Causes Of Road Traffic Accidents Research Articles

Effects of mobile phone texting on postural control and gait parameters in college students

Background: Mobile phone has become a part of everyday life. Mobile phone texting is one of the major causes of road traffic accidents, falls and injuries in young adults. Dual-task activities while using mobile phone increases the risk of falls. Objectives: To find out the changes in postural control and gait parameters while using mobile phone in young college students. Materials and Methods: A total of 100 college students of age 18–25 years participated in the study. NeuroCom Balance Master was used and the subjects were tested with and without phone. The participants had to maintain balance on firm surface and foam surfaces with and without phone. For walking, participants had to walk without phone followed by walking with phone. Outcome measures used were Modified Clinical test for Sensory Interaction on balance and Walk Across for balance and gait respectively. Results: The study showed statistically significant changes in postural control on firm and foam surfaces. Furthermore, the gait parameters such as step length, speed and step length symmetry were altered significantly, except step width while using the mobile phone. Conclusion: Subjects showed increased postural sway, step length and step length symmetry while the step width and speed decreased on using the mobile phone.

Analysis of Factors Affecting Road Traffic Accidents in North Cyprus

Road traffic accidents are a global issue. North Cyprus exhibits a similar trend to the rest of the world. Urbanization and the increasing number of vehicles come along with the increase of road traffic accidents. The objectives of the current study are to draw attention to the issue of road traffic accidents and to identify which factors are the main causes of road traffic accidents in North Cyprus. This article follows a two-stage study to examine the causes of this critical issue. In the first stage, a survey was conducted to determine local public opinions. The participants were asked about how environmental factors, vehicle factors, human factors, and road factors impact accidents. According to the survey outcomes, human factors and road factors have the most significant impact. In the second stage of the study, official data from official statistics were considered. The number of accidents, fatalities, and injured people are indicated initially followed by the causes of accidents. Negligent driving and speeding were identified to be the most frequent causes within the studied period. At the end of the study, the common causes of accidents in official statistics and in survey results were specified. Negligent driving and over-speeding were the major causes of road traffic accidents according to the results.

Trends and Contributing Factors to Road Traffic Accidents in Douala

Introduction: An estimated 1.2 million people are killed in road traffic accidents each year, and as many as 50 million are injured, occupying 30 percent to 70 percent of orthopedic beds in developing countries hospitals. But there is limited information on the burden of RTA in Douala. Aim: The study aims at reporting the epidemiology and pattern of road traffic related injuries in Douala in the Littoral Region of Cameroon using available police and health data. Methods: This was a chart review of hospital based and police department records. The records were reviewed over a period of two years in a District hospital in Douala in the Littoral region of Cameroon and over four years in the Police Department in Douala. The data review was done for two months. The records of all patients received in the emergency department of Bonassama District hospital after a road traffic related injury were reviewed for epidemiological variables, type of vehicle involved, severity of injuries, and outcome of the management. For the police records, they were reviewed for epidemiological variables, type of vehicle involved, and the causes of accident. Results: A total of 2,062 persons were involved in 818 cases of road traffic accidents reported by the police department. The major causes of road traffic accident (RTA) included poor mastery of driving, over speeding and left driving. From the Police records, RTA involving a vehicle and motorcycle increased dramatically in the four-year period from 0.39 % (8) in 2015 to 5.82% (120) in 2018. A total of 1,883 persons with injuries from RTA were received and managed by the Bonassama District Hospital. Majority, 1,590(84.4%) [95% CI: 82.7%-86.1%] of the injuries that were managed in the health units were sustained from RTA involving the motorcycle. Most, 893(47.4%) [95% CI: 45.2%-49.7%] of the accidents occurred during the night hours. Conclusion: The available data in both health and police sectors revealed that there was an increase in the number of RTA in the years under study.

