Traffic Accident Rate Research Articles

Retraction:Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach.

Retraction:Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach.

The Correlation of Subjective Fatigue, Negligence, Knowledge of Safety Riding and Length of Work on Traffic Accidents of Online Motorcycle Taxis in Sidoarjo

Introduction: The number of vehicles in Indonesia has increased every year. The number of two-wheeled vehicles in 2016 was 105.150.082 units and increased to 111.988.863 in 2017 and 120.101.047 in 2018. Unfortunately, along with the increase in motorized vehicle users, the rate of traffic accidents that occurred also increased. One of the causes of the high number of traffic accidents in Indonesia is a large number of jobs in the transportation sector, such as online motorcycle taxis. This study aims to identify the factors that cause traffic accidents, including those caused by fatigue, negligence, knowledge of safety riding, and length of work for online motorcycle taxi drivers. Methods: This study is an analytic observational study with a cross-sectional design. The study population consisted of 110 online motorcycle taxi riders who are members of the Sidoarjo-Porong Online Driver Association Basecamp. Sampling was done by using the total sampling technique. The variables studied included subjective fatigue, negligence, knowledge of safety riding, length of work, and two-wheeled online motorcycle taxi traffic accidents. Data analysis was performed using Cramer’s V Correlation Coefficient or Phi Correlation Coefficient. Results: The results showed a significant correlation between subjective fatigue and the incidence of accidents as indicated by a value of r = 0.289. Furthermore, it was found that a weak correlation between negligence and the incidence of accidents with a value of r = 0.211. No correlation was found between knowledge of safe riding and the incidence of accidents marked with a value of r = -0.169. Meanwhile, there is only a weak correlation between the length of work and the incidence of accidents with a value of r = 0.214. Conclusion: Subjective fatigue, neglect, length of work has a correlation with two-wheeled online motorcycle taxi traffic accidents. There is no correlation between knowledge of safety riding with two-wheeled online motorcycle taxi traffic accidents.

Exploring Countermeasures from a Psychological Perspective to Create a Safe Driving Environment for Personal Mobility Devices

The personal mobility device (E-Powered Personal Mobility Vehicle) has recently been attracting attention as a viable method of transportation for first and last mile travel, primarily due to its portability and ease of mobility. Although the size of its market is increasing rapidly, the number of accidents is also increasing rapidly. Suwon city, in particular, has the highest rate of traffic accidents linked with personal mobility among all of the local governments in the Gyeonggi Province in Korea, as of 2019. The annual average rate of increase has been as high as 151.7% over the past three years. The objective of this study was to analyze the usage of personal mobility devices among Suwon citizens through a questionnaire, which was then analyzed using partial least square structural equation modeling (PLS-SEM). We then examined the impact of psychological attitudes on the future use of personal mobility, and then derived future policy directions from all of the gathered data. According to a survey of Suwon citizens, the ratio of users who had no experience in using the devices was higher than that of those who had some experience in using them. The results of the survey on citizens’ satisfaction with the driving environment revealed that their overall satisfaction level was low, while the response rate regarding the need for safety equipment and systems was high, confirming that the current system had poor safety levels, which results in a very high risk of accidents. However, given that there were many positive responses regarding the users’ intentions to use personal mobility devices in the future, it seems that it is necessary to establish a safer driving environment in order to better incorporate these personal mobility devices into the city.

Cooperation and radio silence strategy in Mix Zone to Protect Location Privacy of Vehicle in VANET

With increase in the population, the number of registered vehicles has dramatically increased over all the world, and this leads to a high rate of traffic accidents on the roads. Therefore, in order to prevent such accidents, an Intelligent Transportation Systems (ITSs) is needed to be installed to notify drivers of obstacles in advance. Recently, the Internet of things (IoT) evolves the vehicular communications and covers this technology under the Internet of vehicles (IoV) application. IoV is a new field for the automotive industry and a significant part of the smart cities. However, protecting the privacy of vehicle's location is the most challenging subject in the vehicular communication, as because it threatens the personal life of drivers. This paper provides cooperation and radio silence strategy in mix zone (CRSMZ) to protect location privacy of vehicle in IoV. The strategy implements either cooperation or radio silence depending on the speed of the vehicle while it is in mix _zone. The simulation results show that CRSMZ is an efficient strategy to protect location information of vehicle drivers. CRSMZ outperforms the existing strategies in terms of mean of the number tracker confusion, continuous tracking period and max of the entropy.

