scholarly journals P.3.19 Effect of occupational work and safety issues on road crash injuries in the philippines

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A101.2-A101
Author(s):  
Sophia Francesca Lu
Keyword(s):  
Drunk Driving ◽  
Work Conditions ◽  
The Philippines ◽  
Public Utility ◽  
Traffic Density ◽  
Work Schedule ◽  
Road Crashes ◽  
The Road ◽  
Metro Manila ◽  
On The Road

BackgroundThis study looked at occupational road crashes and work schedule among truck and bus drivers in comparison to other drivers and motorists on the road of Metro manila which is one of the cities globally with a high traffic density. One of the most precarious work occupations is driving especially buses used for public transportation, and trucks for commercial activities. This is most astute in the metrolopolis.MethodsThe study used meta-analysis of previous studies conducted, grey literature, government statistics, and validation through key database research in concerned national government agencies involved in road traffic from 2010–2015.ResultsThe study found that the in terms of the number of public utility vehicles registered in Metro Manila (2015), 51.27% were buses and 20.21% were trucks. Majority of the drivers worked more than 12 hours a day. In terms of time and peak of accidents, it is alarming to note that about 35% of the road crashes occurred from 22–23 gmt (2010–2015), and 30% from 23–24 (2010–2015) gmt. Human error accounted for the overwhelming cause of road crashes such as drunk driving, beating the red light, sleepiness, accounting for 99.52% in 2012, 99.47% in 2013, 95.33% in 2014, and 97.19% in 2015. Majority of the drivers worked over prolonged hours on the road that may cause fatigue and sleepiness which are the highest risk factor to road accident based on the study.ConclusionThe study has shown how risky driving is as an occupation especially due to the work schedule and work issues. The study suggests developing better information, education and communication campaign as well as policies particularly on work conditions favorable to bus and truck drivers, and likewise, considering work schedule in road safety among drivers which composes one of the risky occupations.

scholarly journals Epidemiologic Profile of Vehicular Accident Patients in the Largest Hospital in the Philippines Covering Ten Years

2021 ◽  
Vol 55 (6) ◽  
Author(s):  
Jinky Leilanie Lu ◽  
Teodoro J. Herbosa ◽  
Sophia Francesca D. Lu
Keyword(s):  
Patient Outcome ◽  
Brain Injuries ◽  
Neck Region ◽  
Road Transport ◽  
The Philippines ◽  
Road Crashes ◽  
The Road ◽  
Metro Manila ◽  
Road Crash ◽  
Clinical Records

Introduction. Globally, the number of people who die from road crashes continues to rise, reaching a high of 1.35 million in 2016. Due to this continued increase in fatalities and injuries within the road transport system, especially in low- and middle-income countries, 2011 to 2020 was declared by the United Nations General Assembly in 2010 as the Decade of Action for Road Safety. Objectives. This study looked into the epidemiology of road crashes and injuries in Metro Manila over ten years, from 2008-2017, from data gathered at the Department of Surgery of the Philippine General Hospital (PGH). Method. A retrospective review of patients’ clinical records was conducted to describe the epidemiology of road crash cases in the Trauma Division, Department of Surgery of the PGH. Clinical records of the road crash patients admitted to the division over the ten years, January 1, 2008, to December 31, 2017, were extracted from the Integrated Surgical Information System (ISIS). Results. A total of 422 patients were admitted to the PGH Department of Surgery and recorded in the ISIS database, from 2008 to 2017, who suffered from road crashes in Metro Manila. Most of these patients (80.8%) were male. The mean age of patients was 32.4 years. The highest number of admissions (27.5%) and road crash deaths (6.9%) were in 2016; the highest number was from the city of Manila (26.7%), and most happened at nighttime (61.8%) between 6:00 PM and 5:59 AM. Throughout the years, motorcycle (52.8%) was the vehicle type involved. Among patients with helmet use information, 65.4% were not wearing helmets, 91.2% had a history of alcohol intake. The majority incurred multiple injuries (82.7%), with the external region (53.8%) as the most common. Patients who sustained injuries to their head and neck region were five times more likely to die and six times more likely to have an unchanged patient outcome than those who did not have these injuries. Patients who had a GCS of 8 and below or those who had severe brain injuries were eight times more likely to die and six times more likely to have an unchanged patient outcome. Conclusion. This study looked into the epidemiology of road crash cases admitted to the Surgery Department of the PGH. Road crash injuries and deaths remain a growing concern among the citizens of Metro Manila. It is hoped that the results of this study will provide policymakers with an objective and data-driven perspective on road crashes.

