جستجوی مقالات مرتبط با کلیدواژه « traffic safety » در نشریات گروه « عمران »

Along with growth of motorcycle use, the accidents and casualties caused by it have also increased, so that motorcycle riders are among the most vulnerable traffic users. On the other hand, the need to deal with the traffic violations of this group of traffic users has led to sedimentation of parking lots, the need to implement the Motoyar project as an alternative punishment to establish Traffic discipline is felt, so the main purpose of this research is to study the effect of Motoryar project implementation on the traffic safety of motorcycle riders. This research is applied in terms of objective, descriptive in nature and quantitative in terms of approach. The statistical population includes all the motorcycle riders of Tehran city and its sampling method was regular random method, equal to Morgan's table, 385 people. To analyze the collected data, including the information related to accidents with damages, injuries and traffic violations of motorcycle riders, one year before and after their participation in the Motoryar project, from paired t-test. It was done using SPSS25 software. The mean average rate of traffic violations by motorcycle riders after participating in the Motoryar project was 22.391, not using helmets, 10.853 special bus lanes, carrying unconventional cargo 4.909, moving on the sidewalk 1.871 , movement in the opposite direction of passing 12/364 and violation of illegible motorcycle license plate 18/287, as well as the average rate of damage accidents 8/52 and injury 12/43 has decreased. The inferential statistics showed a significant relationship between the implementation of the Motoyar project and the safety of motorcycle riders. The implementation of this project, based on the field training of the offending drivers, has been able to improve the traffic behavior of this group of vulnerable traffic users and improve their traffic safety.

The balance between safety and operational efficiency of left turn movements at intersections, especially inner city roads, needs special attention. Among the types of intersections, lighted intersections highlight this need more, because at the same time that protected left turn increases safety, unnecessary left turn protection can cause operational delays. increase significantly. The traditional and common safety evaluation methods are mainly based on traffic accident statistics, due to reasons such as the rarity of accidents, inappropriate reporting level, failure to consider the behavioral aspects of road users, and spending a lot of time and money to collect information. It does not have good efficiency for using short-term strategies and before and after studies. Therefore, in the present research, using its own traffic conflict technique, based on events with a higher frequency of occurrence than accidents, a solution is presented to evaluate the intersection safety of conflict related to left turns.

Traffic crashes are a significant problem in low and middle-income countries, while there is a worrying trend of increasing fatal and injury crashes Iran. This highlights the urgent need to analyze the causes of such accidents to improve road safety and reduce their negative consequences. To address this issue, a study was conducted to investigate the factors that contribute to the severity of rural crashes in Zanjan province, using advanced machine learning models such as Support Vector Machine and Decision Tree. The study utilized a crash database of 25,000 incidents over a 9-year period, and after cleaning the data, the models were developed in Python. The findings suggest that “type of crash”, “at-fault driver's vehicle type”, and “kilometer occurrence of the crash” are key variables for predicting the severity of these crashes. The Decision Tree model was also found to be more accurate than the Support Vector Machine model, particularly in predicting severe crashes. This study provides valuable insights for improving road safety and reducing the harmful effects of traffic crashes in rural areas.

The safety index and accident control are among important criteria evaluating the performance of transportation network, and speed management with the aim of achieving safety for traffic users is considered one of the main needs Considering the use of speed bumps as one of the important tools in traffic calming in Tehran, this research has compared the effect of speed bumps on traffic calming in main and secondary arterial roads. Method This research was applied terms of purpose and descriptive correlation in terms of nature the statistical population of this research was all drivers passing through the main and secondary arterial streets of Tehran. According to Morgan's table, the sample size was 384 people and available sampling was used, Pearson correlation tests and dependent t-test were used. The results of the t-test showed that speed bumps with signs warning signs have a significant effect on reducing the speed of vehicles in the main and secondary arterial roads. The average speed reduction in the distance of 300 meters from the main and secondary streets is 40.7 and 28.6 km/h, respectively. Also, the average speed reduction at a distance of 300 meters from the speed limit without signs and warning signs on the main secondary arterial streets was 41.9 and 24.9 km/h, respectively. The results of this research showed that in order to increase the effectiveness of speed bumps in main and secondary arterial streets, installing warning signs and revealing them increases the safety of traffic users.

