Factors contributing to motorcycle fatal crashes on National Highways in India

This study analyses fatal crash patterns, and identifies the risk factors contributing to motorcycle versus non-motorcycle fatal crashes using binomial logistic regression on two-, four- and six-lane National Highways (NHs) in India utilizing police fatal crash data. The distribution of victims’ mode by striking vehicles shows that percentage share of striking vehicles (truck) against the victims’ vehicles (motorcycle) is 44%, 52% and 37% on two-lane NH-8, four-lane NH-24 and six-lane NH-1, respectively. Nine explanatory variables pertaining to fatal crash, victim, roadway and environment are considered for the model (using combined data of cited three NHs). The results of the logistic regression model (motorcycle versus non-motorcycle fatal crashes) show that for variable ‘collision type’, likelihood of occurrence of ‘rear-end’, ‘sideswipe’ and ‘head-on’ fatal crashes are 42-times, 35-times and 25-times more than ‘hit pedestrian’ respectively. Similarly, for variable ‘number of vehicle’, likelihood is thrice as ‘single-vehicle’ than ‘two or more vehicles’; and, for variable ‘number of lane’, probability is more on ‘two-lane’ NH-8 than ‘four-lane’ NH-24. Based on the study results, it is recommended to upgrade two-lane (undivided carriageway) to four-lane (divided carriageway) NHs to reduce ‘head-on’ collision.     

Severity of alcohol-related motor vehicle crashes in British Columbia: case - control study

The objective of the present study was to compare the injury severity and vehicle damage severity rates of alcohol-related crashes with rates of non-alcohol-related crashes in British Columbia (BC). Injury severity rates and vehicle damage severity rates were taken from 2002 Insurance Corporation of British Columbia traffic collision data. The data were computed in order to compare the differences in injury severity and vehicle damage severity rates of alcohol-related vs. non-alcohol-related motor vehicle crashes. Case - control methods were used in this study to analyse the risk of alcohol-related crashes compared to non-alcohol-related crashes in BC. Odds ratios (OR) and 95% CI were calculated to estimate relative risks. In the case - control analysis, the risk of fatal collision was increased for those drinking and driving compared with those driving sober (OR 4.70; 95% CI 3.15 - 7.01). Risk of injury collision was increased for those drinking and driving compared with those driving sober (OR 1.32; 95% CI 1.19 - 1.37). Importantly, the risk of vehicle damage severity was increased for those drinking and driving compared with those driving sober (write-off vehicle OR 4.24; 95% CI 3.70 - 4.86, severely damaged vehicles OR 1.98; 95% CI 1.77 - 2.21). The study reinforces existing literature to suggest that current evidence is sufficient to show an increased risk of injury and fatality to drivers and occupants in alcohol-related crashes. This paper not only emphasizes this well-known relationship, but also such consequences as increased vehicle damage severity. The connection between drinking and severity of motor vehicle crashes is popularly believed and has now received substantial scientific support. There is strong justification for injury prevention experts and policy-makers to step up motor vehicle crash injury prevention advocacy by implementing evidence-based policies to reduce rates of alcohol-impaired driving in the province of BC. Most unintentional injuries in BC are related to motor vehicle crashes. Significant improvements can be made in these statistics by: increasing the use of occupant protection (safety belt and child restraint seats); reducing alcohol-related injuries through multiple strategies including corrections in the physical environment, extensive enforcement of drinking and driving laws and health promotion/education.     

Safety at play: let's all help to prevent drowning

The association between place of residence, population density, relief and type of event (collision or non-collision of the vehicle) has not been evaluated in developing countries. The main objective of this study is to determine the differential factors associated with the occurrence of deaths of collision and non-collision automobile users in Patagonia, Argentina. A multiple logistic regression analysis was performed using as the dependent variable death by car accident (collision or non-collision of the vehicle) and sex, age, place of residence of the victim, relief and population density as the independent variables. Collision fatalities were related to areas of high population density, while non-collision fatalities were related to areas of low population density, mountainous landscape and place of residence of the victims outside the Patagonian region. The results obtained in this study indicate the need to develop differential primary prevention policies by place of residence of car occupants, focusing on Patagonia non-resident drivers and by emphasising non-collision accidents.     

