Pedestrian crash trends and potential countermeasures from around the world

Analysis of pedestrian accident severity by considering temporal instability and heterogeneity

The aim of this study was to investigate the effects of temporal instability and possible heterogeneity on pedestrian accident severity, 48786 accident data from 2018 to 2021 in the UK STATS database were used as the study object, and accident severity was used as the dependent variable, and 49 accident characteristics were selected as independent variables from 6 characteristics of accident pedestrian, driver, vehicle, road, environment and time to construct the pedestrian accident mean heterogeneity random-parameter logit model and examined its temporal stability. The results of model estimation and likelihood ratio tests indicate that the variables affecting pedestrian injury severity are highly variable and not stable over the years. And further demonstrates the potential of models that address unobserved heterogeneity for significant relationships in pedestrian accident severity analyses.

Visual hazardous models: A hybrid approach to investigate road hazardous events

Road users (drivers, passengers, pedestrians, and Animals) are exposed to hazardous events during their commute. With 23 % of global fatalities among pedestrians, their safety continues to be a principal interest for policymakers worldwide. Owing to limited budgets available, there is a growing emphasis on data-driven stochastic models to decide on policies. However, statistical models have limitations due to crash data having redundant features, inherent heterogeneity, and unobserved characteristics. The random parameter model framework addresses the unobserved heterogeneity, but redundant features and inherent heterogeneity among the data's characteristics still compute the biased estimates. This is further complicated if the data has spatiotemporal attributes. To address this, we developed two visual hazardous (VH) models: (i) addresses the unobserved heterogeneity in the data, and (ii) addresses the dimensionality, inherent heterogeneity among the characteristics and unobserved heterogeneity in the collected data after spatiotemporal pattern identification. The feature selection model reduces the dimensionality, whereas latent class clustering classifies the data into maximum heterogeneity between classes. This integration reduces bias in the estimates. As a use-case, pedestrian crosswalk crashes for a decade (2009-2018) in the Indian state of Tamil Nadu extracted from the Road Accident Database Management System (RADMS) was used to understand model performance. This data comprises the crash location, road, vehicle, driver, pedestrian, and environment details. Results show that visual hazardous model 2 allows for generating crash scenarios with five homogeneous sub-classes and the magnitude with marginal effects of contributing factors impacting it. For example, pedestrians during their crosswalks are likely to sustain 82% more chance of fatal/grievous injuries on expressways (posted speed limit: 100 km per hour) in annual hazardous zone locations. Working pedestrian age group (25-64 years), an older pedestrian (>64 years), the pedestrian position on a pedestrian crossing and not in the centre of the road, pedestrian action: walking along the edge of the road, multiple lanes, two lanes, paved shoulder, straight and flat road, motorcycle, bus, truck, medium-duty vehicle, illegal driver (<=17 years), going ahead/ overtaking, high speed, expressways, and rural region were statistically significant (positively) contributing to the fatal/grievous injury pedestrian crashes during their crosswalk. This technique serves as a structure for engineers, researchers, and policymakers to formulate effective countermeasures that enhance road safety.

Aberrant behaviors of drivers involved in crashes and related injury severity: Are there variations between the major cities in the same country?

INTRODUCTION

Crash data analyses based on accident datasets often do not include human-related variables because they can be hard to reconstruct from crash data. However, records of crash circumstances can help for this purpose since crashes can be classified considering aberrant behavior and misconduct of the drivers involved.

METHOD

In this case, urban crash data from the 10 largest Italian cities were used to develop four logistic regression models having the driver-related crash circumstance (aberrant behaviors: inattentive driving, illegal maneuvering, wrong interaction with pedestrian and speeding) as dependent variables and the other crash-related factors as predictors (information about the users and the vehicles involved and about road geometry and conditions). Two other models were built to study the influence of the same factors on the injury severity of the occupants of vehicles for which crash circumstances related to driver aberrant behaviors were observed and of the involved pedestrians. The variability between the 10 different cities was considered through a multilevel approach, which revealed a significant variability only for the inattention-related crash circumstance. In the other models, the variability between cities was not significant, indicating quite homogeneous results within the same country.

RESULTS

The results show several relationships between crash factors (driver, vehicle or road-related) and human-related crash circumstances and severity. Unsignalized intersections were particularly related to the illegal maneuvering crash circumstance, while the night period was clearly related to the speeding-related crash circumstance and to injuries/casualties of vehicle occupants. Cyclists and motorcyclists were shown to suffer more injuries/casualties than car occupants, while the latter were generally those exhibiting more aberrant behaviors. Pedestrian casualties were associated with arterial roads, heavy vehicles, and older pedestrians.

Hazardous traffic scenarios for motorcyclists in Indonesia: a comprehensive insight from police accident data and self-reports

Motorcycle safety remains a concern in low- and middle-income countries. This study addresses this issue by identifying hazardous scenarios for motorcyclists in Indonesia. We conducted a two-step cluster analysis and injury analysis to examine motorcycle accidents based on the police accident dataset (2020-2021) of Brebes Regency, Indonesia. We integrated the findings with accident self-reports from 104 young motorcyclists using a joint display to obtain a more comprehensive insight. As a result, we identified four hazardous traffic scenarios: motorcycle-to-vehicle collisions on median roads, motorcycle-to-vehicle collisions on non-median roads, motorcycle-to-pedestrian collisions, and single-motorcycle collisions. We suggest countermeasures for each scenario and propose a public transport policy as a safer mobility solution. Applying a two-step cluster analysis on accident data and integrating the findings of accident data and self-report analysis proved beneficial in this study. Therefore, we encourage the use of this novel approach in future studies.

Evaluating safety and compliance of pedestrian crossings in rural contexts: A before and after study of RRFBs and LED-embedded signs

Improving the safety of pedestrian and cyclist infrastructure is critical for reducing traffic-related injuries and fatalities. Pedestrian traffic safety risks are heightened in rural contexts. A key area of focus is the protection of pedestrians crossing roadways between intersections and in high-risk areas such as rural to urban transition zones. One way to reduce safety risks for pedestrians is through the use of crossing treatments such as rectangular rapid flashing beacons (RRFBs) and pedestrian activated LED-embedded signs (LESs), which use a pedestrian activated beacon to increase drivers' awareness of pedestrians. Prior research on these treatments leaves open questions about their effectiveness, particularly in rural contexts. Consequently, rural communities have limited guidance for their use. We address this gap by evaluating the effectiveness of RRFBs and LESs in small and rural communities in Vermont using a rigorous before-after observational study design. Our results indicate that RRFBs improve compliance and safety in rural and small community contexts, while LESs have little to no effect on compliance and safety. Our findings hold in both central locations and rural to urban transition zones.

A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity

Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian exposure, considering factors such as Point of Interest (POI) attributes, POI intensity, traffic volume, and pedestrian walkability. Following risk interpolation and feature engineering, a comprehensive data source for risk prediction was formed. Finally, based on risk factors, the VT-NET deep learning network model was proposed, integrating the algorithmic characteristics of the VGG16 deep convolutional neural network and the Transformer deep learning network. The model involved training non-temporal features and temporal features separately. The training dataset incorporated features such as weather conditions, exposure intensity, socioeconomic factors, and the built environment. By employing different training methods for different types of causative feature variables, the VT-NET model analyzed changes in risk features and separately trained temporal and non-temporal risk variables. It was used to generate spatiotemporal grid-level predictions of crash risk across four spatiotemporal scales. The performance of the VT-NET model was assessed, revealing its efficacy in predicting pedestrian crash risks across the study area. The results indicated that areas with concentrated crash risks are primarily located in the city center and persist for several hours. These high-risk areas dissipate during the late night and early morning hours. High-risk areas were also found to cluster in the city center; this clustering behavior was more prominent during weekends compared to weekdays and coincided with commercial zones, public spaces, and educational and medical facilities.

