Teaching children pedestrian safety in virtual reality via smartphone: a noninferiority randomized clinical trial.

OBJECTIVE: To evaluate whether child pedestrian safety training in a smartphone-based virtual reality (VR) environment is not inferior to training in a large, semi-immersive VR environment with demonstrated effectiveness. METHODS: Five hundred 7- and 8-year-old children participated; 479 were randomized to one of two conditions: Learning to cross streets in a smartphone-based VR or learning in a semi-immersive kiosk VR. The systems used identical virtual environments and scenarios. At baseline, children's pedestrian skills were assessed in both VR systems and through a vehicle approach estimation task (judging speed/distance of oncoming traffic on monitor). Training in both conditions comprised at least six 30-min sessions in the randomly assigned VR platform and continued for up to 25 visits until adult-level proficiency was obtained. Following training and again 6 months later, children completed pedestrian safety assessments identical to baseline. Three outcomes were considered from assessments in each VR platform: Unsafe crossings (collisions plus close calls), time to contact (shortest time between child and oncoming simulated traffic), and missed opportunities (unselected safe opportunities to cross). RESULTS: Participants achieved adult-level street-crossing skill through VR training. Training in a smartphone-based VR system was generally not inferior to training in a large semi-immersive VR system. There were no adverse effects. CONCLUSIONS: Seven- and 8-year-old children can learn pedestrian safety through VR-based training, including training in a smartphone-based VR system. Combined with recent meta-analytic results, the present findings support broad implementation and dissemination of child pedestrian safety training through VR, including smartphone-based VR systems.

A National Study on the Comparative Burden of Pedestrian Injuries from Falls Relative to Pedestrian Injuries from Motor Vehicle Collisions.

Pedestrian injuries from falls are an understudied cause of morbidity. Here, we compare the burden of pedestrian injuries from falls occurring on streets and sidewalks with that from motor vehicle collisions. Data on injurious falls on streets and sidewalks, and pedestrian-motor vehicle collisions, to which Emergency Medical Services responded, along with pedestrian and incident characteristics, were identified in the 2019 National Emergency Medical Services Information System database. In total, 118,520 injurious pedestrian falls and 33,915 pedestrians-motor vehicle collisions were identified, with 89% of the incidents occurring in urban areas. Thirty-two percent of pedestrians struck by motor vehicles were coded as Emergent or Critical by Emergency Medical Services, while 19% of pedestrians injured by falls were similarly coded. However, the number of pedestrians whose acuity was coded as Emergent or Critical was 2.1 times as high for injurious falls as compared with pedestrians-motor vehicle collisions. This ratio was 3.9 for individuals 50 years and older and 6.1 for those 65 years and older. In conclusion, there has been substantial and appropriate policy attention given to preventing pedestrian injuries from motor vehicles, but disproportionately little to pedestrian falls. However, the population burden of injurious pedestrian falls is significantly greater and justifies an increased focus on outdoor falls prevention, in addition to urban design, policy, and built environment interventions to reduce injurious falls on streets and sidewalks, than currently exists across the USA.

Developing machine-learning-based models to diminish the severity of injuries sustained by pedestrians in road traffic incidents.

