Accident Location Research Articles

Modelling of possible tanker accident oil spills in the Istanbul Strait in order to demonstrate the dispersion and toxic effects of oil pollution.

Countries located on the Black Sea coast perform most of their sea trade through the Istanbul Strait (IS). Approximately 50,000 ships pass through the IS each year, with crude oil tankers making up the majority. Thus, the aim of the study is to determine the acute toxic effect of oil pollution that may occur as a result of crude oil tanker accidents in the IS. By utilising data related to accidents that have occurred in the IS, locations of concentrated tanker accidents, or "hot spots," were determined by Kernel Density Analysis. Subsequently, the distribution of potential leaks following an oil tanker accident, within these hot spots, is modelled with GNOME software. Finally, acute toxicity caused by oil pollution in the marine ecosystem is determined by Aliivibrio fischeri luminescent bacteria toxicity test. In this research, 5 hot spots are identified, where the maximum calculated amount of oil that can reach the coastline after 72h is 3096 metric tons. Similarly, oil pollution can affect a total coastline of 30-35km. Furthermore, it was determined that after the oil was diluted in seawater, at a ratio of 1:200,000, the toxic effects decrease (EC50 above 100mg/L), yet the chronic effects may still continue. The results of this study may serve as a reference for coastal state authorities to develop emergency response plans. Having this valuable knowledge of where high-risk accidents are most concentrated, where the accidents occur intensely, which areas can be affected by the pollution, the duration of the pollution effects, and the distance between the areas, will help determine the number of intervention stations to be installed, their locations, and equipment to be installed to the stations.

Gambaran Korban Meninggal Dunia dengan Cedera Kepala pada Kecelakaan Lalu Lintas di Bagian Forensik RSUP dr M Djamil Padang Tahun 2018-2019

Background. A traffic accident is an incident on the road which accidentally involves a vehicle with or without other road users which results in human casualties and/or property loss. The most common injury that occurs during traffic accidents is head injury. Head injury due to traffic accidents is a major cause of disability and mortality in developing countries.Objective. To analyze the overview of victim who died with head injury in traffic accidents at the forensic department of DR. M. Djamil Padang 2018-2019.Methods. This type of research is retrospective descriptive. Sampling was carried out by total sampling technique in the forensic department of RSUP Dr. M. Djamil Padang from March 2020 - September 2020.Results. The results showed that 150 victims who died with head injury in traffic accidents. The conclusion of this study, most of the age is 15-29 years and the incidence was higher in males. The most common injury patterns are abrasions.The head region most affected is the frontalis region. The most time for accidents is at 12.01-18.00 WIB and the most accident days are on Sundays. Most of the accident locations were outside the city of Padang, most types of vehicles were motorbikes, the role of the most victims were motorists and the most types of accidents were being hit by other vehicles.Conclusion. Most of the age is 15-29 years and the incidence was higher in males. The head region most affected is the frontalis region. Most of the accident locations were outside the city of Padang, most types of vehicles were motorbikes, the role of the most victims were motorists and the most types of accidents were being hit by other vehicles

Adaptive Smart Traffic Accidents Management System

<p>The proliferation of smart devices, IoT applications and wireless communication technologies contribute in countries development, society’s security, cost reduction, and customer services satisfactions; since they are used in different aspects of our life. Traffic congestion and accidents are increased recently and reached critical limits, so these contribute in initiating sever problems for researchers, governments and industry over the last few decades. Traffic accidents have many defects relating to increase number of death, infrastructure distribution, and health injuries; therefore, there is a crucial need to develop and modify an approach that utilizes the new technology to limit and prevent the traffic accidents. Wireless sensors networks are developed to support smart solutions in smart cities like smart traffic, smart grid and others. In this research we developed a comprehensive approach to achieve the following three important goals in smart accident elimination. The first goal is to minimize the number of exchange information packets between sensors to save the battery life through developing and adapting clustering schema to minimize the number of exchanges information packets. The second goal is to calculate and determine the optimum route from accident location to the nearest rescue location by developing a dynamic routing schema that is calculated by the control station depending on a cost heuristics function. The third goal is to predicate the accident causes and minimize the probability of accidents occur using a warning message schema and drawing some obstacles on some routing paths. Cupcarbon simulator and MATLAB software tool are developed to simulate different scenarios in order to proof the research goals.</p>

Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain

In recent years, both developed and developing countries have witnessed an increase in the number of traffic accidents. Aside from a significant rise in the overall number of on-road commercial and non-commercial vehicles, advancements in transportation infrastructure and on-road technologies may result in road accidents, which generally result in high mortality. More than half of these fatalities are the result of delayed response by medical and rescue personnel. If an accident site receives quick medical treatment, an accident victim's chances of survival may improve considerably. Based on the IoT-based multiple-level vehicle environment, this study proposes a low-cost accident detection and alarm system. Vehicles are equipped with a "Black Box" board unit and an accident location identification module for the Global Positioning System (GPS), in addition to mechanical sensors (accelerometer, gyroscope) for accurate accident detection. This study has evaluated the proposed system with average packet delivery ratio (PDR) vs. relay nodes. Our simulation results have evaluated the evolution of relay nodes in the mobile / sensor node through internet gateway. It has also been demonstrated that the packet delivery ratio is inversely related to the incremental number of relay nodes.

Accident Detection and Reporting System

A significant rise in the number of road accidents has been observed due to the increasing number of vehicles. Significant research has been conducted on accident for the rescue, particularly on the use of Information and also Communication Technologies for efficient and prompt rescue or saving operations. The majority of such works will provide us the sophisticated solutions that focus on reducing response times. However, such solutions can be very expensive and are not available in all forms of vehicles. Our approach aims to take advantage of the advanced specifications of smartphones to design and develop a low-cost solution for enhanced transportation systems that are deployable in legacy vehicles. In this topic, a customized Android application is developed to collect information regarding speed, attraction, pressure, sound, and location. Speed is one of the factor which is used to improve the identification of the accidents. It arises because of clear differences in environmental conditions or changes (e.g., noise, deceleration rate) that arise in low-speed collisions, versus higher-speed collisions). The information collected is again further processed to detect road incidents. Furthermore, a navigation system is also constructed to report the incident to the nearby hospital. Furthermore, a navigation system is constructed to send and report the accident location and patients details to the nearby hospital! The proposed approach is validated through simulations and comparison with a real data set of road accidents acquired from the Road Safety Open Repository and shows promising results in terms of accuracy.

Automatic Vehicle Accident Indication and Reporting System for Road Ways Using Internet of Things

In India, transport becomes a basic commodity of daily life. As transportation starts increasing, safety has become a major concern for consumers. This paper mainly aims at reducing the fatalities caused due to accidents occurring in roadways. In general, many lives could be saved if emergency service could get accurate accident location and rescue the injured people at the minimum possible time. The Internet of Things has revlontinsed the modern world in recent times. As Global Positioning System has become an integral part of any vehicle system, this effective method is utilized to monitor the location of vehicles and send accident locations to an Accidents Monitoring and Rescue Services Centre (AMRSC) using GSM. The Accelerometer located in the vehicle system gives the live status of the vehicle position while the vehicle is in motion. Whenever an accident occurs, the signal from the accelerometer is fed to the controller. The Node MCU controller is programmed to check whether the accident has occurred and given the information to the user and AMRSC as soon as possible. Now, the system will also send the accident location acquired from the GPS along with the vehicle details through the GSM network to AMRSC. After receiving the alert message from the infected user vehicle system, the rescue team will reach the accident location as soon as possible by reading the data from the server.

Modelling Road Accident using Poisson regression Models

The objective of this research is to evaluate the safety of multi-lane urban roads in India. In this paper, a generalised linear modelling technique is applied for the analysis of the Indian Highway's road accident. The features of road, speed, and traffic data are analysed in Surat on four-lane urban roads. A novel approach to the model of accident prediction for an urban highway is being proposed to include daily average travel (ADT) and average spot speed (AS). The model was developed as a reliant variable and significant variables such as chain width, intersection no, ADT, AS, as separate variables for accidents per kilometre.. The results of the model provide a better assessment of accidents on a multilateral urban road. Because road accidents are different, statistical models do not adequately capture the characteristics of each section. As a result, the results of Poisson regression were the opposite of these variables. There was also no statistically significant type of traffic control. Significant statistically at level 0.05. Accident locations were assessed by correlating the severity of the accident with different attributes. This investigation will contribute to improving urban road safety.

