Published date: Jan 15 2018

Journal Title: KnE Social Sciences

Issue title: The 9th International Conference on Advances in Information Technology (IAIT-2017)

Pages: 119-131

DOI: 10.18502/kss.v3i1.1401

Siam Yamsaengsungsiam@sit.kmutt.ac.thSchool of Information Technology, King Mongkut’s University of Technology Thonburi

Borworn PapasratornSchool of Information Technology, King Mongkut’s University of Technology Thonburi

Traffic congestion is a major problem for large cities, and with the ubiquitous use of smartphones with GPS capabilities, drivers have increasingly come to rely on navigation applications for avoiding traffic congestion and routing to unfamiliar destinations.  However, in certain situations the suggested route may not be what the user expects and could result in perceived delays over known routes, increased stress and frustration for the driver, or even back tracking.  This has created a situation where drivers perceive that the information provided by navigation applications are not completely reliable and do not follow the suggested routes, thereby reducing the overall effectiveness of congestion avoidance. Additionally, drivers also make additional interaction with the navigation applications to verify the believability of the suggestions routes, creating more distraction and reducing on-road safety.  As such, this preliminary work assesses mobility information quality provided by leading navigation applications (Google Maps and Waze) against four dimensions of the PSP/IQ information quality framework to identify areas for improving information quality in three common driving scenarios.  The results indicate that both apps have similar levels of completeness, concise representation, and consistent representation.  And while the relevancy of the information quality is also similar in both apps, Waze’s representation of the some information elements allowed for quicker comparison and decision making. The findings from this work can be used to enhance user interaction and information presentation in navigation applications in order to improve user perceptions of information quality.

Keywords: smart mobility information, mobility information quality, congestion avoidance

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