Predictors of Survival in Motor Vehicle Accidents Among Motorcyclists, Bicyclists and Pedestrians

Bazargani, Homayoun Sadeghi; Vahidi, Reza; Abhari, Ali Akbar

doi:10.5812/traumamon.26019

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…Moreover the pattern of energy transfer for a pillion passenger may be different from the rider or the energy tolerability among the women may be lower than men. According to a previous study in East Azerbaijan, the risk of dying after a motorcycle crash is nearly three times higher than for traffic injuries of other traffic users [23]. In present study motorcycle-vehicle crash followed by rollover comprised the crash mechanism in about 90% of the cases which is in line with most studies showing that overturning and motorcycle-vehicle crash, especially with the cars, are the two most common mechanisms of motorcycle traffic accidents.…”

Section: Discussionsupporting

confidence: 88%

Epidemiology of Traffic Fatalities among Motorcycle Users in East Azerbaijan, Iran

Sadeghi‐Bazargani

Samadirad

Hosseinpour-Feizi

2018

BioMed Research International

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Background The aim of this study was to determine some epidemiological aspects of motorcycle user traffic fatalities including the crash mechanisms and injury patterns in East Azerbaijan, Iran (2006-2016). Methods A total of 1840 motorcycle user mortal cases registered in East Azerbaijan forensic medicine database, in Iran, were analyzed over the time period between March 2006 and March 2016. The distribution and associations of both victim- and crash-related variables such as crash mechanism, types of involved vehicles, types of injuries, and demographic characteristics were investigated. Data were analyzed by Stata v.13 statistical software package. Results Of the 9435 RTI deaths, 1840 (19.5%) were motorcycle users of whom 96.5% were male (mean age of 32.3 ± 18.5 years). The majority of accident mechanisms were motorcycle-vehicle crashes (77.8%), followed by rollover (11.8%). Cars were the leading counterpart crash vehicle comprising about 34.8% of the motorcycle user mortalities. Inner city traffic injuries were the reason for 744 (40.7%) of the motorcycle user mortalities. Head trauma was the main cause of death. About 82% of the victims were motorcycle riders and the remainder were pillion passengers. A decreasing trend of fatal traffic accidents was observed over the study period for both the motorcycle user fatalities and other traffic injuries. The percentage of motorcycle mortalities over all traffic mortalities had a decreasing trend over the past nine years from March 2007 to March 2016 reaching a figure as low as 15.2% through the last year of study. Conclusions Motorcycle traffic fatalities, although having a decreasing trend during the last decade with a better slope than most other traffic injuries, remain to be a major public health in north-west of Iran. There is a need for effective interventional programs to reduce the burden of motorcycle fatalities.

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Section: Discussionsupporting

confidence: 88%

Epidemiology of Traffic Fatalities among Motorcycle Users in East Azerbaijan, Iran

Sadeghi‐Bazargani

Samadirad

Hosseinpour-Feizi

2018

BioMed Research International

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“…Motorcycles are currently one of the most popular means of transport in emerging countries, which results in important fatality rates [4] and a significant environmental impact due to emissions (e.g. P.M. 2.5) [19].…”

Section: Motorcycles As Part Of Urban Trafficmentioning

confidence: 99%

“…These results are consistent with a slightly better precision compared to YOLO and Faster R-CNN, which allows the MDP tracker to obtain less fragmentations (341). Video tracking results can be viewed via the following link 4 .…”

Section: Tracking Performance Metricsmentioning

confidence: 99%

Detection and Tracking of Motorcycles in Congested Urban Environments Using Deep Learning and Markov Decision Processes

Espinosa

Velastín

Branch

2019

Lecture Notes in Computer Science

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This research describes "EspiNet", a Deep Learning Convolutional Neural Network model, in conjunction with a Markov Decision Process (MDP) tracker for detection and tracking of occluded motorcycles in urban environments. The model is trained and evaluated, using a new public dataset with up to 10,000 annotated images, created for this research, and captured in real urban traffic scenes. Images were captured using a moving camera mounted in a drone, where more than 60% of the motorcycles are affected by occlusions. The network design involves many tests, where a promising result of 88.84% in average precision (AP) is achieved, despite the considerable number of occluded vehicles, the movement of the camera and the low angle used for capture. The model predictions are used as input to an MDP tracker, reaching results up to 85.2% in Multiple Object Tracking Accuracy (MOTA). The proposed network architecture outperforms state of the art YOLO (You Look Only Once) v3.0 and Faster R-CNN (VGG16 based) detection models, producing also better tracking results in comparison with the use of the other two models as detector base for the MDP tracker.

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“…In addition, they are presently reported to be the ninth most common cause of death in the world, irrespective of age, and are expected to reach the seventh rank by 2030 (1). Road traffic accidents and their outcomes are more notable in developing countries, especially in Iran, compared to developed countries (2). According to a national health survey in 2005, Iran had the highest rate of deaths due to road traffic accidents worldwide, with an annual rate of 30,721 (44 per 100,000 population) (3).…”

Section: Introductionmentioning

confidence: 99%

A Survey of Non-Fatal Road Traffic Accidents in Babol, Northern Iran

Mohseni¹,

Janmohammadi²,

Zamani³

et al. 2018

Trauma Mon

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Background: Every year, millions of people die or are injured due to road traffic accidents worldwide. Investigating the epidemiology of these accidents could help reduce their frequency. Objectives: This study aimed to evaluate the epidemiological characteristics of non-fatal traffic accidents in Babol, northern Iran, over a seven-year period. Methods: Between 2010 and 2016, all of the orthopedic patients with road traffic accidents hospitalized at Shahid Beheshti hospital of Babol were enrolled in this cross-sectional study. The patients' information, including details of the accidents and demographic characteristics, was collected using predesigned checklists.

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Predictors of Survival in Motor Vehicle Accidents Among Motorcyclists, Bicyclists and Pedestrians

Cited by 5 publications

References 14 publications

Epidemiology of Traffic Fatalities among Motorcycle Users in East Azerbaijan, Iran

Epidemiology of Traffic Fatalities among Motorcycle Users in East Azerbaijan, Iran

Detection and Tracking of Motorcycles in Congested Urban Environments Using Deep Learning and Markov Decision Processes

A Survey of Non-Fatal Road Traffic Accidents in Babol, Northern Iran

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