Introducing Alignment Based Risk Indices into the Highway Traffic Accident Analysis

In recent years there has been serious concern on the increasing rate of road traffic accidents in Nigeria. Geographic Information System (GIS), a high performance computer based tool is useful in road traffic management and vehicular movement study. In this work, the GIS software was used to analyze and depicts the trend and characteristics of road traffic accidents in Nigeria. The data used in this study were obtained from Federal Road Safety Commission Dashboard (FRSC Planning Advisory Unit Analysis) for the year 2012 and 2013 and Nigerian Tribune Publication of Tuesday 3 rd April , 2012. The data obtained was entered and use to developed road traffic accidents information system (RTAIS). Analysis and capability of the developed system was illustrated and shown graphically. A total of 1,060,507 cases of road traffic crashes occurred between the year 1960 and 2012 of which 170,844 were fatal, 456,055 were serious and 428.790 were minor, claiming 322,427 lives. This study further revealed that Federal Capital Territory (FCT) Abuja ranked first with 6.71% based on road traffic crash fatalities per 100,000 human populations on state by state with Kebbi state being the least (0.25%). The GIS –based analysis shows that category of vehicles involved in road traffic crashes in year 2012 on state basis varies with cars having the highest cases(4,632) followed by buses (2,239), motorcycles (1,807),truck(1,037) and tankers/trailers having the least(641). It is recommended that the Nigerian Police Force (NPF), Federal Road Safety Commission (FRSC), Vehicle Inspection Office (VIO) and other agencies linked with road traffic management and safety will find this study useful in identifying remedial measures for the improvement of safety on Nigerian roads. Key Words: Road Traffic, Accident, GIS, Vehicles Analysis, Nigeria

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Traffic accident increased periodically in alarming rate and it was a serious problem throughout the globe particularly in developing countries like Ethiopia. This research concerns on Analyzing Road Traffic Accident in Ethiopia from 2007/08-2017/18. The main objective of the study was to investigate the growth rate of road traffic accident, road network coverage and motorized vehicle, and relationship between them in the past elven (11) year. In order to address the required objective the study use secondary data collected from Ethiopia federal police commission, Ethiopia road authority and Ethiopia federal transport authority. Basically, descriptive and inferential statistical analysis approach was used to analyze the data. The finding of the study revealed that; in the past eleven year more than 291577 Road traffic accident, 912956km road network and 681000 motorized vehicles were developed. Due to Road traffic accident Ethiopia loses around 36.3 billion birr (estimated 1.3 billion $ in current exchange rate of 28 birr for 1$) in the past eleven (11) year in Ethiopia. In average annually Ethiopia loses around 0.9% of budget due to traffic accident in the past eleven year. Average annual growth rate of road traffic accident, road network development and motorized vehicle were 9.16%, 10.81% and 13.34% respectively. In Ethiopia in the past eleven (11) years more than 276491 road traffic accidents, 912956km road network and 681000 number of motorized vehicle were newly introduced since 2007/08 in the study period. The variation on road traffic accident, road network coverage in km and motorized vehicle between commencement of study period (2007/08) or Ethiopia millennium (2000E.C) with end of the study period (2017/18) were estimated around 25914, 82414 and 563003 respectively. Finally, the study intend that road traffic accident had no direct or indirect relation with growth of motorized vehicle and road network coverage in Ethiopia. To curb the problem faced due to road traffic accident the government and other stakeholder must careful the issues to minimize road traffic accidents in Ethiopia.

Traffic accidents cause huge property and life losses, so it is important to study the characteristics of the traffic accidents to reduce the losses and prevent the accidents happening. Applying vectors' inner product method of fuzzy clustering, the traffic accidents data in 2010 in China was analyzed, and the fuzzy similar matrix was established. Then the square method was applied to calculate transitive closure, and the fuzzy equivalent matrix was obtained. Based on the different values of similarity coefficient, dynamic cluster analysis was carried on. Research results indicate that comparing the traffic accident index of the five kinds of traffic modes, namely automobile, motorcycle, tractor, non-motorized vehicle, and pedestrian, traffic accident probability of automobile is the highest, traffic accident probability of tractor, non-motorized vehicle, and pedestrian is similar and in middle level, and traffic accident probability of motorcycle is the lowest.

