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Traffic accident prevention is considered one of the most crucial public safety issues due to the ongoing rise in traffic accidents. The installation of LED in-ground traffic lights is one strategy that has proven to be quite effective in preventing numerous traffic accidents, notably pedestrian accidents. The traffic signal helps reduce accidents for pedestrians, but there is a drawback in that such installations may lead to cognitive errors, such as the driver making a mistaken start or stop. Therefore, it is crucial to validate cognitive errors in advance of the widespread adoption of LED in-ground traffic signals. To this end, in this study, we (i) built an experimental environment that can be employed for various traffic tests using digital twins and virtual simulators; (ii) designed test scenarios and measurement plans for validation to conduct a validation test, and (iii) demonstrated cognitive errors through data from various experiments. As a result, it was proven that there is a possibility that the LED in-ground traffic lights may cause cognitive errors for drivers, and the causes of this were analyzed. In the future, this framework can be used to demonstrate various transportation problems and can contribute to improving the quality of public safety. [ABSTRACT FROM AUTHOR]

Machine learning currently holds a vital position in predicting collision severity. Identifying factors associated with heightened risks of injury and fatalities aids in enhancing road safety measures and management. Presently, Thailand faces considerable challenges with respect to road traffic accidents. These challenges are particularly acute in industrial zones, where they contribute to a rise in injuries and fatalities. The mixture of heavy traffic, comprising both trucks and non-trucks, significantly amplifies the risk of accidents. This situation, hence, generates profound concerns for road safety in Thailand. Consequently, discerning the factors that influence the severity of injuries and fatalities becomes pivotal for formulating effective road safety policies and measures. This study is specifically aimed at predicting the factors contributing to the severity of accidents involving truck and non-truck collisions in industrial zones. It considers a variety of aspects, including roadway characteristics, underlying assumptions of cause, crash characteristics, and weather conditions. Due to the fact that accident data is big data with specific characteristics and complexity, with the employment of machine learning in tandem with the Multi-variate Adaptive Regression Splines technique, we can make precise predictions to identify the factors influencing the severity of collision outcomes. The analysis demonstrates that various factors augment the severity of accidents involving trucks. These include darting in front of a vehicle, head-on collisions, and pedestrian collisions. Conversely, for non-truck related collisions, the significant factors that heighten severity are tailgating, running signs/signals, angle collisions, head-on collisions, overtaking collisions, pedestrian collisions, obstruction collisions, and collisions during overcast conditions. These findings illuminate the significant factors influencing the severity of accidents involving trucks and non-trucks. Such insights provide invaluable information for developing targeted road safety measures and policies, thereby contributing to the mitigation of injuries and fatalities. [ABSTRACT FROM AUTHOR]

The need for continuous research to refine the models used in forensic accident reconstruction appears with the development of new car models that satisfy consumer complaints. This paper analyzed a sub-sequence of car and pedestrian accidents from the perspective of the distance traveled by them in the contact phase with the aim of improving the information regarding the reconstruction of road accidents. This research included the analysis of some real tests with pedestrian dummies, as well as simulations of the impact between different classes of vehicles and pedestrians in two different walking positions. Specialized software was used with complex multibody models of pedestrians, modifying the speed and deceleration parameters of the car at the time of the collision. For pedestrian characteristics, the friction coefficients of the ground, car and its mass were modified. The research results highlight the differences between the bilinear models used in accident reconstruction and the proposed study. They can also be used to determine the distance traveled by the vehicle in the first phase of a collision with pedestrians. [ABSTRACT FROM AUTHOR]

A rectangular rapid flashing beacon (RRFB) is a pedestrian crosswalk countermeasure system that cautions drivers by providing them with real-time warning about the presence of pedestrians in an upcoming crosswalk. This paper investigated the safety effectiveness of existing RRFBs installed in the state of Florida between 2013 and 2018. Additionally, traffic volume, roadway characteristics, and land-use mix were included as explanatory variables. The study evaluated 154 treated sites with RRFB installations and 158 control sites with similar characteristics. Safety performance functions (SPF) were developed, and crash modification factors (CMF) were calculated using the empirical Bayes (EB) methodology for various crash types. A CMF of 0.31 for total pedestrian crashes was estimated, showing that RRFBs have the potential to reduce 69% of total pedestrian-involved crashes. CMF for total vehicular crashes and rear-end crashes were also investigated to ascertain whether RRFBs have adverse effects on rear-end crashes. CMF for total vehicular crashes was found to be 1.14, showing that RRFBs do not have positive effect in reducing total vehicular crashes. Similarly, it was observed that CMF for the rear-end crashes was 1.11, indicating RRFBs might have adverse effect on rear-end crashes because vehicles needs to slow down or stop due to the presence of pedestrians. CMFunctions for significant variables for pedestrian, rear-end, and total crash models were also estimated in this study. An economic analysis indicated that the implementation of RRFBs will yield a benefit to cost ratio (calculated over 3 years) of approximately 85.5 with a 4% discount rate. [ABSTRACT FROM AUTHOR]

