mahmoud saffarzadeh

In the supply chain, factors such as political issues, demand fluctuations, technological changes, financial instability, and natural disasters lead to increased uncertainty and the emergence of various risks. One of the most important and complex stages of logistical support in organizations, particularly in military and law enforcement organizations, is the forecasting process. Due to its vital role in improving logistical functions, this process highlights the necessity of designing and establishing effective forecasting systems. This research examines the importance of forecasting and estimation in logistical functions and analyzes the requirements that must be followed when designing a forecasting system for the country’s 10-year horizon. The research method is a questionnaire survey evaluated by 120 participants. The case study of this research is the Amirabad Special Economic Zone (Mazandaran), from which all necessary information and data have been collected. This region plays a crucial role in trade and economic development in northern Iran, with various investments in logistics and transportation.

The increase in motor vehicles has greatly increased air pollution in the Tehran metropolis and turned it into a challenge. By analyzing transportation pollutants, low-carbon cities and sustainable development strategies for urban districts can be achieved. This study deals with the spatiotemporal analysis of pollutants and transportation accessibility in the urban districts of Tehran. The concentrations of CO and NO2 pollutants were extracted from the Sentinel-5P satellite using coding in the GEE environment. OSM data were used to calculate the accessibility of the 22 urban districts. Moran's global autocorrelation indicated a clustered spatial distribution pattern of pollutants. The high autocorrelation value equal to 0.94 for CO and NO2 pollutants indicated their cumulative state in the atmosphere. By performing LISA, most clusters of these pollutants were identified in the central districts and southern suburbs. The average accessibility indicator of the 22 districts was 24.82 km/km2. About half of Tehran's urban districts had a high density of road transport networks. These districts are located in CO and NO2 clusters owing to the high traffic volume of motor vehicles. The results of this study emphasize the factors that aggravate Tehran's air pollution, including the clustered pattern of pollutants in the atmosphere and dense transportation network in urban districts. By integrating air pollution analysis and accessibility estimations into urban planning frameworks, cities can strive to achieve long-term sustainability goals.

For several decades, finding the optimal location of counting sensors in a traffic network to obtain the best estimates of the O-D matrix has attracted a growing amount of attention. The availability and the accuracy of a priori data in a network such as O-D matrix and route choice probabilities on one hand, and the complexity of the mathematical operations for solving the location problem even in not a large network, on the other hand, are two main concerns of the presented methods. This paper aims to propose a method that identifies optimum locations for counting sensors without utilizing any a priori data. Relying on the network topological characteristics and link travel times as the representation of the network’s pattern of trips is the core concept of this study. By taking benefit of the frame theory algebraic operations, needless of any pre-given a priori data, the location set vector with higher coverage on the network route vectors is identified as the optimal location set of the sensor-equipped network links based on its representation in the route-vectors frame. The most probable used paths are identified utilizing an efficient path algorithm. Additionally, by taking advantage of the matrix operations, the novel method obviates the calculations required in methods using linear or non-linear programming solutions. The presented method is applied on a test network and the results show that in comparison to the non-linear programming method, the proposed method finds a better solution.

Built environmental factors are one of the most important causes of urban accidents. Studies have shown that in addition to accident data, which have spatial heterogeneity, factors influencing accidents also have spatial correlation. The occurrence of urban accidents depends on many human and environmental factors, so identifying the important factors influencing accidents and their spatial effects on each other is of great importance. The main goal of this study is to evaluate the spatial effects of environmental factors on the frequency of accidents in the city of Shiraz, Iran at the TAZ level. In the first step of the study, using component analysis models, important environmental factors affecting the accident were identified and composite indicators were produced as independent variables. In the second step, in order to control the effect of correlation and heterogeneity of model variables, spatial statistical models based on Euclidean distance such as geographically weighted Poisson regression (GWPR), geographically weighted negative binomial distribution (GWNBR) as well as Poisson and distribution models Negative binomial based on neighbor distance is used in spatial Bayes method with INLA approach. The results of the study showed that models based on distance and contiguity in order to evaluate the spatial effects of accident data and the factors affecting it at the TAZ level have higher accuracy than geographic weighted regression models, as well as indicators of land use diversity and access to the system. The public transport produced in the first step is effective in increasing the frequency of accidents, and in TAZs where this index is high, there is a higher probability of an accident. The results of this study can be important for city managers and planners in order to improve inner city safety measures as well as development planning and future city measures.