Modeling drivers’ scrambling behavior in China: An application of theory of planned behavior

Scrambling behavior is one of the main causes of road traffic accidents in China. This study aimed to investigate the characteristics of drivers’ scrambling behavior and its influencing factors based on the theory of planned behavior. A total of 388 drivers answered the questionnaire and 359 provided valid data. The structure equation model of scrambling behavior showed that positive attitudes towards scrambling behavior, subjective norms and perceived behavior control increased the intention of scrambling behavior. Furthermore, the path coefficient of the structural equation model for the scrambling behavior revealed that attitude was the most important factor influencing scrambling behavior. Thus, to prevent drivers from scrambling, traffic regulators should focus on improving drivers’ attitude towards this behavior, while auxiliary measures should be enacted to regulate drivers' subjective norms and perceptual behavior control. Implications on intervention strategy and policy to reduce scrambling behavior are discussed.

Driver Distraction Recognition Using Wearable IMU Sensor Data

Distracted driving has become a major cause of road traffic accidents. There are generally four different types of distractions: manual, visual, auditory, and cognitive. Manual distractions are the most common. Previous studies have used physiological indicators, vehicle behavior parameters, or machine-visual features to support research. However, these technologies are not suitable for an in-vehicle environment. To address this need, this study examined a non-intrusive method for detecting in-transit manual distractions. Wrist kinematics data from 20 drivers were collected using wearable inertial measurement units (IMU) to detect four common gestures made while driving: dialing a hand-held cellular phone, adjusting the audio or climate controls, reaching for an object in the back seat, and maneuvering the steering wheel to stay in the lane. The study proposed a progressive classification model for gesture recognition, including two major time-based sequencing components and a Hidden Markov Model (HMM). Results show that the accuracy for detecting disturbances was 95.52%. The accuracy associated with recognizing manual distractions reached 96.63%, using the proposed model. The overall model has the advantages of being sensitive to perceptions of motion, effectively solving the problem of a fall-off in recognition performance due to excessive disturbances in motion samples.

Basic Methodology of Traffic Management for the Street and Road Network of a Large City with Traffic Lights Regulation

The objective of the article is to develop a system of principles and methods aimed at improving management of transport flows on the street and road network of a large city with traffic lights regulation. The suggested methodology is based on the methods used in Russia and abroad to improve road traffic safety and quality, results of a survey of experts in the field of road design and traffic management, monitoring at regulated crossings, and analysis of road accidents in the city of Volgograd. The primary customer property of a regulated crossing is road safety. Elimination of causes of road traffic accidents associated with road traffic, structural geometric, signalling, and technical conditions is the most important task regarding a regulated crossing. Enhancing road traffic quality at low levels of network load supposed considering demand for transportation, increase in travel comfort, coordination, and flexibility of traffic lights operation. High degree of network load supposes that more attention is paid to traffic capacity of the street and road network elements, restrained access of vehicles to areas of greater congestion, increased duration of a green light cycle (for more than 120 seconds, if this does not affect traffic safety and network congestion degree).

Investigation and Analysis of Road Traffic Accidents in Hefei City

Hefei is the largest city in Anhui Province, and its traffic volume is increasing day by day, and traffic accidents will follow. Therefore, aiming at the traffic road safety problems in Hefei, this paper investigates and analyzes the causes of road traffic accidents in Hefei by visiting questionnaires and collecting data, and concludes that drivers’ driving behavior is an important factor leading to traffic accidents, such as driving and calling, changing lanes and overtaking in a hurry, etc. With the increase of traffic demand, it is necessary for relevant departments to make corresponding measures to reduce the traffic accident rate through investigation and analysis, so as to improve the safety ability of road traffic and further ensure the safety of citizens’ lives and property.

Association between Incidence of Road Traffic Accidents and Provincial EconomicStatus in Thailand: An Application of the Concentration Index

