Severe Traffic Accidents Research Articles

Monitoring the Dynamic Behaviour of Concrete Bridges Using Non-Contact Sensors (IBIS-S)

The maintenance and operation of bridges represent a significant investment in both the public and private domains. In practice, the structural damage of a bridge that accumulates over its life-span is a result of continuous degradation caused mainly by traffic conditions and sudden extreme events (e.g. flooding, fires and severe traffic accidents). However, under heavy truck loading, the deterioration rate of a bridge can be accelerated. As the use of heavier articulated trucks becomes increasingly popular in contemporary freight transportation systems, the development of modern Non-Destructive Testing (NDT) techniques in conjunction with computational modelling becomes necessary. The advancement in this area will allow rapid assessment of the structural health of bridges and detection of ongoing damage to enhance the structural performance of bridges.

Discriminant Analysis of Factors Affecting Traffic Accident Severity During Daytime and Nighttime

PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.

Severity Prediction of Traffic Accident Using an Artificial Neural Network

AbstractIn this paper, an artificial neural network (ANN) was used to predict the injury severity of traffic accidents based on 5973 traffic accident records occurred in Abu Dhabi over a 6‐year period (from 2008 to 2013). For each accident record, 48 different attributes had been collected at the time of the accident. After data preprocessing, the data were reduced to 16 attributes and four injury severity classes. In this study, WEKA (Waikato Environment for Knowledge Analysis) data‐mining software was used to build the ANN classifier. The traffic accident data were used to build two classifiers in two different ways. The whole data set were used for training and validating the first classifier (training set), while 90% of the data were used for training the second classifier and the remaining 10% were used for testing it (testing set). The experimental results revealed that the developed ANN classifiers can predict accident severity with reasonable accuracy. The overall model prediction performance for the training and testing data were 81.6% and 74.6%, respectively. To improve the prediction accuracy of the ANN classifier, traffic accident data were split into three clusters using a k‐means algorithm. The results after clustering revealed significant improvement in the prediction accuracy of the ANN classifier, especially for the training dataset. In this work, and in order to validate the performance of the ANN model, an ordered probit model was also used as a comparative benchmark. The dependent variable (i.e. degree of injury) was transformed from ordinal to numerical (1, 2, 3, 4) for (minor, moderate, sever, death). The R tool was used to perform an ordered probit. For each accident, the ordered probit model showed how likely this accident would result in each class (minor, moderate, severe, death). The accuracy of 59.5% obtained from the ordered probit model was clearly less than the ANN accuracy value of 74.6%. Copyright © 2016 John Wiley & Sons, Ltd.

Multiobjective Optimization of Roadway Lighting Projects

AbstractRoadway lighting systems play a major role in maintaining nighttime traffic safety as they reduce both the number and severity of nighttime traffic accidents. While the design of roadway lighting systems involves multiple objectives, past studies have focused on optimizing only one of the multiple objectives that should be considered. This paper presents a multiobjective optimization model for roadway lighting projects that simultaneously optimizes four design objectives. The incorporated objectives are (1) maximizing the average lighting level on the road surface; (2) maximizing the lighting uniformity along the roadway; (3) minimizing the glare to road users produced by the lighting system; and (4) minimizing the cost of operating the lighting system. The model is designed and developed as a multiobjective genetic algorithm to help decision-makers in their endeavor to provide efficient roadway lighting systems that strike a balance between the four conflicting objectives. The present model consi...

Spatial analysis of data frequency and severity of rural accidents

In this paper, to study the frequency and severity of traffic accidents, a combination of geographic information system and spatial analysis has been used. For this purpose, methods of planar and network statistics including kernel density estimation and nearest neighbor distance analysis were applied for three types of accidents including fatal, injury, and material property damages. In addition, drawbacks of the traditional planar point pattern and the benefits of network analysis are offered. The network statistics are executed through SANET version 4 and ArcMap on the Semnan–Garmsar road in Iran. The nearest neighbor output analysis is consist of four curves, and regarding the fact that the amounts for accidents resulting in fatalities, injuries, and damages, the observed value curve is above the 5% confidence interval; accidents in the study region are more clustered than would be expected by random chance.

Encounter with Psychoanalysis: How I Became a Psychoanalyst

ABSTRACTI encountered psychoanalysis for the first time in my registrar time, when I treated some borderline patients and read borderline papers by Dr. Kernberg. Later, I studied psychoanalytic clinical practice at The Tavistock Clinic in London. This greatly influenced me to choose to be a psychoanalyst.When I was 10, I was involved in a severe traffic accident and was hospitalized. I met many victims and survivors of the atomic bomb there. All of them were suffering from heavy mental trauma. My father himself was harmed in the atomic bomb attack, and he also survived but suffered from profound mental pain and agony through his life. I show that these experiences were influential background for my understanding the importance of psychoanalysis.

