Evaluation of geometrically personalized THUMS pedestrian model response against sedan–pedestrian PMHS impact test data

Objective: Evaluating the biofidelity of pedestrian finite element models (PFEM) using postmortem human subjects (PMHS) is a challenge because differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry, which could alleviate this issue. In this study, the Total Human Model for Safety (THUMS) PFEM (Ver 4.01) was compared to the cadaveric response in vehicle–pedestrian impacts using geometrically personalized models.

Methods: The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy.

Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy.

Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle–pedestrian impact scenarios.     

Analyzing pedestrian crash injury severity under different weather conditions

Objective: Pedestrians are the most vulnerable road users due to the lack of mass, speed, and protection compared to other types of road users. Adverse weather conditions may reduce road friction and visibility and thus increase crash risk. There is limited evidence and considerable discrepancy with regard to impacts of weather conditions on injury severity in the literature. This article investigated factors affecting pedestrian injury severity level under different weather conditions based on a publicly available accident database in Great Britain.

Method: Accident data from Great Britain that are publicly available through the STATS19 database were analyzed. Factors associated with pedestrian, driver, and environment were investigated using a novel approach that combines a classification and regression tree with random forest approach.

Results: Significant severity predictors under fine weather conditions from the models included speed limits, pedestrian age, light conditions, and vehicle maneuver. Under adverse weather conditions, the significant predictors were pedestrian age, vehicle maneuver, and speed limit.

Conclusions: Elderly pedestrians are associated with higher pedestrian injury severities. Higher speed limits increase pedestrian injury severity. Based on the research findings, recommendations are provided to improve pedestrian safety.     

A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China

Objective: Although intersections correspond to a small proportion of the entire roadway system, they account for a disproportionally high number of fatal pedestrian crashes, especially on rural roads situated in low- and middle-income countries. This article examines pedestrian safety at rural intersections and suggests applicable accident prevention treatments by providing an in-depth analysis of 28 fatal pedestrian crashes from 8 low-volume roads in southwest China.

Methods: The driving reliability and error analysis method (DREAM) is a method to support a systematic classification of accident causation information and to facilitate aggregation of that information into patterns of contributing factors. This is the first time that DREAM was used to analyze pedestrian–vehicle crashes and provide suggestions for road improvements in China.

Results: The key issues adversely affecting pedestrian safety can be organized in 4 distinctive thematic categories, namely, deficient intersection safety infrastructure, lack of pedestrian safety education, inadequate driver training, and insufficient traffic law enforcement. Given that resources for traffic safety investments in rural areas are limited, it is determined that the potential countermeasures should focus on low-cost, easily implementable, and long-lasting measures increasing the visibility and predictability of pedestrian movement and reducing speeding and irresponsible driving among drivers and risk-taking behaviors among pedestrians.

Conclusions: Accident prevention treatments are suggested based on their suitability for rural areas in southwest China. These countermeasures include introducing better access management and traffic calming treatments, providing more opportunities for pedestrian education, and enhancing the quality of driver training and traffic law enforcement.     

Can new passenger cars reduce pedestrian lower extremity injury? A review of geometrical changes of front-end design before and after regulatory efforts

Objective: Pedestrian lower extremity represents the most frequently injured body region in car-to-pedestrian accidents. The European Directive concerning pedestrian safety was established in 2003 for evaluating pedestrian protection performance of car models. However, design changes have not been quantified since then. The goal of this study was to investigate front-end profiles of representative passenger car models and the potential influence on pedestrian lower extremity injury risk.

Methods: The front-end styling of sedans and sport utility vehicles (SUV) released from 2008 to 2011 was characterized by the geometrical parameters related to pedestrian safety and compared to representative car models before 2003. The influence of geometrical design change on the resultant risk of injury to pedestrian lower extremity—that is, knee ligament rupture and long bone fracture—was estimated by a previously developed assessment tool assuming identical structural stiffness. Based on response surface generated from simulation results of a human body model (HBM), the tool provided kinematic and kinetic responses of pedestrian lower extremity resulted from a given car's front-end design.

Results: Newer passenger cars exhibited a “flatter” front-end design. The median value of the sedan models provided 87.5 mm less bottom depth, and the SUV models exhibited 94.7 mm less bottom depth. In the lateral impact configuration similar to that in the regulatory test methods, these geometrical changes tend to reduce the injury risk of human knee ligament rupture by 36.6 and 39.6% based on computational approximation. The geometrical changes did not significantly influence the long bone fracture risk.