Effect of Transportation Parameters on Traffic Accident in Urban Areas Comparison study of ANFIS With Statistical Analysis

Traffic accidents present a serious problem for both developed and developing countries and have become an urgent matter to tackle in all large metropolitan areas. This study aims to perform a deep comprehensive analysis of the traffic accidents issue in Istanbul, one of the world’s most populous cities. The accidents were classified and its intensities were presented on Istanbul map using a GIS tool. Furthermore, the performance of Negative Binomial Regression analysis and Adaptive Neuro-Fuzzy Inference System (ANFIS) model was assessed. Data collection of independent variables included distribution of trips, percentage of street parking, rate of car ownership, street density and population density. Trips were divided into three categories, passenger car, minibus and bus trips. The results showed that four legs intersection got the highest proportion of accidents among the other types with (40%). It also demonstrated that increasing both the percentage of bus trips and the percentage of street parking will decrease the traffic accident rate. Furthermore, the implementation of ANFIS model increased the accuracy of forecasts and reduced errors more than the regression model.

Diagnosing the statistical rates of traffic accidents in Dohuk Governorate during the period (2011-2020) / analytical study

The aim of this study is to determine the statistical proportions of traffic accidents in Dohuk province during the period (2011-2020). The importance of this study comes through clarifying the extent of the increase or decrease in those ratios so that the Directorate and the relevant authorities are aware of these results to benefit from them as statistical indicators that may contribute to strengthening their future plans, and the problem of the study lies in the existence of mortality caused by traffic accidents in Dohuk province, and the lack of details as statistical percentages. Based on data recorded in the Traffic Directorate in Duhok province mainly to find statistical ratios using simple statistical methods and based on (Excel, 2016) program. The study adopted hypotheses showing that there was an increase in the number of accidents, injuries, and deaths duration of the study. The study came to a series of conclusions, the most important of which is that Speed in driving was one of the most important reasons that led to the increase in these accidents. Finally, the study suggested Directorate in Duhok province look for appropriate mechanisms that limit the speed of cars and place them within the permitted speed range allowed everywhere.

Research on Road Landscape Scale Design Based on the Neural Network Algorithm

There had high traffic accidents rate in China. The accident rate was on an upward trend every year. The cause of the accidents frequently occur, including the driver’s driving level, the safety performance of the car and the design of the road landscape scale. Therefore, in order to reduce the accident rate, this paper presented the research of road landscape scale design based on neural network algorithm to reduce the accident rate. The scale of the landscape was designed by neural network algorithm, and then transforming variables, size and other design elements were processed. The paper had selected the road as a pilot at random, with the most humane scale design as the standard for regional design investment. Through comparing the monitoring of pilot locations, we found that the rate of traffic accidents had been effectively reduced.

Retrospective Evaluation of Determinants of Road Traffic Injuries at a Naval Station

Introduction: Several factors like globalization, industrialization, migration, access to modern ways of living, increasing income levels, easy availability of vehicles, point of use entertainment/communication gadgets, media influence and others have brought human beings in close contact with a variety of challenges to safe driving, resulting in an increased occurrence of Road Traffic injuries across the globe. Methods and Material: A cross-sectional descriptive study was conducted at naval station amongst victims of road traffic accidents who reported to emergency department of naval hospital over period of six months. Interviews on structured questionnaire to explore various determinants of road traffic injuries (RTI). Data Analysis on 156 victims was carried out for proportion of study variables of interest, Chi square test to determine significant differences between demographic variables and RTA exposure. Results: Of 156 RTA victims, more than 50% were between 21 - 40 years; 69.9% were male; 93% accidents were contributed by driving speed more than 40km/hr; 47% occurred at road junctions followed by civil roads; 27% were due to collision. 23% accidents took place on Saturdays; 36% were in morning 06 - 12 hours. 1/3 accidents were caused by two wheeler vehicles. Negligence of driver (40.4%) poor road condition (24.4%) were major causes of the accident as reported by victims. 44.2% of the victims had minor injury; 58.7% drivers who met accidents were holding valid driving license; 38% were wearing protective gears and 56% narrated that road lights/ traffic signals were available at vantage points. Exposure to accidents was found to be having statistically significant difference when related to age, gender, type of accident, common causes of accident and use of protective gears. Conclusions: The stricter application of traffic laws and safety measures are required to bring down the road traffic accident rate and related mortality.