Bataan-Cavite Interlink Bridge, Philippines – a new 32 km sea crossing

2021 ◽  
Author(s):  
Sammy Yip ◽  
Steve Kite ◽  
Paresh Vishnoi ◽  
Vikas Venkatesha
Keyword(s):  
Economic Growth ◽  
Feasibility Study ◽  
The Philippines ◽  
Preliminary Design ◽  
The Road ◽  
Metro Manila ◽  
To Come ◽  
Optimum Solution

<p>Bataan-Cavite Interlink Bridge (BCIB) in the Philippines is a proposed 32km sea-crossing which will connect Bataan to Cavite, to unlock opportunity for economic growth and expansion outside Metro Manila. A Feasibility Study was carried out to plan the road link, which would involve two major navigation bridges, long marine viaducts, and interchange connections. This paper outlines the Feasibility Study and the preliminary design of the crossing, and highlights how the bridge options were assessed in order to come up with an optimum solution.</p>

TRAFFIC FLOWS MODELING WITH INACCESSIBLE FOR DRIVING ROAD SECTIONS

2021 ◽  
pp. 19-36
Author(s):  
Anastasiya N. Zhukova ◽  
◽  
Marina S. Shapovalova ◽  
Keyword(s):  
Network Formation ◽  
Road Transport ◽  
Traffic Density ◽  
Traffic Flows ◽  
The Road ◽  
Model Modification ◽  
Road Section ◽  
Transport Line ◽  
On The Road ◽  
Python Programming

Computerized traffic modeling makes it possible to find out the modification needs to assess the traffic flow on the roads and detect likely problem areas in order to take timely measures to eliminate them. Competent preparation of a road network formation plan based on the acquired information makes it possible to reduce the load on the road transport line, avoid traffic jams, and also reduce the average time spent by drivers on the roads. The macroscopic and microscopic models of the cars flow were analyzed by authors to implement the computer model. The article considered the model of the cellular automata by Nagel–Schreckenberg, with the author’s addition that takes into account the presence of the road sections inaccessible for driving in. The need to modify the lane change algorithm was implemented: the condition of the need to change the lane when car is meeting an inaccessible road section was added. And also the “polite” drivers algorithm for bypassing inaccessible areas with a high density of the traffic flows was proposed. Such a model is realized on Python programming language. An analysis of vehicles behavior with different traffic density and location of inaccessible road sections for two- and three-lane roads was carried out based on that model modification.

scholarly journals Does the shape of the road influences wildlife roadkills? Evidence from a highway in Central Andes of Colombia

2020 ◽  
Vol 6 (1) ◽  
pp. 58-70
Author(s):  
Julián Arango Lozano ◽  
Dahian Patiño-Siro
Keyword(s):  
Central Andes ◽  
Traffic Density ◽  
Highway Infrastructure ◽  
The Road ◽  
Road Design ◽  
On The Road ◽  
Conservation Plans ◽  
Straight Lines ◽  
Transition Curves ◽  
Wildlife Mortality

Highway infrastructure is a source of multiple environmental problems, where wildlife roadkills is the most noticeable impact. Most of research in roadkills have focused in how different aspects as seasons, traffic density, location of roads, among others, have implications in the wildlife mortality on roads. However, little research have been developed on understanding how geometrical road design affects wildlife mortality. On a highway in the central Andes of Colombia, we tested whether the geometric design, it is horizontal alignment and vertical curves influence the mortality of vertebrate animals on the road. We determined the number of straight lines, circular, transition curves and vertical convex curves along the entire route of the highway (13.9 km), and between April 2018 and December 2019 we made 4 weekly tours in search of wildlife roadkills. With records, we related and compared groups of animal deaths and road shapes. We got 95 roadkills where reptile’s deaths were more than the 47% of total. We found no dependence in the distribution of deaths by Class of animals on the road shapes; the shape in which most deaths occurred was straight line (58 deaths). However, when the mortality rate per meter of route was obtained on the shape units, we found that the circular and transition curves presented two and three times (respectively) higher mortality rates than straight lines. Curved sections are presented as more dangerous geometric designs than straight lines for wildlife, regardless of their length on the road. Our research provides information necessary to take into account the relationship of geometric road design in the development of management and conservation plans of altered ecosystems with road infrastructure.

scholarly journals Tyre Weights an Overlooked Diffuse Source of Lead and Antimony to Road Runoff

2020 ◽  
Vol 12 (17) ◽  
pp. 6790
Author(s):  
Matthew Taylor ◽  
Niklas Kruger
Keyword(s):  
Urban Areas ◽  
Motor Vehicle ◽  
Environmentally Benign ◽  
Motor Vehicles ◽  
Traffic Density ◽  
Road Runoff ◽  
Diffuse Source ◽  
The Road ◽  
Roadside Dust ◽  
On The Road

Lead (Pb) remains elevated in road runoff and roadside dust, which has been attributed to legacy lead in surface soils from leaded petrol. However, “lead” tyre weights, an alloy of 95% Pb and 5% Sb, may be a relatively unrecognised diffuse source of Pb and Sb as they are still used in many countries. An unknown number of these weights drop off tyre rims and deposit on the road where they are abraded and dispersed, potentially causing adverse environmental effects. The type, number and weight of tyre weights lost from motor vehicles were characterised for a range of roading infrastructures and motor vehicle intensities in a 38 month long study of a 6.9 km length of road in Hamilton City, New Zealand. Overall, 1070 tyre weights with a combined mass of 18.6 kg were collected. About 96.4% of the collected weights were made of “lead”, which is an alloy of 95% Pb and 5% Sb, indicating tyre weights can be a major source of Pb and Sb in urban areas. The tyre weight distribution on roads used in this study depended mainly on traffic density and the prevalence of “start stop” patterns in traffic flow influenced by roundabouts and intersections. “Lead” tyre weights should be phased out and replaced with environmentally benign materials.

