Performance of ground-level signal detection when using a phone while walking

Risk of using smartphones while walking for digital natives in realistic environments: Effects of cognitive-motor interference

The effect of using smartphones while walking on the cognitive and physical abilities of the "digital native" generation, i.e., individuals who have grown up in a digital media-centric environment, remains poorly understood. This study evaluated the effects of cognitive-motor interference on the use of smartphones while walking in children and young adults. The study involved 50 individuals from the digital age generation, including 24 children and 26 young adults. The study encompassed three experimental conditions, in which participants were instructed to traverse a distance of 60 m. The initial condition functioned as a control, wherein the participants walked without supplementary stimuli. In the second condition, the participants were provided with explicit instructions to grasp the smartphone device and position it in front of their chest by using both hands. This manipulation introduced a postural component into the experimental setup. The third condition required participants to be ambulatory while concurrently engaging in a cognitive task, namely, participating in a game that necessitated focused attention. Gait parameters were obtained by using inertial measurement unit sensors. Subsequently, the acquired gait characteristics were converted into dual-task costs (DTC). In the cognitive condition, children exhibited significantly greater DTC values for gait speed (76%), stride length (79%), stride time (102%), and stride length coefficient of variation (CV) than the young adults (p < 0.025). Moreover, as shown by the increased CV, a significant association exists between poor performance in smartphone games among children and increased variability in stride length. In children, the DTC of stride time CV decreased as smartphone game scores increased (R2 = 16.5%), and the DTC of stride length CV decreased more markedly as smartphone game scores increased (R2 = 28.2%). In conclusion, children are at a higher risk of pedestrian accidents when using smartphones while walking compared to young adults.

What's that on Your Phone? Effects of Mobile Device Task Type on Pedestrian Performance

BACKGROUND

The number of accidents due to distracted pedestrian is on the rise and many governments and institutions are enacting public policies which restrict texting while walking. However, pedestrians do more than just texting when they use their mobile devices on the go.

OBJECTIVE

Exploring pedestrian multitasking, this paper aims to examine the effects of mobile device task type on pedestrian performance outcomes.

METHOD

We performed two studies in lab simulations where 78 participants were asked to perform different tasks on a mobile device (playing a game, reading, writing an email, texting one person, group texting) while performing a pedestrian visual discrimination task while either standing or walking on a treadmill. Behavioral performance as well as neurophysiological data are collected.

RESULTS

Results show that compared to a no-phone control, multitasking with any of the tasks on a mobile device leads to poor performance on a pedestrian visual discrimination task. Playing a game is the most cognitively demanding task and leads to the greatest performance degradation.

CONCLUSION

Our studies show that multitasking with a mobile device has the potential to negatively impact pedestrian safety, regardless of task type. However, the impacts of different mobile device tasks are not all equivalent. More research is needed to tease out the different effects of these various tasks and to design mobile applications which effectively and safely capture pedestrians' attention.

APPLICATION

Public policy, infrastructure, and smart technologies can be used to mitigate the negative effects of mobile multitasking. A more thorough understanding of mobile device task-specific factors at play can help tailor these counter-measures to better aid distracted pedestrians.

Validity of the Smombie Scale: Sensitivity and specificity in identifying pedestrian risk group

Objective

The objective of this study was to determine the most effective cut-off point for the Smombie Scale and evaluate its ability to screen for pedestrian safety risks among young adults.

Methods

Data were obtained from an online sample of 396 Korean young adults aged 18-39 years. Latent profile analysis was used to distinguish the risk group as a reference measure for the Smombie Scale. Discriminative power was assessed using sensitivity, specificity, receiver operating characteristic (ROC) curves, and the area under the ROC curve. The cut-off points were estimated from the Youden index and the balanced score.

Results

The latent profile analysis showed two different classes: "risk group" of 17.8% and "others." Based on the latent profile analysis, sensitivity, and specificity analysis showed that an adequate cut-off point of 2.78 of five points or higher was associated with a high risk of distracted walking.

Conclusion

The Smombie Scale is a good predictor of problematic smartphone use on the road and can be used as a screening tool for assessing risk levels among young adult pedestrians.

