Predicting Autonomous Shuttle Acceptance in Older Drivers Based on Technology Readiness/Use/Barriers, Life Space, Driving Habits, and Cognition.

Shared autonomous vehicle services (i. e., automated shuttles, AS) are being deployed globally and may improve older adults (>65 years old) mobility, independence, and participation in the community. However, AS must be user friendly and provide safety benefits if older drivers are to accept and adopt this technology. Current potential barriers to their acceptance of AS include a lack of trust in the systems and hesitation to adopt emerging technology. Technology readiness, perceived ease of use, perceived barriers, and intention to use the technology, are particularly important constructs to consider in older adults' acceptance and adoption practices of AS. Likewise, person factors, i.e., age, life space mobility, driving habits, and cognition predict driving safety among older drivers. However, we are not sure if and how these factors may also predict older adults' intention to use the AS. In the current study, we examined responses from 104 older drivers (M age = 74.3, SD age = 5.9) who completed the Automated Vehicle User Perception Survey (AVUPS) before and after riding in an on-road automated shuttle (EasyMile EZ10). The study participants also provided information through the Technology Readiness Index, Technology Acceptance Measure, Life Space Questionnaire, Driving Habits Questionnaire, Trail-making Test Part A and Part B (TMT A and TMT B). Older drivers' age, cognitive scores (i.e., TMT B), driving habits (i.e., crashes and/or citations, exposure, and difficulty of driving) and life space (i.e., how far older adults venture from their primary dwelling) were entered into four models to predict their acceptance of AVs-operationalized according to the subscales (i.e., intention to use, perceived barriers, and well-being) and the total acceptance score of the AVUPS. Next, a partial least squares structural equation model (PLS-SEM) elucidated the relationships between, technology readiness, perceived ease of use, barriers to AV acceptance, life space, crashes and/or citations, driving exposure, driving difficulty, cognition, and intention to use AS. The regression models indicated that neither age nor cognition (TMT B) significantly predicted older drivers' perceptions of AVs; but their self-reported driving difficulty (p = 0.019) predicted their intention to use AVs: R 2 = 6.18%, F (2,101) = 4.554, p = 0.040. Therefore, intention to use was the dependent variable in the subsequent PLS-SEM. Findings from the PLS-SEM (R 2 = 0.467) indicated the only statistically significant predictors of intention to use were technology readiness (ß = 0.247, CI = 0.087-0.411) and barriers to AV acceptance (ß = -0.504, CI = 0.285-0.692). These novel findings provide evidence suggesting that technology readiness and barriers must be better understood if older drivers are to accept and adopt AS.

Construct Validity and Test-Retest Reliability of the Automated Vehicle User Perception Survey.

Fully automated vehicles (AVs) hold promise toward providing numerous societal benefits including reducing road fatalities. However, we are uncertain about how individuals' perceptions will influence their ability to accept and adopt AVs. The 28-item Automated Vehicle User Perception Survey (AVUPS) is a visual analog scale that was previously constructed, with established face and content validity, to assess individuals' perceptions of AVs. In this study, we examined construct validity, via exploratory factor analysis and subsequent Mokken scale analyses. Next, internal consistency was assessed via Cronbach's alpha (α) and 2-week test-retest reliability was assessed via Spearman's rho (ρ) and intraclass correlation coefficient (ICC). The Mokken scale analyses resulted in a refined 20-item AVUPS and three Mokken subscales assessing specific domains of adults' perceptions of AVs: (a) Intention to use; (b) perceived barriers; and (c) well-being. The Mokken scale analysis showed that all item-coefficients of homogeneity (H) exceeded 0.3, indicating that the items reflect a single latent variable. The AVUPS indicated a strong Mokken scale (H scale = 0.51) with excellent internal consistency (α = 0.95) and test-retest reliability (ρ = 0.76, ICC = 0.95). Similarly, the three Mokken subscales ranged from moderate to strong (range H scale = 0.47-0.66) and had excellent internal consistency (range α = 0.84-0.94) and test-retest reliability (range ICC = 0.84-0.93). The AVUPS and three Mokken subscales of AV acceptance were validated in a moderate sample size (N = 312) of adults living in the United States. Two-week test-retest reliability was established using a subset of Amazon Mechanical Turk participants (N = 84). The AVUPS, or any combination of the three subscales, can be used to validly and reliably assess adults' perceptions before and after being exposed to AVs. The AVUPS can be used to quantify adults' acceptance of fully AVs.

Visual Behavior Differences in Drivers Across the Lifespan: A Digital Billboard Simulator Study.