Road accidents and the resulting casualties are one of the current challenges of human societies that have imposed significant economic costs on countries. In Iran, an average of 17,000 people die each year due to road accidents. Among them, human factors have been mentioned as the main cause of accidents, The aim of this study was to find challenges and provide solutions to prevent accidents and reduce casualties. In this study using literature review and interviews with relevant experts , a questionnaire with 24 questions that included human factors affecting accidents was developed and given to the statistical population, which after analyzing the results, the possibility of identifying challenges and providing various solutions to prevent accidents caused by human factors was created. Using document analysis method and basic principles regarding accident prevention were statistically analyzed, and through interviews with experts, the factors affecting the challenges of traffic police in preventing accidents caused by human factors were identified, and after necessary analysis in this field and using the methods of forming IFE and EFE matrices, the necessary environmental analysis was done, and 7 threats and 3 weaknesses were identified, which with the identification of challenges in this regard, the possibility of providing solutions to prevent accidents caused by human factors was created with the help of expert opinions and finally, after being raised in the expert meeting and discussion in this regard, 12 solutions were identified and presented to overcome these challenges

Road accidents and the resulting casualties are one of the current challenges of human societies, which have imposed a lot of economic costs on the economies of countries. In Iran, on average, 17 thousand people die each year due to road accidents. In the meantime, the human factor has been mentioned as the main cause of accidents, and many conditions such as fatigue, sleepiness, lack of skills, consumption of alcoholic beverages, drugs, etc. affect the human factor. In this research, the aim was to find challenges and provide solutions in order to prevent accidents and reduce casualties.

This research is of an applied type and the method of collecting information in it is mixed exploratory. In this research, using a review of the research background, theoretical foundations and interviews with experts in this field, a questionnaire with 24 questions that includes human factors affecting accidents was compiled and applied to a statistical population of 63 people, which includes Experts and experts in this field were given. Then, the data obtained in this stage were analyzed using SPSS software and quantitative description results were obtained. Then, by using the SWOT method, the four roles of these factors were determined, which was obtained after the analysis of the results (the necessary analysis in this field was carried out using the IFE and EFE matrix formation methods and the necessary ecology was also addressed).  It was possible to recognize the challenges and provide different solutions in order to prevent accidents caused by human factors.

The guiding elements in the prevention of accidents caused by human factors were obtained by the foundation data method, and 24 effective factors in the prevention of accidents caused by human factors were determined by the content analysis method; Using the SWOT method, four roles were calculated, which were 3 weakness factors, 7 strength factors, 6 opportunity factors and 7 threat factors (one factor was ineffective and was removed). By identifying the challenges in this regard with the help of expert opinions, it became possible to provide solutions to prevent accidents caused by human factors. According to the phases that were taken in this research, the challenges of IRI Traffic Police in preventing accidents caused by human factors were identified in the form of weaknesses and threats, and finally after being brought up in the expert meeting and discussion. In this context, the number of 19 solutions to solve these challenges were counted and presented.

The results of this research show a plan with 19 solutions whose main goal is to prevent accidents caused by human factors and considering that the human factor is the most important and influential factor in the occurrence of traffic accidents. By implementing the 19 solutions listed by the IRI Traffic Police, an effective step can be taken to reduce human casualties caused by road accidents.

The increasing development of the aviation industry in the last decade as one of the most important axes of development and growth of cities has a special place in economic, social and cultural development programs. Considering the special tourism and economic status of Zanjan province in terms of national and religious aspects and the location of Soltanieh Dome as one of the most important tourist attractions registered by UNESCO in the province, the geotourist attractions of Katlekhor Cave and the colorful mountains of Mahneshan, Hosseinieh religious ceremony Zanjan and the existence of important mining and electrical industries such as Iran Transfo and Pars Switch, copper handicrafts and knives and the agricultural potential of the province, the optimal performance of Zanjan airport can play an effective role in the economic prosperity of the province. The operation of the airport provides local businesses with access to national and global markets and helps to retain and attract business, and thus can provide jobs and economic prosperity for the region. In general, the economic performance of airports is largely directly related to the political, economic, social and cultural importance of the city's urban hierarchy. The aim of this study was to evaluate the economic performance of Zanjan Airport using the TOPSIS method (MADM) which is a multi-criteria decision-making method. According to this study, the results show that in order to improve Zanjan Airport, the community is more in favor of turning the airport into a private airport and the least effect is considered as the parameter of the impact of air agencies.

