scholarly journals Assessment of logistical support for road maintenance to manage road accidents in Vhembe district municipalities

2019 ◽  
Vol 11 (3) ◽  
Author(s):  
Peter Bikam
Keyword(s):  
Service Providers ◽  
Road Accident ◽  
Motor Vehicles ◽  
Road Maintenance ◽  
Road Accidents ◽  
Deficit Model ◽  
Technology Innovations ◽  
Operations And Maintenance ◽  
Materials Used ◽  
Vhembe District

This article discusses the problems of logistical support for road maintenance to manage road accidents in Vhembe district municipalities. A budget deficit model was used to explain the level of inadequate logistics support to manage operations and maintenance of municipal roads as a preventative measure against road accident and disaster risks. A hypothetical road maintenance deficit model informed by current literature on road maintenance was used to explain how cost of road maintenance increases exponentially if initial maintenance was not undertaken when the facility was newly constructed to draw the link between road maintenance and the risk of road accidents. Inadequate logistical support to address road maintenance backlogs in Vhembe district municipalities has been on the increase over the last 10 years. Current studies show that inadequate road maintenance can lead to the development of potholes – a major cause of road accidents and damages to motor vehicles. Literature on logistics support emphasises a comprehensive approach to road maintenance to provide a balance between funding, routine maintenance, quality of materials used for maintenance, use of stipulated specifications, the required maintenance technology, innovations and employment of qualified service providers to ensure quality roads and reduction of accidents on municipal roads.

scholarly journals Road Traffic Accidents by 'Nasimon' and 'Karimon'-A Study in Faridpur

2012 ◽  
Vol 7 (1) ◽  
pp. 6-9
Author(s):  
ASMJ Chowdhury ◽  
MS Alam ◽  
SK Biswas ◽  
RK Saha ◽  
AR Mondal ◽  
...  
Keyword(s):  
Low Socioeconomic Status ◽  
Urban Areas ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Motor Vehicles ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
College Hospital ◽  
Medical College

Road traffic accidents in Bangladesh have been rapidly increasing with huge mortality through road accidents each year. There are many causes of road accidents in recent years; one important cause is running of locally made improvised three wheelers (flat bed tricycle) in the urban areas and also on the highways, popularly known as 'Nasimon' and 'Karimon'. This prospective study was carried out in Faridpur Medical College Hospital from January through June 2011, to study the accident patients caused by 'Nasimon' and 'Karimon'. Fifty six (12%) patients were of RTA by 'Nasimon' and 'Karimon' out of a total of 468 patients admitted into our hospital during this period. Most patients (41, 73.21%) were male, highest accidents (24, 42.86%) were observed among 21-30 years age group and most victims (33, 58.93%) were belonged to low socioeconomic status. Commonest (31, 55.36%) victims were passengers of 'Nasimon' and 'Karimon' while maximum number of accidents (46, 82.14%) took place in the urban areas and on the highways. Injury pattern of victims were similar to that found in any other road accident patients. These three wheelers 'Nasimon' and 'Karimon' are run in violating of Bangladesh Motor Vehicles Act (1983) as they are totally unfit for plying on the highways. Strict surveillance against these illegal and risky vehicles on the highways and in the urban areas by law enforcing agencies is required as a measure to reduce the burden of road accidents in our country.DOI: http://dx.doi.org/10.3329/fmcj.v7i1.10289Faridpur Med. Coll. J. 2012;7(1): 06-09

scholarly journals Road Transport Accidents in Nigeria and the Role of Automotive Active Safety System

2016 ◽  
Vol 11 (1) ◽  
pp. 49-54
Author(s):  
Olasunkanmi Oriola Akinyemi ◽  
Hezekiah O Adeyemi ◽  
Olusegun Jinadu
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Transportation Network ◽  
Road Transport ◽  
Road Accident ◽  
Active Safety ◽  
Road Accidents ◽  
Road Transportation ◽  
Road Traffic Safety