DETEKSI JUMLAH KENDARAAN DENGAN ALGORITMA GAUSSIAN MIXTURE MODEL DI AREA JALAN RAYA

Road safety monitoring systems are developing at this time. The transportation sector is the object of research that continues to be developed and is always an interesting topic. Not only for security purposes and for statistical purposes for the road widening process that supports road user infrastructure, but the detection system is also useful for sales marketing statistics. In this research, propose a vehicle detection system that is useful for widening roads in a certain area or area so that it can reduce traffic congestion and accident rates. The proposed Gaussian Mixture Model method has several weaknesses, such as errors in background substitution with vehicles and failing to distribute the background with vehicle shadows. However, using morphological operations can overcome these problems. The results show a fairly good level of accuracy from the proposed method. It is only less effective when using video objects with poor lighting or at night because in the blob analysis process the detected vehicle objects do not match the actual object. But if the traffic flow is smooth and unidirectional, the proposed method is still acceptable.

Application of multi-attribute group decision-making methods in urban road traffic safety evaluation with interval-valued intuitionistic fuzzy information

With the development of the social economy, the level of motorization has been greatly improved, and the traffic safety problem has been paid more and more attention. In recent years, China’s road traffic accident rate showed a trend of decline after rising first, suggests that the Chinese road traffic safety level is on the decline. Road traffic safety evaluation has a positive effect in found risk factors of road traffic safety in time and reduce the traffic accident rate, so the study of traffic safety evaluation method is imperative. And the urban road traffic safety evaluation is frequently viewed as the multi-attribute group decision-making (MAGDM) problem. Depending on the conventional VIKOR method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel IVIF-VIKOR method to assess the urban road traffic safety. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is [Z1] decided objectively by utilizing CRITIC method. Eventually, an application and some comparative analysis are given. The results show that the designed algorithms are useful for assessing the urban road traffic safety.

Automatic braking system using fuzzy logic method

This research is design an autonomous car control system that can reduce the rate of traffic accident. Car prototype is designed by using Fuzzy Logic Control. Fuzzy logic is as main component of artificial intelligence has significantly influence the design controlled system. Fuzzy logic system is integrated with the arduino Mega 2560 microcontroller as the central control car prototype. In this paper, the Fuzzy logic used Mamdani method and 28 rule base. The fuzzy system was made based on fuzzy mechanism which are fuzzification, inference and defuzzification. Fuzzy logic has a variable input and output variables. Input variables used in this research is the distance between car and obstacle; the speed of car prototype and the output variable is the brake angle. The test is done with 5 variations of distance that is 100 cm, 125 cm, 150 cm, 175 cm, and 200 cm and two variations of speed that are 54 cm/s, and 63 cm/s. The test results showed that the prototype of the car was able to stop with a range of 22 cm - 35 cm from obstacle. The highest deceleration value at the speed of 63 cm/s is - 49.22 cm/s2 and the accuracy of braking on a system that has been designed is between 99.91% -100%.