The highway infrastructure traffic safety performance evaluation is unstable and unreliable based on the traffic accident number or rate directly as well as other non-accident method. The principle of traffic accident spatial distribution along a highway and correlation between highway traffic safety performance and accidents positions for a period of time were researched. An accident aggregation indicator (AAI) was established based on the principle. In order to validate its availability, AAI was applied to evaluate infrastructure traffic safety performance of 6 region highway networks in Heilongjiang Province, China by using traffic accident data occurring on them in the period 3 years. The remarkable difference of AAI was found on 6 region highway networks, which proved the feasibility of the evaluation method based on AAI.

Level crossings between railway and highway causes transportation problems in the form of traffic jams and accidents. The Manahan Flyover development in the Surakarta city is an effort to minimize transportation problems in the Manahan and Kota Barat areas. Field condition shows that traffic congestion in the Manahan Flyover can be minimized, but traffic accident rate is increasing. Within nine months an accident occurred with two dead victims. The potential of traffic accident is inseparable with the design of the Manahan Flyover with the design of three-way intersection. The aim of study is to redesign traffic movement in the Manahan Flyover and surrounding Manahan area. Traffic micro-simulation VISSIM model is used to evaluate the performance of road networks at peak traffic conditions with different simulation models. The scenario simulation model is developed based on the calibrated base simulation model. In order to avoid potential accidents, therefore, the direction of traffic movement at the Manahan Flyover is made with a one-way system. The modelling scenario results indicate that the diversion of traffic movement at the Manahan Flyover must be followed by various traffic management and engineering efforts in the Manahan area including road widening, parking management, application of a one-way system.

Traffic accidents are one of the leading causes of death and disability, as well as a significant source of economic losses for society. However, the nonlinear and heterogeneous relationships between environmental factors and traffic accidents are complex and difficult to comprehend. This study constructs an explainable spatial machine learning framework using a geographically weighted support vector machine (GW‐SVM) model to address issues of nonlinearity, spatial heterogeneity, and interpretability. Based on a large‐scale traffic accident dataset and multisource big data, this study provides both global and local explanations for the nonlinear relationships in California, USA. The study finds that (1) humidity plays a more important role in the relationship between environmental factors and traffic accident severity; (2) all environmental variables, including both natural and socioeconomic variables, exhibit nonlinear and threshold effects on traffic accidents; and (3) compared to the existing models, the GW‐SVM model performs better in predicting the severity of traffic accidents on urban roads. The results of this study are significant for reducing traffic accident risks.

GIS-based Economic Cost Estimation of Traffic Accidents in St. Louis, Missouri

SummaryBackgroundDrink driving is an important risk factor for road traffic accidents (RTAs), which cause high levels of morbidity and mortality globally. Lowering the permitted blood alcohol concentration (BAC) for drivers is a common public health intervention that is enacted in countries and jurisdictions across the world. In Scotland, on Dec 5, 2014, the BAC limit for drivers was reduced from 0·08 g/dL to 0·05 g/dL. We therefore aimed to evaluate the effects of this change on RTAs and alcohol consumption.MethodsIn this natural experiment, we used an observational, comparative interrupted time-series design by use of data on RTAs and alcohol consumption in Scotland (the interventional group) and England and Wales (the control group). We obtained weekly counts of RTAs from police accident records and we estimated weekly off-trade (eg, in supermarkets and convenience stores) and 4-weekly on-trade (eg, in bars and restaurants) alcohol consumption from market research data. We also used data from automated traffic counters as denominators to calculate RTA rates. We estimated the effect of the intervention on RTAs by use of negative binomial panel regression and on alcohol consumption outcomes by use of seasonal autoregressive integrated moving average models. Our primary outcome was weekly rates of RTAs in Scotland, England, and Wales. This study is registered with ISRCTN, number ISRCTN38602189.FindingsWe assessed the weekly rate of RTAs and alcohol consumption between Jan 1, 2013, and Dec 31, 2016, before and after the BAC limit came into effect on Dec 5, 2014. After the reduction in BAC limits for drivers in Scotland, we found no significant change in weekly RTA rates after adjustment for seasonality and underlying temporal trend (rate ratio 1·01, 95% CI 0·94–1·08; p=0.77) or after adjustment for seasonality, the underlying temporal trend, and the driver characteristics of age, sex, and socioeconomic deprivation (1·00, 0·96–1·06; p=0·73). Relative to RTAs in England and Wales, where the reduction in BAC limit for drivers did not occur, we found a 7% increase in weekly RTA rates in Scotland after this reduction in BAC limit for drivers (1·07, 1·02–1·13; p=0·007 in the fully-adjusted model). Similar findings were observed for serious or fatal RTAs and single-vehicle night-time RTAs. The change in legislation in Scotland was associated with no change in alcohol consumption, measured by per-capita off-trade sales (−0·3%, −1·7 to 1·1; p=0·71), but a 0·7% decrease in alcohol consumption measured by per-capita on-trade sales (−0·7%, −0·8 to −0·5; p<0·0001).InterpretationLowering the driving BAC limit to 0·05 g/dL from 0·08 g/dL in Scotland was not associated with a reduction in RTAs, but this change was associated with a small reduction in per-capita alcohol consumption from on-trade alcohol sales. One plausible explanation is that the legislative change was not suitably enforced—for example with random breath testing measures. Our findings suggest that changing the legal BAC limit for drivers in isolation does not improve RTA outcomes. These findings have significant policy implications internationally as several countries and jurisdictions consider a similar reduction in the BAC limit for drivers.FundingNational Institute for Health Research Public Health Research Programme.