Investigating the role of beliefs in influencing the hand-held and hands-free mobile phone use among pedestrians in India

Mobile phone distraction is a significant contributor to pedestrian injuries. However, mobile phone engagement among pedestrians has been scarcely explored in a developing country like India. The present study utilized the beliefs-based theory of planned behaviour to examine the association between pedestrian beliefs towards distracted walking (behavioural, normative, and control) and their mobile phone use frequencies. Based on a survey of 560 pedestrians (64.6% males), it was found that the major use of mobile phones was for listening to music (30.7%), followed by receiving a call (25%), making a call (18.9%), texting (9.8%), navigation (8.5%) and internet browsing (7.1%). A series of multivariate ANOVAs and logistic regression models were developed to investigate the relationships between the beliefs and frequencies of mobile phone use in hands-free and hand-held conditions. Significant multivariate differences were found for behavioural and normative beliefs in hands-free conditions and all three types of beliefs in hand-held conditions. The frequency of mobile phone use was significantly predicted by normative beliefs (p < 0.001) in the hands-free condition, and by behavioural (p = 0.041) and normative beliefs (p = 0.004) in the hand-held condition. The findings may assist the road safety countermeasures in addressing the issue of pedestrian distraction.

Cost-benefit analysis of a distracted pedestrian intervention

OBJECTIVE

Cellphone ubiquity has increased distracted pedestrian behaviour and contributed to growing pedestrian injury rates. A major barrier to large-scale implementation of prevention programmes is unavailable information on potential monetary benefits. We evaluated net economic societal benefits of StreetBit, a programme that reduces distracted pedestrian behaviour by sending warnings from intersection-installed Bluetooth beacons to distracted pedestrians' smartphones.

METHODS

Three data sources were used as follows: (1) fatal, severe, non-severe pedestrian injury rates from Alabama's electronic crash reporting system; (2) expected costs per fatal, severe, non-severe pedestrian injury-including medical cost, value of statistical life, work-loss cost, quality-of-life cost-from CDC and (3) prevalence of distracted walking from extant literature. We computed and compared estimated monetary costs of distracted walking in Alabama and monetary benefits from implementing StreetBit to reduce pedestrian injuries at intersections.

RESULTS

Over 2019-2021, Alabama recorded an annual average of 31 fatal, 83 severe and 115 non-severe pedestrian injuries in intersections. Expected costs/injury were US$11 million, US$339 535 and US$93 877, respectively. The estimated distracted walking prevalence is 25%-40%, and StreetBit demonstrates 19.1% (95% CI 1.6% to 36.0%) reduction. These figures demonstrate potential annual cost savings from using interventions like StreetBit statewide ranging from US$18.1 to US$29 million. Potential costs range from US$3 208 600 (beacons at every-fourth urban intersection) to US$6 359 200 (every other intersection).

CONCLUSIONS

Even under the most parsimonious scenario (25% distracted pedestrians; densest beacon placement), StreetBit yields US$11.8 million estimated net annual benefit to society. Existing data sources can be leveraged to predict net monetary benefits of distracted pedestrian interventions like StreetBit and facilitate large-scale intervention adoption.

Effectiveness of interventions for mobile phone distracted pedestrians: A systematic review

INTRODUCTION

Mobile phones are used universally due to their versatility and easy-to-use features; this includes when users are walking and when crossing streets. At intersections, using a mobile phone is a secondary task that can distract from the primary task of scanning the road environment and ensuring it is safe to traverse. Such a distraction has been shown to increase risky pedestrian behavior compared to non-distracted behavior. Developing an intervention to make distracted pedestrians aware of imminent danger is a promising approach to refocus pedestrians on their primary task and avoid incidents. Interventions have already been developed in different parts of the world, such as in-ground flashing lights, painted crosswalks, and mobile phone app-based warning systems.

METHOD

A systematic review of 42 articles was performed to determine the effectiveness of such interventions. This review found that three types of interventions are currently developed, with differing evaluations. Interventions based on infrastructure tend to be evaluated based on behavioral change. Mobile phone-based apps tend to be evaluated on their ability to detect obstacles. Legislative changes and education campaigns are not currently evaluated. Further, technological development often occurs independently of pedestrians' needs, reducing the likely safety benefits of such interventions. The interventions related to infrastructure mainly focus on warning pedestrians without considering pedestrian mobile phone use, potentially leading to numerous irrelevant warnings and reduced user acceptance. The lack of a comprehensive and systematic approach to evaluating these interventions is also an issue requiring consideration.

PRACTICAL APPLICATIONS

This review demonstrates that despite significant recent progress surrounding pedestrian distraction, more work is required to identify the most effective interventions to implement. Future studies with a well-designed experimental framework are necessary to compare the different approaches, and warning messages, and ensure the best guidance for road safety agencies.