List of Reviewers 2013

Motor vehicle accidents are the leading cause of death in adolescents and young adults worldwide. Nearly three-quarters of road deaths occur in developing countries and men comprise a mean 80% of casualties. The rate of road traffic accidents caused by four-wheeled vehicles is the highest globally reported road traffic accidents statistic. In Saudi Arabia, the motor vehicle is the main means of transportation with one person killed and four injured every hour. Over 65% of accidents occur because of vehicles travelling at excess speed and/or drivers disobeying traffic signals. Road traffic injuries cause considerable economic losses to victims, their families, and to nations as a whole. Strategic prevention plans should be implemented soon by various sectors (health, police, transport, and education) to decrease the mortality and morbidity among adolescent and young age group. Strong and effective coordination between ministry of health and other ministries together with World Health Organization and other related organisations will be an important step towards implementing the international Decade of Action for Road Safety (2011–2020). The aim of this review article is to highlight some aspects of the health impacts of road traffic accidents.     

Observed and unobserved correlation between crash avoidance manoeuvers and crash severity

Understanding drivers’ responses to critical events, analyzing drivers’ abilities to perform corrective manoeuvers, and investigating the correlation between these manoeuvers and crash severity provide the opportunity of increasing the knowledge about how to avoid crash occurrence or at least mitigate crash severity. We extend existing research on the determinants of engaging in crash avoidance manoeuvers by considering that observable and unobservable factors relate to both the selection of corrective manoeuvers and the severity outcome. Accordingly, we propose a joint multinomial-logit ordered-probit model of single-vehicle crashes extracted from the NASS GES database for the years 2005–2009. Results show (1) the existence of unobserved correlation between crash avoidance manoeuvers and crash severity, and (2) the link between drivers’ attributes, risky driving behaviour, road characteristics, and environmental conditions, with the propensity to engage in crash avoidance manoeuvers and experience severe crash outcomes.     

NEWS & EVENTS

Abstract

Seat belt use does not only save lives but prevents the severity of injuries in road traffic crashes (RTCs). Vehicle type and usage have been found to influence the use of seat belt in cities like Kumasi, the host of Kwame Nkrumah University of Science and Technology (KNUST) campus. This paper presents a study on an un-obstructive survey of seat belt use by vehicle occupants entering and leaving KNUST campus through the four entrances from 7 to 9 am and 3 to 5?pm on five weekdays. A total of 5489 vehicles with 9542 occupants comprising 5489 drivers, front-right and first back seat and second back seat passengers were observed. The majority of the private and SUV drivers used seat belts. Meanwhile, almost all the commercial drivers did not use seat belts. There is a statistically significant relationship between vehicle type and use and the use of seat belt in KNUST.     

Factors associated with urban non-fatal road-accident severity

This paper reports on the factors associated with non-fatal urban-road accident severity. Data on accidents were gathered from the local traffic police in the City of Palermo, one of the six most populated cities in Italy.

Findings from a mixed-effects logistic-regression model suggest that accident severity increases when two young drivers are involved, road traffic conditions are light/normal and when vehicles crash on a two-way road or carriageway. Speeding is more likely to cause slight or serious injury even when compared to a vehicle moving towards the opposite direction of traffic. An accident during the summer is more likely to result in a slight or serious injury than an accident during the winter, which is in line with evidence from Southern Europe and the Middle East.

Finally, the severity of non-fatal accident injuries in an urban area of Southern Europe was significantly associated with speeding, the age of the driver and seasonality.     

Underreporting,crash severity and fault assignment of minor crashes in China – a study based on self-reported surveys

Unreported minor crashes have importance as a surrogate for more serious crashes that require infrastructure, education, and enforcement strategies; and they still inflict damages. To study factors that influence underreporting, cause, and severity of minor crashes; a survey was performed in Kunming and Beijing to collect self-reported personal characteristics and crash history data of the three major urban road users in China: automobile drivers, bicycle riders and electric bike (e-bike) riders. Underreporting rates of automobile to automobile, automobile to non-motorized vehicle, and non-motorized vehicle to non-motorized vehicle crashes are 56%, 77% and 94%, respectively. Minor crashes with higher reported injury severity levels are more likely to be reported. E-bike riders without a driver's license are more likely to cause crashes. Licensing and education could be an effective way to reduce their crashes. The party that is not at fault in a crash is more likely to sustain high level of injury.     

Identifying the factors behind fatal and non-fatal road crashes: a case study of Lahore,Pakistan

ABSTRACT

The study identifies the factors behind fatal and non-fatal road crashes in Lahore, Pakistan, by investigating 461 reported cases to Traffic Police Lahore that occurred during January–November 2014. Road crashes are categorized into fatal and non-fatal crashes and, because of the binary nature of the dependent variable, logistic regression is used to identify the factors behind these crashes. As a follow-up, discriminant analysis is employed to classify the factors related to fatal and non-fatal crashes. The logistic regression results reveal that females are at higher risk of fatalities than male drivers. Among vehicle types, rickshaws and cars are more involved in fatal accidents because both are growing at large on roads. Long trucks and trailers are also involved in fatal accidents, mainly because of their huge size and drivers’ risky driving behaviours. It is also noted that risk of fatalities is higher in case where two vehicles bumped each other. Speeding and overloading are the common behaviours resulting in fatal crashes. Better urban transport systems and strict compliance with traffic rules and regulations may improve road safety in Pakistan.     