Vehicle Accident Location Detection Using IoT

Speed is one of the basic reasons for vehicle accident. Many lives could have been saved if emergency service could get accident information and reach in time. Nowadays, GPS has become an integral part of a vehicle system. This paper proposes to utilize the capability of a sensor which will detect the accident and GPS collects the coordinates sends an alert message using GSM module along with accident location. This will help to reach the rescue service in time and save the valuable human life.

Intelligent Accident-Detection and Ambulance - Rescue System

Accidents are the major causes of death, be it in today's most technologically advanced world. Road accidents and traffic congestion are the major problems in urban areas. Currently there is no technology for detection of accidents. Also due to the delay in reaching of the ambulance to the accident location and the traffic congestion in between accident location and hospital increases the chances of the death of the victim. There is a need of introducing a system to reduce the loss of life due to accidents and the time taken by the ambulance to reach the hospital. Yearly lots of visually impaired people lose their lives by being victims of such accidents. To overcome the drawback of existing system we will implement the new system in which there is an automatic detection of accident through sensors and it will send the location of the accident to the Nearest Hospital, Police station and to the family members which will rush an ambulance from a nearest hospital to the accident spot. This will minimize the time of ambulance to reach the hospital. To achieve this we are using like MEMS (Micro Electro Mechanical Systems) (MPU6050), And using GPS module we will get the location where the accident took place and by using NODEMCU and IFTTT messaging protocol we will send the message of obtained location. Along with this there would be control of traffic light signals in the path of the ambulance using RFID TECHNOLOGY. This system is fully automated, thus it finds the accident spot, controls the traffic lights, helping to reach the hospital in time.

Control and Monitoring Vehicle using Arduino and GSM Module

The Black Box control and monitoring system for vehicles concept is derived from the aviation industry, a flight recorder, colloquially known as a black box; although it is now orange-colored for easy search, is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents and incidents. With the advancement in technology and cost coming down, in our project we attempt to build similar device for our cars, not only this device will help us in post-crash analysis but also it will help us in quicker emergency rescue operation. Our research has been targeted towards building an integrated system for emergency rescue services in the event of a road accident. The purpose of the project is to find the accident location using GPS module and to send this location by means of sending a message using GSM module to the pre-coded number. This system is usually placed inside the vehicle. It reduces the time it takes for emergency rescue to arrive at the crash location.

Vehicle Accident Alert and Tracking System

In this project a Vehicle Accident Alert and Tracking System has been developed. Emergencies, by definition, are unpredictable and rapid response may be a key requirement in emergency management. Globally, most number of deaths occurs each year is due to excessive delays in rescue activities. This idea of detection of automobile accidents isn't recent and therefore the automobile industries have created tremendous progress in optimizing the technology. This paper is an attempt to make a contribution there in location of generation. Here we are seeking to find accident through the Accelerometer because it facilitates in identifying the accessibility and if the values of x, y and z parameters are extra than the defined values than it’s getting to set situation to proper and therefore the code written for initiating the intimation and SMS alert gets executed. With this method the accident location is often detected easily and therefore the information of the accident location are often sent via the GPS to the emergency offerings for assistance.

Characteristics of Traffic Accidents on Highways: An Analysis Based on Patients Treated at a Regional Trauma Center

Purpose There have been increasing concerns about serious traffic accidents on highways. The purpose of this study was to analyze factors affecting traffic accidents on highways and the severity of the resulting injuries. Methods This retrospective study was conducted at a regional trauma center. We reviewed 594 patients who had been in 114 traffic accidents on highways from January 2018 to June 2020. We collected demographic data, clinical data, accident-related factors, and meteorological data (weather and temperature). Results Environmental risk factors were found to be significantly associated with the incidence of traffic accidents on highways. Injury severity and the death rate were higher in sedans than in any other type of vehicle. Tunnels were the most common location of accidents, accounting for 47 accidents (41.2%) and 269 injured patients (45.3%). The injury severity of individuals riding in the driver’s seat (front seat) was high, regardless of vehicle type. Three meteorological risk factors were found to be significantly associated with traffic accidents: rainy roads (odds ratio [OR] 2.08; 95% confidence interval [CI] 1.84–3.29; p=0.01), icy or snowy roads (OR 5.12; 95% CI 2.88–7.33; p<0.01), and foggy conditions (OR 2.94; 95% CI 2.15–4.03; p<0.05). Conclusions The injury severity of patients was affected by seat position and type of vehicle, and the frequency of accident was affected by the location. The incidence of traffic accidents was strongly influenced by meteorological conditions (rain, snow/ice, and fog).