The range of visual detection of ground-level cues during distracted walking: Effect of cue contrast and walking speed

Walking while distracted by a smartphone has been a major safety concern for pedestrians. Visual and cognitive attention paid to the smartphone while walking with the head tilted downward would affect the ability to perceive walkway hazards and elevate risks for pedestrian accidents associated with physical contact with obstacles. A laboratory experiment was conducted to evaluate the performance of detecting ground-level visual cues during texting while walking. Forty young smartphone users performed walking trials at faster, preferred, and slower speeds for the dual-task walking on a treadmill and detected approaching cues of three contrast levels. Detection distance was quantified from the location of cue detection to the participants to assess the effects of walking speed and cue contrast on detection performance. Results show that detection distance varied from 1.7 m to 2.9 m for Low to High contrast cues and from 2.3 m to 2.5 m for Slower to Faster walking speeds, and the effects of contrast and speed were statistically significant (p < 0.05). Study findings suggest that higher contrast fixtures or in-ground signals and slower walking would help smartphone users perceive walkway hazards and in-ground safety signals earlier during their distracted walking.

Standing and Walking Attention Visual Field (SWAVF) task: A new method to assess visuospatial attention during walking

Visuospatial attention during walking has been associated with pedestrian safety and fall risks. However, visuospatial attention measures during walking remained under-explored. Current studies introduced a newly-developed Standing and Walking Visual Attention Field (SWAVF) task to assess visuospatial attention during walking and examined its reliability, validity, and stability. Thirty young adults completed a traditional computerized Attention Visual Field (AVF) task while sitting, and the SWAVF task under walking and standing settings. Nine participants also performed the SWAVF task under additional distraction conditions. Results showed good split-half reliability during standing (r = 0.70) and walking (r = 0.69), moderate concurrent validity with the sitting AVF task (r = 0.42), moderate convergent validity between the standing and walking settings (r = 0.69), good construct validity, and moderate rank-order stability (r = 0.53). Overall, the SWAVF task showed good psychometric properties. Potential applications to the evaluation of prosthetic and other exoskeleton devices, smart glasses, and ground-level traffic lights or signs were discussed.

Reducing distracted pedestrian behavior using Bluetooth beacon technology: A crossover trial

BACKGROUND

The number of fatal pedestrian injuries in the United States has steadily increased over the past decade. Multiple factors likely contribute to this trend, but the growth of pedestrians distracted by mobile devices is widely hypothesized to play a major role. Existing strategies to reduce distracted pedestrian behavior are few and mostly ineffective. The present study evaluated StreetBit, a mostly-passive primary prevention program to reduce distracted pedestrian behavior by alerting distracted pedestrians directly on their smartphone when they approach an intersection, reminding them to attend to traffic as they crossed.

METHODS

385 individuals who regularly crossed a target street corner at an urban university downloaded StreetBit on their phones and participated in a crossover design study whereby the app was inactive for 3 weeks (baseline behavior phase), actively provided alerts for 3 weeks (intervention phase), and then was inactive again for 4 weeks (post-intervention phase). User distraction while crossing the intersection was collected electronically for a total of 34,923 street-crossing events throughout the 10-week study.

RESULTS

In crude (unadjusted) models, participant distraction was similar across all phases of the research; this result was maintained after adjusting for potential covariates as well as after conducting a sensitivity analysis limited to data from only week 3 of each study intervention phase. In a model stratified by phone/warning type and baseline distraction rates, Android phone users who received a warning that blocked the full screen and had a high baseline distraction rate (≥75% distracted crossings) had a 64% decreased odds of distraction during the alert phase (OR 0.36, 95% CI 0.25-0.51) and a 52% decreased odds of distraction during the post-intervention phase (OR 0.48, 95% CI 0.25-0.94). Users reported positive impressions about the StreetBit app in a post-intervention survey.

DISCUSSION

StreetBit, an innovative app designed to prevent distracted pedestrian behavior through a mostly-passive primary prevention strategy relying on intrusive reminders, proved effective among smartphone users who received a warning blocking the full screen and who were frequently distracted at baseline, but not among other users. The results appear to reflect the confluence of two influencing factors. First, due to software development limitations, visually-distracted Android users received a highly intrusive app warning that blocked their smartphone screen whereas iOS users received a less intrusive banner notification blocking a small upper portion of the screen. Second, most users were curious to see if the app was functioning properly, creating artificially-inflated estimates of distraction as users purposefully watched their phones when crossing. Thus, our results indicate promise for StreetBit as an effective intervention and warrant continued software development and empirical testing.