In Thailand, various preventive measures have been implemented to control and minimize the volume of road traffic accidents (RTAs). However, the country still faces varying degrees of success in curbing the incidence of RTAs, which has devastating consequences to the Thai economy. Since there are many factors related to the density of RTAs, this study examines the density according to three main causes-humans, the environment, and vehicles-relative to the provincial economic status in Thailand. A time-series cross-sectional design was employed. Descriptive statistics, Spearman’s rank correlation, and the concentration index (CI) were used to measure the degree of inequitable distribution of RTAs relative to the provincial economic levels. The cumulative proportion of accidents was measured against the cumulative proportion of provinces ranked by the gross provincial product per capita. A negative value from CI-RTAs indicated a disproportional accumulation of RTAs among the poor. In contrast, apositive value reflected a disproportional concentration of RTAs among the well-off populations. Since 2006, human causes of RTAs (such as driving while under the influence of alcohol and violation of traffic rules) were the main contribution to RTAs. The RTAs were concentrated among the well-off provinces during 2006-2013, as reflected by positive indices and positive CI-RTAs were stronger for human-caused RTAs. Since 2014, the total in cidence of RTAs was higher among the less well-off provinces (negative CI-RTAs). The shifting trend of CI-RTAs from among the affluent to the less affluent provinces provided insightful information for policymakers and implementation in the Thai public health arena. However, the statistical significance of the associations between RTAs and economic status was observed only in the early years of the investigation. The reasons behind the varying degree of statistical significance in the association should be investigated further. Additional studies on CIs and RTAs, which could help inform policymakers and academics regarding the prioritization and optimization of RTA preventive measures of each individual area, are recommended.

Awareness and Practice of Traffic Rules in Preventing Accidents among Orthopedic Patients

Background of the study : Road Traffic Accidents (RTA) has come out as a prime health concern in India and Abroad which needs multifaceted approach to reduce it. As we all know that nearly 1.35 million people die every year globally due to RTA and every 24 second someone dies on the road. Road traffic injuries are the main cause of death among children and young adults between 5 to 29yrs. One of the most important preventive measures to reduce RTA is following Traffic rules. It’s designed to protect all those who pass on road and if it’s followed nearly 99% of accidents can be prevented. The Aim of this study was to assess the awareness and practice of traffic rules in preventing RTA. Setting and design: A Descriptive survey approach with non-experimental research design was adopted to conduct the study on patients admitted at orthopedic wards at R.L.J Hospital & R.C Methods and Material: 100 samples who fulfilled inclusion criteria were selected using purposive sampling technique admitted at orthopedic wards of R.L.J. Hospital & R.C Kolar. The data was collected by using structured questionnaire on awareness and practice checklist. Statistical analysis: Data was analyzed using Descriptive and Inferential Statistics like mean, percentage, standard deviation, co-relation and chi-square. Results: The study showed that, out of 100 samples, 46(46%) had moderate awareness regarding RTA and majority54 (54%) had average level of practice and there was positive co-relation between awareness and level of practice. Conclusion: Even though people are having adequate awareness about road traffic rules, negligence in following road traffic rules was the major cause of RTA. Hence an awareness program regarding risk of accidents, impact of accidents on individual, family and society is essential in reducing RTA. Keywords: Road Traffic Accidents, Awareness, Traffic rules, Practice

RELIABILITY CRITERION AND A MODEL FOR DETERMINING THE OPTIMAL SPEED OF MOVEMENT ON AUTOMOBILE ROADS IN WINTER SLIDING CONDITIONS

The article presents a model for establishing the optimal speed of movement on highways, taking into account the determination of the braking distance in winter slippery conditions. According to the research results, it was established that the main criterion for the formation of road accidents on highways in winter slippery conditions is the drivers' underestimation of the adhesion qualities of road surfaces. The main criterion of the model under consideration is the interaction of the car wheel (braking distance) with the road (adhesion coefficient) and is a complex that characterizes the stability of the car rolling over on slippery surfaces and the driver's actions in making an effective decision and the duration of the reaction time. In the proposed mathematical model, the accident rate on a slippery road is estimated by the coefficient of adhesion of icy road surfaces, the value of the load or the average wheel pressure. Also, the frequency of load application, the amount of deflection of the coating (at an air temperature above +20 ° C), rolling resistance, the coefficient of adhesion of the car wheel to the coating. One of the main characteristics of the model is a subsystem - the average pressure p = Q / S (S is the area of the imprint of the wheel, cm²), etc. Thus, in the process of analyzing the results of the causes of road traffic accidents, the factors of the driver's reliability and the decisions made will be taken into account, which depend on the speed of vehicles in any condition of the road surface.