Pedestrian crash causation analysis and active safety system calibration

Over 20 % of global crash fatalities involve pedestrians, but pedestrian crash causation and pedestrian protection systems have not been thoroughly developed or reliably tested. To understand the causation characteristics of pedestrian crashes, 398 pedestrian crashes were extracted from the China in-depth accident study (CIDAS), and most of these crashes were aggregated into five scenarios. The two scenarios with the highest proportion of crashes were analyzed by the driving reliability and error analysis method (DREAM) to identify high-risk causation patterns. From these patterns, three main contributing factors were identified: 1) extremely environmental light disturbance; 2) distracted driving caused by drivers' own thoughts; 3) drivers violating pedestrian yield law. Based on these patterns and factors, a pedestrian protection system was designed. It consists of a forward vision sensor and radar to sense the environment and the three-stage autonomous emergency braking (AEB) algorithm to automatically avoid pedestrian collisions. Crash scenarios from CIDAS data were recreated in MATLAB Simulink to test the pedestrian protection system proposed in this study. This system was found to reduce pedestrian crashes by more than 90 %. The optimal parameters for three AEB stages were obtained, with decelerations of 0.2 g, 0.3 g, and 0.6 g. This study designed an active safety system based on causation analysis of the vehicle-pedestrian crashes and calibrated the AEB algorithm of it, thus providing reference and insight for further development of pedestrian protection systems.

Comparative analysis of pedestrian crash severity at United Kingdom rural road intersections and Non-Intersections using latent class clustering and ordered probit model

Pedestrian safety is a critical issue in the United Kingdom (UK) as pedestrians are the most vulnerable road users. Despite numerous studies on pedestrian-vehicle crashes globally, limited research has been conducted to explore the factors contributing to such incidents in the UK, especially on rural roads. Therefore, this study aimed to investigate the severity of pedestrian injuries sustained on rural roads in the UK, including crashes at intersections and non-intersections. We utilized the STATS19 dataset, which provided comprehensive road safety data from 2015 to 2019. To overcome the challenges posed by heterogeneity in the data, we employed a Latent Class Analysis to identify homogeneous clusters of crashes. Additionally, we utilized the Ordered Probit model to identify contributing factors within each cluster. Our findings revealed that various factors had distinct effects on the severity of pedestrian injuries at intersections and non-intersections. Several parameters like the pedestrian location in footway and one-way roads are only statistically significant in the intersection section. Certain factors such as the day of the week, the pedestrian's location in a refuge, and minor roads (class B roads) were found to be significant only in the non-intersection section.Parameters includingpedestrians aged over 65 years and under 15 years, drivers under 25 years, male drivers and pedestrians, darkness, heavy vehicles, speed limits exceeding 96 km/h (60 mph), major roads (class A roads), and single carriageway roadsare significant in both sections. The study proposes various measures to mitigate the severity of pedestrian-vehicle crashes, such as improving lighting conditions, enhancing pedestrian infrastructure, reducing speed limits in crash-prone areas, and promoting education and awareness among pedestrians and drivers. The findings and suggested measures could help policymakers and practitioners develop effective strategies and interventions to reduce the severity of these incidents and enhance pedestrian safety.

Pedestrian Safety in Frontal Tram Collision, Part 1: Historical Overview and Experimental-Data-Based Biomechanical Study of Head Clashing in Frontal and Side Impacts

This article represents the first paper in a two-part series dealing with safety during tram-pedestrian collisions. This research is dedicated to the safety of trams for pedestrians during collisions and is motivated by the increased number of lethal cases. The first part of this paper includes an overview of tram face development from the earliest designs to the current ones in use and, at the same time, provides a synopsis and explanation of the technical context, including a link to current and forthcoming legislation. The historical design development can be characterised by three steps, from an almost vertical front face, to leaned and pointed shapes, to the current inclined low-edged windshield without a protruding coupler. However, since most major manufacturers now export their products worldwide and customisation is only of a technically insignificant nature, our conclusions are generalisable (supported by the example of Berlin). The most advantageous shape of the tram's front, minimising the effects on pedestrians in all collision phases, has evolved rather spontaneously and was unprompted, and it is now being built into the European Commission regulations. The goal of the second part of this paper is to conduct a series of tram-pedestrian collisions with a focus on the frontal and side impacts using a crash test dummy (anthropomorphic test device-ATD). Four tram types approaching the collision at four different impact speeds (5 km/h, 10 km/h, 15 km/h, and 20 km/h) were used. The primary outcome variable was the resultant head acceleration. The risk and severity of possible head injuries were assessed using the head injury criterion (HIC15) and its linkage to the injury level on the Abbreviated Injury Scale (AIS). The results showed increasing head impacts with an increasing speed for all tram types and collision scenarios. Higher values of head acceleration were reached during the frontal impact (17-124 g) compared to the side one (2-84 g). The HIC15 values did not exceed the value of 300 for any experimental setting, and the probability of AIS4+ injuries did not exceed 10%. The outcomes of tram-pedestrian collisions can be influenced by the ATD's position and orientation, the impact speed and front-end design of trams, and the site of initial contact.

Trends and characteristics of severe road traffic injuries in children: a nationwide cohort study in Japan

PURPOSE

The purpose of this study was to evaluate temporal trends of characteristics of severe road traffic injuries in children and identify factors associated with mortality using a nationwide database in Japan.

METHODS

We performed a retrospective analysis of Japan Trauma Data Bank (JTDB) from 2004 to 2018. We included patients with traffic injuries under the age of 18 who were hospitalized. The primary outcome was in-hospital mortality. We evaluated trends in characteristics and assessed factors associated with in-hospital mortality using a logistic regression analysis.

RESULTS

A total of 4706 patients were analyzed. The most common mechanism of injury was bicycle crash (34.4%), followed by pedestrian (28.3%), and motorcycle crash (21.3%). The overall in-hospital mortality was 11.2%. We found decreasing trends in motorcycle crash and in-hospital mortality and increasing trends in rear passenger seats in cars over the 15-year period. The following factors were associated with in-hospital mortality: car crash (aOR 1.69, 95%CI 1.18-2.40), pedestrian (aOR 1.50, 95%CI 1.13-1.99), motorcycle crash (aOR 1.42, 95%CI 1.03-1.95) [bicycle crash as a reference]; concomitant injuries to head/neck (aOR 5.06, 95%CI 3.81-6.79), thorax (aOR 2.34, 95%CI 1.92-2.87), abdomen (aOR 1.74, 95%CI 1.29-2.33), pelvis/lower-extremity (aOR 1.57, 95%CI 1.23-2.00), spine (aOR 3.01, 95%CI 2.02-4.43); and 5-year increase in time period (aOR 0.80, 95%CI 0.70-0.91).

CONCLUSIONS

We found decreasing trends in motorcycle crash and in-hospital mortality, increasing trends in rear passenger seats in cars over the 15-year period, and factors associated with in-hospital mortality such as type of mechanisms and concomitant injuries. Strengthening child road safety measures, particularly for rear passenger seats in vehicles, is imperative to enhance our dedication to injury prevention.

Pedestrians' unsafe road-crossing behaviors in Iran: An observational-based study in West Azerbaijan

OBJECTIVE

Pedestrians are one of the most vulnerable users in road traffic injuries (RTIs). The rate of pedestrians' fatality is high in Iran. It is worthwhile to investigate how pedestrians behave. This observational study aimed to investigate pedestrians' unsafe behaviors while crossing.

METHODS

This cross-sectional study examined the behavior of 1095 pedestrians (69.7% men) using videotaping when they crossed at two intersections and three non-intersections on a weekend and two working days in the morning, at noon, and in the evening. The information obtained was classified into 5 domains including adherence to traffic rule, violation, environmental barriers, visibility, and distraction. Data were analyzed using Stata version 17.

RESULTS

About 60% of the pedestrians ignored the crosswalk and crossed the street wherever they wanted. More than 30% ignored the vehicles passing and crossed the street inattentively. About 60% of the pedestrians committed violations. More than half of pedestrians crossed unsafe crossings diagonally or in a hurry. More than 35% wore dark clothing and had low visibility, and nearly 30% were distracted. Adolescent pedestrians did not adhere traffic rules about 6 times more than the young adult pedestrians. Pedestrians who did not adhere to traffic rules in the morning were significantly more than in the evening. Men committed a violation 1.47 times more than women. The results showed that the pedestrians committed a violation in the morning significantly more than in the evening.

CONCLUSION

The occurrence of pedestrians' unsafe behaviors in Maku was high. Unsafe behaviors were high among men and young adult pedestrians. Therefore, it's essential to implement educational interventions via different media as well as environmental interventions by different organizations to improve safe behavior among pedestrians.