An essential step in devising measures to improve road safety is road accident prediction. In particular, it is important to identify the risk factors that increase the likelihood of severe injuries in the event of an accident. There are two distinct ways of analyzing data in order to produce predictions: machine learning and statistical methods. This study explores the severity of road traffic injuries sustained by pedestrians through the use of machine-learning methodology. In general, the goal of the statistician is to model and understand the connections between variables, whereas machine learning focuses on more intricate and expansive datasets, with the aim of creating algorithms that can recognize patterns and make predictions without being explicitly programmed. The ability to handle very large datasets constitutes a distinct advantage of machine learning over statistical techniques. In addition, machine-learning models can be adapted to a wide range of data sources and problem domains, and can be utilized for numerous tasks, from image identification to natural language processing. Machine-learning models may be taught to recognize patterns and make predictions automatically, minimizing the need for manual involvement and enabling rapid data processing of enormous quantities of data. The use of new data to retrain or fine-tune a machine-learning model allows the model to adapt to changing conditions and enhances its accuracy over time. Finally, while non-linear interactions between variables can be difficult to predict using conventional statistical techniques, they can be recognized by machine-learning models. The study begins by compiling an inventory of features linked to both the accident and the environment, focusing on those that exert the greatest influence on the severity of pedestrian injuries. The "optimal" algorithm is then chosen based on its superior levels of accuracy, precision, recall, and F1 score. The developed model should not be regarded as fixed; it should be updated and retrained on a regular basis using new traffic accident data that mirror the evolving interplay between the road environment, driver characteristics, and pedestrian conduct. Having been constructed using Israeli data, the current model is predictive of injury outcomes within Israel. For broader applicability, the model should undergo retraining and reassessment using traffic accident data from the pertinent country or region.

Pediatric emergency department visits for pedestrian injuries in relation to the enactment of Complete Streets policy.

Introduction: This study aimed to evaluate the rate of pediatric emergency department (ED) visits for pedestrian injuries in relation to the enactment of the Complete Streets policy. Methods: The National Complete Streets policies were codified by county and associated with each hospital's catchment area and date of enactment. Pedestrian injury-related ED visits were identified across 40 children's hospitals within the Pediatric Health Information System (PHIS) from 2004 to 2014. We calculated the proportion of the PHIS hospitals' catchment areas covered by any county policy. We used a generalized linear model to assess the impact of the proportion of the policy coverage on the rate of pedestrian injury-related ED visits. Results: The proportion of the population covered by Complete Streets policies increased by 23.9%, and pedestrian injury rates at PHIS hospitals decreased by 29.8% during the study period. After controlling for years, pediatric ED visits for pedestrian injuries did not change with increases in the PHIS catchment population with enacted Complete Streets policies. Conclusion: After accounting for time trends, Complete Streets policy enactment was not related to observed changes in ED visits for pedestrian injuries at PHIS hospitals.

Pediatric Pedestrian Injuries: Striking Too Close to Home.

BACKGROUND: Pediatric pedestrian injuries (PPI) are a major public health concern. This study utilized geospatial analysis to characterize the risk and injury severity of PPI. METHODS: A retrospective chart review of PPI patients (age < 18) from a level 1 trauma center was performed (2013-2020). A geographic information system geocoded injury location to home and other public landmarks. Incidents were aggregated to zip codes and the Local Indicators of Spatial Association statistic tested for spatial clustering of injury rates per 10,000 children. Predictors for increased injury severity were assessed by logistic regression. RESULTS: PPI encompassed 6% (n = 188) of pediatric traumas. Most patients were black (54%), male (58%), >13 years (56%), and with Medicaid insurance (68%). Nine zip codes comprised a statistically significant cluster of PPI. Nearly half (40%) occurred within a quarter mile of home; 7% occurred at home. Most (65%) PPI occurred within 1 mile of a school, and 45% occurred within a quarter mile of a park. Nearly all (99%) PPI occurred within a quarter mile of a major intersection and/or roadway. Using admission to ICU as a marker for injury severity, farther distance from home (OR 1.060, 95% CI 1.001-1.121, p = 0.045) and age <13 years (3.662, 95% CI 1.854-7.231, p < 0.001) were independent predictors of injury severity. CONCLUSIONS: There are significant sociodemographic disparities in PPI. Most injuries occur near patients' homes and other public landmarks. Multidisciplinary injury prevention collaboration can help inform policymakers, direct local safety programs, and provide a model for PPI prevention at the national level. LEVEL OF EVIDENCE: Level IV.

Modeling pedestrian injury severity in pedestrian-vehicle crashes considering different land use patterns: Mixed logit approach.