Road Traffic Accident Analysis and Identification of Black Spot Locations on Highway

Road safety is the main problem in developing countries. Every year, millions of people die in road traffic accidents, resulting in huge losses of humankind and the economy. This study focuses on the road traffic accident analysis and identification of black spots on the Lahore-Islamabad Highway M-2. Official data of road traffic accidents were collected from National Highway and Highway Police (NH & MP) Pakistan. The data was digitized on MS Excel and Origin Pro. The accident Point weightage (APW) method was employed to identify the black spots and rank of the top ten black spots. The analysis shows that the trend of road traffic accidents on M-2 was characterized by a high rate of fatal accidents of 35.3%. Human errors account for 66.8% as the major contributing factors in road traffic accidents, while vehicle errors (25.6%) and environmental factors (7.6%) were secondary and tertiary contributing factors. The main causes of road traffic accidents were the dozing on the wheel (27.9%), the careless driving (24.6%), tyre burst (11.7%), and the brakes failure (7.4%). Kallar Kahar (Salt Range) was identified as a black spot (223 km, 224 km, 225 km, 229 km, and 234 km) due to vehicle brake failure. The human error was a major contributory factor in road traffic accidents, therefore public awareness campaign on road safety is inevitable and use of the dozen alarm to overcome dozing on the wheel. Doi: 10.28991/cej-2020-03091629 Full Text: PDF

Hybrid Embedded-Systems-Based Approach to in-Driver Drunk Status Detection Using Image Processing and Sensor Networks

Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.

A pragmatic evaluation of trauma care: an evidence from the province of Punjab, Pakistan

Road Traffic Accident (RTA) injuries pose a public health challenge which significantly impacts the human capital development. The Punjab Economic Research Institute (PERI) conducted a study to assess the frequency, causes of trauma injuries, distribution and need and gap analysis of trauma centers in the province of Punjab. For gap/situational analysis, information was extracted through a structured questionnaire from randomly selected 8 District Head Quarters hospitals, 6 Teaching hospitals and 8 independent trauma centers. According to the data of Rescue 1122, 70% of RTA injuries involved the age group 11-40 years. In 295589(63.26%) of the RTA cases the vehicle involved was a motorbike. The major RTA injuries were leg fractures 71699 (16.44%) and head injuries 44738(10.26%). Over speeding 159977(44%) and careless driving 121545 (33.35%) were the major causes of RTAs. Noted was a shortage and mismatch between human resources and equipment in the trauma treatment facilities. Inequality was also found in distribution of trauma care units. Integrated and fully equipped trauma care system along with the establishment of trauma centers in places of high accidents' frequency is recommended. Strict implementation of road traffic safety laws is mandatory.

Auto-Mobile Accident Control and Nigeria Federal Road Safety Corps: A Critical Analysis of the Commercial Drivers’ Experience

Road traffic accidents lead to death and disability as well as financial cost to both society and the individual involved. The causes of road traffic accidents are not just human error or driver’s negligence. Unfortunately, Nigerian highways are arguably one of the worst and most dangerous in the world. This paper therefore provides a critical analysis of the commercial drivers’ assessment of auto-mobile accident control and Nigeria Federal Road Safety Corps. A sample of three hundred commercial drivers purposively selected from fifteen motor parks in Abeokuta, Ijebu-Ode and Sagamu, Ogun State took part in this study. A self-developed instrument was used for collection of data. Four research questions were raised and tested. Data collected was analyzed using descriptive statistics and Multiple Regression Analysis. Findings revealed that the roles of the FRSC on auto-mobile accident control and management was perceived good by the drivers. Also, the FRSC public enlightenment programme to an extent has enhanced positive attitude among road users, while the total variance accounted for by the FRSC public image on the behavior of commercial vehicle drivers is 15.1% (R2 = 0.151, F = 4.712, P > .05). This study concluded that road traffic crashes are predictable, could be prevented, and that whatever change we are clamoring for must start from every one of us – drivers, law enforcement agents, and government alike.

