scholarly journals Numerical Assessment of a Safety System to Minimize Injuries during a Cyclist Run-Over

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
E. H. López-García ◽  
M. F. Carbajal-Romero ◽  
J. A. Flores-Campos ◽  
C. R. Torres-SanMiguel
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Safety System ◽  
Security System ◽  
World Health ◽  
Passive Safety ◽  
Passive Safety System ◽  
Comparative Results ◽  
Health Organization ◽  
The Impact

Background. The World Health Organization has reported that 1.35 million people die on the roads every year due to road traffic accidents. This paper focuses on exploring a passive safety system that reduces lesions in the overtaking run-over scenario. Methods. Head Injury Criterion (HIC) and Combined Thoracic Index (CTI) were evaluated through numerical simulations using LS-Dyna®; in order to compare the computed results, three different speed scenarios were carried out (velocity of running over 40, 50, 60 km/h). Results. The computed results were divided into groups, A for the run-over test without a passive security system and B for the run-over test with a passive security system. For case A.1, the HIC15 was 3325. For case A.2, the HIC15 was 1510, and for case A.3, the HIC 15 was 1208. For case B.1, the HIC15 2605, for case B.2, the HIC15 was 1282, and for case B.3, the HIC was 730. Conclusion. The comparative results show that the passive safety system installed on the bicycle has an increased benefit impact on the severity of the injury on vulnerable road users, decreasing the probability of cranioencephalic lesions in all study cases. In addition, the thorax injuries are cut down only in the impact scenario at a speed of 40 km/h.

scholarly journals Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Hesham M. Eraqi ◽  
Yehya Abouelnaga ◽  
Mohamed H. Saad ◽  
Mohamed N. Moustafa
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Traffic Accidents ◽  
Ad Hoc ◽  
Road Traffic ◽  
Driver Distraction ◽  
World Health ◽  
Skin Segmentation ◽  
Visual Elements ◽  
Health Organization

The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a small set of distractions (mostly, cell phone usage). Unreliable ad hoc methods are often used. In this paper, we present the first publicly available dataset for driver distraction identification with more distraction postures than existing alternatives. In addition, we propose a reliable deep learning-based solution that achieves a 90% accuracy. The system consists of a genetically weighted ensemble of convolutional neural networks; we show that a weighted ensemble of classifiers using a genetic algorithm yields a better classification confidence. We also study the effect of different visual elements in distraction detection by means of face and hand localizations, and skin segmentation. Finally, we present a thinned version of our ensemble that could achieve 84.64% classification accuracy and operate in a real-time environment.

scholarly journals Forecasting road traffic accident deaths in India using seasonal autoregressive integrated moving average model

2018 ◽  
Vol 5 (9) ◽  
pp. 3962
Author(s):  
Manikandan M. ◽  
Vishnu Prasad R. ◽  
Amit Kumar Mishra ◽  
Rajesh Kumar Konduru ◽  
Newtonraj A.
Keyword(s):  
Traffic Accidents ◽  
Time Series Data ◽  
Road Traffic ◽  
Moving Average ◽  
Arima Model ◽  
World Health ◽  
Series Data ◽  
Road Traffic Accidents ◽  
Increasing Trend ◽  
Health Organization

Background: As per World Health Organization (WHO) report 1.24 million people die each year as a result of road traffic accidents (RTA) globally. A vast majority of 20-50 million people suffer from non-fatal injuries, many of them ultimately end in disability. Forecasting RTA deaths could help in planning the intervention at the right time in an effective way.Methods: An attempt was made to forecast the RTA deaths in India with seasonal auto regressive integrated moving average (SARIMA) model. ARIMA model is one of the common methods which are used for forecasting variables as the method is very easy and requires only long time series data. The method of selection of appropriate ARIMA model has been explained in detail. Month wise RTA deaths for previous years data was collected from Govt. of India website. Data for 12 years (2001 to 2012) was extracted and appropriate ARIMA model was selected. Using the validated ARIMA model the RTA deaths are forecasted for 8 years (2013-2020).Results: The appropriate SARIMA (1,0,0) (2,1,0) 12 model was selected based on minimal AIC and BIC values. The forecasted RTA deaths show increasing trend overtime.Conclusions: There is an increasing trend in the forecasted numbers of road traffic accidental deaths and it also shows seasonality of RTA deaths with more number of accidents during the month of April and May in every years. It is recommended that the policy makers and transport authority should pay more attention to road traffic accidents and plan some effective intervention to reduce the burden of RTA deaths.

scholarly journals Modelling Deaths Associated with Road Traffic Accidents and other Factors on Great North Road in Zambia between the Years 2010 and 2016 Using Poisson Models

