scholarly journals COMPARISON OF ROAD TRAFFIC ACCIDENT PREDICTION MODELS FOR TWO-LANE HIGHWAY INTEGRATING TRAFFIC AND PAVEMENT CONDITION PARAMETERS

2019 ◽  
Vol 16 (2) ◽  
pp. 1-10
Author(s):  
O. M. POPOOLA ◽  
O. S. ABIOLA ◽  
S. O. ODUNFA ◽  
S. O. ISMAILA
Keyword(s):  
Road Traffic Accident ◽  
Traffic Accident ◽  
Negative Binomial ◽  
Prediction Models ◽  
Road Traffic ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Accident Prediction ◽  
Explanatory Variables ◽  
Roughness Index

In Nigeria, literature on the integration of traffic of pavement condition and traffic characteristics in predicting road traffic accident frequency on 2-lane highways are scanty, hence this article to fill the gap. A comparison of road traffic accident frequency prediction models on IIesha-Akure-Owo road based on the data observed between 2012 and 2014 is presented. Negative Binomial (NB), Ordered Logistic (OL) and Zero Inflated Negative Binomial (ZINB) models were used to model the frequency of road traffic accident occurrence using road traffic accident data from the Federal Road Safety Commission (FRSC) and pavement conditions parameters from pavement evaluation unit of the Federal Ministry of Works, Kaduna. The explanatory variables were: annual average daily traffic (aadt), shoulder factor (sf), rut depth (rd), pavement condition index (pci), and international roughness index (iri). The explanatory variables that were statistically significant for the three models are aadt, sf and iri with the estimated coefficients having the expected signs. The number of road traffic accident on the road increases with the traffic volume and the international roughness index while it decreases with shoulder factor. The systematic variation explained by the models amounts to 87.7, 78.1 and 74.4% for NB, ZINB and OL respectively. The research findings suggest the accident prediction models that should be integrated into pavement rehabilitation.   Keywords:  

The Prediction Model of Macro-Road Traffic Accident Basing on Radial Basis Function

2011 ◽  
Vol 97-98 ◽  
pp. 981-984 ◽  
Author(s):  
Cheng Ju Song ◽  
Quan Yan Li
Keyword(s):  
Prediction Model ◽  
Radial Basis Function ◽  
Basis Function ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Prediction Models ◽  
Road Traffic ◽  
Accident Prediction ◽  
Radial Basis ◽  
Traffic Operation

The Macro-road traffic accident prediction is an important branch of ITS, which could not only make improving direction, but also improve the traffic operation. The paper based on the analyzing the existing macro prediction model, aiming at the existing shortcomings of prediction models with low accuracy and slow convergence speed, introducing the Radial Basis Function, establishing the accident prediction model between Population, Economic situation, cars, road mileage and the index of accident Statistics, and apply Matlab to Simulation to prove the Feasibility and Practicality of the model.

scholarly journals Analysis of Vehicle Vibrations – New Approach to Rating Pavement Condition of Urban Roads

2012 ◽  
Vol 23 (6) ◽  
pp. 485-494 ◽  
Author(s):  
Stjepan Lakušić ◽  
Davor Brčić ◽  
Višnja Tkalčević Lakušić
Keyword(s):  
Surface Roughness ◽  
Ride Comfort ◽  
Road Traffic ◽  
Heavy Traffic ◽  
Pavement Management ◽  
International Roughness Index ◽  
New Approach ◽  
Pavement Condition ◽  
Roughness Index ◽  
Road Surface Roughness

Urban road infrastructure is daily burdened by heavy traffic volume. Pavement structure roughness observations are significantly more difficult in urban agglomerations than on roads in unpopulated areas. Roughness, expressed by IRI (International Roughness Index), directly affects the quality and safety of road traffic. Within the framework of the pavement management in relation to safety and the achievement of the best possible ride comfort, it is very important to foresee when a road should be reconstructed. The method for quality evaluations of safety and ride comfort on urban roads presented in this paper is based on vehicle vibrations measurements. In the article, measuring of vehicle vibrations was performed on the main urban roads in Zagreb (Croatia). Measurements covered roads with different pavement surface roughness. This method can be simply and very easily used in pavement management aimed at achieving road safety and better ride comfort. The results of measurements according to this method could be used by traffic and civil engineering experts as an indication for the roads that require reconstruction or maintenance. KEY WORDS: urban roads, traffic flow, safety, vehicle vibrations, road surface roughness (IRI)

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 ◽  
Regional State

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. Recently, in Ethiopia, the average number of road traffic accidents has been increasing, particularly the Oromia regional state is experiencing a higher road traffic fatalities. 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 road traffic accidents.Results: Of the total of 3900 road traffic accidents included in the 1188 (30.5%) were giving rise to fatal. The Hurdle 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 road traffic accident factors have been identified. Thus, interventions by the bodies concerned with introduction educational programs that will create awareness about road traffic accidents and the associated human deaths, especially targeting road users, young drivers, passengers and pedestrians.

