that the amount of information visualized is always the same regardless of the fact that an individual may be more familiar with the region or whether an individual is driving at varying speeds. Research has shown that complex visualizations with visual clutter can cause cognitive overload that adversely affects the performance of a user. Additionally, the attention and interaction abilities of a driver are significantly compromised in a vehicular environment. We propose DriveSense, a context-sensitive visualization system that automatically varies the GPS updates and the corresponding visualization being displayed to the user based on the speed of the vehicle as well as the familiarity of the region that the user is driving in. Based on a user evaluation, we found that subjects preferred using the automatic visualizations of route maps generated by DriveSense than the visual representations shown by a standard GPS. We also computed visual clutter for our visualizations at varying speeds and found that the clutter was significantly less for the routes displayed by DriveSense for faster speeds as compared to slower speeds.
Keywords :
automobiles; cartography; data visualisation; driver information systems; DriveSense; GPS updates; automatic visualizations; automobile; cognitive overload; complex visualizations; connectivity enhancements; context-sensitive visualization system; contextual handling; information visualization; large-scale route map data; navigational data; sensor information; vehicular environment; visual clutter; visual representations; visualizing route maps; Clutter; Context; Navigation; Rendering (computer graphics); Servers; Vehicles; Visualization; automobile; context; interface; route maps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691719
Filename :
6691719
Link To Document :
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