As urban populations grow, the demand for smarter and more efficient urban spaces becomes increasingly critical. The advent of autonomous vehicles also presents opportunities and challenges in shaping the future of smart cities. This article examines the complex interactions between resources, technology, and technical aspects of autonomous vehicles and their impact on urban spaces.

A comprehensive research methodology was employed to assess the impact of interactions between resources, technology, and technical aspects of autonomous vehicles on smart urban spaces. This included a review of the literature, data analysis, case studies, and simulations. By integrating findings from various sources and methods, a complete understanding of the subject was achieved.

The findings of this study highlight the multifaceted impact of interactions between resources, technology, and technical aspects of autonomous vehicles on smart urban spaces. Despite their enormous potential to reduce traffic, enhance safety, and improve urban mobility, these interactions raise concerns about privacy, infrastructure compatibility, and equitable access.

Therefore, it is essential for policymakers, urban planners, and technologists to collaborate in developing strong frameworks and regulations to harness the benefits of autonomous vehicle technology while mitigating potential challenges. By promoting innovation and inclusive urban development, cities can leverage the transformative power of autonomous vehicle technology to create smarter, more sustainable, and livable urban environments for all citizens.

Today, one of the most significant points of interference in streets is the signalized intersections; therefore, solving problems of traffic at intersections can increase the capacity of urban transportation. Inability to diagnose the traffic conditions results in the lack of proper timing, phasing and cycle length, all of which are attributed to the abnormal factors concerning intelligent control systems. In this paper, in addition to the introduction of abnormal traffic conditions at signalized intersections, an attempt has been made to intelligently diagnose anomalies for both an approach and its entire intersection. For this purpose, by making use of the data based on the GPS of users' cell phones extracted from NESHAN Application, which consists of 10-minute average speed in streets ending to an intersection, and by behavioral matching with the data concerning the volume and saturation rate in SCATS, and meantime, by analyzing the fundamental traffic relations, an attempt has been made to diagnose the abnormal traffic conditions through SCATS at Toos-Danesh intersection of Mashhad, in which abnormal conditions including the detecting of heavy traffic conditions when the traffic is light and vice versa. To achieve more accuracy, the method was built based on both quartiles and percentiles of DS, degree of saturation, and ADS, average degree of saturation, in SCATS. Finally, anomaly detection based on the 10th and 90th percentiles had 100 percent accuracy and the one based on the 1st and 3rd quartiles had between 57 to 80 percent accuracy, which have been checked by two real datasets.

The main goal of the present study is to provide the basis factor model to determine the optimal capacity of the metro station with the aim of minimizing the incidence of infectious diseases. In this research, the study area, namely Imam Khomeini metro station in Tehran, was investigated. After collecting the information, some indicators affecting the demand and capacity and the statistics obtained in the years before Corona, as well as structural observations during the Corona outbreak, were examined and the information was analyzed. After confirming reliability and validity, factor analysis was evaluated and categorized and prioritized in the conditions of Corona. According to the results of the factor analysis in order to categorize and reduce the variables related to the model for determining the optimal capacity of the Imam Khomeini subway station in the conditions of Covid, the most important of them are, in order: the percentage of employees in the sample per day, the perception of people's access to the subway by taxi, the percentage of the number of car owners, the percentage of commercial and service trips, the average income, the percentage of office trips, and the congestion index on footpaths with respect to social distance are among the seven variables with the most important priority in factor modeling, which are further shown in the proposed regression model. In measuring the optimal capacity of Imam Khomeini metro station, they were measured.

