Why Are Older Adults More at Risk as Pedestrians? A Systematic Review

Coupling intention and actions of vehicle-pedestrian interaction: A virtual reality experiment study

The interactions between vehicles and pedestrians are complex due to their interdependence and coupling. Understanding these interactions is crucial for the development of autonomous vehicles, as it enables accurate prediction of pedestrian crossing intentions, more reasonable decision-making, and human-like motion planning at unsignalized intersections. Previous studies have devoted considerable effort to analyzing vehicle and pedestrian behavior and developing models to forecast pedestrian crossing intentions. However, these studies have two limitations. First, they mainly focus on investigating variables that explain pedestrian crossing behavior rather than predicting pedestrian crossing intentions. Moreover, some factors such as age, sensation seeking and social value orientation, used to establish decision-making models in these studies are not easily accessible in real-world scenarios. In this paper, we explored the critical factors influencing the decision-making processes of human drivers and pedestrians respectively by using virtual reality technology. To do this, we considered available kinematic variables and analyzed the internal relationship between motion parameters and pedestrian behavior. The analysis results indicate that longitudinal distance and vehicle acceleration are the most influential factors in pedestrian decision-making, while pedestrian speed and longitudinal distance also play a crucial role in determining whether the vehicle yields or not. Furthermore, a mathematical relationship between a pedestrian's intention and kinematic variables is established for the first time, which can help dynamically assess when pedestrians desire to cross. Finally, the results obtained in driver-yielding behavior analysis provide valuable insights for autonomous vehicle decision-making and motion planning.

Distraction and related risk factors among professional and non-professional drivers

Background

Distraction is one of the main driver's behavioral factors that reduces the performance of the drivers and might increase the accident risk. Distraction while driving holds significant importance, especially among professional drivers, and failure to address this matter may result in adverse implications for traffic safety. The present study was conducted to investigate distraction and related risk factors between two groups of private vehicle drivers and taxi drivers.

Methods

This analytical cross-sectional study was carried out in Tabriz, Iran in 2022. The total sample size in this study was 701 taxi drivers, professional drivers, and private vehicle drivers. The independent samples t-test was used to determine the statistically significant difference between groups and its sub-scales between the two studied groups. Moreover, the multivariable linear regression analysis was used to determine the predictors that affect distraction score. The test's level of significance was considered at 0.05.

Results

The mean distraction score among taxi drivers surpasses that of private vehicle drivers (2.82 vs. 2.32, p-value<0.05). The drivers with negative scores, over the past year, among private vehicle drivers and taxi drivers were 2.5 % and 5.2 %, respectively (p-value<0.05). A group of taxi drivers exhibits a higher level of distraction while driving and the mean distraction score for private vehicle drivers is lower than that of taxi drivers (β = -0.11, CI 95 %: 0.17, -0.05). Also, a history of damage or injury accidents has a significant impact on distraction while driving (β = 0.12, CI 95 %; 0.06-0.17).

Conclusions

The results indicate that distraction while driving is high amongst taxi drivers rather than private vehicle drivers. To have effective driver safety promotion interventions, it is recommended to consider driver distraction based on professional and non-professional drivers.

Application of immersive virtual reality for assessing chronic neglect in individuals with stroke: the immersive virtual road-crossing task

BACKGROUND

Neglect can be a long-term consequence of chronic stroke that can impede an individual's ability to perform daily activities, but chronic and discrete forms can be difficult to detect. We developed and evaluated the "immersive virtual road-crossing task" (iVRoad) to identify and quantify discrete neglect symptoms in chronic stroke patients.

METHOD

The iVRoad task requires crossing virtual intersections and placing a letter in a mailbox placed either on the left or right. We tested three groups using the HTC Vive Pro Eye: (1) chronic right hemisphere stroke patients with (N = 20) and (2) without (N = 20) chronic left-sided neglect, and (3) age and gender-matched healthy controls (N = 20). We analyzed temporal parameters, errors, and head rotation to identify group-specific patterns, and applied questionnaires to measure self-assessed pedestrian behavior and usability.

RESULTS

Overall, the task was well-tolerated by all participants with fewer cybersickness-induced symptoms after the VR exposure than before. Reaction time, left-sided errors, and lateral head movements for traffic from left most clearly distinguished between groups. Neglect patients committed more dangerous crossings, but their self-rated pedestrian behavior did not differ from that of stroke patients without neglect. This demonstrates their reduced awareness of the risks in everyday life and highlights the clinical relevance of the task.

CONCLUSIONS

Our findings suggest that a virtual road crossing task, such as iVRoad, has the potential to identify subtle symptoms of neglect by providing virtual scenarios that more closely resemble the demands and challenges of everyday life. iVRoad is an immersive, naturalistic virtual reality task that can measure clinically relevant behavioral variance and identify discrete neglect symptoms.

Age-Related Changes in the Utilization of Visual Information for Collision Prediction: A Study Using an Affordance-Based Model

The ability to predict collisions with moving objects deteriorates with aging. We followed the affordance-based model to identify optical variables that older adults had difficulty using for collision prediction. We reproduced a modified version of the interception task used in Steinmetz (Steinmetz, Layton, Powell, & Fajen, 2020, "Affordance-based versus current - future accounts of choosing whether to pursue or abandon the chase of a moving target," Journal of Vision, 20(3), 8) in a virtual reality (VR) environment and newly introduced perturbation for each of three optical variables (vertical and horizontal expansions of a moving object and the bearing angle produced between participants and a moving object). We expected that perturbation would negatively affect the performance only for those who rely on the optical variable to perform the interception task effectively. We tested 18 older and 15 younger adults and showed that older participants were not negatively affected by the perturbation for the vertical and horizontal expansion of a moving object, while they showed decreased performance when the perturbation was introduced with a bearing angle. These findings suggest that predicting collisions with moving objects deteriorates with aging because the perception of object expansion is impaired with aging.

