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http://dx.doi.org/10.12815/kits.2019.18.2.93

Effects of Smartphone Usage on Walking Speed using Machine Learning Method  

Jin, Hye ryun (Center of Infrastructure Asset Management, Hanbat National University)
Do, Myung sik (Dept. of Urban Eng., Hanbat National University)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.18, no.2, 2019 , pp. 93-103 More about this Journal
Abstract
This study analyzed the impact of smartphone usage on walking speed during walking on two pedestrian walkways in Daejeon Metropolitan City. For the analysis, the video data about the actual use of smartphone was acquired and the walking speed was calculated based on the walking density of the pedestrian Level Of Service(LOS) presented in the Road Capacity Manual. Multiple regression analysis and decision tree using machine learning were used to analyze the impact of smartphone usage on walking speed, and as the explanatory variables, gender, disable smartphone, use of smartphone using auditory function, use of smartphone using visual function, LOS A, LOS B, LOS C were adopted. The result showed that LOS C had the highest impact on walking speed change and the women's group using their visual function was founded to have the slowest walking speed in LOS C. In particular, the author found that walking speed significantly decreased in the case of use of visual function rather than listening to music or the hearing on the phone.
Keywords
Machine Learning; Decision tree; Multiple regression; Smartphone; Walking speed;
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