scholarly journals Driver Drowsiness Detection System Based on Eyes, Mouth and Head Tilt

2020 ◽  
Vol 9 (5) ◽  
pp. 506-511
Keyword(s):  
Detection System ◽  
Head Tilt ◽  
Road Accident ◽  
Economic Losses ◽  
Road Accidents ◽  
Essential Requirement ◽  
Automobile Manufacturing ◽  
The Road ◽  
Driver Drowsiness ◽  
The Universe

The modernization of the automobile manufacturing automatically increases the number of automobiles on transportation way. Day by day with the quick increase in automobiles, the number of road accidents seems to be drastically increasing. In our daily life accidents are common phenomenon. In the Universe, yearly the accidents on road may cause fatal injuries, death and economic losses. Drowsiness of the driver may be one of the prime causes for accidents on the way and the driver is prone to a possible accident. So it is essential requirement to find the driver’s drowsiness to reduce the road accident rates. In this paper we proposed a system to find the driver drowsiness based on eye, mouth and head tilt. This system is helpful to monitor a driver’s observance level and warns him for a significant part in avoiding road mishaps.

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 The Effects of Roadside Hazards on Road Accident Severity

2019 ◽  
Vol 49 (2) ◽  
pp. 319-339 ◽  
Author(s):  
Marcin Budzyński ◽  
Kazimierz Jamroz ◽  
Łukasz Jeliński ◽  
Anna Gobis
Keyword(s):  
Road Safety ◽  
Road Accident ◽  
Road User ◽  
Road Accidents ◽  
Safety Equipment ◽  
Design Rules ◽  
The Road ◽  
Run Off ◽  
Safety Strategies ◽  
Accident Severity

Abstract The risk of becoming involved in an accident emerges when elements of the transport system do not operate properly (man – vehicle – road – roadside). The road, its traffic layout and safety equipment have a critical impact on road user safety. This gives infrastructural work a priority in road safety strategies and programmes. Run-off-road accidents continue to be one of the biggest problems of road safety with consequences including vehicle roll-over or hitting a roadside object. This type of incident represents more than 20% of rural accidents and about 18% of all road deaths in Poland. Mathematical models must be developed to determine how selected roadside factors affect road safety and provide a basis for new roadside design rules and guidelines.

scholarly journals Willingness-To-Pay for Estimation the Risk Pedestrian Group Accident Cost

2020 ◽  
Vol 6 (6) ◽  
pp. 1064-1073 ◽  
Author(s):  
Chompoonut Puttawong ◽  
Preeda Chaturabong
Keyword(s):  
Willingness To Pay ◽  
Injury Risk ◽  
Road Accident ◽  
Road Accidents ◽  
The Road ◽  
Statistical Life ◽  
Perception Of Safety ◽  
Road Users ◽  
Pedestrian Injury ◽  
The Cost

The proven willingness-to-pay with contingent valuation (WTP-CV) method is an effective tool for evaluating the cost of road accidents in many countries. In Thailand, the most fatalities on Thailand’s roads involve the vulnerable road users (VRUs) including motorcycle users, bicyclists, and pedestrians. With the effectiveness of using WTP-CV in analyzing the accident cost of motorcycle users and lack of specific accident cost for pedestrians, this research focuses on evaluating the accident cost on the pedestrians which is the second most VRU fatality. In this research, the road accident cost of pedestrians aged 15-39 years in Bangkok by WTP-CV method was determined. The WTP-CV questionnaire was employed as a tool to measure the payment of which each pedestrian is willing to pay to reduce the fatality and injury risk from road accidents. One thousand and two hundred pedestrians in Bangkok were interviewed. With the results, the value of statistical life (VOSL) for pedestrians in Bangkok is valued at US$ 0.43 million, while the value of statistical injury (VOSI) is estimated at about US$ 0.014 million, respectively. In addition, it is found from the regression analysis that for the fatality risk reduction, higher educational levels and private business pedestrians are likely to pay more to save their lives. In order to reduce the risk of injury, respondents, who are single in marriage status, are likely to pay more to reduce the risk of pedestrian injury. However, a high perception of safety is less likely to pay for the reduction of injury risk.

