Abstract
“Smartphone Zombie” (or Smombie) is a new term that describes pedestrians playing with their mobile phones while walking. Research has shown that the usage of mobile phone distracts pedestrians, slows walking and increases the risk of car accidents. Relevant measures and laws have been taken to decrease the phenomenon; however, these measures and laws are costly, and the effects are limited. Therefore, the motivation of this study is to develop an efficient approach to identify and remind Smombies at intersections to reduce accident occurrences. In this approach, a framework for Smombie context awareness is proposed that integrates behavior information from pedestrians within physical and virtual space. In the framework, a set of sensors is employed to recognize the gesture of playing mobile phones. A modified multi-information fusion algorithm is developed to make Smombies aware of their physical context by combining fuzzy mathematics and Dempster-Shafer (D-S) evidence theory. Experiments indicate that the recall and precision of the algorithm are above 0.9, which means the proposed methods can effectively identify Smombies at crossroads.
Highlights
With the popularity of mobile phone use, more and more people become addicted to their phones
The experimental results include the parameter values of the basic probability assignment (BPA) function calculated from the training set and the final discrimination precision and recall obtained from the test set
With the increasing popularity of smartphones, more and more pedestrians are addicted to their mobile phones while across the road
Summary
With the popularity of mobile phone use, more and more people become addicted to their phones. According to an American observational study, approximately one-third of pedestrians displayed mobile-phonedistracted activity while crossing streets [5]. While walking is a dangerous behavior because a smartphone user’s vision is estimated to be only 5% of that of an average pedestrian [5]. These distracted pedestrians might encounter potential safety hazards, for example, tripping over curbs, bumping into other walkers, or even being hit by a car [6]. Based on the National Electronic Injury Surveillance System database, Nasar (2013) reported that the
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