2019 ◽  
Vol 12 (1) ◽  
pp. 68-77
Author(s):  
Ronald Fisa ◽  
Chola Nakazwe ◽  
Charles Michelo ◽  
Patrick Musonda
Keyword(s):  
Incidence Rate ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
World Health ◽  
P Value ◽  
Road Traffic Accidents ◽  
Poisson Models ◽  
Health Organization ◽  
Best Fit

Background: According to the World Health Organization (WHO), 1.24 million people die annually on the world’s roads, with 20-50 million sustaining non-fatal injuries. More than 85% (1.05 million) of the global deaths due to injuries occur in the developing world. Road traffic deaths and injuries are a major but neglected public health challenge that requires concerted efforts for effective and sustainable prevention. The objectives of the study were to estimate the incidence rate of death from RTAs, to determine factors associated with serious and fatal Road Traffic Accidents (RTAs) and to determine which of the poisson models fit the count data better. Methods: Data was collected from Zambia Police (ZP), Traffic Division on accidents that occurred on the Great North Road (GNR) highway between Lusaka and Kapiri-Mposhi in Zambia from January 1, 2010 to December 31, 2016. Results from standard Poisson regression were compared to those obtained using the Negative Binomial (NB), Zero-Truncated Negative Binomial (ZTNB) and the Zero-Truncated Poisson (ZTP) regression models. Diagnostic tests were used to determine the best fit model. The data was analysed using STATA software, version 14.0 SE (Stata Corporation, College Station, TX, USA). Results: A total of 1, 023 RTAs were analysed in which 1, 212 people died. Of these deaths, 82 (7%) were Juveniles and 1, 130 (93%) were adults. Cause of accident such as pedestrians crossing the road accounted for 30% (310/1,023) while 29% (295/1,023) were as a result of driver’s excessive speed. The study revealed that driving in the early hours of the day (1AM-6AM) as compared to driving in the night (7PM-12AM) had a significant increase in the incidence rate of death from RTAs, Incidence Rate Ratio (IRR) of 2.1, (95% CI={1.01-4.41}), p-value=0.048. Results further showed that public transport as compared to private transport had an increased incidence rate of death from RTAs (IRR=5.65, 95% CI={2.97-10.73}), p-value<0.0001. The two competing models were the ZTP and the ZTNB. The ZTP had AIC=1304.55, BIC= 1336.55, whereas the ZTNB had AIC=742.25 and BIC=819.69. This indicated that the ZTNB with smaller AIC and BIC was the best fit model for the data. Conclusion: There is a reduced incidence of dying if one is using a private vehicle as compared to a public vehicle. Driving in the early hours of the day (1AM and 6AM) had an increased incidence of death from RTAs. This study suggests that when dealing with counts in which there are a few zeros observed such as in serious and fatal RTAs, ZTNB fits the data well as compared to other models.

scholarly journals Improving Pre-hospital Care of Road Traffic Accident's Victims with Smartphone Technology

2018 ◽  
Vol 12 (2) ◽  
pp. 130 ◽  
Author(s):  
Osman A. Abdellah ◽  
Majed M. Aborokbah ◽  
Abbdelrahman Osman Elfaki
Keyword(s):  
Traffic Accidents ◽  
Success Factors ◽  
Road Traffic ◽  
Emergency Situation ◽  
Healthcare Services ◽  
World Health ◽  
Viable Solution ◽  
The World ◽  
Information And Communication ◽  
Health Organization

<p class="0abstract">One of the most causes to lose millions of lives around the world is Road Traffic Accidents (RTAs). According to the world health organization (WHO) report, 1.25 million people are killed each year as a result of RTAs, 20 to 50 million people were injured, and the number of killed people by RTAs is expected to increase further by 2020. The recent studies conclude that patient survival during a health emergency situation depends on the effective pre-hospital healthcare services, while the effective communication between the paramedics and prehospital staff is one of the important healthcare success factors. With the rapid growing of information and communication technology (ICT), wireless technologies and mobile services can provide viable solution to overcome the pre-hospital healthcare problems. The aim of this research is to improve the quality of prehospital emergency healthcare services at KSA by developing and implementing a mobile based emergency system. The proposed application is moving the diagnosis time to be started during traveling time witch accelerate the treatment. The proposed system shows satisfactory results in term of effectiveness and satisfaction</p>

Measures on the Impact-Spread of Road Accidents

2012 ◽  
Vol 490-495 ◽  
pp. 1081-1084
Author(s):  
Han Xin Zhang
Keyword(s):  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Safety Evaluation ◽  
Accident Prevention ◽  
Safety System ◽  
The Public ◽  
Emergency Rescue ◽  
The Impact