Road crashes and their consequences are one of the most important problems that affect people's lives. In order to reduce the fatalities and related cost of crashes, traffic safety researchers are continuously investigating approaches to reduce the occurrence and consequences of crashes. Crash type modeling is one of the most common tools for road safety goals in transportation facilities, and the purpose of crash type modeling is to establish a relationship between the frequency of crashes based on its type and other effective variables. One of the advantages of crash type models is that with the help of these models, it is possible to identify the places where there is a possibility of a certain type of crashes and to examine the effect of different variables on different types of crashes. In this research, using the data of freeway accidents in Iran, the type of crash was identified with a new approach called nested logit model. To this aim, crashes were initially divided into two categories of single-vehicle and multi-vehicle crashes, and then single-vehicle crashes were divided into three categories of collision with a fixed object, off-road crashes, and overturning crashes, and multi-vehicle accidents were divided into two categories of collision with a vehicle and multi-vehicle collision crashes. Then the effect of different variables of environment, road, driver, and causes of crashes with different types of crashes were investigated and the effect of significant variables on each type of crash was explored with marginal effect.

Spatial and temporal analyzes of accidents are considered essential in traffic safety in order to discover the relationship between variables more accurately and provide a solution to improve the current situation. In spatial analysis, a phenomenon is analyzed according to its position and surroundings. So that in addition to the phenomenon itself, the impact of neighborhoods and environment is also considered. The purpose of this study is to investigate the location and time of Qazvin urban accidents and to identify hotspots related to various variables according to the age range of drivers for the data of the recent three years. For spatial analysis, the kernel density function tool in ArcGIS software is used and for temporal distributions, the spider plot of Excel software is used. First, hotspots and hot-times for different variables were identified according to the age ranges of the drivers. In the next step, hotspots were distributed among the three defined urban areas, and high-risk areas of the city were introduced, respectively. According to the results, suburban roads and in particular the Islamic Republic Highway had the largest share in the hotspots of Qazvin accidents and the need to control the combination of vehicles on these routes is felt. 12 to 14 was also the most important time for accidents of different age groups, and the two younger age groups (under 26 years old and 26-34 years old) played a greater role in hotspots and the need to educate and supervise these two age groups is felt.

Professional, continuous and effective training is one of the most important solutions for self-protection and sustainable prevention of violations and accidents of motorcycle riders, and in this context, the most basic step in compiling and implementing their training program is the correct implementation based on the reality of the needs assessment process. . Therefore, the main goal of this research is to assess the needs and prioritize training of motorcycle riders. This research was exploratory in terms of applied purpose and mixed method. The statistical population of the experts of the qualitative section of Tehran Traffic Police and Imam Hasan Mojtabi University of Officers and Police Training (AS), in the quantitative section, were the excellent accident experts of the 28 districts of the Tehran Traffic Police. Sampling in the qualitative part by a purposeful method based on criteria until reaching theoretical saturation and in the quantitative part by a simple random method equal to Morgan's table were 274 people. The factor loadings of comprehensiveness with a value of 0.866, value and credibility with a value of 0.861, cultural participation with a value of 0.879, and realism with a value of 0.756 are significant at the level of 0.95 and respectively have the greatest impact. to the comprehensiveness dimension of education - a very strong relationship - and then related to the value and validity of education, a strong relationship, and then related to cultural participation, an average relationship, and finally, the least impact related to the realism dimension in the educational needs assessment and prioritization model It is motorcycle riders. Motorcycle riders need more technical and practical knowledge about self-care and prevention of traffic accidents, which needs to be taken into the attention of those in charge of specialized safety training and the theoretical and practical training programs provided in driving schools are appropriate to Their general, real and practical needs should be changed in a diverse range of educational standards.