Congestion in the public transportation in Tehran is a convenient problem especially in the pick hours. Transferring in a congested transit vehicle makes passengers feel discomfort during their trips. Another important thing is the idea of time which is a subjective issue which means that passengers experience their travel times differently in a specific time interval. The literature has confirmed this issue, so the idea of “perceived travel time” has been introduced for many years. It implies that a passenger travelling by a congested public transport vehicle feels like the time is passing slower compared to those who are travelling in uncongested vehicles. The idea of perceived travel time has led some researchers to the concept of “perceived travel time reliability”. This paper is aimed at demonstrating the necessity of paying attention to these two concepts for the public transport system in Tehran. For this purpose, the first line of BRT system of Tehran has been considered as a case study. Using Automated Fare Collection (AFC) and Automatic Vehicle Location (AVL) data in a pick hour of a work day back in the autumn of 2019 and before spreading the corona virus, the perceived travel time and perceived travel time reliability are calculated. The results show that there is a significant difference between perceived and nominal. The differences show the necessity of reconsidering the analysis of public transport systems using the nominal travel time and travel time reliability. In fact, it seems that using the perceived will be more helpful

The type of land use in each traffic area zone (TAZ) is the most important factor determining the number of vehicles, geometric and traffic characteristics in that zone. Any factor in the urban environment that causes congestion and attraction of vehicles at certain times increases the probability of an accident in that area.In this study, in order to investigate the effect of the share of the types of uses in each of the traffic areas of Shiraz city on the probability of an accident, a two-step method including the identification of the types of uses influencing the occurrence of accidents as well as spatial effects between independent variables and accident data in space Kernel density estimate (KDE) methods have also been used in order to find the suitable bandwidth for searching observations, geographically weighted regression (GWR) and geographically weighted Poisson regression (GWPR) in order to investigate the spatial effects of the contribution of land use types on the occurrence Accident is used .The results of the study have shown that among the mentioned models, the local GWPR model has a better performance than the global Poisson model and the local GWR model based on validation criteria. Also, the presence of residential, commercial, barren and abandoned uses and the mixing of residential and non-residential use have the greatest impact on They have accidents. Examining the spatial effects of land use types in each of the traffic areas in this study can be very important in order to carry out safety measures.

The type of land use in each traffic area zone (TAZ) is the most important factor determining the number of vehicles, geometric and traffic characteristics in that zone. Any factor in the urban environment that causes congestion and attraction of vehicles at certain times increases the probability of a crash in that area. The purpose of this study is to investigate the effect of the share of different types of uses in various traffic areas of Shiraz city on the probability of a crash. A two-step method, including identifying the types of uses influencing the occurrence of crashes and spatial effects between independent variables and crash data in space Kernel density estimate (KDE) methods, has also been used to find the suitable bandwidth for searching observations. In order to investigate the spatial effects of land use types on crash incidence, geographically weighted regressions (GWRs) and geographically weighted Poisson regressions (GWPRs) were used. Based on the validation criteria, the local GWPR model performs better than the global Poisson model and the local GWR model among the mentioned models .Additionally, the presence of residential, commercial, barren, and abandoned uses, as well as the mixing of residential and non-residential uses, significantly impact crashes. Examining the spatial effects of land use types in this study's traffic areas can be very important in carrying out safety measures.

The occurrence of urban accidents depends on many human and environmental factors, so identifying the important factors influencing accidents and their spatial effects on each other is of great importance. The main goal of this study is to evaluate the spatial effects of environmental factors on the frequency of accidents in the city of Shiraz, Iran at the TAZ level. In the first step of the study, using component analysis models, important environmental factors affecting the accident were identified and composite indicators were produced as independent variables. In the second step, in order to control the effect of correlation and heterogeneity of model variables, spatial statistical models based on Euclidean distance such as geographically weighted Poisson regression (GWPR), geographically weighted negative binomial distribution (GWNBR) as well as Poisson and distribution models Negative binomial based on neighbor distance is used in spatial Bayes method with INLA approach. The results of the study showed that models based on distance and contiguity in order to evaluate the spatial effects of accident data and the factors affecting it at the TAZ level have higher accuracy than geographic weighted regression models, as well as indicators of land use diversity and access to The public transportation system is effective and in TAZs where this index is high, there is a higher probability of an accident.

