scholarly journals Development of models to study traffic accidents on the final sections of access roads to the cities: a case study of three major Iranian cities

2021 ◽  
Vol 59 (3) ◽  
pp. 129-148
Author(s):  
Mehdi Fallah Tafti ◽  
Reza Roshani
Keyword(s):  
Traffic Accidents ◽  
Probabilistic Models ◽  
Negative Binomial ◽  
Ann Model ◽  
Lighting Condition ◽  
Traffic Characteristics ◽  
Ann Models ◽  
Accident Rates ◽  
Roadway Lighting ◽  
Major Factors

The final sections of main access roads to the cities require especial attention as the frequency of accidents in these road sections are considerably higher than other parts of interurban roads. These road sections operate as an interface between the rural roads and urban streets. The previous researches available on this subject are limited and they have also mainly focused on a narrow range of factors contributing to the accidents in these areas. The main contribution of this research is to consider a relatively comprehensive range of potential factors , and to examine their impacts through the development and comparison of both conventional probabilistic models and Artificial Neural Network (ANN) models. For this purpose, information related to the main access roads of three major Iranian cities were collected. This information consisted of accident frequency data together with the field observations of traffic characteristics, road-way conditions and roadside features of these roads. Various ANN and probabilistic models were developed. The frequency of accidents, i.e. fatal, injured, or damaged accidents, was considered as the output of the developed models. The results indicated that a hybrid of ANN models, each comprised of 10 input variables representing traffic, roadway and roadside conditions, outperformed several probabilistic models, i.e. Poisson, Negative binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial models, also developed under similar conditions in this study. Moreo-ver, effective roadway width, roadway lighting condition, the standard deviation of vehicles speed, percentage of drivers violating the speed limit, average annual daily traffic, percentage of heavy goods vehicles, the density of road-side commercial and industrial landuses, the density of median U-turns, the density of local access roads, and the effective width of the left-side shoulder were identified as the most effective factors contributing to the accidents in these areas. The developed ANN model can be used as a tool to predict accident rates in these road sections, and to estimate a potential reduction in the accident rates, following any improvements in the major factors contributing to the traffic accidents in these areas.

scholarly journals Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 926
Author(s):  
Huimin Ge ◽  
Mingyue Huang ◽  
Ying Lu ◽  
Yousen Yang
Keyword(s):  
Prediction Model ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Absolute Error ◽  
Vehicle Speed ◽  
Time To Collision ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Conflict Prediction

Due to the randomness and weak symmetry of traffic accidents occurring in the expressway maintenance operation area, it is difficult to use the number of traffic accidents to evaluate the safety of maintenance operation areas. In this paper, the traffic characteristics and traffic conflicts of the maintenance operation area with the lane closed on the outside of the two-way four-lane expressway are studied. By using the statistical method, the distribution of vehicle speed and time headway in different areas of the maintenance operation area are analyzed, and the queuing characteristics of vehicles in the upstream transition zone of the expressway are determined. Based on improved time to collision (TTC) model, the traffic conflict severity of expressway maintenance operation area is divided. The negative binomial distribution is used to establish a traffic conflict prediction model for the enclosed maintenance area of the outer lane of the expressway, and the validity of the traffic conflict prediction model is verified based on the average absolute error percentage (MAPE). The research results show that: when the 0 < TTC < 1.3 s, the traffic conflict is serious conflict; when 1.3 s < TTC, the traffic conflict is non-serious conflict. Furthermore, the traffic conflict prediction model has high accuracy, the MAPE of the warning area and the upstream transition area are 10.8% and 5.0%, respectively.

scholarly journals Statistical modeling of number of human deaths per road traffic accident in Oromia region, Ethiopia

2020 ◽  
Author(s):  
Merga Abdissa Aga ◽  
Berhanu Teshome Woldeamanuel ◽  
Mekonnen Tadesse
Keyword(s):  
Young People ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Daily Basis ◽  
Road Traffic Accidents ◽  
Factors Associated ◽  
Major Factors