Do footbridge and underpass improve pedestrian safety? A Hong Kong case study using three-dimensional digital map of pedestrian network

Hong Kong is a compact city with high activity and travel intensity. In the past decades, many footbridges and underpasses were installed to reduce the pedestrian-vehicle conflicts on urban roads. However, it is rare that the effects of configuration of pedestrian network on pedestrian crashes are investigated. In Hong Kong, many footbridges and underpasses are connected to major transport hubs and commercial building development and become parts of giant elevated and underground walkway systems. It is challenging to characterize such a complicated pedestrian network. In this study, a three-dimensional digital map is applied to estimate the connectivity and accessibility of pedestrian network, and measure the relationship between pedestrian network characteristics and pedestrian safety at the macroscopic level. Hence, the effects of footbridge and underpass on pedestrian safety are examined. For example, comprehensive built environment, pedestrian network, traffic, and crash data are aggregated to 379 grids (0.5 km × 0.5 km). Then, multivariate Poisson lognormal regression approach is applied to model fatal and severe injury (FSI) and slight injury pedestrian crashes, with which the effects of unobserved heterogeneity, spatial correlation, and correlation between crash counts are accounted. Results indicate that population density, traffic volume, walking trip, footpath density, node density, number of vertices per footpath segment, bus stop, metro exit, residential area, commercial area, and government and utility area are positively associated with pedestrian crashes. In contrast, average gradient, accessibility of footbridge, accessibility of underpass, and number of crossings per road segment are negatively associated with pedestrian crashes. In other word, pedestrian safety would be improved when footbridge and underpass are more accessible. Findings have implications for the design and planning of pedestrian network to promote walkability and improve pedestrian safety.

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 impacts of non-motorized traffic enforcement cameras on red light violations of cyclists at signalized intersections

INTRODUCTION

With a significant increase in accidents involving cyclists, more attention has been paid to cycling safety. Previous studies on traffic accident revealed that red-light violations of non-motorized vehicles have become the leading cause of crashes at signalized intersections. The objective of this study is to investigate the impact of non-motorized traffic enforcement cameras (NTECs) on the red-light running behavior of cyclists, including ordinary e-bike riders, delivery e-bike riders, and bicyclists.

METHOD

An observational study of 5,217 cyclists was conducted at six primary intersections in the downtown areas of Nanjing, China. A random parameter logit model was used to explore the safety effect of the NTECs and other factors related to red-light violation behavior.

RESULTS

The results indicate higher reductions in red-light violations at intersections with the NTECs compared than at the non-adjacent intersections without the NTECs. Furthermore, the NTECs demonstrated a beneficial but smaller impact on the reduction of violations at adjacent intersections. Another primary finding was that the effects of the NTECs varied among three types of cyclists (ordinary e-bike riders, delivery e-bike riders, and bicyclists).

CONCLUSIONS

The NTECs were found to be most effective in the case of delivery e-bike riders, followed by ordinary e-bike riders and bicyclists. In addition, the factors associated with the red-light violation behaviors of these three groups were also found to be different. In general, group size, maximum waiting time, waiting position, and visual search were significantly related to the probability of red-light violations in all three groups.

PRACTICAL APPLICATIONS

Based on these findings, this study provides some feasible suggestions for improving the effect of the NTECs and for the future extension of the NTECs installation, such as the randomization of the enforcement and publicity campaigns.

The influence of traffic-infrastructure factors on pedestrian accidents at the macro-level: The geographically weighted regression approach

INTRODUCTION

Walking is an active way of moving the population, but in recent years there have been more pedestrian casualties in traffic, especially in developing countries such as Serbia. Macro-level road safety studies enable the identification of influential factors that play an important role in creating pedestrian safety policies.

METHOD

This study analyzes the impact of traffic and infrastructure characteristics on pedestrian accidents at the level of traffic analysis zones. The study applied a geographically weighted regression approach to identify and localize all factors that contribute to the occurrence of pedestrian accidents. Taking into account the spatial correlations between the zones and the frequency distribution of accidents, the geographically Poisson weighted model showed the best predictive performance.

RESULTS

This model showed 10 statistically significant factors influencing pedestrian accidents. In addition to exposure measures, a positive relationship with pedestrian accidents was identified in the length of state roads (class I), the length of unclassified streets, as well as the number of bus stops, parking spaces, and object units. However, a negative relationship was recorded with the total length of the street network and the total length of state roads passing through the analyzed area.

CONCLUSION

These results indicate the importance of determining the categorization and function of roads in places where pedestrian flows are pronounced, as well as the perception of pedestrian safety near bus stops and parking spaces.

PRACTICAL APPLICATIONS

The results of this study can help traffic safety engineers and managers plan infrastructure measures for future pedestrian safety planning and management in order to reduce pedestrian casualties and increase their physical activity.

Evaluation of automated emergency braking system's avoidance of pedestrian crashes at intersections under occluded conditions within a virtual simulator

Pedestrians' red-light crossing can present a threat to themselves and the safety at intersections, especially for the through vehicles since their speeds are higher compared to the turning vehicles. The automated emergency braking (AEB) system could actively detect pedestrians and react to avoid potential conflicts. This study contributes to evaluate the effectiveness of the AEB system under occlusion conditions. The braking algorithm was developed in the virtual simulator CARLA to control the ego vehicle. Three occlusion scenarios in which the sensor of the AEB system could not detect the pedestrian if the pedestrian is occluded by a stopping vehicle. The evaluation experiments were conducted at a typical 4-leg intersection considering different motion statuses of the ego vehicle and pedestrian. The effects of field of view (FOV) of the sensor and activation threshold of the AEB system were also explored. The study indicated that the effectiveness of the AEB system could be reduced by the occlusion time. A longer activation threshold is recommended if the pedestrian is potentially occluded for a long time. The effects of other factors such as the speed of the ego vehicle and pedestrian and scenarios were also identified.

Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends

Due to the high volume of documents in the pedestrian safety field, the current study conducts a systematic bibliometric analysis on the researches published before October 3, 2021, based on the science-mapping approach. Science mapping enables us to present a broad picture and comprehensive review of a significant number of documents using co-citation, bibliographic coupling, collaboration, and co-word analysis. To this end, a dataset of 6311 pedestrian safety papers was collected from the Web of Science Core Collection database. First, a descriptive analysis was carried out, covering whole yearly publications, most-cited papers, and most-productive authors, as well as sources, affiliations, and countries. In the next steps, science mapping was implemented to clarify the social, intellectual, and conceptual structures of pedestrian-safety research using the VOSviewer and Bibliometrix R-package tools. Remarkably, based on intellectual structure, pedestrian safety demonstrated an association with seven research areas: "Pedestrian crash frequency models", "Pedestrian injury severity crash models", "Traffic engineering measures in pedestrians' safety", "Global reports around pedestrian accident epidemiology", "Effect of age and gender on pedestrians' behavior", "Distraction of pedestrians", and "Pedestrian crowd dynamics and evacuation". Moreover, according to conceptual structure, five major research fronts were found to be relevant, namely "Collision avoidance and intelligent transportation systems (ITS)", "Epidemiological studies of pedestrian injury and prevention", "Pedestrian road crossing and behavioral factors", "Pedestrian flow simulation", and "Walkable environment and pedestrian safety". Finally, "autonomous vehicle", "pedestrian detection", and "collision avoidance" themes were identified as having the greatest centrality and development degrees in recent years.

Mapping pedestrian safety studies between 2010 and 2021: A scientometric analysis

Pedestrian deaths constitute 23% of road traffic deaths globally. Although several research papers have contributed to pedestrian safety analysis, they did not provide a comprehensive overview of the progress in the research domain and publication trends. This makes it difficult to identify trends and insights into the pedestrian research domain in light of the voluminous number of papers. This study fills this gap with a scientometric analysis of research on pedestrian safety analysis indexed in the Web of Science. The scope covers 2594 papers published between 2010 and 2021 in English. This study analyzed the annual publications and citation trends, top ten most cited papers, influential papers in their first three years after publication, contributing authors, funding agencies, and contributing journals. The regional gaps between the proportion of pedestrian deaths and research were also analyzed. The results showed low research productivity from low and middle-income countries although they have a high incidence of pedestrian deaths. Subsequently, the main keyword clusters or frontier topics were identified and topic analysis was employed to identify the evolution of studies. Four keyword clusters were identified, i.e., "vehicle-to-pedestrian crash and injury severity analysis", "pedestrian movement and decision simulation experiments", "improving the vehicle system towards reducing body region impact injuries", "pedestrian behavior in crosswalks and signalized intersections". This study contributes an integrated knowledge map of pedestrian safety analysis, publication trends, the evolution of studies, and under-researched topics to guide future research work in pedestrian safety analysis.