An analysis of risk factors associated with road crash severities in Namibia

Abstract

Road crash is a leading cause of death and disabilities in Namibia and other developing countries. Based on recent trends, the World Health Organization indicated that progress to realize Sustainable Development Goal (SDG) target 3.6 – which calls for a 50% reduction in the number of road traffic deaths by 2020 – remains far from sufficient. To contribute to efforts in reducing road fatalities in Namibia, this study examined risk factors associated with the severity of crashes recorded in the country. Mixed logit modelling methodology was adopted to address the problem of unobserved heterogeneity in injury severity analysis. Model estimation results reveal that collision with pedestrians, head-on collisions, ran-off road collisions and crashes involving high occupancy passenger vehicles were more likely to result in fatalities and severe injuries. The findings and recommendations of this study are expected to enhance countermeasure implementation to reduce road crashes in Namibia.     

The influence of licence status on Kansas child fatalities due to motor vehicle crashes

The influence of driver licensure on child motor vehicle crash (MVC) deaths in Kansas was investigated. Fatalities from 1994-2000 due to MVCs were extracted from the Kansas State Child Death Review Board and the Fatality Analysis Reporting Systems databases. It was found that 14% (52 of 363) of child fatalities from MVCs in Kansas occurred in vehicles where the driver was not licensed. Driver licence status was associated with use of safety restraints, the victim's age and race, weekend driving and rural county location. All child deaths involving unlicensed drivers were preventable. New legislation on vehicle sanctions may be required to assist law enforcement. Safety restraint laws should be enforced and promoted to the public. Transportation options are necessary for unlicensed drivers, particularly if they have young children and live in a rural community. Thus, a multi-system approach involving law enforcement, accident prevention strategies and transportation options will save the lives of children.     

Fatality rate of pedestrians and fatal crash involvement rate of drivers in pedestrian crashes: a case study of Iran

The aim of this study was to uncover patterns of pedestrian crashes. In the first stage, 34,178 pedestrian-involved crashes occurred in Iran during a four-year period were grouped into homogeneous clusters using a clustering analysis. Next, some in-cluster and inter-cluster crash patterns were analysed. The clustering analysis yielded six pedestrian crash groups. Car/van/pickup crashes on rural roads as well as heavy vehicle crashes were found to be less frequent but more likely to be fatal compared to other crash clusters. In addition, after controlling for crash frequency in each cluster, it was found that the fatality rate of each pedestrian age group as well as the fatal crash involvement rate of each driver age group varies across the six clusters. Results of present study has some policy implications including, promoting pedestrian safety training sessions for heavy vehicle drivers, imposing limitations over elderly heavy vehicle drivers, reinforcing penalties toward under 19 drivers and motorcyclists. In addition, road safety campaigns in rural areas may be promoted to inform people about the higher fatality rate of pedestrians on rural roads. The crash patterns uncovered in this study might also be useful for prioritizing future pedestrian safety research areas.     

Gender and age distribution of motorcycle crashes in Spain

This study analysed motorcycle crashes in Spain. Ninety-nine thousand three hundred and four motorcycle crash reports filed in the years 2006–2011 were extracted from the Directorate General of Traffic database of crashes with victims. These data were analysed in terms of gender, age groups, trip purpose, type of crash, speed violation, day of the week, harm caused, use of helmet and psychophysical conditions of the driver to study the characteristics of motorcycle crashes in Spain and to assess the differences between male and female motorcycle drivers in these crashes. Significant differences were found in all the variables considered in the study, which implies gender differences in the profile of the injured motorcycle driver. The severity of motorcycle crashes suffered by male drivers is higher than that of women. These results corroborate the need to develop measures differentiated by gender, based on their profile.     