The type of land use in each traffic area zone (TAZ) is the most important factor determining the number of vehicles, geometric and traffic characteristics in that zone. Any factor in the urban environment that causes congestion and attraction of vehicles at certain times increases the probability of an accident in that area. In this study, in order to investigate the effect of the share of the types of uses in each of the traffic areas of Shiraz city on the probability of an accident, a two-step method including the identification of the types of uses influencing the occurrence of accidents as well as spatial effects between independent variables and accident data in space Kernel density estimate (KDE) methods have also been used in order to find the suitable bandwidth for searching observations, geographically weighted regression (GWR) and geographically weighted Poisson regression (GWPR) in order to investigate the spatial effects of the contribution of land use types on the occurrence Accident is used.The results of the study have shown that among the mentioned models, the local GWPR model has a better performance than the global Poisson model and the local GWR model based on validation criteria. Also, the presence of residential, commercial, barren and abandoned uses and the mixing of residential and non-residential use have the greatest impact on They have accidents. Examining the spatial effects of land use types in each of the traffic areas in this study can be very important in order to carry out safety measures.

In traffic engineering, we deal with a coefficient called the coefficient of riding, which is used to convert the traffic of heavy vehicles into "rides." Buses, trucks, trailers and have a coefficient larger than one, and a bicycle and a multiplier of less than one, which is one third in the code of some countries, and one in two (half) in others. In Iran, this coefficient, like other coefficients in different branches of knowledge and technology, is based on external coefficients and regulations of other countries. In this study, the coefficient of motorcycle riding at the intersection of the lamp is calculated, and the criterion delay parameter is the comparison and calculation is. Accordingly, the coefficient of ride equals the delay created per motorbike delayed by each car in the stream involving only a single riding car. In this study, the coefficient of homogeneity for meta-cycles was obtained, with an average coefficient of 0.4. The results of descriptive statistics analysis of these several time-based groups based on vehicle type along with Zamani Kelly's headline have shown that among the mean values of different groups, two riding groups are very close in pursuit of riding and riding in the pursuit of the engine. All groups with a mean time header are larger than other types. In other words, the average riding time range for riding and motorcycle groups is significantly smaller than the average for the other three.

This study aimed at exploring the effect of consistent design and self-explanatory the horizontal curves on crash frequency in four-lane highways using Zero-Truncated Crashes data. The present study has considered the related variables for 45 curves of four-lane intercity highways in the three-year (2018-2020). The standard Poisson distribution is a benchmark for modeling equi-dispersed count data and could not express under-dispersed Zero-Truncated data. Modeling was performed using Poisson, Negative Binomial, Zero-Truncated Poisson, Zero-Truncated Negative Binomial, and Conway-Maxwell Poisson (COM-Poisson) regression. The results revealed that the COM-Poisson regression distribution could effectively fit the model under-dispersed Zero-Truncated Crashes data. According to the results, the ratio of the curve radius to the average radius of the adjacent curves (as the alignment consistency variable), the difference between the expected and the existing superelevation (as the vehicle stability consistency variable), and the variables of the total self-explaining index and heavy vehicle percentage have significant relationships with crash frequency. As a result, increasing the self-explanatory features of curves is an efficient and prioritized policy for safety improvement on the intercity four-lane highways.

The urban subway network is one of the most vital infrastructures that plays a pivotal role in the sustainable development of cities; therefore, network robustness or maintaining the proper performance in various conditions has great importance. Considering financial and functional limitations, identifying critical nodes is required to prioritize robustness enhance projects. Critical nodes are nodes that their removal deeply affects the connectivity and efficiency of the network. Network robustness and identification of critical nodes in the face of cascading disruptions have been studied, focusing on the network's structural features. On the one hand, cascading disturbances affect several stations simultaneously, which is less likely to occur than concentrated disturbances that affect only one station. On the other hand, focusing on the network structure leads to the loss of dynamic information, resulting in underestimating the length and overestimating the number of paths between network nodes. In this study, the critical nodes in the face of centralized disturbances have been identified using temporal network concepts, which consider both structural and temporal features. The results reveal that Darvazeh-Shemiran, Shadman, Shahid Beheshti, and Mohammadieh Square stations are the critical stations from both efficiency and connectivity points of view. The critical nodes have high values of static and temporal centrality indices, which increase network vulnerability against malicious attacks. In contrast, due to the high ratio of non-critical nodes to critical nodes, the network is robust against random failures. The method developed in this research can be generalized to other transportation networks.