Çiftlik Kazalarında İzole Ortopedik Yaralanma Mekanizmalarının Değerlendirilmesi

Aim: This study aimed to investigate the mechanisms and characteristics of isolated orthopedic injuries from farm accidents which involve the extremities. Methods: The medical records of 138 patients (31 females, 107 males) who presented to the emergency department with isolated orthopedic injuries from farm accidents were reviewed retrospectively. Data on patient age and sex, mechanism of injury, injured site/extremity, injury type, treatment performed, distance from accident location to hospital, approximate time from ac¬cident to hospital arrival, season of injury, and whether skin integrity was impaired were recorded. Results: The mean patient age was 35.08 (7–71) years. The injuries occurred during the use of riding animals (n=14, 10.1%), combine harvester/tractor equipment (n=14, 10.1%), cattle (n=24, 17.4%), saw/ ax/hammer (n=47, 34.1%) and tractors (n=23, 16.7%) and due to falling from height (n=16, 11.6%). Of all accidents, 23 (16.7%) occurred in spring, 66 (47.8%) in summer, 30 (21.7%) in autumn, and 19 (13.8%) in winter. Mechanism of injury was statistically significantly related to season, sex, and site of injury (p=0.001). The time to emergency department visit was shorter in cases with impaired skin integrity (p<0.05). Conclusion: The mechanism of injury can vary seasonally together with the works performed and machines used. The time to emergency department visit can vary according to whether skin integrity is impaired. As a result of the division of labor in families working in agricul¬ture, mechanism of injury can also vary by sex.

Emergency department visits in Reykjavik for electric scooter related injuries during the summer of 2020

Electric scooters have become popular in Iceland. The aim of the current study was to gather data on the incidence, causes, and severity of injuries due to the use of electric scooters in the Reykjavik area during the summer of 2020. MATERIAL AND METHODS: Individuals presenting to the Emergency Department (ED) at Landspitali between June 1 and August 31 were asked about the location and cause of accident, use of protective equipment, and use of recreational drugs and alcohol. Diagnosis and treatment data was gathered from hospital records. RESULTS: During the study period, 149 individuals presented with electric scooter injuries,on average 1.6/day. Patients' age ranged between 8 and 77 years, and 45% were younger than 18 years of age. In 60% of cases the cause of accident was that the patient was riding too fast, lost balance, or uneven road surface. Seventy-nine percent of children reported using a helmet, compared to only 17% of adults. No children reported having been under the influence of alcohol or recreational drugs at the time of the accident, compared to 40% of adults who reported that they were intoxicated. Fractures were diagnosed in 38% of patients, 6% needed hospital admission, but no patient suffered serious injury. CONCLUSION: During the summer of 2020, one to two individuals were injured daily in the Reykjavík capital area while using electic scooters, but no serious injuries occurred. Preventive measures to decrease injury rate from the use of electric scooters should focus on infrastructure, encourage helmet use, and education on the risk of injury associated with operating electric scooters while intoxicated.

Intelligent Traffic Accident Prediction Model for Internet of Vehicles With Deep Learning Approach

In this study, a high accident risk prediction model is developed to analyze traffic accident data, and identify priority intersections for improvement. A database of the traffic accidents was organized and analyzed, and an intersection accident risk prediction model based on different mechanical learning methods was created to estimate the possible high accident risk locations for traffic management departments to use in planning countermeasures to reduce accident risk. Using Bayes’ theorem to identify environmental variables at intersections that affect accident risk levels, this study found that road width, speed limit and roadside markings are the significant risk factors for traffic accidents. Meanwhile, Naïve Bayes, Decision tree C4.5, Bayesian Network, Multilayer perceptron (MLP), Deep Neural Networks (DNN), Deep Belief Network (DBN) and Convolutional Neural Network (CNN) were used to develop an accident risk prediction model. This model can also identify the key factors that affect the occurrence of high-risk intersections, and provide traffic management departments with a better basis for decision-making for intersection improvement. Using the same environmental characteristics as high-risk intersections for model inputs to estimate the degree of risk that may occur in the future, which can be used to prevent traffic accidents in the future. Moreover, it also can be used as a reference for future intersection design and environmental improvements.