Abstract Abstract Background : Globally, road traffic accidents are leading causes of death among young people in general, and the main cause of death among young people aged 15–29 years. This study was conducted to identify the major factors associated with the number of human deaths by road traffic accident in the Oromia Regional State, Ethiopia. Methods: We used data obtained from the Oromia Police Commission Bureau that have been recorded on daily basis road traffic accidents from July, 2016 - July, 2017. Count regression models were was used to assess the factors associated with the number of human deaths from traffic accidents. Results : Of the total of 3900 road traffic accidents included in the 1188 (30.5%) were giving rise to fatal. The Hurde models were of better fit than zero inflated Poisson and zero inflated negative binomial model. Thus, the Hurdle Poisson is recommended in this study. Age of the driver 31-50 years (AOR = 0.289, 95%CI: 0.175, 0.479) and higher than 50 years of age (AOR = 0.311, 95%CI: 0.129, 0.751), driver’s years of experience 5-10 years (AOR = 0.014, 95%CI: 0.007, 0.027), and more than 10 years (AOR = 0.101, 95%CI: 0.057, 0.176), vehicle type automobile (AOR = 8.642, 95%CI: 2.7644, 27.023), vehicle years of service 5-10 years (AOR = 2.484, 95%CI: 1.194, 5.169), and more than 10 years (AOR = 2.639, 95%CI: 1.268, 5.497), type of accident, vehicle upside down (AOR = 5.560, 95%CI: 2.506, 12.336), causes of accident, turning illegal position (AOR = 0.454, 95%CI: 0.226, 0.913), area of accident, residential place (AOR = 108.506, 95%CI: 13.725, 857.798), working areas (AOR = 129.606, 95%CI: 16.448, 1021.263), near hospitals (AOR = 23.789, 95%CI: 3.038, 186.298), geographical locations, Western zones (AOR = 0.275, 95%CI: 0.167, 0.455), and South east zones (AOR = 0.624, 95%CI: 0.410, 0.950) were significant associated number of human deaths per road traffic accident factors in the study area. Conclusion : In this study, 30.5% of accidents were giving rise to at least one human death per road traffic accident and different associated numbers of human deaths per traffic accident factors have been identified.

دية القتل الخطأ في الحوادث المرورية في الفقه الإسلامي: دراسة مقارنة Blood Money for Unintended Manslaughter in Traffic Accidents in Islamic Jurisprudence: A Comparative Study

2015 ◽  
Vol 12 (1) ◽  
pp. 1-29
Author(s):  
عارف علي عارف القره داغي ◽  
فايزة بنت إسماعيل ◽  
ئاوات محمد آغا بابا
Keyword(s):  
Comparative Study ◽  
Mutual Fund ◽  
Traffic Accidents ◽  
Comparative Method ◽  
Inductive Approach ◽  
Legal Provisions ◽  
Islamic Jurisprudence ◽  
The Subject ◽  
Blood Money ◽  
Major Factors