scholarly journals Modeling the Complexity of Road Accidents Prevention

2020 ◽  
Vol 9 (2) ◽  
pp. 24-41
Author(s):  
Alex Kizito ◽  
Agnes Rwashana Semwanga
Keyword(s):  
Traffic Safety ◽  
Police Officers ◽  
Road Transport ◽  
Road Accident ◽  
Road Accidents ◽  
Dynamic Interactions ◽  
The Road ◽  
Dynamic Synthesis ◽  
Road Users ◽  
Synthesis Methodology

Simplistic representations of traffic safety disregard the dynamic interactions between the components of the road transport system (RTS). The resultant road accident (RA) preventive measures are consequently focused almost solely on individual/team failures at the sharp end of the RTS (mainly the road users). The RTS is complex and therefore cannot be easily understood by studying the system parts in isolation. The study modeled the occurrence of road accidents in Uganda using the dynamic synthesis methodology (DSM). This article presents the work done in the first three stages of the DSM. Data was collected from various stakeholders including road users, traffic police officers, road users, and road constructors. The study focused on RA prevention by considering the linear and non-linear interactions of the variables during the pre-crash phase. Qualitative models were developed and from these, key leverage points that could possibly lower the road accident incidences demonstrating the need for a shared system wide responsibility for road safety at all levels are suggested.

scholarly journals Modelling road traffic safety indices by means of regression with panel data

2020 ◽  
Vol 12 (4) ◽  
pp. 40-51
Author(s):  
Katarzyna Brzozowska-Rup ◽  
Marzena Nowakowska
Keyword(s):  
Panel Data ◽  
Traffic Safety ◽  
Road Traffic ◽  
Government Expenditure ◽  
Road Accident ◽  
Road Accidents ◽  
The Road ◽  
Road Traffic Safety ◽  
Safety Indices ◽  
The Impact

Abstract Although the occurrence of road accidents and the number of road accident casualties in almost all Polish voivodeships has decreased over the last few years, the rate of this change varies considerably from region to region. To provide a better understanding of such a tendency, panel data regression models are proposed to conduct this pilot research which evaluates the relative performance of Polish regions in terms of their road traffic safety. Panel data are multi-dimensional data which involve measurements over time. In the research, a voivodeship is a unit analysed at a group level, whereas a year is a unit analysed at a time level. A two-way error component regression model has been applied to survey the impact of regressors, the group effects, and time effects on a dependent variable. The analysis has been conducted using data acquired from the Statistics Poland Local Data Bank website, as well as from the General Directorate for National Roads and Motorways. The panel data from 16 regions in Poland and the 2012–2018 period have been investigated. The examined models refer to road traffic safety indices defined based on the following characteristics: the number of road accidents, the number road fatalities, and the number of people injured. The results of all the three models indicate a negative effect as regards the GDP per capita, (car) motorisation rate, the indicator of government expenditure for current maintenance of national roads, and the road length per capita. A positive association has been found between the truck motorisation rate and the indicator of local government expenditure on roads. The impact of the region's urbanisation indicators on road safety is ambiguous as, on the one hand, its increase causes a reduction in the road accident and accident injury indices, but, on the other hand, it produces a rise in the accident fatality index. In the models, the significance of time effects has been identified; a decreasing time trend suggests a general improvement in road safety from year to year. Most of the group effects have turned out to be highly significant. However, the effects differ as regards both the road accident and the accident injury indices in magnitude and direction.

scholarly journals Contactless Automated Express Evaluation of Damages to a Car Body by Visual Parameters

2019 ◽  
Vol 18 (6) ◽  
pp. 471-475
Author(s):  
M. Tarasovа ◽  
N. Filkin ◽  
R. Yurtikov
Keyword(s):  
Road Safety ◽  
Human Factor ◽  
Road Accident ◽  
The Body ◽  
Road Accidents ◽  
Car Body ◽  
The Road ◽  
Accident Data ◽  
Established Fact ◽  
Time Required