Road safety system has been a concern topic for many scholars worldwide. Although there are many analysis papers on road traffic accident prevention, security, emergency rescue, safety evaluation and other aspects, there is no a thorough and complete opinion on road safety system. The study of these issues can cause a traffic accident prevention, to reduce the incidence of traffic accidents, summing up the spread of some of the impact of traffic on the control of the effective ways to combat the public security organs to reduce the incidence of traffic accidents guidance.

scholarly journals Pedestrians’ Injury Severity in Traffic Accidents in Spain: A Pedestrian Actions Approach

2021 ◽  
Vol 13 (11) ◽  
pp. 6439
Author(s):  
Juan Diego Febres ◽  
Miguel Ángel Mariscal ◽  
Sixto Herrera ◽  
Susana García-Herrero
Keyword(s):  
High Speed ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Motor Vehicle ◽  
Road Traffic ◽  
World Health ◽  
The Road ◽  
The World ◽  
Unsafe Behavior ◽  
Health Organization

Road traffic accidents are currently between the seventh and tenth leading cause of death in the world, with approximately 1.35 million people killed per year. Despite extensive efforts by governments, according to the World Health Organization, road accidents still cause far too many deaths, especially among pedestrians, cyclists and two-wheel motor vehicle riders, who together account for almost 50% of road traffic fatalities. In particular, Spain had 410,974 traffic accidents between 2016 and 2019, involving 722,516 vehicles and 61,177 pedestrians with varying degrees of injury. This study uses the Bayesian network method to understand how the pedestrians’ responsibility and actions at the time of the traffic accident affect the injury suffered by said pedestrian, also considering the variables of the road infrastructure and vehicles at the accident site. The results confirm that the variables linked to the unsafe behavior of pedestrians, and their responsibility in traffic accidents, increase the risk of suffering serious or fatal injuries during an accident; for example, if a pedestrian is distracted this increases his/her probability of suffering a severe injury (27.86%) with respect to not being distracted (20.73%). Conditions related to traffic in high-speed areas, areas with no or poor lighting, and areas lacking sidewalks, also record increases in pedestrian injury, as is the case in the age group of pedestrians over 60 years of age.

scholarly journals Identification of Risk Factors Influencing Road Traffic Accidents

2018 ◽  
Vol 8 (1) ◽  
pp. 2417-2421 ◽  
Author(s):  
M. Touahmia
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Public Awareness ◽  
Seat Belt ◽  
World Health ◽  
Road Traffic Accidents ◽  
The World ◽  
Traffic Law Enforcement ◽  
Health Organization

Road traffic accidents (RTAs) are becoming a major problem around the world, incurring enormous losses of human and economic resources. Recent reports from the World Health Organization (WHO) reveal that each year more than 1.25 million people are killed and 50 million are injured in road traffic accidents worldwide. In Saudi Arabia, statistics show that at least one traffic accident occurs every minute, causing up to 7,000 deaths and over 39,000 injuries annually. In this study, the main causes of RATs in the province of Hail are examined. The data was collected through the use of a survey which was developed to evaluate the effect of influencing parameters on RTA rate. The results show that 67% of RTAs result from human factors, 29% from road conditions and 4% from vehicle defects. Excessive speed and violation of traffic rules and regulations were found to be the main causes of RATs. Low rates of compliance with speed limit signs and seat-belt regulations were also observed. These findings highlight the need of strengthening effective traffic law enforcement alongside with improving traffic safety and raising public awareness.

scholarly journals Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers

2015 ◽  
Vol 34 (2) ◽  
pp. 29-35 ◽  
Author(s):  
Kiarash Ghasemlou ◽  
Metin Mutlu Aydin ◽  
Mehmet Sinan Yıldırım
Keyword(s):  
Traffic Accidents ◽  
World Health ◽  
Injury Rates ◽  
The Road ◽  
Statistical Institute ◽  
Complex Interactions ◽  
Recent Developments ◽  
Detailed Assessment ◽  
Health Organization ◽  
The Impact

Accident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Instıtute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.

scholarly journals AGRESYVUS VAIRAVIMAS: VAIRUOTOJŲ AGRESYVUMO, PYKČIO IR SAVIVEIKSMINGUMO SĄSAJOS

Psichologija ◽  
2011 ◽  
Vol 43 ◽  
pp. 63-77
Author(s):  
I. Čėsnienė ◽  
A. Kašinska
Keyword(s):  
Self Efficacy ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Seat Belt ◽  
World Health ◽  
Aggressive Driving ◽  
Self Assessment ◽  
Driving Anger ◽  
Aggression Questionnaire ◽  
Health Organization