Large number of road crashes and their consequences has made road safety a worldwide challenge. Behind any traffic conflict indicators are assumptions which takes them away from statistical analysis of real road crashes. We conducted road crash simulation using finite element methods and analysis them to asses safety. To high accurate scrutiny crashes, finite element is used. By running crash finite element models in Ls-Dyna simulation is ran based on angles and relative velocities in different states (area stucked in crash). In other words multy body elasto-plastic dynamic finite element model is simulated. By analyzing vehicle sets before and after crash and by means of kinetic energy law, dissipated energy is calculated. Dissipated energy reveals as transformation in area stucked in crash. Therefore for each crash scenario dissipated crash energy is calculated and graph for each one is derived. Different mode of material is assessed and reflected in crash analysis. So by energy absorbtion crash severity is predicted.

Deep reinforcement learning methods have shown promising results in the development of traffic signal controllers. In this paper, we evaluate the flexibility of a controller based on Deep Reinforcement Learning under high traffic volume and under a variety of environmental disruptions, such as accidents, and propose a reliable controller in a dynamic traffic environment. In this method, using the discretization approach, each of the intersection roads is divided into cells and the effect of the size of these cells in terms of whether they are different or identical is studied on the efficiency of the algorithm. By selecting an extended and dense state space, the agent is given information as input that can provide it with a complete understanding of the environment. The Q-deep learning method and experience replay are used to train the agent, and the proposed model is evaluated in the SUMO traffic simulator. The simulation results confirm the efficiency of the proposed method in reducing the queue length even in the presence of a disruption.

According to the statistics of the Iranian Legal Medicine Organization in 2019, about 17,000 people died in driving accidents in Iran, which about 3,300 of them were motorcycles' passengers. Also, intersections all over the world include a major share of accidents. Therefore, due to the increase in the use of motorcycles in the world and their low safety level, It is important to study the impact of various variables on safety of motorcyles at intrsections. Among the variables, the movement speed is particularly important due to its direct relationship with the severity of injuries caused by accidents. In this study, which was conducted by video analysis method, A total of 304 conflicts between vehicles and motorcycles were investigated at intersections in Qom. Then, using one-way ANOVA analysis, an attempt was made to evaluate the effect of road users' movement speed on the safety of motorcyclists in conflict with vehicles at urban intersections, based on TTC and PET conflict indicators. For this purpose, Conflict indicators were investigated in two critical and non-critical states. As a result the value of vehicle's speed has a significant effect on making a conflict critical, so that it was 13 and 25 percent higher than the similar values in the non-critical states of TTC and PET indicators, respectively. while the amount of motorcycles speed did not show significant change in critical situations. It means that in conflicts between vehicles and motorcycles at intersections, among the different road users' speed, the main factor that makes a conflict critical and results in accidents, is the increase in the vehicles' speed not the motorcycles' speed. Therefore, proper safety measures to reduce the speed of these vehicles at intersections such as the use of intelligent speed adaptation systems or infrastructure measures such as visual signs or speed bumps are priorities.

The aim of this study is to identify the important factors influencing lorry drivers overloading on Tehran's highways and to investigate the effect of each variables in committing this violation. To this end, the required information was collected through field surveys at 10 stations on the Tehran urban highways. The tonnage data of freight vehicles were collected using a pair of portable scales as well as other information needed including driver information, vehicle, load and travel by completing the questionnaire. After correcting or deleting incomplete data, 856 data records were used for statistical analysis. The results of statistical models and binary logistic analyzes showed that the highest probability of overloading in the inner-city axes was obtained for construction loads. Also, the results of modeling in traffic type section showed that the highest likelihood of overload for internal loads (origin and destination inside Tehran) and the least probability of overburden (origin and destination outside of Tehran) were obtained. Finally, it was concluded that drivers are more likely to commit overloading on weekends.