Development of Simulated Scenarios for Quadricycle Safety

In Italy, quadricycles can be driven by the youngest category of drivers of 14 years of age. The increasing popularity together with the low-level of safety regulation of these vehicles compared to cars gives cause for concern. Simulators, considered as a training method, provide a realistic reproduction of driving environments so that they can be used to improve driving skills and risk awareness to novice and young drivers. Simulation trial can also be used to evaluate driving performance about safety. At first, the more appropriate simulated accident scenarios for training of young drivers were identified as those with the highest frequency in real world crashes. Since the ISTAT national crash data base includes a multitude of information, but no unique scenario code, it was necessary to use all the available data to classify the proper scenario associated with each crash. To this aim, the taxonomy theory was applied to create a comparable structure for the database. For training and evaluation tests, five accident scenarios were implemented in a simulation course that lasted approximately fifteen minutes. Ten participants driving a simulated quadricycle in a simple one screen simulator were used as a sample to test the working performance of the scenarios. Finally, Traffic Conflict Technique was applied to measure performance indicators derived from the data acquired during the simulation tests. The results confirmed data from the accident database about the location of accidents in rural intersections.

Mapping of Blackspots Accident Area at North South Expressway to Produce Expressway Advisory System

The study was carried out to produce an advisory system based on the blackspot accidents mapping at the North-South Expressway (NSE). Blackspots are location where the road traffic crashes have historically concentrated by type of accident in which the accident caused fatalities, severe injuries, minor injuries and damage. This research aims to identify accident blackspot and plotting accident data into a digital map of the study area to produce advisory systems for highway users. The software used in this study namely Google Earth Pro, ArcMap and ArcGIS online. Results showed that blackspot location are known in the form of mapping where it can be performed online. In addition, the path with high number of accident points weightage location were identified and prioritized. By applying Google Earth Pro and ArcGIS software, the advisory system was created, and these blackspot locations can also be easily accessed by highway users. Therefore, the advisory system helps in facilitate the users for trip planning base on the accident status locations as a precautionary measure and initiative to reduce the rate of road accident in expressway.

Analisis Daerah Rawan Kecelakaan (Black Site) Dan Titik Rawan Kecelakaan (Black Spot) Provinsi Lampung

Traffic accidents are the main indicator of road safety levels. There were 2,225 traffic accidents throughout 2019 in Lampung Province with 724 deaths, 1240 seriously injured, and 2015 minor injuries. The research was conducted to the identification of the black site and black spot in Lampung Province. The method used in this research is the EAN, Z-score, Frequency of accidents method calculates accident-prone areas to get the value of the accident location (Black Site) and the Cumulative Summary method to identify the black spot. The results showed from 93 roads, there is 1 road which is the highest black link of each road status. The accident-prone area (black site) is Jalan Lintas Tengah Sumatra and accident-prone points (black spot) at KM 18-26 are influenced by land use, road geometric, and traffic signs.

The detection and diagnosis model for small scale MSLB accident

The main steam line break accident is an essential initiating event of the pressurized water reactor. In present work, the fuzzy set theory and the signal-based fault detection method has been used to detect the occurrence and diagnosis of the location and break area for the small scale MSLB. The models are validated by the AP1000 accident simulator based on MAAP5. From the test results it can be seen that the proposed approach has a rapid and proper response on accident detection and location diagnosis. The method proposed to evaluate the break area shows good performances for small scale MSLB with the relative deviation within ±3%.

Accident Detection and Alert System using Accelerometer

In today’s world as the population increases day by day the numbers of vehicle also increases on the roads and highways. This results in more accident because of rider’s poor behaviors such as speed driving, drunk driving, riding without helmet protection, riding without sufficient sleep etc. In most of the accident cases, the victims loses their lives because of unavailability of medical facilities instantly. The critical time between the accident and getting victim medical help can be the difference between life and death. It is very difficult to know that an accident has occurred and to locate position where it has happened. To solve this problem “Accident Detection and Alert System” is used to save lives by making the medical facilities arriving on time. To resolve this problem we are developing a wireless system using Accelerometer, GPS and GSM for accident detection and reporting. If any accident occurs, this wireless device will send automated message and call the police, family members giving the exact position where the crash had occurred. So they can provide proper help to victim. This system is used to report information related to accident location and personal profile. Personal profile contains name, blood group, address, phone number of family members. So it will be easy to provide help and identify the victim.