OBJECTIVE: The objective of this study is to identify and compare the contributing factors to pedestrian injury severity in pedestrian-vehicle crashes considering different land use patterns. METHODS: The pedestrian-vehicle crash data from 2007 to 2018 were collected from the North Carolina Department of Transportation (NCDOT). A total number of 15,807 observations with 72 categorical variables were included in the final dataset. Two mixed logit models were developed to analyze the crash dataset with segmentations of two dominant land use areas (i.e., residential and commercial). Fixed and random parameters were found in both models. Estimation results and marginal effects of significant explanatory variables were investigated. RESULTS: In general, the residential model has 24 fixed parameters and 3 random parameters. The commercial model has 31 fixed parameters and 3 random parameters. According to the estimated results, elder or drunk factors are found to have more impacts on severe injuries in residential areas. Large and mid-size vehicles increase the probability of severe injuries in commercial areas. The marginal effect values for severe injury at non-intersections have opposite signs in the two models. Besides, speed limits between 40 and 45 mph and factors related to poor visibility are more likely to result in severe pedestrian injuries. Coarse asphalt pavement can reduce the probability of severe pedestrian injuries. CONCLUSIONS: This study investigated the pedestrian injury severity in pedestrian-vehicle crashes considering two types of land use using a mixed logit approach. Based on the discussions of factors contributing to the pedestrian injury severity, policies and countermeasures to improve traffic safety are suggested. Above all, a mixed-use land development policy is recommended. Other suggestions are summarized below: (1) giving more considerations to older pedestrians when planning and designing residential areas; (2) strengthening laws and education against drunk driving and even drunk walking on/across the roadways; (3) increasing the frequency of the patrols and alcohol tests; (4) improving lighting conditions and road alignments; (5) establishing a limited-truck-passing-period policy especially in commercial areas; and (6) improving the pavement conditions wherever needed.

The incidence burden of unreported pedestrian crashes in Illinois.

OBJECTIVE: Communities with high rates of pedestrians struck by motor vehicles may miss out on mitigation resources and suffer worse medical outcomes if crashes there go unreported to police. This study investigates the places, people, and communities in Illinois where struck pedestrians are most likely to go unreported. A better understanding of the true burden and distribution of struck pedestrians will help guide policy and direct investments and interventions where they are most needed. METHODS: Hospital records of pedestrians treated for injuries sustained by a motor vehicle that were not able to be linked with a corresponding crash report across three consecutive years are investigated. Discordance rates of struck pedestrians are calculated and disaggregated by region. A presentation of summary statistics is accompanied by an ordinary least squares predictive model to estimate the relationship between discordant struck pedestrians and sociodemographic factors. RESULTS: The incidence of unreported struck pedestrians was not randomly distributed. Blacks struck by a motor vehicle were disproportionately likely to go unreported to police. Zip codes with the most unreported crashes per capita on average had double the poverty rate and 2.6 times the carless household rate as the rest of Illinois. Struck pedestrians diagnosed at the hospital with an intoxicating substance went unreported to police nearly 70% of the time. Generally, more severe head and thorax injuries were more likely to be reported. Struck pedestrians outside of Cook County averaged a 60% discordance rate, those within Cook County averaged a discordance rate of about 50%. Struck pedestrian cases reported to police averaged emergency department charges of about $2,500 more than unreported cases. CONCLUSIONS: Underlying and contributing factors influential of a struck pedestrian's decision of whether to report to police is complex and layered by social constructs mixed with difficult economic decisions, often further complicated by the fog of impairment. Recommendations are made for community outreach to stress the importance of reporting incidents to police, along with adjusting case count numbers in police records using hospital data and discordance rates.

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents.

In vehicle-pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle-pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions.

[Analysis of 5-year monitoring of road traffic injuries rates in Kazan]. / Analiz 5-letnego monitoringa statisticheskikh pokazatelei dorozhno-transportnogo travmatizma v Kazani.