Traffic as a Barrier to Walking Safely in the United States: Perceived Reasons and Potential Mitigation Strategies

•

Almost a quarter of US adults perceive traffic as a barrier to safe walking.

•

Vehicle speed is the leading perceived traffic characteristic of concern.

•

Respondents perceive sidewalks as the most favorable strategy to mitigate risk.

Motor vehicle traffic is commonly cited as a barrier to walking, but national level perceptions of traffic characteristics that negatively influence walking and potential traffic mitigation strategies remain unclear. The objectives of this study were to describe perceptions of (1) traffic characteristics that make walking unsafe in the United States and (2) potential mitigation strategies to address these concerns among those who report traffic as a barrier to walking. Data were from FallStyles, a nationwide internet panel survey conducted in October 2019 (n = 3,284 adults). Respondents reported if traffic makes walking unsafe where they live; those who answered yes were then asked about traffic characteristics that make walking unsafe (number of vehicles, speed of vehicles, distracted or impaired driving, types of vehicles, and other reasons) and potential mitigation strategies (new or improved sidewalks, crosswalks, pedestrian signals, street lighting, things that slow vehicles down, separating the sidewalk from the road, fewer vehicle lanes, and other). Prevalence of responses was assessed overall and by select sociodemographic and geographic characteristics, and by walking status. Nearly 25% of US adults reported that traffic is a barrier to walking where they live. Of these, 79% selected vehicle speed as a contributing traffic characteristic, and 57% indicated new or improved sidewalks as a potential mitigation strategy. These top responses were shared across all sociodemographic, geographic, and walking behavior subgroups. Speed reduction efforts and built environment enhancements such as sidewalks may alleviate pedestrian safety concerns. Promotion campaigns may be needed to bring awareness to such changes.

Disability and pedestrian road traffic injury: A scoping review

Disability and ableism remain a nascent area of inquiry in road traffic injury research. A scoping review of academic literature was conducted to understand the state of knowledge on disability and pedestrian-motor vehicle collisions. Sixty-two eligible articles were identified and included. A significantly higher risk of pedestrian collisions, injuries, and fatalities was consistently found among disabled people. Risk factors included individualized factors such as walking speed and crossing decisions of disabled people. The roles of social/political environments in injury risk were less commonly explored. More research is needed to assess how inaccessible or disabling environments may produce elevated risk of pedestrian injury among disabled populations.

Factors explaining pedestrian-involved fatality crashes on National Highways in India

Pedestrians continue to face high risk of getting involved in fatal and serious injury crashes all over the world. In many high-income countries, pedestrian involvement in fatal crashes occur mostly in urban areas. However, in many low- and middle-income countries in Asia and Africa, pedestrian involvement in fatal crashes occur on intercity highways too. This research analyses fatal pedestrian crash characteristics, and identifies probable contributory factors to pedestrian involvement in fatal crashes using logistic regression for two-, four-, and six-lane National Highways. The fatal pedestrian crash density is found to be the highest at 1.37 crashes/km/year on six-lane divided NH-1. The binary logistic regression estimation results for pedestrian involvement in the fatal crash model revealed that the predictors: "number of lanes" and "time of crash" are found to be significant at 95% level. The model results for the variable "number of lanes" highlights the need to study pedestrian crossing behaviour on highways in detail. The design standards for pedestrian crossing facilities in urban areas may not be suitable for National Highways in particular multi-lane highways. In-depth research is required to understand the suitability of various traffic calming measures and other possible interventions which can ensure pedestrian safety on highways.

Using ordered and unordered logistic regressions to investigate risk factors associated with pedestrian crash injury severity in Victoria, Australia

INTRODUCTION

The safety of pedestrians is a major concern in Victoria, Australia. Despite the considerable number of pedestrian fatalities and injuries in traffic crashes, a limited number of studies focused on pedestrian crash severity in Victoria.

METHODS

This study investigates and identifies the influential factors determining the severity of pedestrian injuries in traffic crashes in Victoria by using crash data from 2010 to 2019. An unordered multinomial logit model and an ordered logit model are developed for this purpose.

RESULTS

The results indicate that pedestrian crashes on weekends, in the period of 10 a.m. to 10 p.m., on dark streets, at intersections, in areas with a speed limit above 50 km/h, and on medians or footpaths are associated with a higher probability of severe and fatal injuries. Male pedestrians, children, and older adults (>59) were more likely to sustain a higher level of injury in crashes. Concerning the driver characteristics, no significant relationship was found between pedestrian injury severity and driver gender and license status, but older drivers were more likely to cause severe and fatal injuries. Pedestrian collisions with motorcycles, heavy vehicles, light commercial vehicles, bus/minibus/coach, and trams increase the probability of more severe injuries compared to cars. Moreover, older vehicles are associated with a higher probability of severe pedestrian injuries. Comparison of the model results illustrated that the MNL model was slightly better fitted on the data than the ordered logit model, but the conclusions inferred from these two models were generally similar.

PRACTICAL APPLICATION

To reduce the injuries of pedestrian crashes, we recommend improving lighting conditions and sidewalk design, implementing speed reduction strategies at high pedestrian activity areas, introducing more pedestrian crossings at midblock, installing warning signs to drivers, and discouraging the use of vehicles that are more than 20 years old.

Exploring the impacts of street layout on the frequency of pedestrian crashes: A micro-level study

INTRODUCTION

Pedestrian safety has become a critical issue since walking is increasingly promoted as a sustainable transport mode. However, pedestrians are vulnerable to severe injury and mortality in road crashes. Therefore, it is important to understand the factors that affect the safety of pedestrians. This paper investigates the impacts of street layout on the frequency of pedestrian crashes by examining the interactive pattern of built environment, crossing facilities, and road characteristics.

METHOD

A surrogate exposure variable of pedestrian crashes at the road-segment level is proposed by considering the locations of crossing facilities, distribution of points of interest (POIs), road characteristics, and pedestrian activities. A network-based kernel density technique is used to identify the pedestrian crash risk at the road segment level. Bayesian spatial models based on different exposure variables are employed and compared.

RESULTS

The results suggest that models using the surrogate exposure of pedestrian crashes provide better model fit than the ones simply using the density of pedestrians. It is also found that the presence of POIs is related to a higher risk of pedestrian-vehicle crash. In addition, a significantly higher number of pedestrian crashes are found to occur on segments with more bus stops and metro stations. Results also show that the longer the distance between the crossing facilities and road segments, the more pedestrian crashes are observed.

CONCLUSIONS

The proposed aggregated indicator can provide more efficient exposure and higher prediction accuracy than the density of pedestrians. Besides, the POIs, crossing facilities, and road types were all significantly related to pedestrian crashes.

PRACTICAL APPLICATIONS

Our results suggest that the locations of POIs and transport facilities should be planned in a way that can decrease the number of road crossed or guide pedestrians to take safe crossing path.

An Advanced Machine Learning Approach to Predicting Pedestrian Fatality Caused by Road Crashes: A Step toward Sustainable Pedestrian Safety

More than 8000 pedestrians were killed due to road crashes in Australia over the last 30 years. Pedestrians are assumed to be the most vulnerable users of roads. This susceptibility of pedestrians to road crashes conflicts with sustainable transportation objectives. It is critical to know the causes of pedestrian injuries in order to enhance the safety of these vulnerable road users. To achieve this, traditional statistical models are used frequently. However, they have been criticized for their inflexibility in handling outliers and missing or noisy data, and their strict pre-assumptions. This study applied an advanced machine learning algorithm, a Bayesian neural network, which has the characters of both Bayesian theory and neural networks. Several structures of this model were built, and the best structure was selected, which included three hidden neuron layers—sixteen hidden nodes in the first layer and eight hidden nodes in the second and third layers. The performance of this model was compared with the performances of some other machine learning techniques, including standard Bayesian networks, a standard neural network, and a random forest model. The Bayesian neural network model outperformed the other models. In addition, a study on the importance of the features showed that the individuals’ characteristics, time, and circumstantial factors were essential. They greatly increased model performance if the model used them. This research lays the groundwork for using machine learning approaches to alleviate pedestrian deaths caused by road accidents.