scholarly journals Understanding Air Pollution from Induced Traffic during and after the Construction of a New Highway: Case Study of Highway 25 in Montreal

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Md. Shohel Reza Amin ◽  
Umma Tamima ◽  
Luis Amador Jimenez
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Road Network ◽  
Traffic Density ◽  
Air Contaminants ◽  
Construction Period ◽  
Close Vicinity ◽  
The Road ◽  
On The Road

This study demonstrates through a case study that detailed analyses, even after the construction of a project, are feasible using current technologies and available data. A case study of highway 25 is used to illustrate the method and verify the levels of air contaminants from additionally induced traffic during and after the construction of highway. Natural traffic growth was removed from the effect of observed gas emissions by comparing observed levels on other further locations in the same metropolitan area. This study estimates air pollution from the additional traffic during and after the construction of A-25 extension project. NO2 levels were spatially interpolated during peak and off-peak hour traffic and traffic density simulated on the road network for four scenarios. Comparing the four scenarios, it was found that levels of NO2 concentrations were reduced at neighbor areas due to less traffic during the construction period. Levels of NO2 after the construction were higher than those in 2008. The simulated traffic density for four scenarios revealed that traffic density was significantly increased on both arterial and access roads within the close vicinity of the extension project during and after its construction.

scholarly journals Traffic Density Classification Using Twitter Data and GPS Based On Android Application

2020 ◽  
Vol 14 (2) ◽  
pp. 113
Author(s):  
Mohammad Afrizal ◽  
Idham Ananta Timur
Keyword(s):  
Public Transportation ◽  
Traffic Density ◽  
The Public ◽  
The Road ◽  
Twitter Data ◽  
Average Accuracy ◽  
Android Applications ◽  
On The Road ◽  
The City ◽  
Special Region

Increasing the number of vehicles in Special Region of Yogyakarta caused by congestion occurred at various traffic points in Special Region of Yogyakarta. The solution to reducing congestion is by increasing the use of public transportation within the city, but it still not in demand by the public. Optimizing daily activities, community always tries to avoid the traffic density on the road to be bypassed.Some research on social media has been used to detect traffic density anomalies. However, the system still cannot provide traffic density information on roads that will be passed by the user because it is just a mapping. Based on this problem, this study aims to classify the traffic density on the road that will be passed by users in the Special Region of Yogyakarta into the category of high traffic and low traffic by utilizing Twitter and GPS data.The results show that Android Applications are able to classify traffic density on the road to be traversed using Geonames.org API. Using the naïve bayes classification algorithm, the system can classify traffic density on 14 streets with an average accuracy of 77.5%, 90% precision, 79.1% recall, and 82.8% f-score.

scholarly journals Detection of Coordinate Based Accident-Prone Areas on Road Surface using Machine Learning Methods

2020 ◽  
Vol 12 (3) ◽  
pp. 19-25
Author(s):  
Anitha Kumari Dara ◽  
Dr. A. Govardhan
Keyword(s):  
Spatial Data ◽  
Surface Defects ◽  
Road Accident ◽  
Road Surface ◽  
The Other ◽  
Work Outcomes ◽  
Traffic Density ◽  
Surface Conditions ◽  
The Road ◽  
On The Road

The growth in the road networks in India and other developing countries have influenced the growth in transport industry and other industries, which depends on the road network for operations. The industries such as postal services or mover services have influenced the similar growths in these industries as well. However, the dependency of these industries is high on the road surface conditions and any deviation on the road surface conditions can also influence the performance of the services provided by the mentioned services. Nonetheless, the conditions of the road surface are one of the prime factors for road safety and number of evidences are found, which are discussed in subsequent sections of this work, that the bad road surface conditions are increasing the road accidents. Several parallel research attempts are deployed in order to find out, the regions where the road surface conditions are not proper, and the traffic density is higher. Nevertheless, outcomes of these parallel works are highly criticised due to the lack of accuracy in detection of the road surface defects, detection of accurate location of the defects and detection of the traffic density data from various sources. Thus, this work proposes a novel framework for detection of the road defect and further mapping to the spatial data coordinates resulting into the detection of the accident-prone zones or accident affinities of the roads. This work deploys a self-adjusting parametric coefficient-based regression model for detection of the risk factors of the road defects and in the other hand, extracts the traffic density of the road regions and further maps the accident affinities. This work outcomes into 97.69% accurate detection of the road accident affinity and demonstrates less complexity compared with the other parallel research outcomes

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