Conclusions: The present study reviewed the geometrical changes in car front-ends along with regulatory concerns regarding pedestrian safety. A preliminary quantitative benefit of the lower extremity injury reduction was estimated based on these geometrical features. Further investigation is recommended on the structural changes and inclusion of more accident scenarios.     

The influence of lower extremity postures on kinematics and injuries of cyclists in vehicle side collisions

Objective: A cyclist assumes various cyclic postures of the lower extremities while pushing the pedals in a rotary motion while pedaling. In order to protect cyclists in collisions, it is necessary to understand what influence these postures have on the global kinematics and injuries of the cyclist.

Method: Finite element (FE) analyses using models of a cyclist, bicycle, and car were conducted. In the simulations, the Total Human Model of Safety (THUMS) occupant model was employed as a cyclist, and the simulation was set up such that the cyclist was hit from its side by a car. Three representative postures of the lower extremities of the cyclist were examined, and the kinematics and injury risk of the cyclist were compared to those obtained by a pedestrian FE model. The risk of a lower extremity injury was assessed based on the knee shear displacement and the tibia bending moment.

Results: When the knee position of the cyclist was higher than the hood leading edge, the hood leading edge contacted the leg of the cyclist, and the pelvis slid over the hood top and the wrap-around distance (WAD) of the cyclist's head was large. The knee was shear loaded by the hood leading edge, and the anterior cruciate ligament (ACL) ruptured. The tibia bending moment was less than the injury threshold. When the cyclist's knee position was lower than the hood leading edge, the hood leading edge contacted the thigh of the cyclist, and the cyclist rotated with the femur as the pivot point about the hood leading edge. In this case, the head impact location of the cyclist against the car was comparable to that of the pedestrian collision. The knee shear displacement and the tibia bending moment were less than the injury thresholds.

Conclusion: The knee height of the cyclist relative to the hood leading edge affected the global kinematics and the head impact location against the car. The loading mode of the lower extremities was also dependent on the initial positions of the lower extremities relative to the car structures. In the foot up and front posture, the knee was loaded in a lateral shear direction by the hood leading edge and as a result the ACL ruptured. The bicycle frame and the struck-side lower extremity interacted and could influence the loadings on lower extremities.     

Local vs. national: Epidemiology of pedestrian injury in a mid-Atlantic city

Objective: Understanding pedestrian injury trends at the local level is essential for program planning and allocation of funds for urban planning and improvement. Because we hypothesize that local injury trends differ from national trends in significant and meaningful ways, we investigated citywide pedestrian injury trends to assess injury risk among nationally identified risk groups, as well as identify risk groups and locations specific to Baltimore City.

Methods: Pedestrian injury data, obtained from the Baltimore City Fire Department, were gathered through emergency medical services (EMS) records collected from January 1 to December 31, 2014. Locations of pedestrian injuries were geocoded and mapped. Pearson's chi-square test of independence was used to investigate differences in injury severity level across risk groups. Pedestrian injury rates by age group, gender, and race were compared to national rates.

Results: A total of 699 pedestrians were involved in motor vehicle crashes in 2014—an average of 2 EMS transports each day. The distribution of injuries throughout the city did not coincide with population or income distributions, indicating that there was not a consistent correlation between areas of concentrated population or concentrated poverty and areas of concentrated pedestrian injury. Twenty percent (n = 138) of all injuries occurred among children age ≤14, and 22% (n = 73) of severe injuries occurred among young children. The rate of injury in this age group was 5 times the national rate (Incident Rate Ratio [IRR] = 4.81, 95% confidence interval [CI], [4.05, 5.71]). Injury rates for adults ≥65 were less than the national average.

Conclusions: As the urban landscape and associated pedestrian behavior transform, continued investigation of local pedestrian injury trends and evolving public health prevention strategies is necessary to ensure pedestrian safety.     

Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey

Objective: Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage–only (PDO) traffic accidents in Turkey.

Methods: In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle–vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R).

Results: It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The R values for prediction of fault rates were close to 1 for all folds and scenarios.