Objective: To determine the effectiveness of structural-level environmental interventions on the changes in PA levels in the populations examined. Methods: Natural experiments that involve environmental intervention with structural modification were included. The primary outcome PA levels with consideration of both objective and subjective measurements. An electronic search was carried out in Medline/Pubmed, SCIENCE DIRECT, WEB OF SCIENCE, and CINAHL up to January 2022. Two reviewers screened titles and abstracts, selected studies, extracted relevant data, and examined study quality. A qualitative synthesis was performed. Results: Twenty-six articles were included. The structural-level environmental interventions included 4 fundamental areas: schools, work environments, streets or cities, and neighborhoods or parks. Of the 26 studies, 21 examined outdoor environments like parks, cities, pedestrian walkways, or steps, while 5 examined indoor or closed environments like schools and workplaces revealing that structural-level environmental interventions improve PA levels with the greatest effect in parks and active transportation. A risk of bias is inherent in natural experiments which is a limitation of this study. In schools and work areas, there is evidence of both decrease in sedentary time and an increase in PA related to environmental modifications. Conclusion: Structural-level environmental modifications in parks and active transportation demonstrated greater effects in promoting PA. Environmental modifications can impact physical activity in the population. Given that the economic and cultural setting is a key variable when considering the effectiveness of structural interventions, and since only 1 of the 26 reviewed articles included such data, more studies examining economic factors are needed especially in low- and middle-income countries like in South America. Trial registration: PROSPERO CRD42021229718. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In Austria around 100 trams are involved in accidents with pedestrians every year. Since the service lives of trams are very high, the probabilities are also high that each tram on the network will be involved in an accident of this kind at least once, highlighting the need of protective designs of tram fronts. However, due to lack of studies in this area, this is still a challenging task. Purpose: The aim of this study is to show the applicability and the usability of virtual testing involving HBMs in tram front design studies to improve passive safety in general. Methodology: In this study, the impact of pedestrians with a tram was investigated using a generic tram front model in a basic version and a conceptually improved version, respectively, and detailed finite element human body models (HBM). To consider gender-differences and to avoid designs that unintentionally favour only particular groups of the population, the study simulations were carried out with a male and a female 50th percentile finite element human body model (VIVA+). The risk for head, chest, femur and tibia injuries were analysed as the simulation result, since these body areas were identified based on field data to be most relevant in accidents involving pedestrians and trams. Collision scenarios are evaluated for a wide parameter variation in impact location and speed, respectively. Findings: The results show a reduction in head injury risk for both the female and the male HBM at different speeds and impact locations for impact with the enhanced version of the tram front. Depending on the gender of the HBM, the considered improvement shows different effects for each body region, with a greater reduction in the likelihood of head injury for the female model, and a greater reduction in the likelihood of thoracic injury for the male model. These differences are due to the considered anthropomorphic variations. A reduction for the risk of femur injuries can be achieved in all cases using the modified tram front. The study showcases the application of detailed human body models for tram pedestrian impact analyses in the context of pedestrian safety and in particular for tram front improvements. It was shown that even a minor modification of the tram front with softer front skirt attachments leads to remarkable benefits with respect to injury criteria in all investigated crash scenarios. The presented research goes beyond current technical recommendations and shows the benefit of virtual testing including HBMs and considering a wide variety of impact speeds, anthropometries and injury assessments, respectively. [ABSTRACT FROM AUTHOR]

There are many visually impaired people globally, and it is important to support their ability to walk independently. Acoustic signals and escort zones have been installed on pedestrian crossings for the visually impaired people to walk safely; however, pedestrian accidents, including those involving the visually impaired, continue to occur. Therefore, to realize safe walking for the visually impaired on pedestrian crossings, we present an automatic sensing method for pedestrian crossings using images from cameras attached to them. Because the white rectangular stripes that mark pedestrian crossings are aligned, we focused on the edges of these rectangular stripes and proposed a novel pedestrian crossing sensing method based on the dispersion of the slope of a straight line in Hough space. Our proposed method possesses unique characteristics that allow it to effectively handle challenging scenarios that traditional methods struggle with. It excels at detecting crosswalks even in low-light conditions during nighttime when illumination levels may vary. Moreover, it can detect crosswalks even when certain areas are partially obscured by objects or obstructions. By minimizing computational costs, our method achieves high real-time performance, ensuring efficient and timely crosswalk detection in real-world environments. Specifically, our proposed method demonstrates an impressive accuracy rate of 98.47%. Additionally, the algorithm can be executed at almost real-time speeds (approximately 10.5 fps) using a Jetson Nano small-type computer, showcasing its suitability as a wearable device. [ABSTRACT FROM AUTHOR]

The treatment and analysis of accidents involving heavy transport vehicles and pedestrians include the identification and treatment of a certain number of factors that may differ from the cases of passenger vehicle-pedestrian accidents. The aim of this paper is to develop a new model with better performance for speed estimation and reconstruction of accidents involving heavy vehicles and pedestrians. In a large number of cases during the research, it was observed that the experts used the same models for passenger vehicles as for transport vehicles. Likewise, a number of factors that have an impact on heavy vehicle accidents with pedestrians are not included as factors that have an impact on other accidents. The newly developed model, which has better performance than other models, can help experts in the case of analysis, speed determination, and reconstruction of accidents involving heavy vehicles and pedestrians. The model describes more than 94% of the most influential factors in the model (R2 = 0.945). This model will provide a novel way to examine crashes involving heavy vehicles and pedestrians, generating highly precise results for speed calculation which can be used to recreate the technical aspects of the accident. Additionally, it will help specialists in the field when preparing their expert opinion, specifically when heavy vehicles and pedestrians are involved, by providing a model which is different from the standard approach and yields more reliable outcomes. [ABSTRACT FROM AUTHOR]

In this study, we aim to identify social typologies of pedestrian crashes considering demographics, health impacts, involved vehicle, temporality of the collision, and place of impact in Hermosillo, Mexico. A socio-spatial analysis was performed by using local urban planning information and vehicles-pedestrian crashes records collected by the police department (N = 950) between 2014 and 2017. Multiple Correspondence Analysis and Hierarchical Cluster Analysis were used to determine typologies. Geographical distribution of typologies was obtained with spatial analysis techniques. The results suggest there are four typologies, which portray the physical vulnerability of pedestrians, which reflect the vulnerability to collisions associated to the variables age, gender, and street speed limits. Findings show that children are more likely to be injured during weekends in residential zones (Typology 1), while older females are more likely to be injured during the first three days of the week (Monday – Wednesday) in the downtown area (Typology 2). Injured males during the afternoon in arterial streets represented the most frequent cluster (Typology 3). Also, males were likely to be severely injured by heavy trucks during nighttime in peri-urban areas (Typology 4). These findings indicate that vulnerability and risk exposure vary according to the type of pedestrian involved in the crash, which are linked to the types of places they visit. The design of the built environment plays a major role in the number of pedestrian injuries particularly when it favors motor vehicles over pedestrians or non-motorized vehicles. Because traffic crashes are considered preventable events, cities must embrace a diversity of mobility modes and incorporate the appropriate infrastructures that safeguard the lives of all their travelers, especially pedestrians. [ABSTRACT FROM AUTHOR]