In cost-benefit analysis and prioritization of safety countermeasure, it is necessary to estimate the social costs of accidents. One of the crash costs is the cost of users' time loss due to delays caused by accidents. In most studies, this factor has been ignored or considered only as a general estimate and no specific method has been considered for it. In this research, an analytical method has been proposed to calculate the cost of the delay caused by the accident and the factors affecting it have been investigated. Another objective of this paper is to investigate and compare the cost of time loss to road users in different types of accidents according to type of vehicles and roads. In a case study, total time loss of users in various accidents is calculated according the roads and vehicles types. The results show that accidents on arterial roads and especially heavy vehicle accidents, cause the most wasted time for users. Total time loss in each injury or fatal accident on the freeway-highway, main road and secondary road is 2039.65, 700.39 and 95.90, respectively. Also, it is found that the share of freeway-highway, main and secondary roads from the total time lost in rural accidents is 43.69, 54.92 and 1.39 percent, respectively. The average time lost in each rural accident is 869 people - hour and its cost in 2016 is equal to 27.3 million Rials, which is about 0.6% of the total cost of rural accidents.

Connected and autonomous vehicles (CAVs) with their predicted advantages are becoming reality. But it’s important that experts and scientists find out the advantages and disadvantages of the aforementioned technology before it becomes real. As a result, some studies have been conducted in recent years. According to the literature, CAVs can lead to a safer and more comfortable transportation at a lower price and they also improve capacity of transportation network. In this study, different aspects of CAV technology including its long-term and short-term effects have been assessed, but this study has mainly focused on how CAVs affect traffic safety. One may challenge the claims about advantages of CAVs and label them as exaggerated, because CAVs may eliminate driver mistakes but they cannot prevent vehicle and road problems. According to the past studies near 90 percent of accidents happen as a result of human mistake and CAVs may help lower number of accidents by reducing the role of human in driving. On the other hand, connected vehicles can alarm the driver if the vehicle is getting close to an obstacle including pedestrians and other vehicles, therefore pedestrian casualties may get substantially lower by applying connected vehicle technology.

Nowadays traffic collisions in highways is frequent and they not only cause delay in trips but they also may lead to secondary accidents which may be 6 times more dangerous than the primary accident. In order to manage traffic collisions, reducing secondary accidents is a key factor. However, enough attention has not been paid to secondary accidents, which is because of the random nature of these accidents. As a result, most of the past studies have focused on the definition and recognition of secondary accidents. After recognizing secondary accidents, defining the factors that affect them is the main procedure to reduce this kind of accidents. In fact, when the key factors influencing a phenomenon is not yet known, presenting methods to deal with it, is useless. Therefore, many of the past studies have focused on the key factors that cause a secondary accident, such as road geometry, traffic condition, weather and vehicle characteristics. After defining the key factors affecting secondary accidents, it is possible to reduce them, and some of the previous studies have presented these methods. In this article, a general review on all of the 3 aforementioned categories of study, has been provided.

Transportation and logistics play an important role in the economy of countries, while road transport is one of the most important modes of transportation for load transportation, especially in developing countries. Accidents are directly related to driving offenses, and drivers who commit more offenses are more prone to accidents. Therefore, reducing driving offenses can reduce accidents. Hence, the recognition of common driving offenses among heavy vehicle (truck) drivers and the effective factors in directing them to reduce driving offenses can consequently reduce the frequency and severity of accidents. Thus, there is a necessity for conducting further studies to carry out research in this regard more than ever before. The main objective of this study is to identify and evaluate important factors affecting lorry drivers committing traffic offenses. To this end, the required information was divided into six categories: traffic tonnage, not wearing a seatbelt, unauthorized speed, impaired driving, talking on the phone, lacking a scalp leaf, and these factors are known as dependent variables. Also, the influencing factors in the group of driver characteristics, vehicle, and mileage were considered by using a demographic questionnaire and Driving Behavior Questionnaire (DBQ) and interviews with 420 drivers over 60 days at the Shahid Kheibari Terminal in Mashhad. After correcting or removing incomplete questionnaires, the information of 351 drivers was used for statistical analysis. Besides, statistical analysis of data using the multivariate logistic regression model showed that drivers with discharging and loading of five or six times per month are less likely to commit excess tonnage than drivers with discharging and loading of more than 12 times per month. The results also proved that drivers with less slip behavior and not so-called distraction would be less likely to commit unauthorized speed offenses and 85.4% less likely to commit this violation. Finally, analysis of statistical analysis showed that drivers with aggressive driving behavior were more likely to commit lacking a scalp leaf offense.