Driving behavior at midblock crosswalks with Rectangular Rapid Flashing Beacons: Hidden Markov model approach using naturalistic data

Pedestrian fatalities have increased in the U.S. with the largest increase being observed on urban arterials and away from intersections. Rectangular Rapid Flashing Beacon (RRFB) has been widely implemented as a safety countermeasure to improve driver awareness and visibility of pedestrians, especially for midblock crosswalks. Studies show that drivers are more likely to yield to pedestrians at crosswalks with an RRFB. These studies are often based on a binary outcome of whether or not drivers yield to pedestrians. Nevertheless, it is also important to consider the drivers' deceleration behavior as a dynamic process at these crosswalks and the impact of pedestrians being present or not. Understanding this dynamic behavior and the related circumstances can provide information on the design of alerting systems that help drivers make more appropriate decisions at these crosswalks to avoid a vehicle-pedestrian crash. This study examined this research topic using Hidden Markov Models (HMMs) and data from a naturalistic study. More specifically, four HMMs were applied to the naturalistic brake and jerk data from the Safety Pilot Model Deployment (SPMD) program given drivers' intention to slow down, the RRFB activation status, and the presence of pedestrians. The time-based data sequence was converted to distance-based through a moving window to enhance result comparison and interpretation. Grid-search was used to select the best moving window parameters and the optimal number of hidden states. This study confirmed the high compliance at an activated RRFB when pedestrians were present. Even without pedestrians, one in five traversals showed drivers slowing down to less than 8.94 m/s (20 mph) within 35 m of the crosswalk. Model results further indicate that drivers started braking as far back as 180 m before the crosswalk and stopped braking from 70 m before the crosswalk at an activated RRFB without pedestrians. When there were pedestrians, drivers would start braking 20 to 30 m later but would brake more firmly and for longer. Finally, drivers were not likely to brake or decelerate when RRFB was off and no pedestrians were present.

Association of human mobility with road crashes for pandemic-ready safer mobility: A New York City case study

BACKGROUND

The COVID-19 pandemic has reshaped our cities in many ways. The number of motor vehicles on the road has plummeted during lockdowns, and an increasing number of people are turning to walking and biking. From a road safety perspective, the overall question is what effects the human behavior shift brings on the crash occurrence and, more importantly, how to support decision-makers on safer mobility policies?

METHOD

Based on anonymous mobile phone location and crash report data in New York City, this study attempts to provide some new insights by using survival analysis (the hazard function approach) to explore the effects of human mobility changes due to the pandemic on crashes that involve injuries and fatalities (of pedestrian, cyclist or motorist).

RESULTS

(1) the increased percentage of people staying at home improves pedestrian and cyclist safety, which adds evidence for making walking and cycling more appealing; (2) the increased percentage of people staying at home raises the likelihood of injuries for motor vehicle drivers, suggesting that it will be critical to monitor the driving behavior and establish new speed limits during the future pandemic waves and in the post-pandemic era as well; (3) non-work trips (e.g., shopping, recreation, personal business, etc.) are positively associated with crash injuries for motor vehicle drivers as well as pedestrian and cyclist; (4) human mobility factors were found not related to crash fatalities; (5) control NPIs implemented increased the motor vehicle drivers' crash risk.

Child Pedestrian Safety: Study of Street-Crossing Behaviour of Primary School Children with Adult Supervision

Road traffic accidents are the primary cause of injuries and fatalities among children. The current study focuses on children’s (un)safe crossing behaviour in a real traffic situation accompanied by an adult at a crosswalk in front of their school. The study aims to investigate if there are differences in crossing behaviour related to road infrastructure (i.e., one-way and two-way street, elevated and non-elevated street crossing), the gender of the child, and the effect of the accompanying adult’s behaviour on the child’s crossing behaviour. Primary school children from two urban schools in Flanders (Belgium) were observed for three days while crossing the street in front of their school in the morning and afternoon. A total of 241 child–adult pairs were observed. Descriptive analysis, Pearson chi-square tests, and binary logistic regression models were used to find differences between groups. More than half of the crossings exhibited two or more unsafe behaviours. Not stopping at the curb before crossing was the most unsafe behaviour, exhibited by 47.7% of children; not looking for oncoming traffic before and during the crossing was the second most unsafe behaviour, exhibited by 39.4% of the children. The only difference between boys’ and girls’ crossing behaviour was in stopping at the curb with girls 1.901 times more likely to stop before crossing as compared to boys. Adults holding hands of the child resulted in safer behaviours by children. The children not holding hands displayed significantly riskier behaviour in running or hopping while crossing the street and being distracted. The study reinforces the need to improve the transportation system through infrastructural interventions (elevated crosswalks), as well as educating and training children and the parents on safe crossing behaviour in traffic.

[Analysis of 5-year monitoring of road traffic injuries rates in Kazan]

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.

Citizens’ Perceptions in Relation to Transport Systems and Infrastructures: A Nationwide Study in the Dominican Republic

One of the challenges currently faced by emerging countries is to get their citizens to decide to use sustainable transport for their regular trips, in order to reduce the current vehicular pollution rates. The objective of this descriptive research is to examine the perceptions of Dominicans regarding the state of the country’s transport systems and road infrastructure. For this purpose, a nationwide survey procedure was performed. This cross-sectional research used the data retrieved from a sample of 1260 citizens aged over 18, proportional in gender, age, habitat, and province of the Dominican Republic. The results showed how Dominicans believe that, compared to other road features, pedestrian roads and public transport vehicles remain in a very poor condition. Further, citizens report to be more interested about the improvement of road infrastructures than in the implementation of any other set of measures performed to promote sustainable road mobility, including those related with alternative transport means. Finally, this study claims for the need of fostering educational, communicative and participative actions and measures aimed at increasing the value given to sustainable transportation, and the relevance of integrate potential structural and vehicular improvements with those related to human behavior in mobility.

Spatio-temporal patterns in pedestrian crashes and their determining factors: Application of a space-time cube analysis model

The number of vehicle accidents involving pedestrians in Korea has decreased gradually since the Pedestrian Safety and Convenience Enhancement Act was enacted in 2012, but the number of serious pedestrian-related crashes per capital remains near the top of a list of such rates for member countries of the Organization of Economic Cooperation and Development. Previous studies of pedestrian safety have been conducted based on various built environments. However, few have analyzed spatio-temporal changes and influential factors over more than 10 years, despite dramatic changes in the built environment during such time spans. Here, we examine big data on pedestrian-related crashes in Seoul from 2009 to 2018 using a space-time cube methodology and binary logistic regression analysis. The results show that the trend in pedestrians killed or severely injured is decreasing with pedestrian environment enhancement projects and pedestrian safety measures in Seoul. Also, the analysis reveals a need to pay more attention to pedestrian safety in areas with a large older population. Pedestrian safety measures should be reinforced in areas of concentrated wholesale and retail businesses. This study also indicates that illegal parking poses a threat to pedestrian safety. Lastly, this study confirms some positive impacts of redeveloped or newly developed areas and pedestrian environment enhancement projects on pedestrian safety.

Development of pedestrian- and vehicle-related safety performance functions using Bayesian bivariate hierarchical models with mode-specific covariates

INTRODUCTION

Pedestrian safety is a major concern as traffic crashes are the leading cause of fatalities and injuries for commuters. Traffic safety research in the past has developed various strategies to counteract traffic crashes, including the safety performance function (SPF). However, there is still a need for research dedicated to enhancing the SPF for pedestrians from perspectives of methodological framework and data input. To fill this gap, this study aims to add to the current SPF development practice literature by focusing on pedestrian-involved collisions, while considering the typical vehicle ones as well.