الملخّصيتعلق هذا البحث بموضوع دية القتل الخطأ في الحوادث المرورية في الفقه الإسلامي في العصر الحاضر لكثرة وقوعها وحاجة الناس إلى بيان أحكامها من حيث كيفية تقديرها. وتحرير الخلاف في دية المرأة، ومسألة دية الجنين في حال تعرضه للموت في بطن أمه نتيجة الحادث المروري، أو في حالة تعرضه للإجهاض والموت، وتناول أيضًا دية شخصين إذا ماتا نتيجة اصطدام سيارتين؛ فكيف تقدَّر الدِّية؟ وعالج البحث مسألة العاقلة في الوقت الحاضر التي تساعد الطرفين (الجاني والمجني عليه وذلك بجمع الدية وإعطائها للمجني عليه). وذلك من خلال استخدام المنهج الاستقرائي والمنهج المقارن: حيث يتم من خلاله جمع النصوص المتعلقة بالموضوع، وآراء العلماء المتقدمين، والمعاصرين، والمقارنة بينهما لمعرفة نقاط الاتفاق والاختلاف، لتجلية معالم الموضوع، وتسهيل مناقشتها بصورة دقيقة، ثم بيان الرأي الراجح. وقد توصلت الدراسة إلى أنَّ دية القتل في الحوادث المرورية في العصر الحاضر تساوي بالدينار الذهبي، الذي يساوي 4.250 جرامًا من الذهب، أو بما يساويها من النقد. وأنَّ الراجح هو تساوي دية الرجل مع دية المرأة. وفي حالة عدم وجود العاقلة لابأس من إنشاء شركة تعاونية لمساعدة من وقع منه الحادث.الكلمات المفتاحية: الدِّية، حوادث المرور، دية المرأة، دية الجنين، العاقلة. Abstract         This research addresses the subject of blood money for unintended manslaughter in traffic accidents according to Islamic jurisprudence in the present era due to the frequency of their occurrence and the need for people to understand the legal provisions concerning determining the amount. In this regard, we seek to clarify the disagreements regarding the blood money for women and foetuses that die in the mother’s womb as a result of traffic accidents or abortion. We also address the issue of blood money for two people who die as a result of collision between two cars. We also examine the issue of ʿĀqilah (those who pay the blood money) who helped the two parties (the offender and the victim by collecting blood money and giving it to the victim). To clarify these issues, we use the inductive approach and comparative method wherein we collect the various texts on the subject, and the views of classical and contemporary scholars to engage in a comparison between them in order to identify the points of agreement and disagreement between views. From here, we also hope to identify the major factors pertaining to such issues in order to facilitate a precise and concrete discussion to arrive at the most correct opinion. The study found that blood money for manslaughter in traffic accidents in the present era is equal to a gold dinar, which is equal to 4.250 grams of gold, or its cash equivalent. We advocate that the correct view is that the amount of blood money paid to a man is equal to that of a woman, and that in the absence of an ʿĀqilah it is possible to form a cooperative or mutual fund to render assistance to the victim.Keywords: blood money, traffic accidents, women, foetus, ʿĀqilah.

scholarly journals Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhonghui Thong ◽  
Jolena Ying Ying Tan ◽  
Eileen Shuzhen Loo ◽  
Yu Wei Phua ◽  
Xavier Liang Shun Chan ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Sensitivity Threshold ◽  
Ann Model ◽  
Blood Samples ◽  
Ann Models ◽  
Artificial Neural ◽  
The Impact ◽  
Age Prediction

AbstractRegression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction than the regression model. Additionally, we showed that ethnicity did not affect age prediction among local Chinese, Malays and Indians. Although the predicted age of males were marginally overestimated, sex did not impact the accuracy of age prediction. Lastly, we present a one locus, dual CpG model using 25 ng of input DNA that is sufficient for forensic age prediction. In conclusion, the two ANN models validated would be useful for age prediction to provide forensic intelligence leads.

Are Older Drivers Safe on Interchanges? Analyzing Driving Errors Causing Crashes

2021 ◽  
pp. 036119812110312
Author(s):  
Denis Elia Monyo ◽  
Henrick J. Haule ◽  
Angela E. Kitali ◽  
Thobias Sando
Keyword(s):  
Latent Class ◽  
Time Of Day ◽  
Older Drivers ◽  
Contributing Factors ◽  
Lighting Condition ◽  
Crash Data ◽  
Traffic Characteristics ◽  
Road Users ◽  
Traffic Conflicts ◽  
Penalized Logistic Regression

Older drivers are prone to driving errors that can lead to crashes. The risk of older drivers making errors increases in locations with complex roadway features and higher traffic conflicts. Interchanges are freeway locations with more driving challenges than other basic segments. Because of the growing population of older drivers, it is vital to understand driving errors that can lead to crashes on interchanges. This knowledge can assist in developing countermeasures that will ensure safety for all road users when navigating through interchanges. The goal of this study was to determine driver, environmental, roadway, and traffic characteristics that influence older drivers’ errors resulting in crashes along interchanges. The analysis was based on three years (2016–2018) of crash data from Florida. A two-step approach involving a latent class clustering analysis and the penalized logistic regression was used to investigate factors that influence driving errors made by older drivers on interchanges. This approach accounted for heterogeneity that exists in the crash data and enhanced the identification of contributing factors. The results revealed patterns that are not obvious without a two-step approach, including variables that were not significant in all crashes, but were significant in specific clusters. These factors included driver gender and interchange type. Results also showed that all other factors, including distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment, were significant in all crashes and few specific clusters.