Abstract Analysis of road traffic accidents revealed that most accidents are as a result of drivers’ errors. Over the years, active safety systems (ASS) were devised in vehicle to reduce the high level of road accidents, caused by human errors, leading to death and injuries. This study however evaluated the impacts of ASS inclusions into vehicles in Nigeria road transportation network. The objectives was to measure how ASS contributed to making driving safer and enhanced transport safety. Road accident data were collected, for a period of eleven years, from Lagos State Ministry of Economic Planning and Budget, Central Office of Statistics. Quantitative analysis of the retrospective accident was conducted by computing the proportion of yearly number of vehicles involved in road accident to the total number of vehicles for each year. Results of the analysis showed that the proportion of vehicles involved in road accidents decreased from 16 in 1996 to 0.89 in 2006, the injured persons reduced from 15.58 in 1998 to 0.3 in 2006 and the death rate diminished from 4.45 in 1998 to 0.1 in 2006. These represented 94.4 %, 95 % and 95 % improvement respectively on road traffic safety. It can therefore be concluded that the inclusions of ASS into design of modern vehicles had improved road safety in Nigeria automotive industry.

scholarly journals Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction

Computers ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 157
Author(s):  
Daniel Santos ◽  
José Saias ◽  
Paulo Quaresma ◽  
Vítor Beires Nogueira
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Road Accident ◽  
Influential Factors ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Economic Losses ◽  
Learning Approaches ◽  
Road Accidents ◽  
Accident Data

Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this work is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR), and naive Bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using the C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Further, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots.

scholarly journals TRAFFIC-RELATED MORTALITY IN MOLDOVA

2020 ◽  
pp. 140-147
Keyword(s):  
Life Expectancy ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Road Accidents ◽  
Continuous Increase ◽  
Risk Of Death ◽  
Significant Difference ◽  
Related Mortality

This article analyses the mortality caused by road accidents in Moldova depending on the degree of involvement of pedestrians, cyclists, motorcyclists, drivers and passengers of transport units, depending on age and sex. Results suggest that traffic-related mortality in Moldova has shown an increased incidence among the young and working-age population, where a significant difference between males and females is observed. Among the youth, traffic-related deaths register between 10-27% of the overall mortality in both sexes. The risk exposure of dying in a traffic accident decreases with age and is less significant in the retired ages. During the years 1998-2015, avoidance of trafficrelated deaths would have assured an increase in life expectancy between 0.40-0.56 years in males, and 0.09-0.23 years in females. The continuous increase in the number of transport units on public roads, as well as in the number of hours spent in traffic, influences the degree of exposure to the risk of death or injury as a result of road traffic accidents. Trauma resulting from road accidents increases the incidence of premature mortality and disability among the population, which is reflected by the decrease of healthy life expectancy. It is ascertained that the road accident mortality requires a detailed and comprehensive analysis given the multitude of factors influencing deaths and injuries related to a traffic accident among the population. Thus, in order to improve road safety and reduce mortality incidence among traffic participants, a range of actions has to be implemented by the liable actors, including through the international experience.

scholarly journals Investigating the Availability and Usage of Seatbelts in Malawi for Policy Review and Formulation

2020 ◽  
Vol 31 (3) ◽  
pp. 48-56
Author(s):  
Gibson Mpokonyoka Ngwira ◽  
Benjamin Bolaane ◽  
Bhagabat P. Parida
Keyword(s):  
Mitigation Measures ◽  
Motor Vehicles ◽  
Health Concern ◽  
Primary Data ◽  
Road Accidents ◽  
Vehicle Ownership ◽  
Chi Square ◽  
Chi Square Test ◽  
Road Fatality ◽  
Major Factors