Traffic accidents are mainly caused by driver-to-pedestrian collisions or driver-to-driver collisions. Prosocial driving behavior indicates that drivers exhibit altruistic behavior toward other drivers on roads. Yielding behavior demonstrates that drivers grant the right of passage to pedestrians at unsignalized crossings, while yielding attitude presents the subjective emotional and cognitive inclination to yield to pedestrians at unsignalized crossings. This study aims to explore the effect of altruism and drivers' perceived stress on prosocial driving behavior, yielding behavior, and yielding attitude. In addition, we endeavor to explore the effect of stress on prosocial driving behavior exhibiting an inverted "U-type" curve as Yerkes-Dodson's law suggests and test the moderating role of perceived stress on altruism and prosocial driving behavior/yielding behavior/yielding attitude. Using a survey method, we asked 454 participants to complete an altruism scale from the IPIT measuring altruism, a Perceived Stress Scale-10 measuring drivers' perceived stress, a prosocial driving scale from the PADI measuring prosocial driving behavior, and items on yielding behavior and yielding attitude. Then, a correlational matrix, a hierarchical multiple nonparametric regression analysis, and a moderating analysis of perceived stress were employed in sequence to reach our objective. The hierarchical multiple nonparametric regression analysis showed that altruism positively predicts yielding attitude (F = 41.56, p < 0.001), yielding behavior (z = 8.46, p < 0.001, odds ratio = 4.90) and prosocial driving behavior (F = 110.66, p < 0.001), but stress predicts only prosocial driving behavior (F = 7.63, p < 0.001), not yielding attitude (F = 0.51, p > 0.05) or yielding behavior (z = 0.12, p > 0.05), which exhibits an inverted "U-type" curve. Moderating analyses showed that stress only moderates the relationship between altruism and yielding attitude (B = −0.24, t = −2.62, p < 0.01). Altruism is positively related to prosocial driving behavior, yielding behavior, and yielding attitude. Stress influences prosocial driving behavior only and exhibits an inverted "U-type" curve. Stress does not directly influence the yielding behavior. Instead, stress moderates the relationship between altruism and yielding attitude only and may further increase the possibility of yielding behavior. [ABSTRACT FROM AUTHOR]

This paper develops a pedestrian potentially dangerous behaviour prediction method based on attention‐long‐short‐term memory (Attention‐LSTM) architecture to predict pedestrian trajectory and intention for the unexpected pedestrian crossing accident avoidance. To extract the road scene information for short periods of time, and improve the accuracy of subsequent intention inference and trajectory prediction, the panoramic segmentation is used to extrapolate pedestrian instances and segment areas of the environment. Next, an encoder–decoder framework based on Attention‐LSTM model is proposed to infer a pedestrian's intention to run or walk out into oncoming traffic straight and to predict the future trajectory. The proposed network involves two parts: temporal feature encoder and multi‐task decoder. The temporal feature encoder is mainly used to selectively emphasize the temporal features using attention mechanism, and then LSTM is employed for its encoding. In the multi‐task decoder, a multi‐head self‐attention mechanism and LSTM are used to forecast the pedestrians' intention and future trajectory, respectively. Extensive experiments on pedestrian intention estimation (PIE) datasets demonstrate that the authors' proposed approach surpasses prior studies in terms of prediction accuracy in trajectory and intention. This study can not only effectively avoid serious accidents caused by illegal road crossing but also achieve early warning for collision avoidance. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) CFD model was developed, covering a square area of 3.64 km2 and comprising the Holy Mosque near its center, the actual terrain, and the main surrounding buildings. The gust wind effects on the existing cranes and the collapsed tower crane in 2015, the comfort of the pedestrians, and the air quality were studied for the first time in this area. The air quality was related to calm speed, accelerating the spreading of infectious diseases. The wind comfort levels were achieved in all selected locations. The wind speeds are generally low in the area. However, gusting wind currents appeared from limited directions, causing increments in wind speeds up to 30% and causing the tower crane to collapse. Therefore, finalizing work on some cranes is recommended soon, lowering the crane boom and stopping working on windy days or changing their places. The air quality in some sites may be relatively poor, such as at the lower terraces level. New tall buildings surrounding the mosque from the north and the east are not recommended unless studying their impacts on the air quality. Pruning north and east mounts can remarkably improve natural ventilation. Large-scale fans are another solution after a detailed simulation study. [ABSTRACT FROM AUTHOR]

Injuries caused by road traffic have become the leading cause of death in people aged 5 to 29 years, with pedestrians and cyclists being disproportionately affected. Research has demonstrated age and sex differences in road accidents in European populations. The purpose of this study was to determine age and sex-specific differences in pedestrian and cyclist accidents involving passenger cars at a single Level 1 Trauma Center in a major US metropolitan area. We performed a retrospective chart review of 1,845 patients that presented to a single level 1 trauma center from January 1, 2016 - October 1st, 2021, and were involved in a motor vehicle vs. pedestrian or motor vehicle vs. cyclist accidents. Demographics, injury pattern, abbreviated injury scores (AIS), and hospital stay were analyzed, and the data was stratified by pedestrian vs. cyclist, biological sex, and race. Chi square analysis, t tests, and binomial logistic regression was used to examine sex and age-based differences. Pedestrian vs. motor vehicle collisions (N = 1359, 74%) occurred more frequently than cyclists (N = 475, 26%) with an overall mortality rate of 6%. The mean age of pedestrians and cyclists was 39 and 42 years of age, respectively. Overall, more female than male patients had hand (mean=0.05 vs. 0.02) (p = 0.03) and pelvis fractures (mean 0.28 vs. 0.19) (p = 0.007). Females had a 1.2 times higher likelihood of getting a pelvis fracture than males (95% CI, 1.06 to 1.43). Linear regression analysis found a statistically significant relationship between older age and increased AIS severity (p <.001). Half of our sample consisted of Black patients (49.6% Black vs. 42.1% white). Female pedestrians and cyclists are at increased risk of obtaining pelvis fractures when in a traumatic road accident than males, regardless of age stratification, and age is a predictor of injury severity. Our study also found that race-based differences exist, with Black patients being injured more frequently. Further research is needed to better understand demographics at risk for traumatic road accidents, as well as evaluation of city infrastructure for biking and walking. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 disease has given rise to various negative effects on human life in terms of health and economic and social well-being. We believe that these negative effects may have led to increased forensic incidents such as violence and suicide. Therefore, in this study, we sought to examine the effects of COVID-19 in forensic cases admitted to an emergency department. Methods: This is a retrospective observational study, performed at the emergency department of Fatih Sultan Mehmet Education and Research Hospital. Forensic cases admitted between March and June 2020 (pandemic period) and forensic cases admitted between March and June 2019 (pre-pandemic period) were compared in the study. Results: A total of 4296 patients were included in the study, of which 3011 were admitted during the pre-pandemic period and 1285 during the time of the COVID-19 pandemic. While the percentages of suicide attempts (3.6%), motorcycle traffic accidents (7.4%), and violent incidents (29.4%) were higher during the pandemic period, the percentages of in-vehicle traffic accidents (5.4%) and pedestrian traffic accidents (2.2%) were lower (respectively, p = 0.035, p = 0.005, p < 0.001, p = 0.015, p = 0.008). At the time of the pandemic, the percentages of incidents of violence against women (44.2%) and traffic accidents with a motorcycle involving men (9.3%) were higher than during the time before the pandemic (p < 0.001 and p < 0.001, respectively). Conclusions: The effects of the pandemic on our lifestyle are indisputable. This study reveals that the pandemic also affected patients who were admitted to the emergency department for forensic reasons. In addition, the increase in the percentages of suicide and violent events indicates that pandemics probably increase feelings of fear, loss, and hopelessness, and special precautions should be taken to maintain order in the society. [ABSTRACT FROM AUTHOR]