Conclusions: This study focuses on exhibiting new aspects and scientific approaches for determining fault rates of involvement in most frequent PDO accidents occurring in Turkey by discussing some deficiencies in THTA and without regard to initiative and/or experience of experts. This study yields judicious decisions to be made especially on forensic investigations and events involving insurance companies. Referring to this approach, injury/fatal and/or pedestrian-related accidents may be analyzed as future work by developing new scientific models.     

Analysis of the influence of passenger vehicles front-end design on pedestrian lower extremity injuries by means of the LLMS model

Objective: This work aims at investigating the influence of some front-end design parameters of a passenger vehicle on the behavior and damage occurring in the human lower limbs when impacted in an accident.

Methods: The analysis is carried out by means of finite element analysis using a generic car model for the vehicle and the lower limbs model for safety (LLMS) for the purpose of pedestrian safety. Considering the pedestrian standardized impact procedure (as in the 2003/12/EC Directive), a parametric analysis, through a design of experiments plan, was performed. Various material properties, bumper thickness, position of the higher and lower bumper beams, and position of pedestrian, were made variable in order to identify how they influence the injury occurrence. The injury prediction was evaluated from the knee lateral flexion, ligament elongation, and state of stress in the bone structure.

Results: The results highlighted that the offset between the higher and lower bumper beams is the most influential parameter affecting the knee ligament response. The influence is smaller or absent considering the other responses and the other considered parameters. The stiffness characteristics of the bumper are, instead, more notable on the tibia. Even if an optimal value of the variables could not be identified trends were detected, with the potential of indicating strategies for improvement.

Conclusions: The behavior of a vehicle front end in the impact against a pedestrian can be improved optimizing its design. The work indicates potential strategies for improvement. In this work, each parameter was changed independently one at a time; in future works, the interaction between the design parameters could be also investigated. Moreover, a similar parametric analysis can be carried out using a standard mechanical legform model in order to understand potential diversities or correlations between standard tools and human models.     

Characteristics and clinical outcomes of head-injured cyclists with and without helmets in urban and rural areas of Taiwan: A 15-year study

Objective: Bicycle riding is increasingly popular in Taiwan, but the number of cyclists injured and cyclists' death rates are both increasing. The aim of this study was to investigate the different characteristics and clinical outcomes of traffic accident–related head injuries among cyclists in urban and rural areas.

Methods: Records of 812 patients (533 urban and 279 rural) admitted to 27 hospitals in Taipei City and Hualien County as the result of a traumatic head injury while bicycling between 1998 and 2013 were retrieved for study. Demographics, details about the accident, protective helmet use, and clinical outcomes were then subjected to analysis.

Results: Urban victims were more likely to be injured during morning and early evening rush hours and rural victims during the day; most urban victims were between 19 and 34 years of age and injured in the slow lane; rural victims tended to be younger or older and were injured in the fast lane (all P ≤.001). Riders who wore a helmet were less likely to suffer loss of consciousness (odds ratio [OR] = 0.31), amnesia (OR = 0.069), neurological disorders (OR = 0.205), or facial fractures (OR = 0.369). Older age, more severe head injuries, and bicycle–motor vehicle collisions influenced the severity of symptoms on admission and the residual effects at discharge.

Conclusions: Differences in the characteristics of injuries in urban and rural areas and the utilization of protective helmets may help government authorities adopt appropriate policies to promote safer and more enjoyable cycling.     

How do children learn to cross the street? The process of pedestrian safety training

Objective: Pedestrian injuries are a leading cause of child death and may be reduced by training children to cross streets more safely. Such training is most effective when children receive repeated practice at the complex cognitive–perceptual task of judging moving traffic and selecting safe crossing gaps, but there is limited data on how much practice is required for children to reach adult levels of functioning. Using existing data, we examined how children's pedestrian skills changed over the course of 6 pedestrian safety training sessions, each composed of 45 crossings within a virtual pedestrian environment.

Methods: As part of a randomized controlled trial on pedestrian safety training, 59 children ages 7–8 crossed the street within a semi-immersive virtual pedestrian environment 270 times over a 3-week period (6 sessions of 45 crossings each). Feedback was provided after each crossing, and traffic speed and density were advanced as children's skill improved. Postintervention pedestrian behavior was assessed a week later in the virtual environment and compared to adult behavior with identical traffic patterns.