METHODS

First, bivariate models are used to account for the common unobserved heterogeneity shared by the pedestrian- and vehicle-related crashes at the same intersections. Second, variable importance ranking technique is used, along with correlation analysis, to determine mode-specific feature input. Third, the exposure information for both modes, annual pedestrian count, and annual daily vehicles traveled are used for model development. Fourth, a recent Bayesian inference approach (integrated nested Laplace approximation (INLA)) was adopted for bivariate setting. Finally, different evaluation criteria are used to facilitate comprehensive model assessment.

RESULTS

The results reveal different statistically significant factors contributing to each of the modes. The offset intersection provides better safety performance for both pedestrians and drivers as compared to other intersection designs. The model findings also corroborate the sensibility of using the bivariate models, rather than the separate univariate ones. Practical Applications: The study shows that pedestrians are more vulnerable to various intersection features such as left-turn channelization, intersection control, urban and rural population group, presence of signal mastarm on the cross-street, and mainline average daily traffic. Greater focus should be directed toward such intersection features to improve pedestrian safety.

The Effectiveness of Selected Devices to Reduce the Speed of Vehicles on Pedestrian Crossings

Accidents involving pedestrians often result in serious injury or death. The main goal of this conducted research is to evaluate selected devices that will help reduce the speed of vehicles on pedestrian crossings. Many devices from a group of “speed control measures” and “mid block tools” (refugee islands, speed tables, and raised pedestrian crossings) are examined to find the most effective ones. In our research, the range of reduction of a vehicle’s speed is used as a main measure of effectiveness, but a wider statistical analysis was conducted as well. One of the results of the research is the identification of three categories of devices referred to as high effectives (good), medium effectives (intermediate), and low or lack of effectives (bad). The content of the paper starts by highlighting the reasons to reduce the vehicle’s speed on pedestrian crossings (as an introduction). Next, we present the description of devices used to reduce the vehicle’s speed with a presentation of the research of their effectiveness. The studies that have been conducted are described in the following chapters: first, the characteristic of method and location, second, with discussion, the results of research and identification of the three categories of devices. The paper is then summarized by conclusions and comments. The research only covered the issues of road traffic engineering. The research was made in Poland, but the conclusions could be useful worldwide due to similar traffic rules and technical solutions.

Active Signage of Pedestrian Crossings as a Tool in Road Safety Management

The main objective of the study was to verify the effectiveness of active pedestrian crossings equipped with flashing lights activated automatically by detected pedestrians. A pilot study was conducted in two sites, where speed profiles of vehicles over the distance of 30 m before the crossing were analyzed. The study produced promising results in terms of reducing vehicle speeds so the next study investigated four other unsignalized pedestrian crossings. They were video-recorded for 48 h each, before, after and a year after installation. The ANOVA test was used to check the statistical significance of changes in selected indicators. Even after a year from the installation, the effect of the active signage remained significant. The average percentage of drivers yielding to pedestrians was 77.4% higher and the average waiting time 25.2% lower than before the installation. The average speeds of vehicles were 3.53 km/h lower on collector and 2.60 km/h lower on arterial streets. A decline in the probability of a pedestrian being killed or severely injured (KSI) ranged from 6.3 pp (9.4%) on the arterial streets immediately after the installation up to 12.9 pp (31.7%) on the collector streets one year after.

Hidden patterns among the fatally injured pedestrians in an Iranian population: application of categorical principal component analysis (CATPCA)

Background

Identifying hidden patterns and relationships among the features of the Fatal Pedestrian Road Traffic Injuries (FPRTI) can be effective in reducing pedestrian fatalities. This study is thus aimed to detect the patterns among the fatally injured pedestrians due to FPRTI in East Azerbaijan province, Iran.

Methods

This descriptive-analytic research was carried out based on the data of all 1782 FPRTI that occurred in East Azerbaijan, Iran from 2010 to 2019 collected by the forensic organization. Categorical Principal Component Analysis (CATPCA) was performed to recognize hidden patterns in the data by extracting principal components from the set of 13 features of FPRTI. The importance of each component was assessed by using the variance accounted for (VAF) index.

Results

The optimum number of components to fit the CATPCA model was six which explained 71.09% of the total variation. The first and most important component with VAF = 22.04% contained the demographic and socioeconomic characteristics of the killed pedestrians. The second-ranked component with VAF = 12.96% was related to the injury type. The third component with VAF = 10.56% was the severity of the injury. The fourth component with VAF = 9.07% was somehow related to the knowledge and observance of the traffic rules. The fifth component with VAF = 8.63% was about the quality of medical relief and finally, the sixth component with VAF = 7.82% dealt with environmental conditions.

Conclusion

CATPCA revealed hidden patterns among the fatally injured pedestrians in the form of six components. The revealed patterns showed that some interactions between correlated features led to a higher mortality rate.

Exploratory Analysis of Pedestrian Road Trauma in Finland

In Finland, all fatal on-road and off-road motor vehicle crashes are subject to an in-depth investigation coordinated by the Finnish Crash Data Institute (OTI). This study presents an exploratory and two-step cluster analysis of fatal pedestrian crashes between 2010 and 2019 that were subject to in-depth investigations. In total, 281 investigations occurred across Finland between 2010 and 2019. The highest number of cases were recorded in the Uusimaa region, including Helsinki, representing 26.4% of cases. Females (48.0%) were involved in fewer cases than males; however, older females represented the most commonly injured demographic. A unique element to the patterns of injury in this study is the seasonal effects, with the highest proportion of crashes investigated in winter and autumn. Cluster analysis identified four unique clusters. Clusters were characterised by crashes involving older pedestrians crossing in low-speed environments, crashes in higher speed environments away from pedestrian crossings, crashes on private roads or in parking facilities, and crashes involving intoxicated pedestrians. The most common recommendations from the investigation teams to improve safety were signalisation and infrastructure upgrades of pedestrian crossings, improvements to street lighting, advanced driver assistance (ADAS) technologies, and increased emphasis on driver behaviour and training. The findings highlight road safety issues that need to be addressed to reduce pedestrian trauma in Finland, including provision of safer crossing facilities for elderly pedestrians, improvements to parking and shared facilities, and addressing issues of intoxicated pedestrians. Efforts to remedy these key issues will further Finland’s progression towards meeting Vision Zero targets while creating a safer and sustainable urban environment in line with the United Nations sustainable development goals.

Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas

Pedestrian safety is becoming a global concern and an understanding of the contributing factors to severe pedestrian crashes is crucial. This study analyzed crash data for San Antonio, TX, over a six-year period to understand the effects of pedestrian–vehicle crash-related variables on pedestrian injury severity based on the party at fault and to identify high-risk locations. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian crashes. High-risk locations were identified through heat maps and hotspot analysis. A failure to yield the right of way and driver inattention were the primary contributing factors to pedestrian–vehicle crashes. Fatal and incapacitating injury risk increased substantially when the pedestrian was at fault. The strongest predictors of severe pedestrian injury include the lighting condition, the road class, the speed limit, traffic control, collision type, the age of the pedestrian, and the gender of the pedestrian. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. Resource allocation to high-risk locations, a reduction in the speed limit, an upgrade of the lighting facilities in high pedestrian activity areas, educational campaigns for targeted audiences, the implementation of more crosswalks, pedestrian refuge islands, raised medians, and the use of leading pedestrian interval and hybrid beacons are recommended.

An investigation of urban pedestrian behaviour in Bangladesh using the Perceptual Cycle Model

In Bangladesh, pedestrians remain the most neglected road user group in terms of research and safety measures, even though they are involved in nearly 50% of all fatal collisions. In the Dhaka metropolitan area, this statistic rises to around 65%. To reduce the recurrence of such collisions, it is necessary to understand the underlying thought processes of pedestrians, and how pedestrians interact with different road users, particularly when crossing the road. This study contributes to knowledge through the analysis of verbal data from 46 pedestrians, framed in terms of the Perceptual Cycle Model, where cognitive processes are described in terms of three categories: schema (mental templates), action (doing things), and world (environmental information). Concurrent verbal reports were provided by participants while they negotiated a busy area of mixed traffic in the centre of Dhaka city. The analysis revealed some of the factors that affected decision-making (for road crossing behaviour) at the different road sections. Many external factors (e.g., street sellers, rubbish blocking the path, lack of shade and poor pavement condition) prevented the pavement from being used and contributed to riskier road crossing behaviour. Some safety implications and related recommendations are presented.