Improving cabin thermal environment of parked vehicles under direct sunlight using a daytime radiative cooling cover

Car overheating after parking under the direct sunshine leads to not only more energy consumption of air conditions but also potential security issues, such as higher traffic accident rates and heatstroke of passengers. In this study, we propose a new type of car cover with the daytime radiative cooling effect (named as Cover R) to reduce interior temperature when parking outside. With utilizing a layer of innovative meta-material coating, this cover is capable of reflecting most sunlight and effectively emitting infrared radiation in the atmospheric window band (8–13 μm). Experimental results have shown that under strong solar irradiation (>900 W/m2), the usage of Cover R decreases cabin air temperature by 31.1 °C and 19.6 °C compared that for a car without a cover and with a traditional cover, respectively, which efficiently avoids thermal shock to the passengers. A simulation model that reproduces experimental data well suggests that Cover R is able to improve personal comfort in hot days. Considering the initial energy cost of air conditions for high interior temperatures, the application of Cover R also saves gasoline and reduces carbon dioxide emission.

Statistical Evaluation of BIS-11 and DAQ Tools in the Field of Traffic Psychology

This paper focuses on the statistical evaluation of two independent research tools in the field of traffic psychology. Our research focuses on young drivers in the Slovak Republic and conducts an international comparison. At present, these young drivers make up only about 7% of the total number of drivers, but they cause about 20% of accidents. The paper analyzes the traffic accident rate of young as well as inexperienced drivers. All drivers in the survey had a short period of driving experience. The traffic-psychological survey obtained detailed data via two independent tools. We aimed to find relations between the factors and subfactors of the tools used, namely the BIS-11 (Barratt Impulsiveness Scale) and DAQ (Driver Attitude Questionnaire). The researchers also used these tools in other countries, so it was possible to compare the results obtained. The results from these tools should reveal the psychological causes of as many traffic accidents as possible. Our paper shows the possibilities for the evaluation of the tools used with correlation analysis. The results of our research are shown in symmetrical matrixes of correlation coefficients. Our study also compares its values with the results of foreign authors. Such research has revealed some facts about young drivers’ violations connected with drunk driving, speeding, and other traffic offenses. Our aim was to find connections between the driver’s history (skills, traffic accidents, age, etc.) and psychological characteristics, and we have answered several research questions. In conclusion, we have highlighted the most significant relationships between the factors of driver psychology.

Comparison of Physical, Occupational, and Sociocognitive Characteristics of Corporate and Private Taxi Drivers in Korea.

Taxis are a form of public transport which is very closely related to the safety of the public. Although private and corporate taxis have quite different characteristics, there have only been a few studies comparing the characteristics of corporate and private taxis. Moreover, among various characteristics, research was conducted mainly focusing on occupational characteristics. This study was undertaken to compare various physical, occupational, and sociocognitive characteristics of corporate and private taxi drivers. A descriptive cross-sectional study was conducted from 22 August to 11 September 2018. The subjects of this study were 960 corporate and private taxi drivers over 30 years old in Seoul to compare the means and association between private and corporate taxi drivers’ characteristics. In terms of the physical characteristics, corporate taxi drivers’ general physical health status was worse. In terms of the occupational characteristics, corporate taxi drivers had a high working intensity, and the incidence rate of traffic accidents and near misses was also high. This comparison of the characteristics of corporate and private taxis is expected to serve as evidence for developing tailored policies and programs to improve the health of corporate and private taxi drivers.

Justification of the system parameters for alerting drivers about the emergency situation occurrence

The article analyzes the road traffic accident rate in Russia and the Krasnoyarsk territory. As a way to reduce traffic accident rate on road sections outside built-up areas, a system for alerting drivers in conditions of a lack of visual information about a possible emergency situation is proposed. The results of mathematical modeling and physical experiments are presented, which allow us to justify the values of the system parameters and algorithms for its functioning.

Good Roads:- Using machine learning to measure how socio and non-socio-economic factors differently influence traffic accident injury rates

This project is based on analyses of socio-economic factors in conjunction with traditional traffic accident, collision and injury data to analyze if they play a meaningful role in predicting motor vehicle-related injury rates and thus be used to help improve traffic safety. Road and census variables are analyzed for socio economic factors. Factual reasons for accidents and vehicle types are analyzed for non-socio-economic factors. Project is divided in two parts consisting of socio and non-socio factors which includes data exploration, prediction modeling and feature extraction. Total casualties per person is taken as target variable and remaining factors as explanatory variables. For socio economic part, two prediction models are created in which prediction curves are compared to perfect ranking curve. Selected model is then tested on LA and DC datasets followed by feature extraction using XGBoost and random forest. Population density and road length are top reasons for total casualties. Relationship between important features and total casualties is analyzed using OLS regression. For non-socio-economic part, two models are considered, from which random forest has a better normally distributed residual vs fitted curve and hence was selected as the final model. Driver inattention and following too closely are the top causes of vehicular accidents.