Results: Over the course of training, children entered traffic gaps more quickly and chose tighter gaps to cross within; their crossing efficiency appeared to increase. By the end of training, some aspects of children's pedestrian behavior was comparable to adult behavior but other aspects were not, indicating that the training was worthwhile but insufficient for most children to achieve adult levels of functioning.

Conclusions: Repeated practice in a simulated pedestrian environment helps children learn aspects of safe and efficient pedestrian behavior. Six twice-weekly training sessions of 45 crossings each were insufficient for children to reach adult pedestrian functioning, however, and future research should continue to study the trajectory and quantity of child pedestrian safety training needed for children to become competent pedestrians.     

Probabilistic risk assessment for pedestrian–vehicle collision considering uncertainties of pedestrian mobility

Objectives: The uncertainties of pedestrian mobility are important factors affecting the accuracy and robustness of an active pedestrian protection system. This study is to provide the means for probabilistic risk evaluation of pedestrian–vehicle collision by counting the uncertainties in pedestrian motion.

Method: The pedestrian is modeled by a first-order Markov model to characterize the stochastic properties in mobility according to field experiments of pedestrians crossing an uncontrolled road. Based on the assumption of Gaussian distribution, unscented transformation (UT) is employed to predict the collision risk probability with the symmetric σ-set constructed on the basis of discrete trajectory simulation. Simulation experiments were carried out with 10,000 Monte Carlo (MC) simulations as the reference.

Results: The probability density distributions of time-to-collision, minimal distance, and collision probability estimated by UT coincide with the reference ones under various vehicle–pedestrian conflict scenarios, and the maximal deviation of collision probability from the reference is 5.33%. The UT method is about 600 times faster than the MC method (10,000 runs), which means that the proposed method has the potential for online application.

Conclusions: This article presents an effective and efficient algorithm to estimate the collision probability by using a UT method to solve the nonlinear transformation of uncertainties in pedestrian motion. Simulation results show that the UT-based method achieves accurate collision probability estimation and higher computation efficiency than MC and provides more valuable information concerning collision avoidance than the deterministic methods in the design of a pedestrian collision avoidance system.     

Features of fatal injuries in older cyclists in vehicle–bicycle accidents in Japan

Objective: The purpose of this study was to identify and better understand the features of fatal injuries in cyclists aged 75 years and over involved in collisions with either hood- or van-type vehicles.

Methods: This study investigated the fatal injuries of cyclists aged 75 years old and over by analyzing accident data. We focused on the body regions to which the fatal injury occurred using vehicle–bicycle accident data from the Institute for Traffic Accident Research and Data Analysis (ITARDA) in Japan. Using data from 2009 to 2013, we examined the frequency of fatally injured body region by gender, age, and actual vehicle travel speed. We investigated any significant differences in distributions of fatal injuries by body region for cyclists aged 75 years and over using chi-square tests to compare with cyclists in other age groups. We also investigated the cause of fatal head injuries, such as impact with a road surface or vehicle.

Results: The results indicated that head injuries were the most common cause of fatalities among the study group. At low vehicle travel speeds for both hood- and van-type vehicles, fatalities were most likely to be the result of head impacts against the road surface.

The percentage of fatalities following hip injuries was significantly higher for cyclists aged 75 years and over than for those aged 65–74 or 13–59 in impacts with hood-type vehicles. It was also higher for women than men in the over-75 age group in impacts with these vehicles.

Conclusions: For cyclists aged 75 years and over, wearing a helmet may be helpful to prevent head injuries in vehicle-to-cyclist accidents. It may also be helpful to introduce some safety measures to prevent hip injuries, given the higher level of fatalities following hip injury among all cyclists aged 75 and over, particularly women.     

A virtual test system representing the distribution of pedestrian impact configurations for future vehicle front-end optimization

Objectives: The purpose of this study is to define a computationally efficient virtual test system (VTS) to assess the aggressivity of vehicle front-end designs to pedestrians considering the distribution of pedestrian impact configurations for future vehicle front-end optimization. The VTS should represent real-world impact configurations in terms of the distribution of vehicle impact speeds, pedestrian walking speeds, pedestrian gait, and pedestrian height. The distribution of injuries as a function of body region, vehicle impact speed, and pedestrian size produced using this VTS should match the distribution of injuries observed in the accident data. The VTS should have the predictive ability to distinguish the aggressivity of different vehicle front-end designs to pedestrians.