The objective of the study is to establish a set of possible causes and patterns that influence the frequency and severity of road traffic accidents with fatalities. The results of the 5-year monitoring analysis of fatal road traffic injuries in Kazan are presented. We analyzed 662 cases. It was established that the main risk group for fatal road accidents includes subjects aged 20-39. The risk group for drivers is 30-39 years old, passengers 20-29 years old, and pedestrians 55-64 years old. Children account for 3% of all traffic fatalities; 80% of them are under 10 years old. Most children (70%) were in the vehicle at the time of the crash, and their parents may not have been using special equipment (car seats and seat belts). We identified the most traumatic months of the year, days of the week and times of the day for drivers, passengers and pedestrians. These patterns can be used for organizational measures to prevent road accidents.

Effect of urban street trees on pedestrian safety: A micro-level pedestrian casualty model using multivariate Bayesian spatial approach.

In the past decades, trees were considered roadside hazard. Street trees were removed to provide clear zone and improve roadside safety. Nowadays, street trees are considered to play an important role in urban design. Also, street tree is considered a traffic calming measure. Studies have examined the effects of urban street trees on driver perception, driving behaviour, and general road safety. However, it is rare that the relationship between urban street trees and pedestrian safety is investigated. In this study, a micro-level frequency model is established to evaluate the effects of tree density and tree canopy cover on pedestrian injuries, accounting for pedestrian crash exposure based on comprehensive pedestrian count data from a state in Australia, Melbourne. In addition, effects of road geometry, traffic characteristics, and temporal distribution are also considered. Furthermore, effects of spatial dependency and correlation between pedestrian casualty counts of different injury severity levels are accounted using a multivariate Bayesian spatial approach. Results indicate that road width, bus stop, tram station, on-street parking, and 85th percentile speed are positively associated with pedestrian casualty. In contrast, pedestrian casualty decreases when there is a pedestrian crosswalk and increases in tree density and canopy. Also, time variation in pedestrian injury risk is significant. To sum up, urban street trees should have favorable effect on pedestrian safety. Findings are indicative to optimal policy strategies that can enhance the walking environment and overall pedestrian safety. Therefore, sustainable urban and transport development can be promoted.

Microscale pedestrian environment surrounding pedestrian injury sites in Washington state, 2015-2020.

OBJECTIVE: While microscale pedestrian environment features such as sidewalks and crosswalks can affect pedestrian safety, it is challenging to assess microscale environment associated risk across locations or at scale. Addressing these challenges requires an efficient auditing protocol that can be used to assess frequencies of microscale environment features. For this reason, we developed an eight-item pedestrian environment virtual audit protocol and conducted a descriptive epidemiologic study of pedestrian injury in Washington State, USA. METHODS: We used data from police reports at pedestrian-automotive collision sites where the pedestrian was seriously injured or died. At each collision site, high school students participating in an online summer internship program virtually audited Google Street View imagery to assess the presence of microscale pedestrian environment features such as crosswalks and streetlighting. We assessed inter-rater reliability using Cohen's kappa and explored prevalence of eight microscale environment features in relation to injury severity and municipal boundaries. RESULTS: There were 2248 motor vehicle crashes eliciting police response and resulting in death or serious injury of a pedestrian in Washington State between January 1, 2015 and May 8, 2020. Of the crashes resulting in serious injury or death, 498 (22%) resulted in fatalities and 1840 (82%) occurred within municipal boundaries. Cohen's kappa scores for the eight pedestrian features that were audited ranged from 0.52 to 0.86. Audit results confirmed that features such as sidewalks and crosswalks were more common at collision sites within city limits. CONCLUSIONS: High school student volunteers with minimal training can reliably audit microscale pedestrian environments using limited resources.

Opposite Effect of Cyclic Loading on the Material Properties of Medial Collateral Ligament at Different Temperatures: An Animal Study.