Growth of population and urbanization, transport expansion as well as demand of road trips in developing countries such as Iran, cause to the increase of the number of vehicles day by day, which this matter leads to the enhancement of the unreasonable of travel time and high rate of accidents. The data of accidents show that in whole of the world around 13 million people die every year from accidents and more than 50 million people are injured or physically handicapped due to this matter. Therefore, in order to achieving the proper traffic planning to reduce of accidents number and casualties, assessing the road safety with considering effective factors is very important. In general, different methods are used to evaluation of the safety of transportation facilities, which most commonly methods of them are statistical models. The main purpose of this paper is to present an improved method, to evaluate the safety of different urban intersections by using a statistical model of urban accidents. This study was conducted on 140 three-way and four-way intersections which included lights and no lights cross. In these cases data of accidents on three years period, from 1387 to 1390, have been collected from the 113 police reports and other required data have been gathered by field investigation (research). A multiplicative form based on Haier equation has been used to build the considered model, where descriptive variables choose in continuous and binary forms and with a predetermined function are introduced to the equation. The results showed that in the urban intersections, incoming traffic has the greatest impact on accident rates, and for a certain traffic volume, effects of intersection geometry (3-way and 4-way) and also type of traffic control (signalized and no lights) on the rate of accident are negligible.

Identifying the effective factors in traffic accidents in terms of transport safety is one of the basic issues that researchers have been focusing on for many years. A severe incident is a comprehensive result of several variables that causes accidents. The purpose of this study is to consider the effective factors on improving traffic safety and reducing motorcycle losses. Eighty five person selected from statistical population which included 200 person with experts in the field of accidents and safety and regulations. In this research, information was collected through a library study and the data was analyzed using the AHP technique and the Expert Choice software. This practical research has been conducted by designing a main question called "Effective components on improving traffic safety and reducing motorcycle losses". The results of this research, by introducing effective components, define the importance of each component for quantitative evaluation. Accordingly, the five main components of the effective factors on improving traffic safety and reducing motorcycle losses, together with their weight, are control of the skill of motorists, frequent education and information by the media, systematic planning to reduce intra-city travel citizens with motorcycles, judiciary intervention in the discussion of motorcycle driving violations and the strict implementation of motorcycle driving laws. he results of this paper can provide an appropriate perspective on designing a model for better understanding and preventing accidents from motorcycle accidents in the future by identifying the factors affecting the promotion of transport safety and reducing motorcycle losses.

Abstract The most injuries of pedestrians happen when crossings, especially at mid-block crosswalk without traffic lights. Based on this, understanding the behavior of pedestrians and finding effective parameters during crossing can be very important from the point of view of safety. In this article, we tried to analyze pedestrian’s behavior in expose to vehicles, and determine effective factors in gap acceptance at mid-block crosswalk. For this purpose, filming was performed after identify suitable locations. By analyzing videos, effective variables were considered. After analyzing the data, the relationship between the characteristics of pedestrians by with their waiting time along the street to crossing was determined. Also attempts to safety pass and gap acceptance were presented in two models. In the waiting time model, the results showed that women had lower waiting time than men. By increasing  age, the waiting time also increases. The cautiousness of the pedestrian also increases the waiting time. In the gap acceptance model, which was obtained as a probability function by using logistic regression, the distance between the pedestrian to the approaching vehicle and following mode were influential variables on the probability of accepting the distance by pedestrians. The result was shown following pedestrians are more likely to accept the distance.