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.

Someone to Watch Over You: Using Bluetooth Beacons for Alerting Distracted Pedestrians.

In the United States, an estimated 7,005 (crude rate 2.13) pedestrians were killed in traffic crashes in 2020, according to the Centers for Disease Control and Prevention (CDC). This statistic is currently increasing annually and research suggests that distraction by smartphones may be a primary reason for the increasing number of pedestrian injuries and deaths. Timely interruptions may alert inattentive pedestrians and prevent fatalities. To this end, we developed StreetBit, a Bluetooth beacon-based system that warns distracted pedestrians with a visual and/or audible interruption when they approach a potentially dangerous traffic intersection while distracted by their smartphones. We posit that by using StreetBit, we can educate distracted pedestrians and elicit behavioral change to reduce or remove smartphone-based distractions when they enter and cross roadways. To demonstrate the feasibility of StreetBit, we conducted a field study with 385 participants. Results show that the system demonstrates adequate feasibility and behavior change in response to the StreetBit program.

Distracted pedestrian behavior: An observational study of risk by situational environments.

OBJECTIVE: Pedestrian-related death rates are increasing in the United States, partly due to increased use of distracting smartphones by pedestrians. Previous research documents high frequency of smartphone use while crossing streets near college campuses and in downtown business districts, but little is known about distracted pedestrian behavior in other urban environments. The current study used observational methods to examine and compare distracted pedestrian behavior in four urban areas - near an urban college campus, in a downtown commercial business district, near middle and high schools, and in entertainment districts - as well as examining whether the occurrence of distraction was associated with unsafe crossing behaviors. METHODS: We observed 112 intersections in 46 downtown, 30 school, 25 entertainment district, and 11 college campus-area intersections. Coders recorded distraction, crossing safety, pedestrian demographics, and traffic volume. Chi-square tests compared pedestrian characteristics by intersection type. Log binomial regressions estimated risk ratios (RRs) and associated 95% confidence intervals (CIs) for associations between pedestrians walking alone and traffic volume with distracted crossing behavior, adjusting for age and gender. Similar models examined risk of unsafe crossing behavior by distraction behavior. All models were stratified by intersection type. RESULTS: Distraction incidence was highest in campus locations (52.9%) and lowest in entertainment districts (16.2%). Walking alone was associated with a 45% higher risk of distraction (RR 1.45, 95% CI 1.30-1.62), although the increased association was limited to entertainment locations (RR 1.61, 95% CI 1.25-2.08) and was significantly decreased in all other locations. Higher traffic volume was associated with lower risk of distraction in downtown locations (RR 0.69, 95% CI 0.56-0.85) but higher distraction risk in entertainment locations (RR 1.71, 95% CI 1.27-2.31). Associations between distraction and unsafe crossing behaviors were minimal. CONCLUSION: Distracted pedestrian behavior occurs at different rates and in different circumstances, depending on the setting. These results offer valuable data to inform intervention programs that target appropriate populations in appropriate locations.

StreetBit: A Bluetooth Beacon-based Personal Safety Application for Distracted Pedestrians.

The safety of distracted pedestrians presents a significant public health challenge in the United States and worldwide. An estimated 6,704 American pedestrians died and over 200,000 pedestrians were injured in traffic crashes in 2018, according to the Centers for Disease Control and Prevention (CDC) [1]. This number is increasing annually and many researchers posit that distraction by smartphones is a primary reason for the increasing number of pedestrian injuries and deaths. One strategy to prevent pedestrian injuries and death is to use intrusive interruptions that warn distracted pedestrians directly on their smartphones. To this end, we developed StreetBit, a Bluetooth beacon-based mobile application that alerts distracted pedestrians with a visual and/or audio interruption when they are distracted by their smartphones and are approaching a potentially-dangerous traffic intersection. In this paper, we present the background, architecture, and operations of the StreetBit Application.

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.

Using Bluetooth beacon technology to reduce distracted pedestrian behaviour: a cross-over trial study protocol.

OBJECTIVE: Over 6400 American pedestrians die annually, a figure that is currently increasing. One hypothesised reason for the increasing trend is the role of mobile technology in distracting both pedestrians and drivers. Scientists and policy-makers have attended somewhat to distracted driving, but attention to distracted pedestrian behaviour has lagged. We will evaluate Bluetooth beacon technology as a means to alert and warn pedestrians when they approach intersections, reminding them to attend to the traffic environment and cross streets safely. METHODS: Bluetooth beacons are small devices that broadcast information unidirectionally within a closed proximal network. We will place beacons at an intersection frequently trafficked by urban college students. From there, the beacons will transmit to an app installed on users' smartphones, signalling users to attend to their environment and cross the street safely. A cross-over trial will evaluate the app with 411 adults who frequently cross the target intersection on an urban university campus. We will monitor those participants' behaviour over three distinct time periods: (1) 3 weeks without the app being activated, (2) 3 weeks with the app activated and (3) 4 weeks without the app activated to assess retention of behaviour. Throughout the 10-week period, we will gather information to evaluate whether the intervention changes distracted pedestrian behaviour using a logistic regression to estimate the likelihood of key behavioural outcome measures and adjusting for any residual confounding. We also will test for changes in perceived risk. The trial will follow CONSORT (Consolidated Standards of Reporting Trials) statement guidelines, as modified for cross-over design studies. CONCLUSION: If this program proves successful, it offers exciting implications for future testing and ultimately for broad distribution to reduce distracted pedestrian behavior. We discuss issues of feasibility, acceptability and scalability.