GamIM

Pong, Ke-Chen; Wang, Chi-An; Hsu, Shuo Hsiu

doi:10.1145/2559206.2581168

Cited by 8 publications

References 8 publications

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ConTEXT: context-aware adaptive SMS client for drivers to reduce risky driving behaviors

Khan¹,

Khusro

2022

Soft Comput

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Text messaging while driving has been considered a dangerous activity that may lead to serious injuries and tra c fatalities. Several assistive technologies and solutions have been developed to simplify texting activity. However, due to inconsistent and complex interface design, lack of logical navigational order, lack of context, complicated text-entry layouts, and laborious activities, the existing texting-related activities can lead to accidents. This paper recognized the risky driving patterns using the real-time AutoLog application. Based on this risky driving behavior, we have proposed ConTEXT, a usable SMS client, to overcome the issues pertaining to the usability of textual activities on smartphones while driving. ConTEXT application is evaluated both empirically as well as through real-time AutoLog application. We have collected data from 117 drivers through a questionnaire. The results show that the data is found reliable also alpha scores for all factors seem internally consistent as it ranges from 0.70 to 0.79 which is good. Similarly, we have reported Principal Component Factor Analysis (PCFA), which was found satis ed and appropriate as the Eigenvalue for all the factors is greater than zero. Furthermore, results obtained from the AutoLog dataset show an improved user experience, better control over the touch screen with minimum visual, physical, and mental load.

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