Explosive development of computer technologies and their availability made it possible to extensively focus nowadays on emerging state-of-the-art technologies, digitalization, artificial intelligence, and automated systems, including in the field of road safety. It would be reasonable to implement some technical devices in this respect to remove human factor and automate some procedures completed at the scene of a road accident. Automatically filled up road accident inspection records and, mainly, diagrams of the accident will reduce time required for the examining inspector and remove human factor. Ultimately, an automated road accident data sheet is suggested to be established. To tackle the issues above requires a technique to determine whether the produced damages to the car body result from the same road accident. The fact remains that there are circumstances when even vehicle trace examination would not do the job, in case of multiple corrosive damage to the body. In view of the above, a technique designed to determine whether the damages produced are caused at the same point of time gains its ground. A technique for a time-related corrosion examination is offered herein to cut expenditures for diagnostics and expert examination of road accidents. That will also eliminate the matters of argument with respect to the road accident evaluation in court. Among added benefits of the technique are that it is simple, quick to implement, and requires no human involvement. It is a well-established fact that each chemical element or a mixture of substances has its own timeinvariant color attributes which allows to determine availability of one or another substance during corrosion of metal surfaces, by emission from the surface in question.

scholarly journals Accident Alarming and Collision Avoiding System for Drowsy Drivers

2021 ◽  
pp. 89-95
Author(s):  
M. Ravindra Kumar ◽  
P. Satya ◽  
S. Swathi ◽  
S. Manoj Kumar ◽  
P. Sandeep
Keyword(s):  
Driving Force ◽  
Automatic System ◽  
Vehicle Control ◽  
Automobile Driving ◽  
Road Accident ◽  
Road Accidents ◽  
Sleep State ◽  
Driver Drowsiness ◽  
Smoke Sensor ◽  
And Control

Now a day’s road accident is one of the principal concerns in our states. Reckless automobile driving and driver drowsiness are the major motives in the back of those road accidents. The alarming rate of accidents and uncontrollable automobiles on the streetdemand an automatic system that could guide drivers right now in dangerous conditions. While any obstacle (just like the human, vehicle, and some other item) comes in front of the vehicle, control speed of the vehicle is the viable strategy to keep away from injuries. While a driver in a drowsy state or sleep state, give warning to the driver and control the velocity of the vehicle is the possible way to keep away from injuries. We endorse a solution in our mission to avoid avenue injuries and to manipulate the rate of automobiles. The machine will locate boundaries and motive force drowsiness using an ultrasonic Sensor and eye blink sensor and Arduino will execute a collision-avoidance gadget according to a pre-burnt code in the Arduino. The machine has also velocity manipulate features. It’s going to reduce or increase the rate of the vehicle relying on the impediment distance from the shifting car to decrease the damage or collision of an accident. Furthermore, if any obstacle from the bottom comes in the direction of cars, right now a buzzer will alert the driving force, and if any quick circuit happens in the engine element smoke sensor detecting and gives alert to the driving force and stop the automobile.

scholarly journals Prioritization of Black Spots in Hilly Road Segment using Road Engineering Data

2020 ◽  
Vol 9 (3) ◽  
pp. 4418-4422
Keyword(s):  
Black Spot ◽  
Road Transport ◽  
Road Accident ◽  
Industrialized Countries ◽  
Road Accidents ◽  
Road Engineering ◽  
The Road ◽  
Black Spots ◽  
Accident Data ◽  
On The Road

Road accidents are one of the causes of disability, injury and death. As per the latest road accident data released by the Ministry of Road Transport & Highways (MoRTH), the total number of accidents increased by 2.5 percent from 4,89,400 in 2014 to 5,01,423 in 2015. The analysis reveals that about 1,374 accidents and 400 deaths take place every day. Every single year, it has been estimated that over three lakh persons die and 10-15 million persons are injured in road accidents throughout the world. According to the analyses, statistics of global accident indicate that in developing countries, the rate of fatality per licensed vehicle is very high as compared to that of industrialized countries. A road stretch of about 500 metres in length in which either ten fatalities or five road accidents (involving grievous injuries/fatalities) took place during last three calendar years, on National Highways is considered as a road accident black spot according to MoRTH, Government of India. In the present study the identified black spots of Haridwar and Dehradun city were included comprising of a total of 81 black spots out of which there were 49 black spots which were identified in Dehradun followed by 32 black spots in Haridwar. The present study was an attempt to carry out the prioritization of these identified blackspots with respect to the factors that were considered to evaluate accident prone locations on the road. The identified black spots were then prioritized using the classification scheme (ranking from low to high).The study reveals that the advantage of using this approach for prioritizing accident black spots on roads is that it requires very less additional data other than the road network maps.