In traffic accidents, the medial collateral ligament (MCL) injury of the knee joint of pedestrians is common. Biofidelic material is important to realize MCL's native biomechanics in simulations to clarify the injury mechanisms of pedestrians. Pedestrians' MCLs usually experience cyclic loading at the intra-articular temperature of the knee joint before accidents. Temperature influences the material behaviors of ligaments. However, the mechanical properties of ligaments under cyclic loading have been widely evaluated only at room temperature rather than physiological temperature. Therefore, this study aimed to determine whether the difference between room and intra-articular temperatures influences the effect of cyclic loading on the mechanical properties of MCL. We measured the tensile properties of 34 porcine MCLs at room temperature (21-23°C) and intra-articular temperature (35-37°C), with either 10 cycles or 240 cycles of cyclic loading, a total of four different conditions. The structural responses and geometric data were recorded. After 240 cycles of cyclic loading, stiffness increased by 29.0% (p < 0.01) at room temperature and decreased by 11.5% (p = 0.106) at intra-articular temperature. Material properties were further compared because the geometric differences between samples were inevitable. At room temperature, after 240 cycles of cyclic loading, elastic modulus increased by 29.6% (p < 0.001), and failure strain decreased by 20.4% (p < 0.05). By contrast, at intra-articular temperature, after 240 cycles of cyclic loading, modulus decreased by 27.4% (p < 0.001), and failure strain increased by 17.5% (p = 0.193), insignificant though. In addition, there were no significant differences between the four groups in other structural or material properties. The results showed that temperature reversed the effect of cyclic loading on the mechanical properties of MCL, which may be caused by the high strength and thermally stable crosslinks of MCL. Therefore, for improving the fidelity of knee joint simulations and elucidating the injury mechanism of pedestrians, it is better to measure the mechanical properties of MCL at intra-articular temperature rather than room temperature.

Exploring the impacts of built environment on pedestrian injury severity involving distracted driving.

INTRODUCTION: This study develops an injury severity model that demonstrates level of pedestrians' injury severity during pedestrian-vehicle collisions, specifically those involving distracted driving. METHOD: It uses data from a police-reported collision database that contains pedestrian-vehicle collision information in Nova Scotia, Canada. A latent segmentation-based ordered logit (LSOL) model is developed in this paper that comprehensively examines the influence of built environment characteristics on pedestrian injury severity. It estimates a latent segment allocation model within LSOL modeling framework to capture unobserved heterogeneity across pedestrians. Two latent segments, high- and low-risk segments, are identified probabilistically based on pedestrian characteristics and action, driver action, and collision attributes. RESULTS: Results suggest that higher mixed land-use, transit stop density, length of sidewalk in the collision locations, and collisions occurring near schools yield lower pedestrian injury severity. In contrast, pedestrian-vehicle collisions in arterial roads, curved roads, sloped roads, and roundabouts tend to result in severe injuries. Interactions between distracted driving type and built environment characteristics are examined in this study. For example, using a communication device while driving on straight roads increases likelihood of higher pedestrian injury severity. This study also confirms the existence of heterogeneity across latent segments. For instance, higher percentage of people commuting by walking in the collision areas yield severe pedestrian injury in high-risk segments and lower injury severity in low-risk segments. Practical applications: The findings of this study will assist transportation planners and road safety stakeholders in developing effective and prioritized policies to reduce pedestrian injury severity involving distracted driving incidents.

Causal Inference with Case-Only Studies in Injury Epidemiology Research.

Purpose of Review: We review the application and limitations of two implementations of the "case-only design" in injury epidemiology with example analyses of Fatality Analysis Reporting System data. Recent Findings: The term "case-only design" covers a variety of epidemiologic designs; here, two implementations of the design are reviewed: (1) studies to uncover etiological heterogeneity and (2) studies to measure exposure effect modification. These two designs produce results that require different interpretations and rely upon different assumptions. The key assumption of case-only designs for exposure effect modification, the more commonly used of the two designs, does not commonly hold for injuries and so results from studies using this design cannot be interpreted. Case-only designs to identify etiological heterogeneity in injury risk are interpretable but only when the case-series is conceptualized as arising from an underlying cohort. Summary: The results of studies using case-only designs are commonly misinterpreted in the injury literature.

Modelling bus-pedestrian crash severity in the state of Victoria, Australia.