Methods: The proposed VTS includes 2 parts: a simulation test sample (STS) and an injury weighting system (IWS). The STS was defined based on MADYMO multibody vehicle to pedestrian impact simulations accounting for the range of vehicle impact speeds, pedestrian heights, pedestrian gait, and walking speed to represent real world impact configurations using the Pedestrian Crash Data Study (PCDS) and anthropometric data. In total 1,300 impact configurations were accounted for in the STS. Three vehicle shapes were then tested using the STS. The IWS was developed to weight the predicted injuries in the STS using the estimated proportion of each impact configuration in the PCDS accident data. A weighted injury number (WIN) was defined as the resulting output of the VTS. The WIN is the weighted number of average Abbreviated Injury Scale (AIS) 2+ injuries recorded per impact simulation in the STS. Then the predictive capability of the VTS was evaluated by comparing the distributions of AIS 2+ injuries to different pedestrian body regions and heights, as well as vehicle types and impact speeds, with that from the PCDS database. Further, a parametric analysis was performed with the VTS to assess the sensitivity of the injury predictions to changes in vehicle shape (type) and stiffness to establish the potential for using the VTS for future vehicle front-end optimization.

Results: An STS of 1,300 multibody simulations and an IWS based on the distribution of impact speed, pedestrian height, gait stance, and walking speed is broadly capable of predicting the distribution of pedestrian injuries observed in the PCDS database when the same vehicle type distribution as the accident data is employed. The sensitivity study shows significant variations in the WIN when either vehicle type or stiffness is altered.

Conclusions: Injury predictions derived from the VTS give a good representation of the distribution of injuries observed in the PCDS and distinguishing ability on the aggressivity of vehicle front-end designs to pedestrians. The VTS can be considered as an effective approach for assessing pedestrian safety performance of vehicle front-end designs at the generalized level. However, the absolute injury number is substantially underpredicted by the VTS, and this needs further development.     

Personal injury recovery cost of pedestrian–vehicle collisions in New South Wales,Australia

Background: There is a need for routine estimates of injury recovery costs from pedestrian collisions using hospital separation records for economic evaluations.

Objective: To estimate the cost of injury recovery following pedestrian–vehicle collisions using the personal injury recover cost (PIRC) equation using key demographic and injury characteristics.

Method: An estimation of the costs of on-road pedestrian–vehicle collisions involving individuals who were injured and hospitalized in New South Wales (NSW), Australia, from 2002 to 2011 using the PIRC equation. The PIRC estimates individual injury recovery costs and does not include costs associated with property damage, vehicle repair, or rescue services. Individual recovery costs associated with severe traumatic brain injury (TBI) were estimated. The injured individual's mean, median, and total injury recovery costs are described for key demographic, injury, and crash characteristics.

Results: There were 9,781 pedestrians who were injured, costing an estimated total of $2.4 billion in personal injury recovery costs, an annual cost of $243 million. Males had a total injury recovery cost 1.7 times higher than females. The median injury recovery cost decreased with increasing age. TBI ($248,491) and spinal cord and vertebral column injuries ($264,103) had the highest median injury recovery costs for the body region of the most severe injury. TBI accounted for 22.6% of the total injury recovery costs for the most severe injury sustained. Just over one third of pedestrians sustained 4 or more injuries, with a median cost of $243,992, which was 1.6 times higher than the cost for a pedestrian who sustained a single injury ($153,682).

Conclusions: Personal injury recovery costs following pedestrian–vehicle collisions where a pedestrian is injured are substantial in NSW. The PIRC equation enables the economic cost burden of road traffic injury to be calculated using hospital separation data. The PIRC enables comprehensive personal injury recovery costs to be estimated and would aid in economic evaluations of preventive strategies in road safety.     

Detection of the toughest: Pedestrian injury risk as a smooth function of age

Objective: Though it is common to refer to age-specific groups (e.g., children, adults, elderly), smooth trends conditional on age are mainly ignored in the literature. The present study examines the pedestrian injury risk in full-frontal pedestrian-to–passenger car accidents and incorporates age—in addition to collision speed and injury severity—as a plug-in parameter.

Methods: Recent work introduced a model for pedestrian injury risk functions using explicit formulae with easily interpretable model parameters. This model is expanded by pedestrian age as another model parameter. Using the German In-Depth Accident Study (GIDAS) to obtain age-specific risk proportions, the model parameters are fitted to the raw data and then smoothed by broken-line regression.