ObjectiveTo identify determinants of regional differences in traffic accident mortality in Italy.Data and methodsMultiple linear regression models were conducted assessing the associations between regional differences in traffic mortality, case fatality and accident rates (dependent variables) with socio-demographic factors, and variables describing road behaviour, vehicles, infrastructure and medical care (independent variables). Data were derived from the National Institute of Statistics, the National Institute of Health and the Italian Automobile Club. In addition to analyses for the whole country of Italy, separate models were conducted for Northern and southern regions.ResultsIn Italy large regional differences in traffic mortality rates can be observed, ranging from 5.5 to 20 per 100.000 person-years. There is a North-South gradient with higher mortality rates in the Northern part of Italy. Strong predictors of regional differences in both traffic mortality and accident rates are the employment rate (directly associated) and alcohol use (directly associated). This is observed in the whole of Italy, and separately in Northern and southern regions.ConclusionOur study has shown the need for regional policies to improve road behaviour to reduce traffic accident and mortality rates in identified high-risk areas.

ABSTRACTObjective: This study aimed to describe the trends of motorization and mortality rates from road traffic accidents and examine their associations in a rapidly urbanizing city in China, Shenzhen.Methods: Using data from the Shenzhen Deaths Registry between 1994 and 2013, we calculated the annual mortality rates of road traffic accidents, in addition to the age- and sex-specific mortality rates and their annual percentage changes (APCs) for the period of 2000–2013. We also examined the associations between mortality rate of road traffic accidents and traffic growth with Spearman's rank correlation analysis and a log-linear model derived from Smeed's law.Results: A total of 20,196 deaths due to road traffic accidents, including 14,391 (71.3%) male deaths and 5,805 (28.7%) female deaths, were recorded in Shenzhen from 1994 to 2013. The annual mortality rates in terms of deaths per population and deaths per vehicle changed in similar patterns, demonstrating an increase since 1994 and peaking in 1997, followed by a steady decrease thereafter. The decrease in mortality was faster in individuals aged 20 year or older compared to those younger than 20 years. The mortality rates in term of deaths per population were positively correlated with the total number of vehicles per kilometer of road but negatively correlated with the motorization rate in term of vehicles per population. The estimated model for deaths due to road traffic accidents in relation to the total population and the number of registered vehicles was ln (deaths/10,000 vehicles) = −1.902 × ln (vehicles/population) − 1.961. The coefficient was statistically significant (P < .001) and the coefficient of determination was 0.966, indicating a good model fit.Conclusions: We described a generally decreasing trend in the mortality rates of road traffic accidents in a rapidly urbanizing Chinese city based observations in the 20-year period from 1994 to 2013. The decreased mortality rate may be explained by the expansion of road network construction, improved road safety regulations and management, as well as more accessible ambulance services in recent years. Nevertheless, road traffic accidents remain a universal problem of great public health concern in the whole population.