Understanding the relationship between bus-pedestrian crash severity and factors contributing to such crashes is important. However, there exists a dearth of research on the factors affecting bus-pedestrian crash severity. This study aims to fulfil this gap by investigating the factors affecting the severity of pedestrian injuries. A data set of bus-pedestrian crashes in the State of Victoria, Australia was analysed over the period of 2006 - 2019. Through the results of association rule discovery method, the factors that increase the risk of pedestrian fatality are darkness, pedestrian walking on carriageway with traffic, intersections, high speed zone, old pedestrian, young bus driver and weekend holidays. Furthermore, co-occurrence of factors that increase the risk of a pedestrian fatality were extracted. To reduce the injuries of bus-pedestrian crashes, we recommend improving the light conditions, reducing the jaywalking behaviour of pedestrians, implementing speed bumps in high speed zones and installing pedestrian detection systems on buses.13 years of bus-pedestrian crashes in Victoria, Australia was analyzed.Association rules discovery was used for modeling pedestrian fatality.Darkness, pedestrian movement, zone speed and age effect the rate of fatality.Pattern of pedestrian fatality in collision with bus was extracted.

Relationship between pedestrian detection specifications of parking sensor and potential safety benefits.

Measures to protect vulnerable road users during low-speed maneuvers are required. For example, systems that use cameras to display the vehicle's rearview are popular. However, some vehicles are difficult to equip with a rear view camera system. To avoid a crash when driving in reverse, it is also effective to identify the presence of pedestrians via an audible warning using a device (e.g., clearance sonar). It may be cheaper to install than a rearview camera system. Installation cost is also important for the spread of equipment that reduces a crash. It is necessary to clarify the minimum specifications that balance cost and reduce crashes. Device specifications (e.g., detection distance and response delay) may affect the crash reduction rate. There should be a detection distance required for the sonar to have the same crash reduction effect as the rear view camera system. Thus, in this study, we conducted experiments and obtained data about how a vehicle moves and driver reactions to audible warnings when driving in reverse. Based on the acquired data, a numerical simulation was performed to determine whether a driver could avoid a crash under various circumstances. As a result, it was shown that the clearance sonar must have a detection distance of 0.8 m or more to expect the same effect as a rearview camera system. In other words, to expect sonar to have the same performance as a rearview camera, a detection distance of at least 0.8 m should be set as a specification.

A Multilevel Model Approach for Investigating Individual Accident Characteristics and Neighborhood Environment Characteristics Affecting Pedestrian-Vehicle Crashes.

Walking is the most basic movement of humans and the most fundamental mode of transportation. To promote walking, it is necessary to create a safe environment for pedestrians. However, pedestrian-vehicle crashes still remain relatively high in South Korea. This study employs a multilevel model to examine the differences between the lower-level individual characteristics of pedestrian crashes and the upper-level neighborhood environmental characteristics in Seoul, South Korea. The main results of this study are as follows. The individual characteristics of pedestrian-vehicle crashes are better at explaining pedestrian injury severity than built environment characteristics at the neighborhood level. Older pedestrians and drivers suffer more severe pedestrian injuries. Larger vehicles such as trucks and vans are more likely to result in a high severity of pedestrian injuries. Pedestrian injuries increase during inclement weather and at night. The severity of pedestrian injuries is lower at intersections and crosswalks without traffic signals than at crosswalks and intersections with traffic signals. Finally, school zones and silver zones, which are representative policies for pedestrian safety in South Korea, fail to play a significant role in reducing the severity of pedestrian injuries. The results of this study can guide policymakers and planners when making decisions on how to build neighborhoods that are safer for pedestrians.

Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea.

