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.     

Effects of ethyl alcohol on injuries severity according to injury severity scales in pedestrian fatal injury in traffic crashes

Abstract

Introduction: The dominant cause of injuries in traffic crashes. A significant portion of them affects victims under the influence of ethyl alcohol. The goal of the studies was to assess the correlation between the state of sobriety and the severity of injuries expressed by injury severity scales in fatal pedestrian victims of traffic crashes. Research Material and Method: The data were obtained from the Warsaw Medical University's Department of Forensic Medicine. The analysis covered the data for 2009–2013 and included 200 fatal pedestrian victims hit by passenger cars. The assessment of the effect of risk factors on injury severity expressed in terms of injury severity scales such as Life Threat Indicator (LTI), International Classification based Injury Severity Score (ICISS), Injury Severity Score (ISS) and New Injury Severity Score (NISS), was made using adequately selected methods of statistical analysis. Results: As alcohol concentration increases in women, the values of LTI, ICISS-10 and ICISS-15 decrease, which denotes more severe injuries. In the ISS and NISS, the effect of alcohol concentration on the severity of injuries turned out to be negligible. However, these injuries are significantly heavier in women than in men. According to all the scales used, the older the victims, the milder injuries cause their death. Conclusions: The studies show that ethyl alcohol concentration may harm injury severity, especially in the case of women. The assessment of the severity of injuries in traffic crash victims is significantly influenced by their age and gender. The more risk factors the scale takes into consideration, the more precise is the assessment.     

A hybrid clustering and classification approach for predicting crash injury severity on rural roads

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011–2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.     

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.     

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.     

Road traffic crashes at night-time: characteristics and risk factors

Abstract

The study was to examine the nature and risk factors associated with road traffic crashes at night in Ghana and identify potential measures to control them. Crash and injury data for the period 2013-2017 were analyzed. The fatality index and fatal crash ratio measures were employed to assess the severity of injuries among traffic participants. Statistical analysis was carried out for the variables using contingency tables and the chi-square (χ²) tests to assess statistical significance. Generally, night-time traffic crashes resulted in severer injury outcomes than crashes in the hours of daylight (χ²(2)=292.7, p?<?0.001). The relative risk of death in a night traffic crash was 1.3 times that during the daytime. The risk of death was highest among pedestrians (44%) and motorcyclist (18%) compared to bus/mini-bus occupants (16%) and car occupants (11%) and the observed percentage differences were significant (χ²(14)=2303.2, p?<?0.001). Most of the collisions (67%) occurred at the early hours of the night, between 18:00 and 22:00?hours. Poor night visibility coupled with poor visual guidance on roads are the key contributory risk factors associated with night travels. Policies must be geared towards provision of functioning street lights in built-up areas, road line markings, delineators and signage for the highways and arterial roads.     

Effect of driver,roadway, collision,and vehicle characteristics on crash severity: a conditional logistic regression approach

The aim of the study is to examine the factors that appear to have a higher potential for serious injury or death of drivers in traffic accidents in Turkey, such as collision type, roadway surface, vehicle speed, alcohol/drug use, and restraint use. Driver crash severity is the dependent variable of this study with two categories, fatal and non-fatal. Due to the binary nature of the dependent variable, a conditional logistic regression analysis was found suitable. Of the 16 independent variables obtained from Turkish police accident reports, 11 variables were found most significantly associated with driver crash severity. They are age, education level, restraint use, roadway condition, roadway type, time of day, collision location, collision type, number and direction of vehicles, vehicle speed, and alcohol/drug use. This study found that belted drivers aged 18–25 years involving two vehicles travelling in the same direction, in an urban area, during the daytime, and on an avenue or a street have better chances of survival in traffic accidents.     

Analysis of the effects of visibility and warning devices on driver injury severity at highway-rail grade crossings considering temporal transferability of data

Abstract

This study explores the joint effect of visibility and warning devices on driver injury severity at the highway-rail grade crossings (HRGCs), while also considering other contributing factors. For this purpose, four mixed logit models are developed to estimate the determinants of driver injury severity considering the combinations of visibility conditions (daylight vs. no daylight) and type of warning devices (active vs. passive warning). The models were calibrated using the data obtained from the USDOT Federal Railroad Administration for HRGC crashes that occurred over a ten-year period 2008–2017 Federal Railroad Administration (FRA) Office of Safety Analysis. (2017). Accident data as reported by railroads. Retrieved July, 2018, from https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx [Google Scholar] across the United States. A temporal transferability test was conducted and confirmed the stability of model specifications considering a ten-year span of collected data. The pseudo-elasticity analysis was conducted to ascertain marginal impact of the contributing factors on driver injury severity in each model. While the vehicle speed, train speed, time of day and driver age are found to be common significant factors among the four models, there are marked differences between parameters associated with various crash factors. The study provides new insight into the driver injury severity in train-vehicle collisions considering visibility and type of warning devices, which can help in setting up proper policies to improve safety at HRGCs.     

Cost analysis of road traffic crashes in China

Abstract

Fatalities and injuries resulting from road traffic crashes is always a serious problem. The overall economic losses caused by road traffic crashes are beyond imagination. Including the economic cost of property damage, productivity loss, medical cost, travel delay time cost, legal cost and insurance cost, the total economic cost of traffic crashes in China in 2017 is calculated as 490.1 billion yuan (72.6 billion USD 2017), which is equivalent to 0.60% of the GDP. The cost of productivity loss accounts for the highest proportion of total economic cost, which is 72%. The second is the travel delay cost, accounting for 12% insurance cost, property damage cost and medical cost are followed. The more serious the injury, the higher the unit economic cost. The unit cost of a crash that caused only property damage is 11,274 yuan. The unit cost of a minor injured crash is 20,223 yuan. The highest unit economic cost is the unit cost of a fatal crash, which is 3,181,394 yuan. This study provides important insights into the cost-benefit analysis of China's road safety policies.     