What's new in critical illness and injury science? Driving characteristics and rates of road traffic accidents and associated serious injuries and fatalities during the COVID-19 pandemic

What's new in critical illness and injury science? Driving characteristics and rates of road traffic accidents and associated serious injuries and fatalities during the COVID-19 pandemic

Integrating urban traffic models with coastal flood maps to quantify the resilience of traffic systems to episodic coastal flooding

Sea level rise and coastal floods are disrupting coastal communities across the world. The impacts of coastal floods are magnified by the disruption of critical urban systems such as transportation. The flood-related closure of low-lying coastal roads and highways can increase travel time delays and accident risk. However, quantifying the flood-related disruption of the urban traffic system presents challenges. Traffic systems are complex and highly dynamic, where congestion resulting from road closures may propagate rapidly from one area to another. Prior studies identify flood-related road closures by spatially overlaying coastal flood maps onto road network models, but simplifications within the representation of the road network with respect to the coastline or creeks may lead to an incorrect identification of flooded roads. We identify three corrections to reduce potential biases in the identification of flooded roads:1. We correct for the geometry of highways;2. We correct for the elevation of bridges and highway overpasses; and3. We identify and account for road-creek crossings.Accounting for these three corrections, we develop a methodology for accurately identifying flooded roads, improving our ability to quantify flood impacts on urban traffic systems and accident rates.

Impact of Traffic Accidents in the Saudi Arabia

Traffic accidents are one of the world's leading deaths, with an estimated seventh death cause by 2030. Road traffic accidents have become common in all over the world. Traffic accidents result in a great loss to individual and communities. While unknown and unacknowledged pandemics such as RTC mortality are frequently overlooked globally, without help, the developing countries will face increasing challenges in the coming decades. Globally, around 1.2million are passed away with the traffic accidents on the road and 20 million are affected with the injuries. The most critical aspect of road safety is the safety of all road users. There are numerous ways to discipline a road user and improve their safety. Saudi Arabia is one of the countries with many traffic incidents worldwide. There are many studies have been documented in the Saudi Arabia with the traffic accidents. The aim of this review was to document the prevalence of traffic accidents in Saudi Arabia. The maximum number of accidents in the kingdom has been reported. However, more studies were therefore documented through the region wide. Compared to foreign figures of 8:1, Saudi Arabia has an accident/ injury ratio of 8:6. Accident to death rates in 1993 were 283:1 in the USA and in 1995 they were 32:1 in Saudi Arabia. This review concludes the incidence rates of traffic accidents is high in the Saudi Arabia.

Research on Safety Evaluation of Commercial Vehicle Driving Behavior Based on Data Mining Technology

The arrival of big data era of internet of vehicles promotes the rapid development of logistics industry, which also indirectly leads to the high traffic accident rate, resulting in huge casualties and property losses. Driving behavior is considered the most central factor leading to traffic accidents. Therefore, a scientific and effective method for evaluating the safety of commercial vehicle driving behavior is urgently needed. In this study, a comprehensive evaluation model of driving behavior security based on multimembership function is proposed, and entropy weight method (EWM), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation algorithm are integrated. Firstly, the evaluation system of commercial vehicle safety of driving behavior is established. Secondly, the weight vector of each evaluation index is determined by combining EW‐AHP to eliminate the subjectivity of the traditional AHP algorithm. Then, the fuzzy comprehensive evaluation matrix is calculated based on the multimembership function and fuzzy mathematics theory, and the quantitative evaluation of driving behavior safety is realized based on the matrix. Finally, the real road vehicle driving data and driving behavior data are verified by experiments. The experimental results show that the model can accurately and reasonably evaluate the safety of driving behavior, which is of great significance to improve road traffic safety.