Pedestrian-vehicle crashes can result in serious injury to pedestrians, who are exposed to danger when in close proximity to moving vehicles. Furthermore, these injuries can be considerably serious and even lead to death in a manner that varies depending on the pedestrian's age. This is because the pedestrian's physical characteristics and behaviors, particularly in relation to roads with moving vehicles, differ depending on the pedestrian's age. This study examines the determinants of pedestrian injury severity by pedestrian age using binary logistic regression. Factors in the built environment, such as road characteristics and land use of the places where pedestrian crashes occurred, were considered, as were the accident characteristics of the pedestrians and drivers. The analysis determined that the accident characteristics of drivers and pedestrians are more influential in pedestrian-vehicle crashes than the factors of the built environmental characteristics. However, there are substantial differences in injury severity relative to the pedestrian's age. Young pedestrians (aged under 20 years old) are more likely to suffer serious injury in school zones; however, no association between silver zones and injury severity is found for elderly pedestrians. For people in the age range of 20-39 years old, the severity of pedestrian injuries is lower in areas with more crosswalks and speed cameras. People in the age range of 40-64 years old are more likely to be injured in areas with more neighborhood streets and industrial land use. Elderly pedestrians are likely to suffer fatal injuries in areas with more traffic signals. This study finds that there are differences in the factors of pedestrian injury severity according to the age of pedestrians. Therefore, it is suggested that concrete and efficient policies related to pedestrian age are required to improve pedestrian safety and reduce pedestrian-vehicle crashes.

Qualitative Field Observation of Pedestrian Injury Hotspots: A Mixed-Methods Approach for Developing Built- and Socioeconomic-Environmental Risk Signatures.

Road traffic injuries constitute a significant global health burden; the World Health Organization estimates that they result in 1.35 million deaths annually. While most pedestrian injury studies rely predominantly on statistical modelling, this paper argues for a mixed-methods approach combining spatial analysis, environmental scans, and local knowledge for assessing environmental risk factors. Using data from the Nova Scotia Trauma Registry, severe pedestrian injury cases and ten corresponding hotspots were mapped across the Halifax Regional Municipality. Using qualitative observation, quantitative environmental scans, and a socioeconomic deprivation index, we assessed hotspots over three years to identify key social- and built-environmental correlates. Injuries occurred in a range of settings; however, clear patterns were not observed based on land use, age, or socio-economic status (SES) alone. Three hotspots revealed an association between elevated pedestrian injury and a pattern of geographic, environmental, and socio-economic factors: low- to middle-SES housing separated from a roadside attraction by several lanes of traffic, and blind hills/bends. An additional generalized scenario was constructed representing common risk factors across all hotspots. This study is unique in that it moves beyond individual measures (e.g., statistical, environmental scans, or geographic information systems (GIS) mapping) to combine all three methods toward identifying environmental features associated with pedestrian motor vehicle crashes (PMVC).

Explaining crash modification factors: Why it's needed and how it might be done.

Although the Highway Safety Manual (HSM) now provides empirical tools for predicting the safety consequences of highway engineering decisions, these tools represent the driver and vehicle conditions prevailing in the United States during the last few decades. As automated vehicles improve in capability and increase in market share these conditions will change, possibly reducing the accuracy of HSM predictions. Assessing the transferability of a crash modification factor to new situations almost certainly requires an explanation of how the modification achieves its effect, but at present there is little guidance on how such explanations might be posed and tested. This paper describes the use of micro-simulation to develop an explanation of how pedestrian hybrid beacons (PHB) modify pedestrian crash likelihood. Since the literature indicated that PHBs can affect both pedestrian and driver behavior it was necessary to include both possibilities in the model. To simulate injury severity distributions similar to those recorded in a crash database it was necessary to propose that almost all simulated drivers attempt to brake in pedestrian/vehicle encounters. Then changing the simulated fraction of careful pedestrians from between 0% and 30% to between 80% and 90% gave simulated crash modification factors similar to estimates reported in the literature. The resulting working hypothesis then is that PHBs achieve their crash reduction effect in large part by modifying pedestrian behavior. This is not so much a direct observation as it is an inference to the best explanation. That is, the support for the hypothesis comes from its ability to explain the data at hand. This hypothesis should be tested further, and additional tests are proposed.