Driver distraction is implicated in a significant portion of motor vehicle collisions; evidence has suggested that billboards can contribute to such distraction, but many knowledge gaps remain. The purpose of this study was to evaluate the effects of various types of billboards (static, 250-foot digital transition, 500-foot digital transition, and a control [no billboard] condition) and age group (teen, middle, and older) on visual behavior through the use of a driving simulator. To address gaps in the existing literature, the effects of age group and billboard type on the following visual attention variables were considered: percent of time participants looked at billboards, average glance length, number of glances, and glance pattern activity. Significant main effects of age group were found, suggesting that teen drivers exhibited significantly different visual behavior as compared to drivers in the other age groups. An Age Group x Billboard Type interaction for one outcome provided some evidence that percent of time spent looking at billboards significantly increased as billboard transition time increased for drivers, except for older adults, who spent more time looking at static billboards. This study helps lay the groundwork for future studies that may consider how young drivers' differential scanning patterns impact driving safety.

Community-based pedestrian safety training in virtual reality: A pragmatic trial.

Child pedestrian injuries are a leading cause of mortality and morbidity across the United States and the world. Repeated practice at the cognitive-perceptual task of crossing a street may lead to safer pedestrian behavior. Virtual reality offers a unique opportunity for repeated practice without the risk of actual injury. This study conducted a pre-post within-subjects trial of training children in pedestrian safety using a semi-mobile, semi-immersive virtual pedestrian environment placed at schools and community centers. Pedestrian safety skills among a group of 44 seven- and eight-year-old children were assessed in a laboratory, and then children completed six 15-minute training sessions in the virtual pedestrian environment at their school or community center following pragmatic trial strategies over the course of three weeks. Following training, pedestrian safety skills were re-assessed. Results indicate improvement in delay entering traffic following training. Safe crossings did not demonstrate change. Attention to traffic and time to contact with oncoming vehicles both decreased somewhat, perhaps an indication that training was incomplete and children were in the process of actively learning to be safer pedestrians. The findings suggest virtual reality environments placed in community centers hold promise for teaching children to be safer pedestrians, but future research is needed to determine the optimal training dosage.

The impact of billboards on driver visual behavior: a systematic literature review.

OBJECTIVE: External distraction appears to affect at least 6-9% of distraction-affected motor vehicle collisions. Billboards may be good models for studying external distraction in general, and it is also desirable to understand billboard-related distraction per se. However, there has not yet been a clear consensus on the scope of billboard-related distraction or its dynamics with respect to characteristics of drivers, billboards, traffic, and the roadway. To narrow these knowledge gaps, a systematic literature review was conducted on billboard-related changes in driver visual behavior. METHODS: A systematic literature search yielded 443 results, of which 8 studies met all inclusion criteria. Five studies meeting all inclusion criteria were later identified and added. RESULTS were analyzed in terms of 4 categories of visual behavior: (1) gaze variability (GV), glance pattern activity (GPA), and percentage of time spent glancing at the forward roadway; (2) glances at unexpected drive-relevant stimuli; (3) glances at expected drive-relevant stimuli; and (4) glances at billboards. RESULTS: There was considerable evidence that about 10-20% of all glances at billboards were ≥0.75 s, that active billboards drew more glances and more long glances (≥0.75 s, ≥2.0 s) than passive billboards but did not attract a longer average glance, and that there was large variability among individual billboards within categories (e.g., active vs. passive). The extent to which billboards attracted glances ≥ 2.0 s was uncertain. There was tentative evidence that billboards did not affect GPA, glances at expected drive-relevant stimuli, or the proportion of time drivers spent glancing at the forward roadway and that they did affect vertical GV and glances at unexpected drive-relevant stimuli. CONCLUSIONS: Generally, billboard-related distraction appeared to be minor and regulated by drivers as the demands of the driving task changed. However, this review's findings suggest that this may not be true in all cases. Future research should emphasize the tails of the distribution in addition to average cases, in terms of both the analysis of visual behavior and the complexity of driving tasks. Further research is also needed to understand the effects of billboard design, driver characteristics, and road and traffic context.

Impact of distracted driving on safety and traffic flow.

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16-25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted.

Incident and emergency medical services management from a regional perspective.

Traffic crashes and other emergencies have impacts on traffic operations in transportation networks, often resulting in non-recurring congestion. Congestion, in turn, may impede the ability of Emergency Medical Services (EMS) to provide timely response to those in need of medical attention. The work in this paper investigated the impact of incidents of varying severity and duration on transportation network performance in the Birmingham (AL, USA) area. The intensity and extent of the impact over space and time were assessed on the basis of average speeds. The analysis of incident scenarios was performed using the Visual Interactive System for Transport Algorithms (VISTA) platform. Moreover, first responders' travel times to the scene of the incident were collected to identify best units for responding, in an effort to improve current dispatching practices. Finally, a secondary incident on the EMS to the hospital was considered to further demonstrate the superiority of Dynamic Traffic Assignment (DTA) over traditional static assignment methods in capturing dynamically changing traffic conditions. The study findings are expected to benefit local transportation planners, traffic engineers, emergency responders, and policy makers by allowing them to assess various response strategies to major incidents and emergencies and select the ones that minimize their potential impacts.