Surrogate safety measure (SSM) plays a key role in early safety evaluation. Previous research has indicated potential associations between SSM and road crashes. Several attempts have been made to develop SSM. Most studies in the field of SSM have only focused on rear-end conflicts in witch the two vehicles move in a just one lane. The principal objective of this paper was to develop a new area-based SSM (ASSM) which can take into account the two-dimensional movement of vehicles. ASSM provides a novel approach to quantifying safety. The two-dimensional hypothetical areas around the vehicle that are required for the safe movement are introduced as the influence area. The mathematical equation of the influence area is derived as a function of vehicle speed, and then ASSM could be calculated by examining the extent of overlap and intersection of the influence areas of different vehicles at any given time. In this study, techniques for ASSM were developed and applied to real-world traffic data (NGSIM). The findings indicated that there was a positive relationship between ASSM and the time of the driver's decision to change his driving position to avoid a collision. The findings can contribute to a better understanding of human driving behavior in critical situation.

 Air pollution is one of the major challenges of urban management in Tehran. Nowadays, the problem of air pollution and traffic congestion in the metropolis of Tehran, like most major cities in the world, is quite concerning. Land use and transportation are two main sectors that have a maximum contribution to environmental pollution.

The impetus of this article is to investigate the urban land use efficiency, the distribution of land use, and their impact on transportation and pollutants. For this purpose, the following question was raised: What has been the impact of urban land-use efficiency and distribution of land use in Tehran on transportation and air pollution over the last two decades?

The present paper is a real-life case study for which data was collected through documentary-library, municipal data, and satellite images. In this study, Landsat satellite images, ENVI 5.3, ArcGIS 10.8, Google Earth Pro, and SPSS 24 were used.

The results of this study indicate the expansion of Tehran, the loss of vegetation,and their transformation into built lands. Over the past two decades, the growth of the built-up area in Tehranhas exceeded the population growth which indicates the inefficiency of the land during this period. In other words, the expansion of the city has been more towards the suburbs with low population density. The study of the correlation between land use types during the period 2004-2016 indicates the scattered growth of Tehran. In such situations, residents use more private cars, which increases traffic congestion, fuel consumption, and air pollution.

Transportation and land use are the two major sectors that contribute the most to the spread of environmental pollution. Transportation through accessbility affects land use while land use through the production and attraction of trip affects transportation. The purpose of this study is to investigate the accessibility of 22 districts of Tehran metropolis, how the city develops and their impact on increasing air pollution. This is an applied research where the data and information used in this research were obtained from Tehran Municipality and Statistics Center of Iran and for their classification and analysis, depending on the need, SPSS, Arc GIS and Google Earth software have been used. The results of Pearson correlation show that about 24% of land uses in Tehran have a significant relationship, which indicates a high separation between types of land uses and ultimately the scattered growth of Tehran. By analyzing and calculating the accessbilities, it was found that 38% of the internal communications between the districts are at the level of good and very good accessbility, 32% have the average level of accessbility and 30% are at the level of poor and very poor. The average route factor of Tehran is estimated to be 1.52, which indicates that Tehran is classfied in the average level of accessbility. Another finding of this study is the effect of land uses and accessbility levels on increasing air pollution in Tehran which is important to urban planners and policy makers.

Congestion is one of the problems that has bothered many countries in recent decades and has imposed huge costs on many countries. For this reason, many researchers are looking for ways to reduce congestion in transportation networks. On the other hand, it is predicted that the emergence of Automated Vehicles and Connected and Automated Vehicles can be effective in reducing congestion on the roads and increasing the capacity of the roads. For this reason, this study investigates the effect of Automated Vehicles and Connected and Automated Vehicles on the capacity of roads. In this study, a freeway network with the Merge section is used and the simulations are implemented using SUMO microscopic simulator software. In this study, to determine the driving behavior, the car following model for longitudinal movements and the lane changing model for lateral movements have been used. The Krauss car-following model and the LC2013 lane-changing model were used to determine driving behavior in this study. The simulation results show that Automated Vehicles can increase road capacity by up to 52% and Connected and Automated Vehicles can increase road capacity by up to 65%, which indicates the potential of these vehicles to increase capacity and reduce congestion. The results also show that these vehicles can have a significant impact on capacity when the presence of these vehicles on the road is significant.