• The U.S. food supply chain, from manufacturer to retailer, is a relatively hazardous occupation for workers, with higher morbidity and mortality rates versus other industries. • Employees in food manufacturing, wholesaling, and even retailing experience relatively high numbers of occupational injuries and fatalities. One reason for the high hazard rates may be the reliance on a synergistic packaging system designed to load and transport food products within and between manufacturers, wholesalers, and retailers. • This paper examined severe injuries related to the packaging and movement of food products in segments of the food and beverage supply chain from manufacturing to retailing. We used an OSHA database to investigate all severe injuries in the six years from 2015 to 2020. • Results show there were 1,084 severe injuries and 47 fatalities during the six-year period. Fractures of the lower extremities were most prevalent, with the most frequent event type being transportation-related such as pedestrian-vehicle incidents. Significant differences were seen in the three parts of the food supply chain. The paper discusses how pressure from various parts of the food supply chain may be increasing risks for workers. Introduction : The modern food supply chain presents unique hazards to employees that result in higher morbidity and mortality rates versus other industries. Employees in food manufacturing, wholesaling, and even retailing experience relatively high numbers of occupational injuries and fatalities. One reason for the high hazard rates may be the reliance on a synergistic packaging system designed to load and transport food products within and between manufacturers, wholesalers, and retailers. Packaged food products are often aggregated using palletizers before they can be transported by forklifts and pallet jacks. Materials handling within facilities is critical to the efficient functioning of all members of the food-related supply chain, but product movement can be a source of occupational injuries. No previous research has examined the cause and result of such hazards. Method: This paper aims to examine severe injuries related to the packaging and movement of food products in segments of the food and beverage supply chain from manufacturing to retailing. An OSHA database was used to investigate all severe injuries in the six years from 2015 to 2020. The focus was on the food supply chain for the period since OSHA began mandating new reporting procedures for severe injuries. Results: Results show there were 1,084 severe injuries and 47 fatalities during the six-year period. Fractures of the lower extremities were most prevalent, with the most frequent event type being transportation-related such as pedestrian-vehicle incidents. Significant differences were seen in the three parts of the food supply chain. Practical Applications: Implications are drawn for key sectors of the food-related supply chain to reduce packaging- and product movement-related hazards. [ABSTRACT FROM AUTHOR]

This paper introduces a protocol for the verification of multi-physics wildfire evacuation models, including a set of tests used to ensure that the conceptual modelling representation of each modelling layer is accurately implemented, as well as the interactions between different modelling layers and sub-models (wildfire spread, pedestrian movement, traffic evacuation, and trigger buffers). This work presents a total of 24 verification tests, including (1) 4 tests related to pedestrians, (2) 15 tests for traffic evacuation, (3) 5 tests concerning the interaction between different modelling layers, along with 5 tests for wildfire spread and trigger buffers. The evacuation tests are organized in accordance with different core components related to evacuation modelling, namely Population, Pre-evacuation, Movement, Route/destination selection, Flow constraints, Events, Wildfire spread and Trigger buffers. A reporting template has also been developed to facilitate the application of the verification testing protocol. An example application of the testing protocol has been performed using an open wildfire evacuation modelling platform called WUI-NITY and its associated trigger buffer model k-PERIL. The verification testing protocol is deemed to improve the credibility of wildfire evacuation model results and stimulate future modelling efforts in this domain. [ABSTRACT FROM AUTHOR]

Copyright of Museologia e Patrimônio is the property of Museologia e Patrimonio and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• The present study demonstrates the danger posed by talking with passengers as a distracted driving factor on pedestrian crossing safety. • Talking with passengers near pedestrian crossing areas causes significant dysfunction in driving. • yielding behavior The most critical evasive maneuver is to change lanes while talking with passengers. • Drivers who talk with passengers are less likely to use evasive maneuvers to prevent pedestrian crashes. Talking with passengers while driving may impair driver performance. However, little is known about the extent to which this factor affects driver behavior. Since distracted driving accounts for most pedestrian accidents, the present study seeks to demonstrate the danger posed to pedestrian crossing safety by talking with passengers. Based on a real-world driving approach, the current study examines how talking with a passenger affects a driver's behavior when encountering pedestrians. A study of 41 participants' driving behavior at different locations was conducted, and 2,922 conflicts with pedestrians were coded according to four conditions (without or with passengers, and at marked crossings or at other locations). Using binary regression, it was found that this factor near pedestrian crossing areas causes significant dysfunction in driving yielding behavior. Distraction negatively affects driver-yielding behavior when drivers engage in speeding, resulting in a fivefold decrease in evasive maneuvers. In addition, a multinomial regression model indicated that drivers would reduce their evasive maneuvers by more than 60%, with lane changes accounting for most of these maneuvers. Also, the present study concluded that pedestrian crossing gaps should be at least two times larger when drivers converse with passengers than when they do not do so. This study may contribute to the development of legislation, policy, countermeasures, and future research aimed at reducing distracted driving. [ABSTRACT FROM AUTHOR]