scholarly journals Identification of Road Accident by using Black Spot Method Between Panthaghati to Dhalli Road

2020 ◽  
Vol 9 (2) ◽  
pp. 723-728
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Research Paper ◽  
Road Accident ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
The Road ◽  
Black Spots

In India road accidents are very serious problem because of large population and high traffic density of vehicles. Most of the road accidents occur mainly due to the negligence of driver and poor infrastructure only a few accidents occur due to the technical error of vehicles. The main purpose of this research paper is prevention of road traffic accidents and improvement of road safety in Shimla. Road safety is very important aspect of today’s life, so it is important that everybody should aware about road safety. To do this study a section of 12km length is chosen between Panthaghati to Dhalli in district Shimla on NH 5 where accidents black spots are identified for the section by analyzing secondary data used to prevent road accidents. In this study primary data is used for observing the road conditions and secondary data is used to find accidents black spot. Black Spot is a point or a place on the road where road accident occurs repeatedly one after another which is known as accident black spot. To identify these black spots we use weighted severity index (WSI) method. It is one the most reliable and effective method for determining the most proven accidents black spots. Shimla is a hilly area and it has narrow roads, blind curve and black spots which increase the chances of road traffic accidents. In past recent years road traffic accidents are increasing in Shimla and this study deals with identification of major issues causing road traffic accidents. This research paper helps to improve the road safety in Shimla because in this study the analysis has been done to identify the major problems responsible for gradually increasing road accidents. This research paper is also used in future research paper as reference purpose and it will also provide an overview to other researchers who want do their research on similar kind of topics.

Pregnancy and public road accident: Frequency, socio-demographic and materno-fetal prognostics at the Prefectoral Hospital of Siguiri, Guinea

2021 ◽  
Vol 1 (1) ◽  
pp. 048-051
Author(s):  
Boubacar Siddi Diallo ◽  
Boubacar Alpha Diallo ◽  
Ibrahima Conte ◽  
Oumar Diawara ◽  
Maurice Koivogui ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Women Victims ◽  
In Utero ◽  
Traditional Healers ◽  
Road Accident ◽  
Premature Delivery ◽  
Road Accidents ◽  
The Road ◽  
Minor Injuries ◽  
Epidemiological Profile

Objectives: To calculate the frequency of road accidents among pregnant women, to describe the epidemiological profile and to establish the maternal and fetal prognosis at the prefectural hospital of Siguiri. Methodology: this was a prospective study of a descriptive type lasting six (6) months from August 1, 2019 to January 31, 2020. It concerned all pregnant women victims of road accidents admitted to Siguiri prefectural hospital during the study period. All pregnant women who were victims of road accidents received at the hospital during the study period and who gave their consent were included. All pregnant victims of road accidents who did not give their consent were included and cases of trauma unrelated to the road accident. We conducted an exhaustive recruitment of all highway accident cases among pregnant women during the study period. The limitations or constraints of the study were the delay in the care of some pregnant women who first sought treatment from traditional healers. Results: The frequency of road accidents among pregnant women was 52.08% (n = 25) taking into account pregnant women victims of trauma (n = 48). The epidemiological profile was that of a woman in the age group 14-23 years and 24-33 years (44%), housewife (72%) and city dwellers (76%). The majority of pregnant women were received through a police requisition (68%) followed by themselves (24%). The predominant type of accident gear was two-wheeled (88 %) Pregnant women in the second trimester of pregnancy were the most affected (68%). The predominant bodily injuries were minor injuries (52%) followed by no injuries (simple contusion) (32%) and then serious injuries (poly trauma) (16%). The road accident had no impact on the pregnancy in (84%) followed by death in utero 12% then threat of premature delivery 4%. All pregnant women with minor injury or without injury (with a living fetus) received treatment with spasfon / salbutamol plus progesterone for 48 hours and delivery was directed to patients with death in utero. We recorded a maternal mortality rate of 12% and an in utero fetal death rate of 12%. Conclusion: Road accidents involving a pregnant woman are frequent in the prefecture of Siguiri, occurring in young women traveling on two-wheeled vehicles. Trauma and pregnancy management were multidisciplinary.

Sign in / Sign up

Export Citation Format

Share Document