Fuzzy analysis of students' perception of traffic safety in school environments: the case of a small Brazilian city

Thousands of lives are lost every year due to traffic accidents worldwide, and youths are the most affected. The goal of this paper is to analyze the differences in young students' perceptions about traffic safety in school surroundings in order to help in the formulation of public policies and the development of infrastructure to make school travels safer. A questionnaire was used to obtain the perception of high school students from institutions with different urban characteristics. Data modelling with fuzzy logic and statistical analysis of variance indicated that students' perceptions are influenced by the different realities these youths are exposed to daily, such as school socioeconomic category, transport mode, urban environment and gender. Traffic engineering measures, public policies and road safety education action, inciting active mobility, can be validated and supported by these results. This road safety analysis may also be a participative alternative for locations with low data access.

Systems Engineering Information Model of Vehicle-Pedestrian Collisions

Engineering analysis of motor vehicle collisions as a complex type of research combines the application of scientific approaches from different fields: mechanics, mathematics, structural design, etc. This implies accurate and unambiguous determination of input data and their application in computational procedures for finding solutions in iterative mode. Hence, the reason to apply the specific research method of information modelling in the present study to one of the main types of road accidents, namely the pedestrian-car collision.

Identify the key characteristics of pedestrian collisions through in-depth interviews: a pilot study

This study aimed to assess the feasibility of recruiting injured pedestrians from the emergency department of a major trauma centre, using an in-depth interview shortly post collision. Convenience sampling was used to prospectively recruit injured pedestrians from the Alfred Hospital Emergency and Trauma Centre. Of the 102 injured pedestrians, 39 met eligibility criteria and of these, 30 (77%) consented and completed the questionnaire. Over half of the collisions occurred at an intersection (57%), and of these the most common pre-impact vehicle manoeuvre was a vehicle turning into the street the pedestrian was crossing. In-depth interview during the early post-crash period was a feasible and effective method of collecting detailed data in an accessible sample. However, only 38% of patients met eligibility criteria. To enhance representativeness, supplementing interview data with police-reported crash data, recruiting from hospital wards and crash location assessment is recommended.

Factors affecting pedestrian behaviors at signalized crosswalks: An empirical study

INTRODUCTION

Safety of pedestrians depends, among other factors, on their behavior while crossing the road. This study aims to assess behaviors of pedestrians at signalized crosswalks.

METHOD

Following a literature review and a pilot study, 25 vital pedestrian crossing factors and behaviors were determined. Then data was randomly collected for 708 pedestrians at 10 lighted crossings in Sharjah (UAE), five at road intersections and five mid-block crossings.

RESULTS

Results indicated that 17.4% of pedestrians observed crossed partly or fully on red and that crossing speed was 1.22 m/s, on the average, which is slightly faster than most speeds recorded in the literature. Moreover, female pedestrians were more likely to cross while chatting with others, less likely to cross on red, and more likely to walk slower than male pedestrians. Results also showed that pedestrians who crossed at road intersections walked slower than those who crossed at mid-block crossings. It was also found that longer red pedestrian times and narrower roads tended to encourage pedestrians to cross on red and that the majority of pedestrians did not look around before crossing.

PRACTICAL IMPLICATIONS

Use of the Health Belief Model for pedestrian safety are discussed.

A joint probability model for pedestrian crashes at macroscopic level: Roles of environment, traffic, and population characteristics

Road safety is a major public health issue, with road crashes accounting for one-fourth of all documented injuries. In these crashes, pedestrians are more vulnerable to fatal and/or severe injuries than car occupants. Therefore, it is necessary to have a better understanding of the relationship between pedestrian crashes and possible influencing factors, including road environment, traffic conditions, and population characteristics. In conventional studies, separate prediction models were established for pedestrian crashes and other crash types, which could have ignored possible correlations among the different crash types. Additionally, these influencing factors can contribute to pedestrian crashes in two manners, i.e., contributing to crash occurrence and propensity of pedestrian involvement. Furthermore, extensive pedestrian count data were generally not available, affecting the estimation of pedestrian crash exposure. In this study, a joint probability model is adopted for the simultaneous modeling of crash occurrence and pedestrian involvement in crashes; effects of possible influencing factors, including land use, road networks, traffic flow, population demographics and socioeconomics, public transport facilities, and trip attraction attributes, are considered. Additionally, trip generation and pedestrian activity data, based on a comprehensive household travel survey, are used to determine pedestrian crash exposure. Markov chain Monte Carlo full Bayesian approach is then applied to estimate the parameters. Results indicate that crash occurrence is correlated to traffic flow, number of non-signalized intersections, and points of interest such as restaurants and hotels. By contrast, population age, ethnicity, education, household size, road density, and number of public transit stations could affect the propensity of pedestrian involvement in crashes. These findings indicate that better design and planning of built environments are necessary for safe and efficient access for pedestrians and for the long-term improvement of walkability in a high-density city such as Hong Kong.

"My right to walk, my right to live": pedestrian fatalities, roads and environmental features in Benin

Background

The implementation of road safety interventions in many developing countries usually focuses on the behavior of users. In order to draw more attention on the role of road infrastructure and physical environment in road safety interventions, this study aims to analyze the environmental and road factors associated with the pedestrians involved in traffic crashes in Benin.

Method

The method used was an analysis of national road crash statistics for the period 2008 to 2015. The information available included the circumstances surrounding the collision, the road infrastructure, the vehicles and the individuals involved. A multiple logistic regression was used to identify predictors of pedestrian mortality in traffic crashes.

Results

During the period studied, 3760 crashes involved at least one pedestrian. The death rate among these pedestrians was 27.74% (CI 95%: 26.31–29.20). The mortality predictors were the area in which the crash occurred (OR = 4.94; CI 95%: 4.10–5.94), the day of the crash (OR = 2.17; CI 95%:1.34–3.52), light levels (OR = 1.30; CI 95%: 1.06–1.59), road classification (OR = 1.79; CI 95%: 1.46–2.20), the condition of the road surface (2.04, CI 95%: 1.41–2.95) and the position of the pedestrian during the crash (OR = 1.69; CI 95%: 1.19–2.38).

Conclusions

These results support the need for a holistic approach to interventions aiming to tackle deaths on roads. Interventions should integrate environmental factors for greater pedestrian safety around roads with appropriate signs, roads in good condition and awareness campaigns for a proper use of road infrastructures.

Promoção de Comportamento Seguro no Trânsito: Relato de uma Intervenção

Resumo Este artigo objetiva relatar uma intervenção em Psicologia do Trânsito, visando conscientizar jovens estudantes sobre aspectos importantes do trânsito que estão envolvidos no cotidiano. O projeto “Meu Primeiro Certificado UFPR” foi elaborado como projeto piloto para implementação durante a Feira de Profissões da Universidade Federal do Paraná, desenvolvendo quatro temáticas: o pedestre e uso do celular; cinto de segurança; mobilidade com a bicicleta; e entrar no carro com motorista alcoolizado. Estandes com os temas foram montados em pontos estrategicamente distribuídos na feira. Ao entrar na feira, os estudantes recebiam um material já no primeiro estande; ao visitarem os outros quatro estandes, recebiam carimbos de presença em cada um; e, ao final da feira, o estudante recebia um certificado mediante a apresentação do cartão carimbado. Ao todo, o projeto alcançou diretamente 2674 estudantes de Ensino Médio, 68,7% adolescentes mulheres. Os participantes tinham entre 14 e 19 anos (M = 16,59). Do total de jovens, 72,3% estudam em escola pública. Concluiu-se que a aplicação do piloto foi relevante, uma vez que houve grande alcance do público-alvo, que demonstrou interesse em visitar os estandes e dialogar sobre as temáticas apresentadas. O projeto foi bem avaliado pelos participantes, a maioria (75%) classificando-o como excelente.

Towards activity-based exposure measures in spatial analysis of pedestrian-motor vehicle crashes

BACKGROUND

Although numerous efforts have been devoted to exploring the effects of area-wide factors on the frequency of pedestrian crashes in neighborhoods over the past two decades, existing studies have largely failed to provide a full picture of the factors that contribute to the incidence of zonal pedestrian crashes, due to the unavailability of reliable exposure data and use of less sound analytical methods.