Evaluation of Strategies to Mitigate Culvert-Involved Crashes

2021 ◽  
pp. 036119812199207
Author(s):  
Hitesh Chawla ◽  
Megat-Usamah Megat-Johari ◽  
Peter T. Savolainen ◽  
Christopher M. Day
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Cost Effective ◽  
Negative Binomial Regression Model ◽  
Promising Alternative ◽  
Roadside Safety ◽  
Adverse Conditions ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
Binomial Regression

The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.

Safety Evaluation of Destination Lighting Treatment at Stop Controlled Cross-Intersections

2018 ◽  
Vol 2672 (16) ◽  
pp. 113-121 ◽  
Author(s):  
Amrita Goswamy ◽  
Shauna Hallmark ◽  
Theresa Litteral ◽  
Michael Pawlovich
Keyword(s):  
Rural Areas ◽  
Negative Binomial ◽  
Safety Evaluation ◽  
Negative Binomial Regression ◽  
State Agencies ◽  
Crash Frequency ◽  
Binomial Regression ◽  
Manual Selection ◽  
Roadway Lighting ◽  
Selection Of

Intersection crashes during nighttime hours may occur because of poor driver visual cognition of conflicting traffic or intersection presence. In rural areas, the only source of lighting is typically provided by vehicle headlights. Roadway lighting enhances driver recognition of intersection presence and visibility of signs and markings. Destination lighting provides some illumination for the intersection but is not intended to fully illuminate all approaches. Destination lighting has been widely used in Iowa but the effectiveness has not been well documented. This study, therefore, sought to evaluate the effect on safety of destination lighting at rural intersections. As part of an extensive data collection effort, locations with destination/street lighting were gathered with the assistance of several state agencies. After manual selection of a similar number of control intersections, propensity score matching using the caliper width technique was used to match 245 treatments with 245 control sites. Negative binomial regression was used to evaluate crash frequency data. The presence of destination lighting at stop-controlled cross-intersections generally reduced the night-to-day crash ratio by 19%. The presence of treatment or destination lighting was associated with a 33%–39% increase in daytime crashes across all models but was associated with an 18%–33% reduction in nighttime crashes. Injuries in nighttime crashes decreased by 24% and total nighttime crashes reduced by 33%. Property damage crashes were reduced by 18%.

scholarly journals The Contribution of Avoidable Mortality to the Life Expectancy Gains in Korea between 1998 and 2017

2020 ◽  
Vol 17 (18) ◽  
pp. 6499
Author(s):  
Jinwook Bahk ◽  
Kyunghee Jung-Choi
Keyword(s):  
Public Health ◽  
Health Policy ◽  
Life Expectancy ◽  
Traffic Accidents ◽  
Causes Of Death ◽  
Cross Sectional Study ◽  
Cerebrovascular Diseases ◽  
Avoidable Mortality ◽  
Cross Sectional ◽  
Major Factors

This study evaluated the contribution of avoidable causes of death to gains in life expectancy between 1998 and 2017 in Korea. This is a multi-year, cross-sectional study using national data. Death certificate data from 1998 to 2017 were obtained from Statistics Korea. The difference in life expectancy between 1998 and 2017 by age and cause of death were decomposed using Arriaga’s method. Life expectancy rose 7.73 years over 20 years in Korea, which was largely (more than 50%) due to changes in avoidable causes of death. As age increased, the contribution to changes in life expectancy increased, and the gain in life expectancy due to avoidable causes also tended to increase. The major factors that drove that gain in life expectancy were avoidable causes such as cerebrovascular diseases and traffic accidents. The gain in life expectancy from preventable diseases was greater in men than in women. The results of this study indicate that active public health programs have been effective in improving life expectancy in Korea. Moreover, avoidable mortality could be further improved with good public health policy. Health policy aimed at reducing amenable and preventable deaths should be further implemented to promote population health.