In this research, researchers are looking to prioritize countermeasures in one of the important intersections of Darrehshahr city. The four countermeasures including installing a traffic signal, installing a speed hump in the minor approach, drawing a stop line in the minor approach +sign and creating a rumble stripe in the major and minor approach for this intersection are considered. The research method is the economic evaluation method in HSM. In the economic evaluation of countermeasures, the costs of fatal crashes, injuries and damages for the year 1399 have been calculated. Also, the expected crashes before and after the implementation of the countermeasures and the reduction in the frequency and severity of the crashes caused by the implementation of the countermeasures have been estimated. By calculating the annual benefits of crashes reduction and calculating the current value of benefits, assuming a 3 percent discount rate and a service life of 10 years for countermeasures, cost-benefit analysis and cost-effectiveness of countermeasures have been performed. The results show that according to the Benefit-Cost Ratio method, the stop line in the minor approach +sign, the creation of the rumble stripe in the major and minor approach, the installation of the speed hump in the minor approach and the installation of the traffic signal have priority, respectively. Also, for every million Rials spent on the implementation of the stop line in the minor approach +sign, the ratio of benefit to cost during the 10-year lifespan is 396508.5 to 1.

In this study, in order to identify vulnerable links, the performance of the network due to the obstruction of each link is evaluated by considering the simultaneous effects of supply and demand and assuming that drivers are aware of the obstruction status during the trip. Accordingly, by considering a specific routing pattern by users, the performance of the network is evaluated in the case of blockage of that link, and links whose removal does not lead to unacceptable changes in the network versus non-blocking, are considered as reliable links. In the following, it was implemented in the Tehran network based on 0.35 percent as acceptable changes. This value is equal to the minimum value of acceptable performance changes which makes it possible to access all points to evacuation destinations using the remaining reliable links. The basis for access will also be the possibility of creating an access tree. According to the evaluation of network performance due to the blocking of each link in EMME2 software and its comparison with the acceptable limit, 17.3% of the links of Tehran network will be unreliable links as a result of a possible earthquake. The most unreliable links of the network are observed in arterial roads, especially in the CBD. Therefore, although the removal of vulnerable links with arterial type can increase the reliability of the evacuation network by other existing links in terms of continuity and travel time, but this is due to the role and importance of this road type in network integrity and network efficiency, will lead to disruption of the network evacuation capacity. It makes necessary to development of parts of the network in the form of widening or adding links to the network in order to provide the required evacuation capacity. Obviously, if this is not possible or it is costly, especially in areas with dense texture, solutions such as retrofitting buildings as much as possible can be put on the agenda to reduce the demand for evacuation.

Lack of an appropriate local model of management, both criminal and non-criminal of crime and traffic violations for commanders and managers of urban traffic and traffic managers of the Islamic Republic of Iran, is one of the most important issues facing them in carrying out important prevention mission in driving violations and offenses in the current situation. Therefore, the purpose of this study is to design a model for the prevention of driving offenses.

This research is applied-developmental in terms of purpose and descriptive-survey in terms of quantitative methods of data collection. The statistical population includes traffic police officers in Tehran, as well as drivers who violated the law in the investigation period. Simple random sampling and statistical sample included 264 and 277 drivers and traffic police officers, respectively. Data were collected using a researcher-made questionnaire and data were analyzed using SPSS and Smart PLS statistical software.

It showed that at the level of 0.95, there is a relatively strong relationship between the variables with the pattern of crime prevention and driving violations, which has the highest effect of prevention related to the prevention of circuit growth with 63.8 (strong relationship), criminal prevention with 42 (Strong relationship), social prevention with a value of 38.1 (moderate relationship) and finally the lowest value related to situational prevention with a value of 16.5 (weak relationship) compared to the pattern of prevention of crimes and driving violations. Also, the factor loads of developmental prevention are equal to 0.789, criminal prevention is equal to 0.648, social prevention is equal to 0.617 and finally situational prevention is equal to 40.6 which are more than 0.4 which is at the level of 0.95. It is meaningful.

Finally, 4 variables, 14 components and 104 indicators including growth-oriented prevention variables including family-oriented programs, school-based programs, for social prevention variables including social constraints, risk management, awareness, program Community-based and specialized police training, for the situation prevention variable including patrolling, intangible control, use of cameras and intelligent systems for recording violations, and finally for the criminal prevention variable components of punishment certainty, certainty of punishments and The severity of the punishments.