Smombie Forecaster: Alerting Smartphone Users About Potential Hazards in Their Surroundings

Goh, Hwarang; Kim, Woojeong; Han, Jae‐Ho; Han, Kyungsik; Noh, Youngmin

doi:10.1109/access.2020.3017653

Cited by 8 publications

(5 citation statements)

References 11 publications

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“…Delays and potential conflicts in the pedestrian flow can cause inefficient station operation or even safety problems. Inspired by the measure of installing traffic lights on sidewalks by KICT ( 5 ), it may be advisable to deploy clear directions, warning signals, or sounds around bottlenecks to draw passengers’ attention from their smartphones to the surroundings. Thereby, when passengers using smartphones walk by, their attention may be drawn from their smartphones for seconds and they may change their walking patterns (e.g., check point 1, as shown in Figure 14, where those dressed in white are smartphone users, and those in black are normal pedestrians).…”

Section: Results Of Analysismentioning

confidence: 99%

“…For instance, Korea Institute of Civil Engineering and Building Technology (KICT) attempted to install traffic lights on sidewalks and warn users of approaching vehicles through mobile apps. Seemingly, the duration of pedestrians’ pauses in smartphone usage was increased around 1.59 times by these measures ( 5 ). In Yamato City, Japan, regulations were imposed to prohibit people from using smartphones while walking in public places.…”

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confidence: 99%

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Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model

Shen

Mao

Hsu

et al. 2022

Transportation Research Record: Journal of the Transportation R

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The smartphone has become nearly indispensable in people’s daily lives. Prevalent smartphone usage can be observed on various occasions, even during walking. However, pedestrians’ perception of their surroundings may decline because they are absorbed by using the smartphone. The behavior of pedestrians using smartphones while walking at transit stations can be viewed as disturbance to pedestrian flows, thereby reducing the efficiency of station operation or even creating safety problems. This study seeks to describe such behavioral features mathematically and provide relevant implications for transit station design. Based on the social force model, the parameters reflecting the effect of smartphone usage on the perceived driving and repulsive forces are added and calibrated. By extracting trajectory data from the videos filmed in the field, the genetic algorithm is employed for the calibration process to minimize the gaps between the actual and projected trajectories. Two sets of parameter settings, for pedestrians with and without using smartphones, are determined and further applied to microscopic pedestrian simulation for a transfer station of the metro system in Taipei, Taiwan. The results indicate that pedestrians using smartphones are more prone to being affected by other pedestrians, revealing that their velocities are relatively unstable, while they need longer relaxation time to attain their desired walking statuses. The simulation results also visualize the potential bottlenecks in the station, where smartphone users may become obstacles to other pedestrians and increase the congestion level, highlighting the importance of incorporating the behavior modeling of pedestrians using smartphones into transit station design.

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Section: Results Of Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model

Shen

Mao

Hsu

et al. 2022

Transportation Research Record: Journal of the Transportation R

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“…In an observational study of pedestrians walking in the street in a medium-sized Spanish city, Fernandez et al (2020) found that certain population groups (especially young women) have a high risk of being involved in accidents due to smartphone usage whilst walking. A related body of research has examined the possibility of introducing smartphoneaided pedestrian safety devices (apps) to alert users of hazards and obstacles whilst walking in public (Goh et al, 2020;Zhuang and Fang, 2020;Kim et al, 2018a;Hincap e-Ramos and Irani, 2014;Foerster et al, 2014;Wang et al, 2012). Indeed, Kashimoto et al (2020) developed such an app to monitor smartphone zombie behaviours over a 15-day period, but their small sample (n 5 7; n 5 5 with complete data) limits the scope of their findings.…”

Section: Previous Research On Smartphone Zombiesmentioning

confidence: 99%

“…(2020) found that certain population groups (especially young women) have a high risk of being involved in accidents due to smartphone usage whilst walking. A related body of research has examined the possibility of introducing smartphone-aided pedestrian safety devices (apps) to alert users of hazards and obstacles whilst walking in public (Goh et al ., 2020; Zhuang and Fang, 2020; Kim et al ., 2018a; Hincapé-Ramos and Irani, 2014; Foerster et al ., 2014; Wang et al ., 2012). Indeed, Kashimoto et al .…”

Section: Previous Research On Smartphone Zombiesmentioning

confidence: 99%

The problematic use of smartphones in public: the development and validation of a measure of smartphone “zombie” behaviour

Pressey¹,

Houghton²,

Istanbulluoğlu³

2023

ITP

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PurposeWe have witnessed an evolution in the use of smartphones in recent years. We have been aware for some time of the potentially deleterious impact of smartphones on users' lives and their propensity for user addiction, as reflected in the large and growing body of work on this topic. One modern phenomenon – the distracted mobile phone user in public, or “smartphone zombie” – has received limited research attention. The purpose of the present study is to develop a robust measure of smartphone zombie behaviour.Design/methodology/approachThe research deign comprises three studies: A round of focus groups (n = 5) and two online surveys (survey one n = 373, survey two n = 386), in order to develop and validate a three-factor, 15-item measure named the Smartphone Zombie Scale (SZS).FindingsFollowing the round of focus groups conducted, Exploratory Factor Analysis and a Confirmatory Factor Analysis, the SZS measure (Cronbach's α = .932) is demonstrated to be robust and comprises three factors: Attention Deficit (Cronbach's α = .922), Jeopardy (Cronbach's α = .817) and Preoccupation (Cronbach's α = .835), that is shown to be distinct to existing closely related measures (Smartphone Addiction scale and Obsessive Compulsive Use).Originality/valueThe present study represents the first extant attempt to produce a measure of smartphone zombie behaviour, and provides us with a reliable and valid measure with which we can study this growing phenomenon.

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“…Several technologies have been developed to reduce distraction from smartphone use, such as RFID technology [57] or the creation of specific applications for smartphones and tablets [58].…”

Section: Distractorsmentioning

confidence: 99%

Child-Pedestrian Traffic Safety at Crosswalks—Literature Review

et al. 2022

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Child pedestrians make up 30% of the total number of children injured in road traffic in the EU. They are a particularly vulnerable subgroup because they exhibit specific traffic behavior related to cognitive and physical development, sociodemographic characteristics, and environmental conditions. This paper provides an overview of research of parameters that affect the safety of children in the conflict zones of the intersection—crosswalks. The overview was undertaken targeting available research mostly conducted in the last 10 years all over the world, related to the identification of parameters that affect the safety of child-pedestrians, and models developed for the prediction of pedestrian and child-pedestrian behavior. Research conducted on various urban networks provides insight into locally and more widely applicable impact parameters connected to child characteristics and infrastructural and traffic elements, but also distractors (e.g., electronic devices) as new phenomena influencing children’s road safety. A review of pedestrian behavior-prediction models suggests that models are being developed for the general population, and models for children’s behavior, with specific parameters, are missing. For further research, more detailed analysis of the impact of distractors and of COVID–19 pandemic non-mobility, as well as an analysis of possible infrastructural solutions to increase children’s road traffic safety, is suggested.

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Smombie Forecaster: Alerting Smartphone Users About Potential Hazards in Their Surroundings

Cited by 8 publications

References 11 publications

Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model

Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model

The problematic use of smartphones in public: the development and validation of a measure of smartphone “zombie” behaviour

Child-Pedestrian Traffic Safety at Crosswalks—Literature Review

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