Hierarchical clustering analysis framework of mutually exclusive crash causation parameters for regional road safety strategies

Hierarchical clustering analysis framework is developed to identify benchmark and critical regions for effective road safety strategies. The regions are grouped based on agglomeration coefficient of mutually exclusive crash causation parameters. Subsequently, regions from groups with lower than a threshold index value are selected as benchmark for the poorly performing critical counterparts. Euclidean distance-based Ward's, median and centroid clustering techniques are explored through a case study of Indian states and Union Territories. As per data between 2006 and 2015, fatal crash percentages of driving under influence of drug and alcohol, excessive speeding, vehicle malfunction and road conditions related crash causation parameters, severity index and its growth rate are assessed based on respective threshold values of 6.35%, 43.28%, 2.42%, 1.79%, 26.7 and 3.1%. These are the national average of respective indices. It demonstrated the unique application of hierarchical clustering analysis in benchmark and critical region identification.     

A study of factors affecting intersection crash frequencies using random-parameter multivariate zero-inflated models

Recent research demonstrates the appropriateness of multivariate regression models in crash count modelling when one specific type of crash counts needs to be analysed, since they can better handle the correlated issues in multiple crash counts. In this paper, a random-parameter multivariate zero-inflated Poisson (RMZIP) regression model is proposed as an alternative multivariate methodology for jointly modelling crash counts simultaneously. Using this RMZIP model, we are able to account for the heterogeneity due to the unobserved roadway geometric design features and traffic characteristics. Our formulation also has the merit of handling excess zeros in correlated crash counts, a phenomenon that is commonly found in practice. The Bayesian method is employed to estimate the model parameters. We use the proposed modelling framework to predict crash frequencies at urban signalized intersections in Tennessee. To investigate the model performances, three models – a fixed-parameter MZIP model, a random-parameter multivariate negative binomial (RMNB) model, and a random-parameter multivariate zero-inflated negative binomial (RMZINB) model – have been employed as the comparison methods. The comparison results show that the proposed RMZIP models provide a satisfied statistical fit with more variables producing statistically significant parameters. In other word, the RMZIP models have the potential to provide a fuller understanding of how the factors affect crash frequencies on specific roadway intersections. A variety of variables are found to significantly influence the crash frequencies by varying magnitudes. These variables result in random parameters and thereby their effects on crash frequencies are found to vary significantly across the sampled intersections.     

Investigation of adolescent accident predictive variables in hilly regions

The study aims to determine the significant personal and environmental factors in predicting the adolescent accidents in the hilly regions taking into account two cities Hamirpur and Dharamshala, which lie at an average elevation of 700--1000 metres above the mean sea level (MSL). Detailed comparisons between the results of 2 cities are also studied. The results are analyzed to provide the list of most significant factors responsible for adolescent accidents. Data were collected from different schools and colleges of the city with the help of a questionnaire survey. Around 690 responses from Hamirpur and 460 responses from Dharamshala were taken for study and analysis. Standard deviations (SD) of various factors affecting accidents were calculated and factors with relatively very low SD were discarded and other variables were considered for correlations. Correlation was developed using Kendall's-tau and chi-square tests and factors those were found significant were used for modelling. They were – the victim's age, the character of road, the speed of vehicle, and the use of helmet for Hamirpur and for Dharamshala, the kind of vehicle involved was an added variable found responsible for adolescent accidents. A logistic regression was performed to know the effect of each category present in a variable on the occurrence of accidents. Though the age and the speed of vehicle were considered to be important factors for accident occurrence according to Indian accident data records, even the use of helmet comes out as a major concern. The age group of 15–18 and 18–21 years were found to be more susceptible to accidents than the higher age groups. Due to the presence of hilly area, the character of road becomes a major concern for cause of accidents and the topography of the area makes the kind of vehicle involved as a major variable for determining the severity of accidents.     

Exploring the factors influencing pedestrian-vehicle crash severity in Dhaka,Bangladesh

Abstract

Although the rate of road crashes and their severity is relatively higher in developing countries, there is still a lack of research on pedestrian-vehicle crash severity in these contexts, particularly in Bangladesh. Therefore, this study aimed to identify the contributing environmental, road, and vehicular factors that influenced pedestrian—single-vehicle crash severity in Dhaka, a megacity and the capital of Bangladesh. A binary logistic regression model was developed in this study by analyzing a data set of pedestrian—single-vehicle crashes involving casualties in Dhaka from 2010 to 2015. The model identified seven significant factors influencing pedestrian-vehicle crash severity. Significant factors increasing the likelihood of fatal crashes included crashes during adverse weather, dawn/dusk period, night period (where street light was absent), off-peak period, crashes where road divider was unavailable, road geometry was straight and flat, and crashes those were occurred by heavier vehicles. Besides, crashes at three-legged intersections were less likely to be fatal. Both similarities and differences were found among the significant factors influencing pedestrian-vehicle crash severity in Dhaka from the findings of the developed countries. The findings of this study would help transport engineers and planners to design safer roadways for both pedestrians and vehicles.     

A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.