Straipsnyje analizuojami agresyvų vairavimą aiškinančių veiksnių – vairuotojų agresyvumo, pykčio ir saviveiksmingumo – ypatumai. Buvo keliami šie tyrimo uždaviniai: a) įvertinti Lietuvos vairuotojų agresyvumo, vairavimo pykčio ir saviveiksmingumo rodiklius; b) nustatyti šių rodiklių tarpusavio sąsajas bei ryšius su kitais agresyvų vairavimą aiškinančiais veiksniais (lytimi, amžiumi, vairavimo ypatumais); c) nustatyti eismo įvykio tikimybę geriausiai prognozuojančius rodiklius. Naudojant Buss ir Perry agresijos klausimyną, Vairavimo pykčio skalę, Adelaidės vairavimo saviveiksmingumo skalę bei vairavimo ypatumus atskleidžiančius kintamuosius, buvo ištirti 196 vairuotojai. Gauti rezultatai rodo, kad vairuotojų pykčio ir agresyvumo ryšys yra statistiškai reikšmingai teigiamas, o vairavimo pykčio ir vairuotojų saviveiksmingumo ryšys – statistiškai reikšmingai neigiamas. Nebuvo nustatyta reikšmingų ryšių tarp vairuotojų agresyvumo ir jų vairavimo saviveiksmingumo. Vairuotojų agresyvumo įverčiai geriausiai prognozuoja patekimą į eismo įvykius.Pagrindiniai žodžiai: agresyvus vairavimas, agresyvumas, vairavimo pyktis, vairavimo saviveiksmingumas.Aggressive Driving: the Role of Aggression, Driving Anger, and Self-efficacyČėsnienė I., Kašinska A. SummaryAccording to the World Health Organization (2004), road traffic accidents are one of the ten leading causes of death. Many of these fatalities involve aggressive driving. P. Ellison-Potter et al. (2001) suggest that aggressive driving is any driving behaviour that intentionally endangers others psychologically, physically, or both. Examples of aggressive driving include behaviours such as excessive speeding, tailgating, horn honking, traffic weaving, profanity, obscene gestures, headlight flashing, etc. In order to understand this phenomenon, researchers have examined aggressive driving in terms of several levels of variables such as sociocultural, situational or personal (Valleries et al., 2005). Moreover, self-assessment of driving skills is a central dimension of driving activity. The evaluation of specific skills may be conceptualized by self-efficacy. Self-efficacy refers to individuals’ belief in their ability to accomplish specific goals (Bandura, 1995).The article reports the findings concerning the relationship between aggression, anger and self-efficacy among Lithuanian drivers. The sample consisted of 196 drivers (99 males, 97 females) aged 18 to 74 years. The Buss–Perry Aggression Questionnaire (Buss and Perry, 1992), the Driving Anger Scale (Deffenbacher et al., 1994), and the Adelaide Driving Self-efficacy Scale (George et al., 2007) were used in the study. Participants were administered also a questionnaire measuring a variety of demographical characteristics and driving-related factors.The results showed that more aggressive drivers tend to express the higher levels of driving anger than do less aggressive drivers. A negative relation between driving anger and driving self-efficacy was found. Further, the driving self-efficacy was higher in males than in females. Research findings indicate that there are gender differences in aggression, i.e. male drivers are more aggressive than female drivers. There are significant age differences in driver anger. In addition, high anger and aggression were related to unsafe driving behaviours. Seat-belt wearing tends to be less frequent among male drivers than among females. Aggression was found to be a predictor of crash-related outcomes. Finally, limitations of the study are discussed.Keywords: aggressive driving, aggression, driving anger, driving self-efficacy.

THE RELEVANCE OF OPTIMIZING THE APPROACH TO TRAINING POLICE OFFICERS IN FIRST AID MEASURES

2021 ◽  
pp. 11-13
Author(s):  
I. Lovchikova ◽  
A. Chursin ◽  
A. Zhuromsraya
Keyword(s):  
Police Officers ◽  
Traffic Accidents ◽  
Road Traffic ◽  
First Aid ◽  
World Health ◽  
Road Accidents ◽  
Production Factors ◽  
First Aid Training ◽  
Health Organization ◽  
High Level

This article develops the idea of the need to use new methods in training police officers in first aid measures to increase their motivational and professional readiness to provide first aid at the scene. The current statistics of road traffic accidents (road accidents) are analyzed in the context of the number of injured and dead, world according to the World Health Organization (WHO), local according to the federal bodies of the Ministry of Internal Affairs (MIA). The relevance of making changes to the first aid training programs for organizations with a high level of exposure to production factors is considered by the example of police officers in the context of accident statistics and survey data of police officers in the context of first aid to victims at the scene.

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