scholarly journals Expressway Traffic Accidents Involving Human Injuries and Fatalities in Ethiopia: Negative Binomial Regression Model

2021 ◽  
Author(s):  
Yesuf Abdela Mustefa ◽  
Addis Belayhun
Keyword(s):  
Regression Model ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression

Abstract Background: Road traffic accident is a major public health as well as economic challenge that rated the eighth leading cause of death. The severity became higher in developing countries. Ethiopian is among the most confronted countries in the world. We utilized the Ethiopian Toll Roads Enterprise data to provide insights and model significant determinants of accidents involving injuries and fatalities. Besides utilizing recent dataset, we applied the most appropriate but forwent statistical model. Moreover, we examined the significance of the effects of drivers’ age and gender that have not been the cases in the literatures.Methods: We made descriptive insights available on the basis of graphs from integrated traffic accident and flow datasets. We tested for the presence of over-dispersion in a total of 1824 observations of accident data recorded from September, 2014 to December, 2019 for inferential analysis. Finally, we modeled the effects of significant variables on the number of injuries using the negative binomial regression model. Results: we found that the number of injuries in accidents were significantly determined by type of vehicles, ownership status of vehicles, accident time weather condition, driver-vehicle relationship, drivers’ level of education, and drivers’ age.Conclusions: Heavy trucks were more likely to cause more number of injuries than medium or small vehicles. Hot and windy weather conditions were associated with higher probability of the number of injuries. The likelihood of the number of injuries were lower when drivers are owner of the vehicle; drivers level of education is above secondary school; and the age of the driver is between 18 and 23 years old. Moreover, due concern needs to be given for traffic road rules.

scholarly journals Using Multivariate Regression and ANN Models to Predict Properties of Concrete Cured under Hot Weather: A Case of Rawalpindi Pakistan

2021 ◽  
Vol 13 (18) ◽  
pp. 10164
Author(s):  
Ahsen Maqsoom ◽  
Bilal Aslam ◽  
Muhammad Ehtisham Gul ◽  
Fahim Ullah ◽  
Abbas Z. Kouzani ◽  
...  
Keyword(s):  
Construction Material ◽  
Pulse Velocity ◽  
Ann Model ◽  
Quadratic Regression ◽  
Split Tensile Strength ◽  
Curing Conditions ◽  
Curing Methods ◽  
Ann Models ◽  
Hot Weather ◽  
The Individual

Concrete is an important construction material. Its characteristics depend on the environmental conditions, construction methods, and mix factors. Working with concrete is particularly tricky in a hot climate. This study predicts the properties of concrete in hot conditions using the case study of Rawalpindi, Pakistan. In this research, variable casting temperatures, design factors, and curing conditions are investigated for their effects on concrete characteristics. For this purpose, water–cement ratio (w/c), in-situ concrete temperature (T), and curing methods of the concrete are varied, and their effects on pulse velocity (PV), compressive strength (fc), depth of water penetration (WP), and split tensile strength (ft) were studied for up to 180 days. Quadratic regression and artificial neural network (ANN) models have been formulated to forecast the properties of concrete in the current study. The results show that T, curing period, and moist curing strongly influence fc, ft, and PV, while WP is adversely affected by T and moist curing. The ANN model shows better results compared to the quadratic regression model. Furthermore, a combined ANN model of fc, ft, and PV was also developed that displayed higher accuracy than the individual ANN models. These models can help construction site engineers select the appropriate concrete parameters when concreting under hot climates to produce durable and long-lasting concrete.

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