• Zebra crossings are being installed at T-intersections in Victoria, Australia. • Counterintuitive rules mean the zebras could reduce walkability at a systems level. • A survey and interviews ascertained some risk of unintended consequences. • We recommend a rule to require drivers to give way to pedestrians at stop lines. • The repeal could reduce ambiguity and improve health and wellbeing via walkability. Local governments in Melbourne are installing zebra crossings at prioritised T-intersections within activity centres and neighbourhoods. These treatments are well-intentioned and meant to increase certainty for road users, to create a more equitable and safer mobility environment for pedestrians, and to work as one small part of an integrated approach to encourage walking for transport. However, there is complexity in, and poor knowledge of the road rules with which the treatment interacts: Drivers turning into such an intersection are already required to give way to pedestrians, while, somewhat counterintuitively for many road users, drivers turning out are not. As a result, there is a risk that the treatment may have systems level unintended negative consequences for walkability. This study used a community survey and a series of expert interviews to test this hypothesis. The results show that while zebra crossings at the terminating road of a T-intersection can eliminate the uncertainties implicated by the current version of the road rules at the sites in which they are installed, there is also a very real risk that their use at some but not all T-intersections could undermine walkability in the neighbourhoods in which they are used. A recommendation, supported by a recent UK precedent, to change the Victorian road rules to require car drivers to give way to pedestrians who are crossing the terminating road of T-intersections, is made. The change would standardise the rules for T-intersections to create a generalised and unambiguous duty for drivers to give way on turning. It would play a small part in facilitating walking for transport and in doing so would contribute to enhancing opportunities for incidental exercise and social interaction, both of which benefit health and are important aspects of liveability. [ABSTRACT FROM AUTHOR]

Pedestrian accidents contribute significantly to the high number of annual traffic casualties. It is therefore crucial for pedestrians to use safety measures, such as a crosswalk, and to activate pedestrian signals. However, people often fail to activate the signal or are unable to do so – those who are visually impaired or have occupied hands may be unable to activate the system. Failure to activate the signal can result in an accident. This paper proposes an improvement to crosswalk safety by designing a system that can detect pedestrians and trigger the pedestrian signal automatically when necessary. In this study, a dataset of images was collected in order to train a Convolutional Neural Network (CNN) to distinguish between pedestrians (including bicycle riders) when crossing the street. The resulting system can capture and evaluate images in real-time, and the result can be used to automatically activate a system such as a pedestrian signal. A threshold system is also implemented that triggers the crosswalk only when the positive predictions pass the threshold. This system was tested by deploying it at three real-world environments and comparing the results with a recorded video of the camera's view. The CNN prediction model is able to correctly predict pedestrian and cyclist intentions with an average accuracy of 84.96% and had an absence trigger rate of 0.037%. The prediction accuracy varies based on the location and whether a cyclist or pedestrian is in front of the camera. Pedestrians crossing the street were correctly predicted more accurately than cyclists crossing the street by up to 11.61%, while passing (i.e., non-crossing) cyclists were correctly ignored more than passing pedestrians, by up to 18.75%. Based on the testing of the system in real-world environments, the authors conclude that it is feasible as a back-up system that can complement existing pedestrian signal buttons, and thereby improve the overall safety of crossing the street. Further improvements to the accuracy can be achieved with a more comprehensive dataset for a specific location where the system is deployed. Implementing different computer vision techniques optimized for tracking objects should also increase the accuracy. [ABSTRACT FROM AUTHOR]

Pedestrian safety has been evaluated based on the mean number of pedestrian-involved collisions. Traffic conflicts have been used as a data source to supplement collision data because of their higher frequency and lower damage. Currently, the main source of traffic conflict observation is through video cameras that can efficiently gather rich data but can be limited by weather and lighting conditions. The utilization of wireless sensors to gather traffic conflict data can augment video sensors because of their robustness to adverse weather conditions and poor illumination. This study presents a prototype of a safety assessment system that utilizes ultra-wideband wireless sensors to detect traffic conflicts. A customized variant of time-to-collision is used to detect conflicts at different severity thresholds. Field trials are conducted using vehicle-mounted beacons and a phone to simulate sensors on vehicles and smart devices on pedestrians. Proximity measures are calculated in real-time to alert smartphones and prevent collisions, even in adverse weather conditions. Validation is conducted to assess the accuracy of time-to-collision measurements at various distances from the phone. Several limitations are identified and discussed, along with recommendations for improvement and lessons learned for future research and development. [ABSTRACT FROM AUTHOR]

Objective: Mobile phone usage while performing postural-locomotor tasks is everyday activity across persons of all ages in various environmental contexts and health conditions. However, it is also an important factor contributing to accidents. To lower the risk of pedestrian accidents, this meta-analysis aimed to examine how mobile phones affect pedestrian gait and identify how mobile phone tasks and participant age affect gait differently. Methods: Electronic database searches were performed in The Cochrane Library, PubMed, and Medline. Two examiners evaluated the eligibility and quality of included studies using the Downs and Black checklist. The mean differences (MD) or standardized mean differences (SMD) were calculated for each outcome. Subgroup analyses were used to compare the differential effects of mobile phone task and participant age on gait. Results: Among 22 eligible studies, 592 participants in 10 countries were analyzed in this meta-analysis. The overall meta-analysis showed that using a mobile phone significantly decreased pedestrian gait velocity (SMD = -1.45; 95% CI: -1.66 to -1.24; p < 0.00001; I² = 66%), step length (SMD = -1.01; 95% CI: -1.43 to -0.59; p < 0.00001; I²length (SMD = -0.9; 95% CI: -1.19 to -0.60; p < 0.00001; I² = 79%), significantly increased pedestrian step time (SMD = 0.77; 95% CI: 0.45 to 1.08; p < 0.00001; I² = 78%), stride time (SMD = 0.87; 95% CI: 0.69 to 1.06; p < 0.00001; I²95% CI: 0.34 to 1.24; p = 0.0006. I² = 75%), double support time (SMD = 1.09; 95% CI: 0.86 to 1.31; p < 0.00001; I² = 42%), and double support (%gait cycle, %GC) (MD = 2.32; 95% CI: 1.75 to 2.88; p < 0.00001; I² = 26%). Conclusion: In summary, the effects of mobile phone tasks and participant age on gait were inconsistent. Our study found that resource-intensive tasks (texting and reading) significantly reduced gait velocity, and step time; however, small resource-intensive tasks (calling, talking, and dialing) did not affect these outcomes. In contrast to young adults, step length and step time were not affected by mobile phone use in older adults. Tips: Pedestrians should consider using a mobile phone in their daily lives according to the application scenarios (walking environment, the complexity of mobile phone tasks, pedestrians' task processing abilities, etc.) as appropriate to avoid dangerous accidents. [ABSTRACT FROM AUTHOR]