Morbidity and mortality from road traffic crashes in children in Metro West,City of Cape Town – 2014

The road traffic crash injury burden significantly impacts the lives of South African children. This study aimed to assess the fatal and non-fatal pattern of road traffic crash injury of children under 13 years old from Metro West, City of Cape Town, from 1 January until 31 December 2014. The data were stratified by age, sex and mechanism of road traffic crash. The overall mortality rate was 8.7 per 100 000 population and pedestrians contributed the most to this burden (72.5%). There were more male children involved in a road traffic crash (p?=?0.0001). The greatest proportion of fatal and non-fatal road traffic crash injuries was observed in children aged 5–9 years. Fractures contributed to the greatest rate of years lived with disability (3.0 years of life lived with disability per 100 000). Our study found that the burden of road traffic crashes primarily affects male pedestrians aged 5–9 years old.     

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.     

The effect of natural and built environmental characteristics on pedestrian-vehicle crash severity in Ghana

Despite the benefits of walking as a means of travelling, walking can be quite hazardous. Pedestrian-vehicle crashes remain a major concern in Ghana as they account for the highest percentage of fatalities. The objective of this study is to determine the effect of both natural and built environmental features on pedestrian-vehicle crash severity in Ghana. The study is based on an extensive pedestrian-vehicle crash dataset extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana. Using a multinomial logit modelling framework, possible determinants of pedestrian-vehicle crash severity were identified. The study found that fatal crashes are likely to occur during unclear weather conditions, on weekends, at night time where there are no lights, on curved and inclined roads, on untarred roads, at mid-blocks and on wider roads. The developed model and its interpretations will make important contributions to road crash analysis and prevention in Ghana with the possibility of extension to other developing countries. These contributing factors could inform policy makers on road design and operational improvements.     

Identifying the factors contributing to the severity of truck-involved crashes

To address the dilemma between the need for truck transportation and the costs related to truck-involved crashes, the key is to identify the risk factors that significantly affect truck-involved crashes. The objective of this research is to estimate the effects of the characteristics of traffic, driver, geometry, and environment on severity of truck-involved crashes. Based on four crash severity categories (fatal/incapacitating, non-incapacitating, possible injury, and no injury/property damage only), a multinomial logit model is conducted to identify the risk factors. The investigation of risk ratios indicates that lower traffic volume with higher truck percentage is associated with more serious traffic crash with fatal/incapacitating injury while a non-standard geometric design is the main cause of non-incapacitating crashes. The influences of weather are significant for the possible-injury crashes while driver condition is the principal cause of no-injury/property-damage-only crashes. In addition, the statistical results demonstrate that the influence of the truck percentage is significant. One-unit change in the truck percentage will cause more than one times probability of being in an injury.     

Matching of police and hospital road crash casualty records – a data-linkage study in Malaysia

Underreporting of road crashes hampers the development of appropriate road safety countermeasures in many countries. In this study, police and hospital records from road crash casualties in the Melaka Tengah district in Malaysia from 2014 were collected to determine their matching and reporting rates. Based on authentic personal identifiers from both types of records, Microsoft SQL was used to reveal how the matching rate varies due to multiple factors. The results showed that 311 cases (of 7625 hospital records) could be linked to both databases, yielding a 4.1% matching rate and a 4.7% police reporting rate. Both the reporting and matching rates increased with the level of injury severity. The significant underreporting in the police database showed that complementary data are necessary for enhancing the current official crash data records.     

An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data

Retail managers have been interested in learning about cross-category purchase behavior of their customers for a fairly long time. More recently, the task of inferring cross-category relationship patterns among retail assortments is gaining attraction due to its promotional potential within recommender systems used in online environments. Collaborative filtering algorithms are frequently used in such settings for the prediction of choices, preferences and/or ratings of online users. This paper investigates the suitability of such methods for situations when only binary pick-any customer information (i.e., choice/non-choice of items, such as shopping basket data) is available. We present an extension of collaborative filtering algorithms for such data situations and apply it to a real-world retail transaction dataset. The new method is benchmarked against more conventional algorithms and can be shown to deliver superior results in terms of predictive accuracy.     

Under-reporting of road traffic crash data in Ghana

Having reliable estimates of the shortfalls in road traffic crash data is an important prerequisite for setting more realistic targets for crash/casualty reduction programmes and for a better appreciation of the socio-economic significance of road traffic crashes. This study was carried out to establish realistic estimates of the overall shortfall (under-reporting) in the official crash statistics in Ghana over an eight-year period (1997–2004). Surveys were conducted at hospitals and among drivers to generate relevant alternative data which were then matched against records in police crash data files and the official database. Overall shortfalls came from two sources, namely, ‘non-reporting’ and ‘under-recording’. The results show that the level of non-reporting varied significantly with the severity of the crash from about 57% for property damage crashes through 8% for serious injury crashes to 0% for fatal crashes. Crashes involving cyclists and motorcyclists were also substantially non-reported. Under-recording on the other hand declined significantly over the period from an average of 37% in 1997–1998 to 27% in 2003–2004. Thus, the official statistics of road traffic crashes in Ghana are subject to significant shortfalls that need to be accounted for. Correction factors have therefore been suggested for adjusting the official data.     

强跟踪Unscented滤波器及其在无源跟踪中的应用

本文研究用递推算法实现只测量到达角和多普勒频移的无源双基地雷达的目标运动分析。基于Unscented卡尔曼滤波器和强跟踪滤波器,提出了一种新的强跟踪Unscented滤波器算法。新算法在无源双基地雷达目标跟踪的仿真实验中显示了高精度鲁棒滤波的性能。