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Studying the effectiveness of MOVE: a contextually optimized in-vehicle navigation system
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
Portland, Oregon, USA
SESSION: In-vehicle interfaces table of contents
Pages: 571 - 580  
Year of Publication: 2005
ISBN:1-58113-998-5
Authors
Joonhwan Lee  Carnegie Mellon University, Pittsburgh, PA
Jodi Forlizzi  Carnegie Mellon University, Pittsburgh, PA
Scott E. Hudson  Carnegie Mellon University, Pittsburgh, PA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 19,   Downloads (12 Months): 139,   Citation Count: 8
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ABSTRACT

In-vehicle navigation has changed substantially in recent years, due to the advent of computer generated maps and directions. However, these maps are still problematic, due to a mismatch between the complexity of the maps and the attentional demands of driving. In response to this problem, we are developing the MOVE (Maps Optimized for Vehicular Environments) system. This system will provide situationally appropriate map information by presenting information that uses appropriate amounts of the driver's attention. In this paper, we describe our findings of studies to help shape the design of the MOVE system, including studies on map reading and in-vehicle navigation, and studies on the effectiveness of a variety of contextually optimized route map visualizations in a simulated driving context.Results show that contextually optimized displays designed for the MOVE system should significantly reduce perceptual load in the context of driving. In our laboratory experiment there was a six-fold decrease in the total map display fixation time and nearly threefold decrease in the number of glances needed to interpret the contextually optimized display compared to a static display.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  8

Collaborative Colleagues:
Joonhwan Lee: colleagues
Jodi Forlizzi: colleagues
Scott E. Hudson: colleagues