Pedestrian fatality rate plays a key role in examining effectiveness of the road safety. The present study attempts to examine the effect of various categories of accused vehicles and the average 85th percentile speed at accident location on the pedestrian crash fatality. The study also attempts to develop pedestrian crash severity models using the binary logistic regression and boosted trees technique. Historical crash data, along with the video recording technique at accident sites, have been utilized for the present study. From regression equations, it is observed that when the heavy vehicle (HV) hits a pedestrian as compared to two-wheeler (2W), the average chance of death increases 2.44 times. According to the Boosted tree model, the contribution of speed is 60 %, whereas the contribution of category of accused vehicle is 40 % for pedestrian fatality prediction. The study should help in planning better strategies like all red time at intersections or pedestrian foot over bridge at critical locations. [ABSTRACT FROM AUTHOR]

The importance of an external interaction interface (eHMI) has grown in recent years. Most eHMI concepts focus on communicating autonomous vehicle (AV)'s yielding intention to pedestrians at a crossing. However, according to previous studies, pedestrians at a crossing rely mainly on the vehicle's movement information (implicit communication) rather than information from eHMIs (explicit communication). This paper has the purpose of proposing a specific use case in which the eHMI of future AVs could play an indispensable role in the safety of other road users (ORUs). Often VRUs cannot see the traffic flow due to a series of parked or stopped vehicles, which is a frequent cause of fatal traffic collision accidents. Drivers may also not be able to see approaching pedestrians or other cars from the side for the same reason. In this paper, the impact of an eHMI is tested from the perspective of drivers with limited visibility when a jaywalker steps into the road. A combination of colors, shapes, and information levels is presented on an eHMI. We show that our proposed eHMI design, in the deadlock scenario of a jaywalker and a driver who both lack visibility, significantly reduced the reaction time compared to when there was no eHMI. In the experiment, the willingness to stop, varying from 0 to 5, was measured from the driver's perspective. The results showed that most users felt uncertainty and did not move quickly when seeing the light band color alone. Textual information on the eHMI was significantly more effective in providing an urgent warning of this specific scenario than vertical and horizontal light bands with color without text. In addition, red color, blinking rapidly above 3 Hz, and egocentric messages were also necessary to reduce the PRT(perception response time). By using text-added eHMI (Vertical + Text eHMI), the mean time to achieve a score above 4 for willingness to stop was 2.113 s faster than when there was no eHMI. It was 2.571 s faster than the time until the slider of the participants reached the maximum level for willingness to stop. This is a meaningful amount of difference when considering a PRT of 2.5 s, which is the Korean road design standard. As eHMIs tend to be applied for smarter mobility, it is expected that they will be more effective in preventing accidents if the eHMI is standardized in autonomous driving level 2 to 3 vehicles driven by humans before fully autonomous driving becomes a reality. [ABSTRACT FROM AUTHOR]

The transportation system undergoes severe impacts due to potholes and the presence of stray animals on the roads resulting in accidents and fatal injuries. The utilization of intelligent transportation systems would reduce accidents and impart safety to the overall transportation network. This research aims to impart transportation safety through a real-time alert warning system for avoiding accidents due to potholes and the presence of stray animals. The study incorporates real-time detection of transportation entities like vehicles, animals, and pedestrians through a YOLO v3 computer vision algorithm processed on the GPU environment for a higher frame rate. The potholes and animal hotspots are mapped to form a geospatial database on which the buffer tool of geographic information system (GIS) is applied. The buffer zone was implemented on the geospatial layer to alert the driver in real-time, while the vehicle approaches the buffer zone. The system yields high precision of 0.976 mean average precision (mAP) score of entity detection and the real-time alert warning alerts the driver to ensure transportation safety while avoiding any possible accidents or fatal crashes. [ABSTRACT FROM AUTHOR]

This paper employed finite-element simulation together with a human body model (HBM) — THUMS to study the head injury risk of a pedestrian involved in a frontal impact with a sedan car. While previous studies have gained an intensive understanding of the effects of various factors on pedestrian injury, their results were mainly based on standard-sized HBMs. Hence, a scaling procedure was first applied for the THUMS to obtain a model that possesses Vietnamese anthropometry. A total of thirty simulations were conducted to investigate the effect of various parameters, including impact angle, impact location, and impact speed, on the head injury criterion (HIC) of the scaled THUMS. Besides, each simulation covered not only the car-to-pedestrian impact but also the pedestrian-to-ground impact. Thus, the head injury of the pedestrian in both primary impact and secondary impact could be evaluated. Results showed that HIC increased consistently with impact speed for primary impact. An impact at the center of the car was more critical than that at the corner. Whereas, the effect of impact angle varied depending on the impact location. Regarding the secondary impact, HIC value was found to be highly sensitive to the posture of the pedestrian before impacting to the ground. In most cases, HIC was much higher in secondary impact than in primary impact. In other words, secondary impact poses a high risk of fatality to pedestrians in a traffic accident. [ABSTRACT FROM AUTHOR]