There has been a growing concern in traffic road accident rates in recent years. Thailand's average death rate of 24,326 people per year is the second highest globally. It is now down to 32.7 per 100,000 inhabitants, with 22,491 deaths per year and an average of 60 deaths per day. While Thailand has the third-highest proportion of motorcycle-related deaths globally at 74.4%, it has a population of over 66 million with a fatality rate of 24.3 motorcyclists per 100,000 people. In addition, when considering the report of the leading presumptive causes of road accidents, it was found that the leading causes of the crash can be classified by general characteristics of collisions and their contributing factors collisions (human factors, vehicle factors and road and environment factors). This paper focuses on the case of the suburban area by applying the spatial-statistical analysis to identify the risk locations of motorcycle traffic accidents (known as “hot spots”). Kernel Density Estimation (KDE), data plots and space and time pattern mining tools are used to describe spatial hotspots. The finding can help in the measurement of motorcycle traffic accidents reduction and effectively improve road safety situation, which is crucial to investigate the root cause of road traffic accidents with an in-depth understanding of spatial patterns of this problematic.

A combined and thorough medical and engineering study of road traffic accidents in Iraq is presented in this paper. The medical investigation covered about 1500 road traffic accident patients transported by ambulance to various hospitals in Baghdad. In most cases, the medical survey team covered the diagnosis of the injury as soon as it was confirmed and death at the moment of arrival of the patient to the emergency department of the hospital. Multi-organ injury was predominating and the required injuries were performed successfully for single organ injury but the chance of successful operation decreased as the number of injured organs increased. To arrive at the major cause of death and/ or heavy injured road traffic accident patients, analysis of speed of vehicles on rural highways in Iraq was made. The traffic engineering study revealed that high speed of vehicles, exceeding the design speed of the highway with abnormality of spot speed distribution, was the major reason of such severe accidents. Death rate from road traffic accident in Iraq is 44.7 which makes Iraq the fourth country in the rate of road traffic accidents. Road traffic accidents are leading cause of both internal and external injuries and major cause of death. This paper reveals that liver, spleen and neck were the most reported organ injuries in road traffic accidents in Iraq. Pre hospital care, time between the crash and the admission to a trauma center and the availability of trauma center can affect significantly the outcome of the crash. Similarly, the use of seat belt, front and sideway airbags can decrease the rate of organs injuries due to road traffic accidents. A comparison of results of this study with those in other studies in different countries is presented and both agreements and disagreements are discussed.

Analysis of traffic accident causes based on data augmentation and ensemble learning with high-dimensional small-sample data

Road traffic accidents (RTA) are commonly encountered incidents that can cause injuries, death, and property damage to members of society. Ethiopia is one of the highest incident rates of road traffic accidents. Report of Transport and Communication from 2012 to 2014, shows an increment in the number of traffic accidents in Ethiopia. Amhara region accounted for 27.3% of the total road traffic accident-related deaths in Ethiopia during the year 2008/9, which is the highest share among all regions in Ethiopia. The current research aims to model the trend of injury, fatal and total road traffic accidents in the Amhara region from September 2013 to May 2017. Monthly reported traffic accidents were obtained from the traffic department of the Amhara region police commission. The most universal class of models for forecasting time series data called Auto-regressive Integrated Moving Averages (ARIMA) models were applied to model the trends and patterns of road traffic accident cases in the Amhara region. The average number of observed injury RTA, fatal RTA, and total RTA were 27.2, 14, and 78.2 per month respectively. It was observed that a relatively large number of RTA’s are reported on Tuesday, Thursday, and Saturday relative to other days of the week. The data also reveals that more than 60% of accidents involve drivers between the ages of 18–30 years. ARIMA (2,0,0) (1,0,0) ARIMA (2,0,0) and ARIMA (2,0,0) (1,1,0) were fitted as the best model for total injury accidents, fatal RTA and total RTA data respectively. A 48 months forecast was made based on the fitted models and it can be concluded that road traffic accident cases would continue at the non-decreasing rate in the Amhara region for the predicted periods. Therefore, the findings of this study draw attention to the importance of implementing improved better policies and close monitoring of road trafficking to change the existing non-decreasing trend of road traffic accidents in the region.