Results: The approach supplies explicit probabilities for pedestrian injury risk conditional on pedestrian age, collision speed, and injury severity under investigation. All results yield consistency to each other in the sense that risks for more severe injuries are less probable than those for less severe injuries. As a side product, the approach indicates specific ages at which the risk behavior fundamentally changes. These threshold values can be interpreted as the most robust ages for pedestrians.

Conclusions: The obtained age-wise risk functions can be aggregated and adapted to any population. The presented approach is formulated in such general terms that in can be directly used for other data sets or additional parameters; for example, the pedestrian's sex. Thus far, no other study using age as a plug-in parameter can be found.     

Impact of improving vehicle front design on the burden of pedestrian injuries in Germany,the United States,and India

Objective: European car design regulations and New Car Assessment Program (NCAP) ratings have led to reductions in pedestrian injuries. The aim of this study was to evaluate the impact of improving vehicle front design on mortality and morbidity due to pedestrian injuries in a European country (Germany) and 2 countries (the United States and India) that do not have pedestrian-focused NCAP testing or design regulations.

Methods: We used data from the International Road Traffic and Accident Database and the Global Burden of Disease project to estimate baseline pedestrian deaths and nonfatal injuries in each country in 2013. The effect of improved passenger car star ratings on probability of pedestrian injury was based on recent evaluations of pedestrian crash data from Germany. The effect of improved heavy motor vehicle (HMV) front end design on pedestrian injuries was based on estimates reported by simulation studies. We used burden of disease methods to estimate population health loss by combining the burden of morbidity and mortality in disability-adjusted life years (DALYs) lost.

Results: Extrapolating from evaluations in Germany suggests that improving front end design of cars can potentially reduce the burden of pedestrian injuries due to cars by up to 24% in the United States and 41% in India. In Germany, where cars comply with the United Nations regulation on pedestrian safety, additional improvements would have led to a 1% reduction. Similarly, improved HMV design would reduce DALYs lost by pedestrian victims hit by HMVs by 20% in each country. Overall, improved vehicle design would reduce DALYs lost to road traffic injuries (RTIs) by 0.8% in Germany, 4.1% in the United States, and 6.7% in India.

Conclusions: Recent evaluations show a strong correlation between Euro NCAP pedestrian scores and real-life pedestrian injuries, suggesting that improved car front end design in Europe has led to substantial reductions in pedestrian injuries. Although the United States has fewer pedestrian crashes, it would nevertheless benefit substantially by adopting similar regulations and instituting pedestrian NCAP testing. The maximum benefit would be realized in low- and middle-income countries like India that have a high proportion of pedestrian crashes. Though crash avoidance technologies are being developed to protect pedestrians, supplemental protection through design regulations may significantly improve injury countermeasures for vulnerable road users.     

Influence of pedestrian age and gender on spatial and temporal distribution of pedestrian crashes

Objectives: Every year, about 1.24 million people are killed in traffic crashes worldwide and more than 22% of these deaths are pedestrians. Therefore, pedestrian safety has become a significant traffic safety issue worldwide. In order to develop effective and targeted safety programs, the location- and time-specific influences on vehicle–pedestrian crashes must be assessed. The main purpose of this research is to explore the influence of pedestrian age and gender on the temporal and spatial distribution of vehicle–pedestrian crashes to identify the hotspots and hot times.

Methods: Data for all vehicle–pedestrian crashes on public roadways in the Melbourne metropolitan area from 2004 to 2013 are used in this research. Spatial autocorrelation is applied in examining the vehicle–pedestrian crashes in geographic information systems (GIS) to identify any dependency between time and location of these crashes. Spider plots and kernel density estimation (KDE) are then used to determine the temporal and spatial patterns of vehicle–pedestrian crashes for different age groups and genders.

Results: Temporal analysis shows that pedestrian age has a significant influence on the temporal distribution of vehicle–pedestrian crashes. Furthermore, men and women have different crash patterns. In addition, results of the spatial analysis shows that areas with high risk of vehicle–pedestrian crashes can vary during different times of the day for different age groups and genders. For example, for those between ages 18 and 65, most vehicle–pedestrian crashes occur in the central business district (CBD) during the day, but between 7:00 p.m. and 6:00 a.m., crashes among this age group occur mostly around hotels, clubs, and bars.