Causes of road accidents in Botswana: An econometric model

Background: Road traffic accidents claim over 1.3 million lives annually around the globe and remain a key socio-economic challenge today. At 20.1 per 100 000, Botswana’s fatality rate is higher than the global average of 17.4. Previous studies on the causes of road crashes in Botswana have not explored statistical causality. This study is thus grounded on the theory of causality. Objectives: This study sought to determine the causes of road traffic accidents and fatalities in Botswana. For this purpose, the article discusses the accident count model based on Botswana data. Method: The study used road accident data from 2008 to 2017. Econometric modelling on Gretl was used to compute two ordinary least squares (OLS) regression models. Manual elimination of insignificant variables was performed through the iterations. Results: Both models are statistically significant at p ≤ 0.001, but the accident count model, with an adjusted R 2 value of 0.99 against 0.83, is more robust and has a better predictive power as opposed to the fatalities model. At the individual variable level, the analysis shows mixed results. Conclusion: The study contends that increased exposure and night-time travel increase road crashes, whilst expansion of road infrastructure is inversely related to road accidents. An increase in both population density and exposure leads to increased fatalities. Regulating the importation of used vehicles and investment in rail transport is a potential policy panacea for developing economies. Future studies should investigate the causes of pedestrian fatalities and night accidents.

Prevalence of road traffic accident and associated risk factors among drivers of three and four-wheeler vehicles, western Ethiopia, 2017

Background: Nowadays, worldwide road traffic-related injuries, disabilities, and deaths are becoming a major public health threat. It is projected that by the year 2020, road traffic injuries are becoming the third-largest cause of disabilities in the world. More than 85% of the world’s road fatalities are attributed to developing countries. Objective: This study aims to assess the prevalence of road traffic accident and associated factors among drivers of three and four-wheeled vehicles in East Wollega, Western Ethiopia 2017. Methodology: A cross-sectional study design was employed to gather information from 400 drivers of three and four-wheeled vehicles from February to March 2017. Data were entered into Epi info version 3.5.3, cleaned and analyzed using SPSS version 20. Bivariate and multivariate analyses were used to examine the association between dependent and independent variables. Statistical significance was declared at P-value 0.05. Result: The data were collected from 400 drivers making response rate of 94.6%. The mean age of the study participants was 28.4±4.3. About one third (33%) of the drivers encountered an accident in the last one year. Living in urban (AOR=0.29, 95% CI [.09-.095]), Age of respondents 25-34 years (AOR=2.58, 95 %CI [1.46-4.54]) & >=35 years (AOR=2.53, 95%CI [1.20-5.33], sometimes angry(AOR=0.40, 95% CI [0.21- 0.77], don’t angry at all (AOR=0.26, 95% CI [0.11- 0.60], Mobile speaking habit while driving (AOR=1.67, 95% CI [1.21- 2.74]), driving on straight road (AOR=0.5, 95% CI [0.31-0.78]) and being penalized (AOR= 1.89, 95% CI [1.18-3.06],) were among factors associated with road traffic accident. Conclusion: The prevalence of road traffic accident revealed in this study is a public health significance. The most perceived cause of road traffic accidents mentioned was an overcrowded road which is shared by drivers, pedestrians, and animals. Therefore, it is better if the zonal and town transport agency office work on the management of road traffic utilization and continuously follow the driver’s behaviors.

A Support Vector Machine Approach in Predicting Road Traffic Mortality in Malaysia


 
 
 The traffic mortality rate is the baseline through which road safety plans of a country could be evaluated. A reliable and reasonable analysis of road traffic-related injuries and their leading causes is vital to the road safety investigation, evaluation as well as policymaking. Malaysia has the third highest fatality rate from road traffic accidents in Asia as well as in Southeast Asia. Although many researchers have attempted to provide predictive models of Road Traffic Mortality (RTM) in the country, the predictions are found to be rather unsatisfactory in forecasting the causes as well as the future road fatality. It is hypothesized that the inability of the previous models to provide a good prediction of the RTM might be attributed to the complicated and non-linear data relationship of the underlying causes of road traffic accidents. A Support Vector Machine (SVM) is demonstrated to be effective in solving both classifications as well as regression problems owing to its efficacy to cater for the non-linear relationship of a dataset. The present investigation proposed the application of SVM based model variations namely the Linear, Quadratic, Cubic, Fine, Medium, as well as Coarse Gaussian-based SVM in predicting the RTM. A dataset from 1972 to 1994 was obtained from the Malaysian road traffic database. The data were trained on the SVM model variations. It was demonstrated that the Linear-based SVM model can provide a reasonable prediction of the RTM with only a 12 % error. It is, therefore, inferred that a reasonable prediction of RTM in Malaysia could be achieved through the employment of non-conventional statistical techniques.
 