METHODS

Based on a crowdsourced dataset in Hong Kong, we first proposed a procedure to extract pedestrian trajectories from travel-diary survey data. We then aggregated these data to 209 neighborhoods and developed a Bayesian spatially varying coefficients model to investigate the spatially non-stationary relationships between the number of pedestrian-motor vehicle (PMV) crashes and related risk factors. To dissect the role of pedestrian exposure, the estimated coefficients of models with population, walking trips, walking time, and walking distance as the measure of pedestrian exposure were presented and compared.

RESULTS

Our results indicated substantial inconsistencies in the effects of several risk factors between the models of population and activity-based exposure measures. The model using walking trips as the measure of pedestrian exposure had the best goodness-of-fit. We also provided new insights that in addition to the unstructured variability, heterogeneity in the effects of explanatory variables on the frequency of PMV crashes could also arise from the spatially correlated effects. After adjusting for vehicle volume and pedestrian activity, road density, intersection density, bus stop density, and the number of parking lots were found to be positively associated with PMV crash frequency, whereas the percentage of motorways and median monthly income had negative associations with the risk of PMV crashes.

CONCLUSIONS

The use of population or population density as a surrogate for pedestrian exposure when modeling the frequency of zonal pedestrian crashes is expected to produce biased estimations and invalid inferences. Spatial heterogeneity should also not be negligible when modeling pedestrian crashes involving contiguous spatial units.

Urban road space allocation incorporating the safety and construction cost impacts of lane and footpath widths

INTRODUCTION

Walkability continues to attract great attention from urban planners, designers, and engineers as they recognize not only the merits of pedestrian facilities in terms of the health benefits but also their demerits in terms of accident risk to pedestrians. Wide footpaths improve the pedestrian environment and experience, and thereby motivate travelers to walk as much as possible. However, if footpaths are too wide, they may leave a smaller space for the roadway. On the other hand, wide road lanes may lead to higher road vehicle safety but are costly to construct and maintain and also may leave little space for the footpath. Evidently, for a fixed urban space, what is needed is an optimal balance between the vehicle lane and pedestrian path. This problem is encountered routinely in dense cities including Hong Kong where land availability is severely limited.

METHOD

To address the issue, this paper first establishes safety performance functions (SPFs) for the pedestrian space and the road space, using the random-parameter negative binomial regression. The results indicate the extent to which road lane and footpath width changes are associated with changes in in-vehicle occupant and pedestrian casualties. Then the paper uses the SPFs to develop a methodology for optimizing the width allocations to the road lanes and footpaths, duly considering the user (safety) costs and agency (construction) costs associated with each candidate allocation of the widths. Finally, the paper analyzes the sensitivity of the optimal solution to the relative weights of user cost and agency cost.

RESULTS

When user and agency costs are considered equally important, the optimal lane width is 5.4 m.

CONCLUSION

It is observed that the road space allocation ratio used by the Hong Kong road agency suggests that the agency places a higher weight to user cost compared to agency cost. Practical Application: The findings can help incorporate design-safety relationships, and the stakeholders (agency and users) perspectives in urban road and footpath design.

Characteristics of pedestrian injuries caused due to impacts with powered 2-wheelers in India

Objective: This study aims to understand the nature, severity, and sources of injuries sustained by pedestrians involved in crashes with powered 2-wheelers (PTWs) in India. Further, it aims to understand the pedestrian injury pattern and injury mechanism based on the pedestrian contact location on the PTW. Methods: Eight years of field data from the Road Accident Sampling System-India (RASSI) database were considered for the study. Analyses were performed using both weighted and unweighted RASSI data. A sample of 57 crashes between pedestrians and PTWs was analyzed to determine the pedestrian injury characteristics, pedestrian orientation with PTW, and PTW contact zone (PCZ) or the pedestrian contact location on PTW. The PCZs were classified into 3 types. The risk of sustaining a Maximum Abbreviated Injury Scale (MAIS) injury to the head and pedestrian injury mechanism across the 3 PCZs was analyzed. Results: The results of both weighted and unweighted RASSI data were consistent. About 67% of pedestrians who were killed sustained MAIS 3+ head injuries and 52% of pedestrians with nonfatal injuries sustained MAIS 2+ lower extremity injuries. The risk of MAIS 3+/fatal head injury is notably higher (86%) for pedestrians struck from behind compared to pedestrians struck from the side (36%). Of the 3 PCZs, about 80% of the pedestrians contacting PCZ-1 (corner of the PTW front end) sustained fatal head injuries and only 5% contacting PCZ-2 (center of the PTW front end) sustained fatal head injuries. About 40% contacting PCZ-3 (combination of PCZ-1 and PCZ-2) sustained fatal head injuries. Of all AIS 3+ head injuries, 88% were associated with ground impacts. Of all AIS 2+ lower extremity injuries, 96% were associated with impacts to PTW front-end parts. Conclusions: The results show that head injuries account for most pedestrian fatalities in crashes with PTWs and lower extremity injuries account for most nonfatal injuries. Head injuries are associated with ground contacts and lower extremity injuries are associated with contacting PTW front-end parts. Pedestrians contacting the corner of the PTW are highly prone to MAIS 3+ head injuries, whereas pedestrians contacting the center of the PTW are less prone to MAIS 3+ head injuries. This difference is predominantly because of the varied injury mechanisms seen across PCZs.

The role of perceived pedestrian safety on designing safer built environments

OBJECTIVE

This study aimed to explore how pedestrians´ safety perception concerning the built environmental characteristics can assist in designing a safer built environment in an urban area in Mexico.

METHODS

The study involved two stages of data collection. In the first stage, a physical audit on selected urban roads was performed to assess the characteristics that may increase the perceived risk of a collision. An observational framework to evaluate the crossing areas, sidewalks and organizational factors was developed and used for data collection. In the second stage, an on-street questionnaire was applied to collect the perception of a group of 299 pedestrians about safety risks, road characteristics and their ideas for designing a safer built environment.

RESULTS

The physical road audit identified several features in the crossing areas and sidewalks, such as parked cars, movable and fixed obstacles, and lack of traffic signage, which may increase the risk of a pedestrian being involved in a collision. More than half of the road users who were interviewed either agree (27%) or strongly agree (29%) with the statement that crossing the roads in the area was safe. However, pedestrians also identified the following elements as detrimental for the safe use of roads: lack of traffic lights, too much traffic, lack of signs, and parked cars that obstruct visibility. Participants also raised issues beyond the physical infrastructure; for instance, a lack of respect shown by drivers to pedestrians. For designing a safer built environment, participants suggested several ideas highlighting pedestrianization of the road and widening the sidewalks, along with restricting parking of cars on the road.

CONCLUSIONS

This combination of findings provide valuable support for the premise that pedestrians may have a good sense of recognizing safety problems and the ability to see the solutions. Although the research was undertaken in the context of a municipality in Guadalajara, the role of pedestrian safety perception may be applicable in other urban settings in low and middle-income countries (LMICs), where local authorities are in charge of designing the road environment. This study highlights the relevance of including pedestrians' participation for a safer and human-centred design of our cities.

Development of systemwide pedestrian safety performance function using stratified random sampling and a proxy measure of pedestrian exposure

The lack of pedestrian counts at a systemwide level prompts the need to find other innovative ways of assessing pedestrian traffic crash risks using proxy measures of exposure. This study aims to formulate the methodology for developing pedestrian safety performance functions (SPF) using the proxy measure of pedestrian exposure and stratified random sampling. The case study was all urban intersections in Michigan State that comprise of collector and arterial roads. The stratified random sampling strategy was deployed to select the sample which is representative of all urban intersections in the state of Michigan. Factor analysis was used to develop a proxy measure of pedestrian exposure at urban intersections using a walkability measure (walk score), among other factors. The performances of various count models were compared using the goodness of fit measures based on the Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and Vuong test. The final pedestrian SPFs was formulated using the Zero-Inflated Poisson (ZIP) model with AADT at a major approach, AADT at the minor approach, and a proxy measure of pedestrian exposure. The proposed methodology in this study can benefit transportation agencies that have embarked on systemwide planning of pedestrian facilities to improve the safety of pedestrians but lack systemwide analytical tools and pedestrian counts to make data-driven decisions.