This study attempts to clarify the characteristics of light-duty truck collision accidents involving pedestrians during right-turn maneuvers by analyzing actual pedestrian accident data in Japan. Evidence differences were observed between the daytime and nighttime. The number of injured and fatal pedestrians during the day was larger than that during the night. The rate of vehicle travel velocity ≤ 10 km/h in the daytime (47.0 %) was significantly higher than that in the nighttime (39.2 %), whereas the rate of vehicle travel velocity ≤ 20 km/h in the nighttime (52.7 %) was significantly higher than that in the daytime (46.9 %). The highest rate in the daytime was presented for the age group of 13 ∼ 64 years in minor injuries (54.1 %) and for those 75 years or older in serious injuries (47.5 %) and fatalities (64.3 %). For pedestrian crossing directions on the crosswalk, the pedestrian crossing from the forward left-side corner to the right-side corner exhibited the highest percentage in the daytime (39.2 %), and the opposite direction of crossing from the right-side corner to the forward left-side corner exhibited the highest percentage in the nighttime (39.6 %). The characteristics obtained in this study will contribute to the development and evaluation of advanced safety systems that are specialized for right-turning maneuvers of light-duty trucks. [ABSTRACT FROM AUTHOR]

The safety of vulnerable road users, especially pedestrians, on Polish roads remains among one of the lowest levels among EU countries. A high number of accidents involving pedestrians occur in areas with zebra crossings, and excessive speed is often mentioned in police records as a leading cause of accidents. A number of investigations highlight that drivers' speed strongly influences the impact on pedestrian safety; hence, it should be controlled in areas with pedestrian crossings through effective management. According to traffic law regulations, drivers are required to give special attention and slow down while approaching a pedestrian crossing. The aim of the article is to explore drivers' speed behaviors at zebra crossings depending on their localization. Investigated zebra crossings were located on single and dual carriageways on straight segments and approach sections of intersections without traffic lights. Speed measures were performed under free-flow traffic conditions. The conducted analysis allowed for the identification of road geometry-related parameters significantly influencing vehicles' speeds at pedestrian crosswalk locations. Based on the analyzed parameters, regression models were developed and validated. [ABSTRACT FROM AUTHOR]

The increasing occurrence of urban flooding in recent years demands a more accurate flood hazard assessment. Therefore, a better understanding of the predominant hydraulic processes in urban flood flows is required. The present paper reports an experimental study conducted in a laboratory scale model, which represents an urban area consisting of a rectangular city block and four surrounding streets. The objective is to quantify the impact of open areas within the city block on the key features of floodwaters. Tests are carried out under unsteady flow conditions, by using three inflow hydrographs with different unsteadiness levels. For each inflow hydrograph, the space available for floodwater volume storage within the block (storage capacity, ϕ) is varied, keeping the boundary conditions unchanged. A case where the city block has no space for floodwater storage (i.e., ϕ = 0) is used as a reference case. The results indicate that the unsteadiness level of the inflow hydrograph, especially during the rising stage, has a strong influence on the floodwater volume stored within the city block. The increase in storage capacity within the city block leads to a reduction of the global peak outflow discharge, a decrease in flow depths and a local increase in velocities in some streets and within the city block. Finally, with these variations in floodwater features, the level of risk to pedestrians is also impacted, increasing locally when the storage capacity of the block increases. Key Points: Access facilities to buildings and empty spaces within city blocks can modify the flood risk for the inhabitants of an urban areaThe block storage capacity can reduce flow depths by up to 13% and increase velocities by up to 20% in the streets for the tested casesThe inflow hydrograph unsteadiness level has a strong influence on the floodwater volume stored in the block and thereby on the flood flows [ABSTRACT FROM AUTHOR]

Researchers are studying CNN (convolutional neural networks) in various ways for image classification. Sometimes, they must classify two or more objects in an image into different situations according to their location. We developed a new learning method that colored objects from images and extracted them to distinguish the relationship between objects with different colors. We can apply this method in certain situations, such as pedestrians in a crosswalk. This paper presents a method for learning pedestrian situations on CNN using Mask R-CNN (Region-based CNN) and CDA (Crosswalk Detection Algorithm). With this method, we classified the location of the pedestrians into two situations: safety and danger. We organized the process of preprocessing and learning images into three stages. In Stage 1, we used Mask R-CNN to detect pedestrians. In Stage 2, we detected crosswalks with the CDA and placed colors on detected objects. In Stage 3, we combined crosswalks and pedestrian objects into one image and then, learned the image to CNN. We trained ResNet50 and Xception using images in the proposed method and evaluated the accuracy of the results. When tested experimentally, ResNet50 exhibited 96.7% accuracy and Xception showed 98.7% accuracy. We then created an image that simplified the situation with two colored boxes of crosswalks and pedestrians. We confirmed that the learned CNN with the images of colored boxes could classify the same test images applied in the previous experiment with 96% accuracy by ResNet50. This result indicates that the proposed system is suitable for classifying pedestrian safety and dangerous situations by accurately dividing the positions of the two objects. [ABSTRACT FROM AUTHOR]

Pedestrian deaths account for the highest percentage of fatality caused by traffic accidents in Japan. Increasing pedestrian safety is a key objective for reducing such deaths. For pedestrian fatality caused by vehicles at low speed, turning the vehicle toward the right was the most common behavior under left-hand traffic. Autonomous emergency braking (AEB) systems for pedestrian safety have great potential to mitigate pedestrian injuries and fatalities in traffic accidents. However, pedestrian-AEB systems, especially for vehicles turning right, are still under development. This study identified the characteristics of dangerous traffic scenarios between vehicles turning right and pedestrians, focusing on two directions of pedestrian crossing: from the left to the right side (Left-Pedestrian) and from the right to the left side (Right-Pedestrian). The ego vehicle recorded near-miss incidents using a drive recorder. The results revealed that the Left-Pedestrian and Right-Pedestrian scenarios had different features for both the width of roads going to and through the intersection and the average of the travel speeds of the ego vehicles. They had similar characteristics in terms of the presence of other vehicle categories, but differences in the relationship of numbers and/or travel directions of other vehicles. The findings of this study will contribute to the development and evaluation of safety systems for preventing collisions between right-turning vehicles and pedestrians at intersections. [ABSTRACT FROM AUTHOR]