 

Traffic Safety Factors in the Qassim Region of Saudi Arabia

This study investigates the factors that affect traffic safety in the Qassim region. A questionnaire was developed on the basis of the Handbook of road safety and consisted of 85 items measuring seven dimensions: area-wide traffic calming (22 items), vehicle design and protective devices (26 items), road design (24 items), road maintenance (three items), traffic education (four items), police campaigns and sanctions (three items), and post-accident care (three items). A sample encompassing 1,500 Qassim University students, and visitors was randomly selected to collect data. A total of 1,500 questionnaires were distributed to students, and visitors of which 1,053 were retrieved. The elimination of data outliers resulted in a sample of 909 subjects. The results pointed out a moderate level of traffic safety in the Qassim region. Furthermore, 10 leading causes of road traffic accidents emerged, namely, excess speed, irregular bypasses, irregular rotations, lack of prioritization of other drivers, irregular stops, lack of road readiness, driver carelessness, use of a mobile phone while driving, noncompliance with traffic signals, and, finally, nonuse of seat belts. On the basis of these results, conclusions and policy implications were provided.

EFFECT OF AUTOMATED SPEED ENFORCEMENT SYSTEMS ON DRIVING BEHAVIOR AND ATTITUDES ON MOUNTAINOUS ROADS IN THAILAND

Speeding is one of the leading causes of road traffic accidents in mountainous areas in Thailand. Recently, the government has been gaining attention to employ automated speed enforcement systems for monitoring speeding behavior on major highways. This study aims to evaluate the effectiveness of an automated speed enforcement system implemented along mountainous road sections in Thailand. Specifically, the study examines whether such system changes driving behavior and attitudes. The study has two thrusts. First, the study conducted the observational before-and-after speed study and performed the statistical analyses to evaluate driving behavior. Second, the study conducted the questionnaire surveys and applied the sequential equation modelling analyses together with the Theory of Planned Behavior concept to evaluate driving attitudes toward speeding and speed enforcement system. The study used the Highway No.118, one of the most hazardous mountainous corridors in Thailand as a case study. The results showed the changes in both driving behavior and attitudes. After implementing automated speed enforcement system. there were significant reductions in speed and the number of violators. Moreover, psychologically, drivers believe that they would increase the opportunity to perform overspeed if there is no speed control. Therefore, this study provides decision-makers better understand the characteristics of driving attitudes and behavior in Thailand and ensures the effectiveness of automated speed enforcement system.

Survey on the Causes of Road Traffic Accidents in Sulaymaniyah, Kurdistan Region, Iraq

Background: Due to the stability and economic development in the Kurdistan region of Iraq, increase in the number of traffic crashes has been one of the serious challenges that local authorities have faced with. The present study was conducted to investigate the prevalence of road traffic accidents (RTAs), road traffic injuries (RTIs), and their causes in Sulaimaniyah City, Kurdistan Region, Iraq. Materials and Methods: The present descriptive study was conducted based on the data collected from the Health Directorate/ MOH and the Traffic Department/ Ministry of Interior in Sulaimaniyah. A questionnaire was also used to collect required data from RTA casualties who were admitted to Sulaimaniyah Main Emergency Hospital during a 6-month period from January first till the end of June 2014. The collected data were analyzed using SPSS software version 21.0. Results: Based on the results obtained from Sulaimaniyah Main Emergency Hospital, there were 251 RTA victims in 2014 within the age range of 1 to 81 years. Moreover, RTAs led to the death of 270 and 280 individuals in 2012 and 2013, respectively. The main causes of RTAs were respectively over speeding (33%), the sudden appearance of a vehicle (13.9%), and vehicle slip (10.4%), speeding (48.7%), followed by drowsiness of the drivers (36.9%), and drunken driving (5.6%). Conclusion: In order to reduce RTAs, the overall quality of roads, quality of cars, and general driving skills should be improved. Moreover, for decreasing the rate of crashes inside the city, public transport modes such as tram or train should be prepared.