Conclusions: This research reveals that temporal and spatial distributions of vehicle–pedestrian crashes vary for different pedestrian age groups and genders. Therefore, specific safety measures should be in place during high crash times at different locations for different age groups and genders to increase the effectiveness of the countermeasures in preventing and reducing vehicle–pedestrian crashes.     

Factors associated with prehospital death among traffic accident patients in Osaka City,Japan: A population-based study

Objective: Although it is important to assess the factors associated with traffic accident fatalities to decrease them as a matter of public health, such factors have not been fully identified.

Methods: Using a large-scale data set of ambulance records in Osaka City, Japan, we retrospectively analyzed all traffic accident patients transported to hospitals by emergency medical service personnel from 2013 to 2014. In this study, prehospital death was defined as that occurring at the scene or in the emergency department immediately after hospital arrival. We assessed prehospital factors associated with prehospital death due to traffic accidents by logistic regression models.

Results: This study enrolled 28,903 emergency patients involved in traffic accidents, of whom 68 died prehospital. In a multivariate model, elderly patients aged ≥75 years (adjusted odds ratio [AOR] = 4.34; 95% confidence interval [CI], 2.29–8.23), nighttime (AOR = 2.75; 95% CI, 1.65–4.70), and type of injured person compared to bicyclists such as pedestrians (AOR = 9.58; 95% CI, 5.07–17.99), motorcyclists (AOR = 2.75; 95% CI, 1.21–6.24), and car occupants (AOR = 2.98; 95% CI, 1.39–6.40) were significantly associated with prehospital death due to traffic accidents. In addition, the AOR for automobile versus nonautomobile as the collision opponent was 4.76 (95% CI, 2.30–9.88).

Conclusions: In this population, the factors associated with prehospital death due to traffic accidents were elderly people, nighttime, and pedestrian as the type of patient. The proportion of prehospital deaths due to traffic accidents was also high when the collision component was an automobile.     

Risk factors affecting the severity of traffic accidents at Shanghai river-crossing tunnel

Objective: With increasing traffic volume and urban development, increasing numbers of underground tunnels have been constructed to relieve conflict between strained land and heavy traffic. However, as more long tunnels are constructed, tunnel traffic safety is becoming increasingly serious. Thus, it is necessary to acquire their implications and impacts. This study examined 4,539 traffic accidents that have occurred in 14 Shanghai river-crossing tunnels for the period 2011–2012 and analyze the correlation between potential factors and accident injury severity.

Methods: An ordered logit model was developed to examine the correlation between potential factors and accident injury severity.

Results: Results show that increased injury severity is associated with male drivers, drivers aged 65 years or older, accident time from midnight to dawn, weekends, wet road surface, goods vehicles, 3 or more vehicles, 4 or more lanes, middle speed limits (50–79 km/h), zone 3, extra-long tunnels (over 3,000 m), and maximum longitudinal gradient.

Conclusions: This article aims to provide useful information for engineers to develop interventions and countermeasures to improve tunnel safety in China.     

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data

Objective: Understanding the various factors that affect accident risk is of particular concern to decision makers and researchers. The incorporation of real-time traffic and weather data constitutes a fruitful approach when analyzing accident risk. However, the vast majority of relevant research has no specific focus on vulnerable road users such as powered 2-wheelers (PTWs). Moreover, studies using data from urban roads and arterials are scarce. This study aims to add to the current knowledge by considering real-time traffic and weather data from 2 major urban arterials in the city of Athens, Greece, in order to estimate the effect of traffic, weather, and other characteristics on PTW accident involvement.

Methods: Because of the high number of candidate variables, a random forest model was applied to reveal the most important variables. Then, the potentially significant variables were used as input to a Bayesian logistic regression model in order to reveal the magnitude of their effect on PTW accident involvement.

Results: The results of the analysis suggest that PTWs are more likely to be involved in multivehicle accidents than in single-vehicle accidents. It was also indicated that increased traffic flow and variations in speed have a significant influence on PTW accident involvement. On the other hand, weather characteristics were found to have no effect.

Conclusions: The findings of this study can contribute to the understanding of accident mechanisms of PTWs and reduce PTW accident risk in urban arterials.