The present paper addresses the performance of the λ type enforcement braking device (EBD) aimed to prevent traffic accidents in a road construction region. Our research concerns the EBD-mechanism installed in the road works area with the traffic-lane regulation. Here we contend that the employment of the discussed device leads to a significant increase of the drivers’, pedestrians’ and workers’ safety protection. The presented evaluation of breaking characteristics and further optimization of EBD structure reveals the effect of the tool’s performance improvement on the collision safety and reliability of the proposed solution. In this study, a particular attention is given to the role of the mast on the EBD’s operation, while our previous papers 6, 7) elaborated the influence of the arm-shape, arm-length and the connecting height of the arm for the mast on braking properties. A simple model collision tests and theoretical calculations based on the conservation law of energy and momentum were employed in our study. The obtained results enabled us to disregard that possible effect of the arm shape and conclude that the use of the long arm and higher connecting height are effective for the shortening of the braking distance, which constitutes the significant extension of our previous studies. The collision tests carried out with three different velocities and the EBD model with extended arm lengths was employed. We arrived to a proper structure optimization by careful examinations of the influence of the mast angle in the λ-type long arm EBD on the braking characteristics. [ABSTRACT FROM AUTHOR]

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Autonomous vehicles have gained popularity in recent years, but they are still not compatible with other vulnerable components of the traffic system, including pedestrians, bicyclists, motorcyclists, and occupants of smaller vehicles such as passenger cars. This incompatibility leads to reduced system performance and undermines traffic safety and comfort. To address this issue, the authors considered pedestrian crosswalks where vehicles, pedestrians, and micro-mobility vehicles collide at right angles in an urban road network. These road sections are areas where vulnerable people encounter vehicles perpendicularly. In order to prevent accidents in these areas, it is planned to introduce a warning system for vehicles and pedestrians. This procedure consists of multi-stage activities by sending warnings to drivers, disabled individuals, and pedestrians with phone addiction simultaneously. This collective autonomy is expected to reduce the number of accidents drastically. The aim of this paper is the automatic detection of a pedestrian crosswalk in an urban road network, designed from both pedestrian and vehicle perspectives. Faster R-CNN (R101-FPN and X101-FPN) and YOLOv7 network models were used in the analytical process of a dataset collected by the authors. Based on the detection performance comparison between both models, YOLOv7 accuracy was 98.6%, while the accuracy for Faster R-CNN was 98.29%. For the detection of different types of pedestrian crossings, YOLOv7 gave better prediction results than Faster R-CNN, although quite similar results were obtained. [ABSTRACT FROM AUTHOR]

Pedestrians are more likely to be seriously injured in vehicle collisions. In fact, multiple collisions between vehicles and pedestrians occur on residential roads that lack street-to-sidewalk dividers and have numerous blind spots. Traditional traffic safety features and equipment, such as speed bumps and traffic signs, are not always sufficient to prevent pedestrian accidents on such residential roads. Therefore, we suggest a collision risk warning service for residential roads as a solution to this issue. We use CCTVs with computer vision techniques and radar to accurately detect objects in real-time and to trace their trajectories. In addition, we employ a time-to-collision-based method to identify dangerous situations. The service warns drivers and pedestrians about hazardous situations using a light-emitting diode sign board. We applied our service to three different roads on a university campus in Seoul, Korea, and then conducted a user survey to evaluate the service. In summary, more than 90% of respondents stated that the service was necessary for these specific locations, and 76.9% noted that the service significantly contributed to traffic safety on the campus. This implies that the proposed service improved traffic safety and can be applied to various locations on residential roads. [ABSTRACT FROM AUTHOR]

In this paper, an integrated wearable airbag is proposed to protect the vulnerable pedestrian during a vehicle–pedestrian collision accident. To evaluate the protection performance of this newly proposed integrated wearable airbag, the airbag inflator finite element model is first verified via an inflator tank test, and the simulated results agree very well with the test. Next, the finite element model of the vehicle–pedestrian model is established, including a simplified vehicle model and a biomechanical HBM with the integrated wearable airbag. The numerical results show the newly proposed wearable airbag can effectively protect the pedestrian by significantly reducing injuries to the head and chest. Since head injury is the most important injury type, a complete set of injury indexes is adopted to evaluate severity of head injury, including HIC15, 3 ms resultant acceleration, and intracranial pressure. To further improve the protection performance of the airbag on the HBM's head, a parametric study is conducted towards two design parameters of the wearable airbag: inflator gas mass and pulling strap length. The parametric investigation shows 26 g gas and a 20 mm pulling strap can provide the best protection for the HBM's head. [ABSTRACT FROM AUTHOR]

Tumble and stampede in a dense crowd may be caused by irrational behaviours of individuals and always troubles the safety management of crowd activities. Risk evaluation based on pedestrian dynamical models can be regarded as an effective method of preventing crowd disasters. Here, a method depending on a combination of collision impulses and pushing forces was used to model the physical contacts between individuals in a dense crowd, by which the acceleration error during physical contacts caused by a traditional dynamical equation can be avoided. The human domino effect in a dense crowd could be successfully reproduced, and the crushing and trampling risk of a microscopic individual in a crowd could be quantitatively evaluated separately. This method provides a more reliable and integral data foundation for evaluating individual risk that shows better portability and repeatability than macroscopic crowd risk evaluation methods and will also be conducive to preventing crowd disasters. [ABSTRACT FROM AUTHOR]

Fear of crime has been rising persistently in Chile, even in periods where actual crime rates have decreased, making the perception of crime an important policy issue. This paper presents the results of the impact evaluation of a pilot public policy designed to reduce fear of crime around a shopping centre in Santiago, Chile. The pilot policy consisted of installing a team including police officers and local government officials that handed out information leaflets and talked to passers-by about crime prevention. Pre-intervention and post-intervention surveys were conducted in the shopping centre where the programme was implemented and in a control shopping centre nearby to identify the causal effects of the policy using a difference-in-differences empirical strategy. The results indicate that the programme was effective in reducing fear of crime around the shopping centre, especially at night among its workers, and that it reduced actual crime. However, a deeper analysis suggests that the programme might have actually increased fear of crime among the individuals who directly interacted with the programme. The reduction in crime might have indirectly resulted in an overall reduction in fear among workers, who are likely to be up to date on criminal occurrences in the area, explaining how an increase in fear in those directly contacted is consistent with an overall reduction in fear across workers. [ABSTRACT FROM AUTHOR]

Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy. [ABSTRACT FROM AUTHOR]