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.

scholarly journals Effect of Traffic and Geometric Characteristics of Rural Two Lane Roads on Traffic Safety: a case study of Ilesha-Akure-Owo road, South-West, Nigeria

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Monsuru O Popoola ◽  
Oladapo S Abiola ◽  
Simeon O Odunfa
Keyword(s):  
Road Safety ◽  
Traffic Accident ◽  
Negative Binomial ◽  
Prediction Models ◽  
Negative Binomial Regression ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
South West ◽  
Binomial Regression ◽  
Accident Data

Road safety engineering involves identifying influencing factors causing traffic crashes through accident data, carrying out detailed accident studies at different locations and implementing relevant remedial measures. This study was carried out to establish relationship between traffic accident characteristics (frequency and severity) and traffic and road design characteristics on a two-lane highway. Statistical models applied in traffic accident modeling are Poisson regression, Negative Binomial regression (NB), and Zero-Inflated Negative Binomial regression (ZINB).; Traffic flow and road geometry related variables were the independent variables of the models. Using Ilesha-Akure-Owo highway, South-West, Nigeria accident prediction models were developed on the basis of accident data obtained from Federal Road Safety Commission (FRSC) during a 4-year monitoring period extending between 2012 and 2015. Curve radius (CR), lane width (LW), shoulder factor (SF), access road (CHAR), average annual daily traffic (AADT), parentage heavy good vehicle (HGV) and traffic sign posted (TSP) were the identified effective factors on crash occurrence probability. Finally, a comparison of the three models developed proved the efficiency of ZINB models against traditional Poisson and NB models. Keywords— Traffic accidents. Single carriageway, accident prediction model, road geometric characteristics.

Road traffic accident prediction modelling: a literature review

2017 ◽  
pp. 1-10 ◽  
Author(s):  
George Yannis ◽  
Anastasios Dragomanovits ◽  
Alexandra Laiou ◽  
Francesca La Torre ◽  
Lorenzo Domenichini ◽  
...  
Keyword(s):  
Literature Review ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Accident Prediction ◽  
Prediction Modelling

Chest Trauma Evaluation and Outcome of Management in a Tertiary Hospital - One Year Experience

2020 ◽  
Vol 22 (2) ◽  
pp. 110-117
Author(s):  
Md Mahmudul Islam ◽  
Khondkar AK Azad ◽  
Md Aminul Islam ◽  
Rivu Raj Chakraborty
Keyword(s):  
Road Traffic Accident ◽  
Traffic Accident ◽  
Chest Trauma ◽  
Road Traffic ◽  
Tube Thoracostomy ◽  
Rib Fracture ◽  
Medical College Hospital ◽  
College Hospital ◽  
Medical College ◽  
The Mean

Background: Chest trauma is responsible for 50% of deaths due to trauma. This kind of death usually occurs immediately after the trauma has occurred. Various therapeutic options have been reported for management of chest injuries like clinical observation, thoracocentesis, tube thoracostomy and open thoracotomy. Objective: To observe the pattern and outcome of management in chest trauma Methods: This is an observational study carried out in Casualty department of Chittagong Medical College Hospital (CMCH), Chittagong, between April 2015 to March 2016. Our study was included all patients, both sexes, following chest injury at Casualty units of Chittagong Medical College Hospital. All the data were recorded through the preformed data collection sheet and analyzed. Result: The mean age was found 37.7±18.1 years with range from 12 to 80 years. Male female ratio was 11.8:1. The mean time elapsed after trauma was found 6.1±3.1 hours with range from 1 to 72 hours. Almost one third (35.7%) patients was affecting road traffic accident followed by 42(27.3%) assault, 35(22.7%) stab injury, 15(9.7%) fall and 7(4.5%) gun shot . More than three fourth (80.5%) patients were managed by tube thoracostomy followed by 28(18.2%) observation and 2(1.3%) ventilatory support. No thoracotomy was done in emergency department. 42(27.2%) patients was found open pneumothorax followed by 41(26.6%) rib fracture, 31(20.1%) haemopneumothorax, 14(9%) simple pneumothorax, 12(7.8%) haemothorax, 6(3.9%) chest wall injury, 5(3.2%) tension pneumothorax, and 3(1.9%) flail chest. About the side of tube 60(39.0%) patients were given tube on left side followed by 57(37.0%) patients on right side, 9(5.8%) patients on both (left & right) side and 28(18.2%) patients needed no tube. Regarding the complications, 13(30%) patients had persistent haemothorax followed by 12(29%)tubes were placed outside triangle of safety, 6(13.9%) tubes were kinked, 6(13.9%) patients developed port side infection, 2(4.5%)tube was placed too shallow, 2(4.5%) patients developed empyema thoracis and 2(4.5%) patients developed bronchopleural fistula. The mean ICT removal information was found 8.8±3.6 days with range from 4 to 18 days. Reinsertion of ICT was done in 6(4.7%) patients. More than two third (68.2%) patients were recovered well, 43(27.9%) patients developed complication and 6(3.9%)patients died. More than two third (66.9%) patients had length of hospital stay 11-20 days. Conclusion: Most of the patients were in 3rd decade and male predominant. Road traffic accident and tube thoracostomy were more common. Open pneumothorax, rib fracture and haemopneumothorax were commonest injuries. Nearly one third of the patients had developed complications. Re-insertion of ICT needed almost five percent and death almost four percent. Journal of Surgical Sciences (2018) Vol. 22 (2) : 110-117

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