Road fatalities remain a major public health concern as over 1.3 million people across the world die in road accidents annually, and another 20-50 million sustain injuries. Malawi, with vehicle ownership about 437,416, has not been an exception to this, with reported fatality rates of 35 crash deaths per 100,000 population, possibly due to limited understanding of factors that contribute to such high road fatality rates. This may have resulted in implementing inappropriate and ineffective mitigation measures. Thus, the overall objective of this study was to investigate the availability, including their functionality and usage of seatbelts in motor vehicles, which could possibly be one of the major factors for increase in road fatalities. To establish the rates of availability, ncluding their functionality and usage of seatbelts in motor vehicles, primary data through survey for a sample of 1,200 vehicles were investigated. The independent ariables of data were cross tabulated with the dependent variables to establish these rates. Chi-square test was also performed to establish the significance of associations between the cross tabulated variables. The analysis found that Malawi’s drivers and assengers poorly comply with seatbelt laws. The overall seatbelt usage rate was 35.8%. In this regard, where over 90% of motor vehicles in Malawi have functional seatbelts, poor enforcement of existing seatbelt laws and awareness on the dangers of not using eatbelts could account for the low usage.

Reported Consequences Following Road Accidents

1996 ◽  
Vol 2 (2) ◽  
pp. 29 ◽  
Author(s):  
Sue Jeavons ◽  
Kenneth Greenwood ◽  
David Horne
Keyword(s):  
Response Rate ◽  
Poor Response ◽  
Road Accident ◽  
Psychiatric Diagnoses ◽  
Road Accidents

The literature on the sequelae of road accidents is limited but generally focuses on psychiatric diagnoses. Reported here are the results of a survey that assessed the degree of physical, social and occupational effects, counselling received, and perceptions of treatment of road accident victims, up to two years after the accident. There was a poor response rate and some methodological weaknesses, but results showed that there were marked effects in these aspects of people's lives and that few had received counselling or follow-up.

Augmenting Classifiers Performance through Clustering

2018 ◽  
Vol 8 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Sachin Kumar ◽  
Prayag Tiwari ◽  
Kalitin Vladimirovich Denis
Keyword(s):  
Traffic Accident ◽  
Latent Class ◽  
Safety Concern ◽  
Health And Safety ◽  
Road Accident ◽  
Support Vector ◽  
Road Accidents ◽  
Real World Data ◽  
The Public ◽  
Accident Data

Road and traffic accident data analysis are one of the prime interests in the present era. It does not only relate to the public health and safety concern but also associated with using latest techniques from different domains such as data mining, statistics, machine learning. Road and traffic accident data have different nature in comparison to other real-world data as road accidents are uncertain. In this article, the authors are comparing three different clustering techniques: latent class clustering (LCC), k-modes clustering and BIRCH clustering, on road accident data from an Indian district. Further, Naïve Bayes (NB), random forest (RF) and support vector machine (SVM) classification techniques are used to classify the data based on the severity of road accidents. The experiments validate that the LCC technique is more suitable to generate good clusters to achieve maximum classification accuracy.

Road Safety Model: Some Fundamental Ideas

1996 ◽  
Vol 1563 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Francis P. D. Navin ◽  
Arthur Bergan ◽  
Guanyu Zhang
Keyword(s):  
Developing Countries ◽  
Road Safety ◽  
Developed Countries ◽  
Road Accident ◽  
Personal Safety ◽  
Road Accidents ◽  
Fundamental Relationship ◽  
The Social ◽  
Special Cases ◽  
Accident Statistics

A fundamental relationship has been developed that explains road accident statistics in developed and developing countries. The model uses two variables, traffic hazard measured as deaths per vehicle and motorization measured as vehicles per person, to estimate personal hazard as deaths per person. Special cases of the model are those by Smeed, Trinca et al., and Koornstra. The model of fatalities has two extremes. Early motorization has high traffic hazard and personal safety is low and increasing. Full motorization is characterized by a moderate and falling traffic hazard and a low and decreasing personal safety. Between these extremes, there is a maximum number of fatalities per population. Models for personal injury and total road accidents in developed countries appear to follow a similar trend. Available world data fit the proposed relationships well. The models allow planners and engineers to estimate the future maximum road fatalities for developing countries. The model has been extended to incorporate an automobile ownership model that explains some of the growth in motorization. A traffic hazard model is also outlined, in part on the basis of the ideas developed by Koornstra. The extended models should allow a more detailed analysis of some of the social and engineering factors that contribute to road safety.

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