A Space–Time Multivariate Bayesian Model to Analyse Road Traffic Accidents by Severity

SummaryThe paper investigates the dependences between levels of severity of road traffic accidents, accounting at the same time for spatial and temporal correlations. The study analyses road traffic accidents data at ward level in England over the period 2005–2013. We include in our model multivariate spatially structured and unstructured effects to capture the dependences between severities, within a Bayesian hierarchical formulation. We also include a temporal component to capture the time effects and we carry out an extensive model comparison. The results show important associations in both spatially structured and unstructured effects between severities, and a downward temporal trend is observed for low and high levels of severity. Maps of posterior accident rates indicate elevated risk within big cities for accidents of low severity and in suburban areas in the north and on the southern coast of England for accidents of high severity. The posterior probability of extreme rates is used to suggest the presence of hot spots in a public health perspective.

Examines the role of human factors in the severity of traffic accidents in urban areas, with an emphasis on motorcyclists

Every year 1.2 million people worldwide lose their lives due to traffic accidents and more than 50 million others are injured. Ninety percent of deaths caused by traffic accidents involving low or middle income countries. Statistics show that in Iran. After cardiovascular diseases, traffic accidents are the leading cause of death in all age groups and is the first cause of death in those under forty years. Pedestrians, cyclists, motorcyclists, drivers and passengers in cars and other vehicles, are at greater risk of high-risk road user as they remembered. Among the most important role in preventing accidents drivers in this traffic, so that a driver unsafe driving not only their lives, but the lives of others in danger. Amending and enforcing laws and traffic regulations, creating safe way and promote a safety culture among the factors reducing traffic accidents are statistics. Given the importance of this paper is descriptive - analytic method has been tried, the role of human factors in the severity of traffic accidents in cities, with an emphasis on motorcyclists in the city of Eslamshahr - Saveh Road to be addressed. Research findings show an increase in the number of vehicles, facilitating increased sales of motorcycles, young population and special charm motorcycles over the past decade, production, sale and use of motorcycles in the country has an increasing trend. And consequently the number of fatal crashes, injury and damage to the motorcycle riders were guilty, relative to the total vehicle accidents, rising substantially shows.

Speed Compliance in Freeway Variable Speed Limit System – Case Study of the Prague City Ring

Many previous studies have confirmed the strong relationship between speed compliance and the frequency and severity of traffic accidents. Variable...

Prevention and control of traffic incidents, with priority given to high-risk motorcyclists Tehran Municipality in Region

The results are alarming facts about the country and has achieved the risky behavior motorcyclists. Motorcyclists are the most frequent victims of accidents on urban streets and rural Iran and with risky behaviors that put themselves and others at risk. Without understanding the causes of these behaviors, health and safety will not be effective. Pedestrians, cyclists, motorcyclists, drivers and passengers in cars and other vehicles, are at greater risk of high-risk road user as they remembered. Among the most important role in preventing accidents drivers in this traffic, so that a driver unsafe driving not only their lives, but the lives of others in danger. Amending and enforcing laws and traffic regulations, creating safe way and promote a safety culture among the factors reducing traffic accidents are statistics. Given the importance of this paper is descriptive - analytic method has been tried, the role of human factors in the severity of traffic accidents in cities, with an emphasis on motorcyclists in the Tehran Municipality in Region 1 to be addressed. Research findings show an increase in the number of vehicles, facilitating increased sales of motorcycles, young population and special charm motorcycles over the past decade, production, sale and use of motorcycles in the country has an increasing trend. And consequently the number of fatal crashes, injury and damage to the motorcycle riders were guilty, relative to the total vehicle accidents, rising substantially shows.

Impact Assessment of Speed Calming Measures on Road Safety

Traffic calming and speed reduction are one of the core factors that influences traffic accident rate and severity. In the last decades a lot of speed calming measures were implemented in the Lithuanian roads of national significance and city streets. As it was foreseen the result was very effective. The paper presents research methodology and analysis of results of vertical traffic calming measures (speed bumps, speed humps, raised crosswalks), safety islands and speed cameras influence to the road safety on Lithuanian roads.

Risk analysis for severe traffic accidents in long road tunnels

In the recent years, with a globally increasing private motoring, tunnelling has gained a particular importance. After a series of dramatic accidents, the public opinion has turned its attention to tunnel fire safety. This paper focuses on the risk analysis in road tunnels, using the well-established Europe PIARC-OECD Quantitative Risk Assessment Model (QRAM). In the first part, a brief literature review - also on forensic investigations in tunnels - is performed, and the logic behind this method is briefly reassumed, focusing on the risk indicators. In the second part, a comprehensive risk analysis is performed in a long tunnel in Southern Italy, accounting for multifaceted aspects and parameters. The paper is completed with a sensitivity analysis on specific parameters that have an influence on the risk.