A methodology for the public health surveillance and epidemiologic analysis of outdoor falls that require an emergency medical services response

BACKGROUND

Falls are a common cause of injury with significantly associated medical costs yet public health surveillance of injuries from falls is underdeveloped. In addition, the epidemiologic understanding of outdoor falls, which have been reported to account for 47% of all injurious falls, is scant. Here we present methods to use emergency medical services (EMS) data as a public health surveillance tool for fall injuries, including those that occur secondary to syncope and heat illness, with a focus on the scope and epidemiology of outdoor fall injuries.

METHODS

Using the 2019 National Emergency Medical Services Information System (NEMSIS) data, we developed an approach to identify EMS encounters for fall injuries, syncope and heat illness. NEMSIS variables used in our algorithm included the EMS respondent's impression of the encounter, the reported major symptoms and the cause of injury. With these data we identified injuries from falls and, using the NEMSIS data on the location of the encounter, we identified fall injuries as occurring indoors or outdoors. We present the descriptive epidemiology of the identified patients.

RESULTS

There were 1,854,909 injuries from falls that required an EMS response identified in the NEMSIS data, with 4% of those injuries secondary to episodes of syncope (n = 73,126) and heat illness. Sufficient data were available from 94% of injurious falls that they could be assigned to indoor or outdoor locations, with 9% of these fall injuries occurring outdoors. Among fall injuries identified as occurring outdoors, 85% occurred on streets and sidewalks. Patient age was the primary sociodemographic characteristic that varied by location of the injurious fall. Sixty-six percent of fall injuries that occurred indoors were among those age 65 years or older, while this figure was 34% for fall injuries occurring outdoors on a street or sidewalk.

CONCLUSION

The occurrence of outdoor fall injuries identified in the NEMSIS data were substantially lower than reported in other data sets. However, numerically fall injuries occurring outdoors represent a substantial public health burden. The strengths and weaknesses of using this approach for routine public health surveillance of injuries from falls, syncope and heat illness are discussed.

Epidemiology and patterns of nasal bone fracture in elderly patients in comparison to other age groups: an 8-year single-center retrospective analysis

Background: Nasal bone fractures are the most common type of facial bone fracture, but are under-studied in adults above 65 years of age. Therefore, we investigated the epidemiology and patterns of nasal bone fractures among older adults in comparison to different age groups.Methods: This retrospective study included 2,321 nasal bone fracture patients who underwent surgery at our hospital from January 2010 to December 2017. The patients were classified by age as preschoolers, school-age children, young and middle-aged adults, and the elderly. We performed pairwise comparisons between elderly patients and each other age group in terms of sex, cause of injury, and fracture type.Results: The 2,321 nasal bone fracture patients included 76 elderly patients (50 men [65.8%] and 26 women [34.2%]). In these patients, the two most common injury causes were falling or slipping down (n = 39; 51.3%) and road traffic accidents (n = 19; 25.0%). According to the Stranc and Robertson classification, the most common force vector was lateral, and plane 2 fractures with lateral forces predominated.Conclusion: The elderly showed similar patterns of nasal bone fractures to those observed in young and middle-aged adults, but significant differences from preschoolers (in the injury vector and plane of fracture) and from school-age children (in the sex ratio and plane of fracture). However, elderly patients presented significantly different epidemiological characteristics compared to the other three groups. Therefore, it is necessary to improve the quality of life of the elderly and prepare for the upcoming super-aged society by taking steps to reduce the incidence and severity of fractures. Possible options for doing so include strengthening individual-level safety factors and expanding the social safety net for the elderly.

The Impact of Visual and Cognitive Dual-Task Demands on Traffic Perception During Road Crossing of Older and Younger Pedestrians

With the help of the current experiment, we wanted to learn more about the impact of visually demanding vs. cognitively demanding secondary tasks on the attention allocation of older pedestrians during the phase of traffic perception within the process of road crossing. For this purpose, we used two different road crossing tasks as well as two different secondary tasks. The road crossing “stop task” was a signal detection task, where an approaching car had to be detected. The road crossing “go task” was a dynamic visual search task, where the resolution of a busy road situation had to be identified. The visual secondary task was a static visual search task and the cognitive secondary task was a 1-back (memory) task. One younger group (≤ 30 years) and one older group (≥ 65 years) of participants completed the tasks as single vs. dual-tasks in all possible combinations. Performance was measured through errors and response time; in addition, the subjective workload was assessed via NASA-TLX. Analyses show that the visual secondary task reduces performance in the road crossing more strongly than the cognitive task, while the visual task itself is less impaired by the road crossing tasks than is the cognitive task. Overall, performance diminishes from single to dual-task completion. Results further indicate age effects in terms of increased errors and response time for older compared to younger participants. In addition to these age effects, age-specific dual-task effects emerge for response time in the go task along with the visual task as well as for response time in the cognitive task along with the go task. Subjective workload is higher in the dual-task conditions than in the single tasks. Findings are discussed with regard to theoretical and practical implications.