Analysis of traffic accident severity on Great Britain roadways and junctions

Safety and accident issues are considered one of most important problem of the world. The purpose of this paper is to identify the factors that are more significant than other factors. The study collected STATS19 accident data from the UK data service over the year 2011 to 2013. Two separate analyses have been done for roadways and for junctions of Great Britain. Depending on characteristics of data and outcome variables, different statistical models have been used in previous researches. These are: type of vehicle, gender of driver, age of driver, time of day, day of week, season of year, speed limit, light condition and weather condition. First, a preliminary analysis has been conducted by frequency distribution. Finally a multivariate analysis has been done by developing two models for roadways and for junctions. One variable shows no difference in probability on severity. Detected significant factors are: motor cycle, male driver, elderly driver age above 60 years, midnight and early morning, non-built-up areas with speed limit >40 mph, darkness without lighting, fine weather.

Analysis of traffic accident severity on Great Britain roadways and junctions

Safety and accident issues are considered one of most important problem of the world. The purpose of this paper is to identify the factors that are more significant than other factors. The study collected STATS19 accident data from the UK data service over the year 2011 to 2013. Two separate analyses have been done for roadways and for junctions of Great Britain. Depending on characteristics of data and outcome variables, different statistical models have been used in previous researches. These are: type of vehicle, gender of driver, age of driver, time of day, day of week, season of year, speed limit, light condition and weather condition. First, a preliminary analysis has been conducted by frequency distribution. Finally a multivariate analysis has been done by developing two models for roadways and for junctions. One variable shows no difference in probability on severity. Detected significant factors are: motor cycle, male driver, elderly driver age above 60 years, midnight and early morning, non-built-up areas with speed limit >40 mph, darkness without lighting, fine weather.

A Study on the Analysis of Driver Behavior in Traffic Accidents Using Driving Video Recorder

The automobiles in Korea have approximately 60 years of history and this is relatively short compared to advanced countries. However, considering the traffic accident rate or severity related to automobiles, various efforts are required to reduce traffic accidents. Various problems caused by traffic accidents are not only related to individual damages but also have become social problems. In order to resolve this, it is important to analyze the cause of traffic accidents. This study aims to suggest methods to reduce traffic accidents by analyzing driving behavior, which is one of the reasons for a number of traffic accidents that were collected through traffic accident videos reported using DVRs (Driving Video Recorder) and were aired to the public via a SBS TV program for the past two years and four months. In particular, unlike other existing studies that aim at analyzing the causes of traffic accidents simply using data, this study constructed a database by analyzing every single DVR that stores the situation before and after the accident using relatively high-resolution video information to provide practical plans to reduce traffic accidents through statistical analysis.

Bayes classifiers for imbalanced traffic accidents datasets

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009–2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents.

Analysis of Factors Affecting Traffic Accident Severity on Freeway Climbing Lanes

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.

Análise da severidade dos acidentes com motocicletas utilizando modelos probit e logit ordenados

<h2>O ambiente de circulação rodoviário brasileiro tem apresentado um aumento desproporcional da utilização de motocicletas ao longo dos últimos 15 anos. A mesma tendência acompanha o número de acidentes de trânsito da categoria em parte por sua relativa vulnerabilidade. O objetivo deste trabalho é identificar fatores que influenciam a severidade dos acidentes com motocicletas nas vias urbanas de Fortaleza com a utilização dos modelos ordenados do tipo probit e logit. Foram desenvolvidos modelos ordenados categóricos utilizando uma amostra com 3.232 observações de acidentes de trânsito de 2004 a 2011. A severidade resultante dos acidentes de trânsito foi classificada em quatro categorias. Os resultados da calibração dos modelos indicaram que motociclistas que utilizam capacete e pilotam durante o dia têm um menor risco de sofrer lesões mais graves. De outra forma, motociclistas mais velhos e que sofreram acidente ocorrido em finais de semana apresentaram um maior risco de lesões mais graves</h2>

Traffic accidents and the London congestion charge

In a rare effort to internalize congestion costs, London recently instituted charges for traveling by car to the central city during peak hours. Although the theoretical influence on the number and severity of traffic accidents is ambiguous, we show that the policy generated a substantial reduction in both the number of accidents and in the accident rate. At the same time, the spatial, temporal and vehicle specific nature of the charge may cause unintended substitutions as traffic and accidents shift to other proximate areas, times and to uncharged vehicles. We demonstrate that, to the contrary, the congestion charge reduced accidents and the accident rate in adjacent areas, times and for uncharged vehicles. These results are consistent with the government's objective to use the congestion charge to more broadly promote public transport and change driving habits.