علی نادران

Travel production in transportation management has led to extensive studies for different travel purposes. Trips due to the daily activities of citizens are divided with the purposes of work, shopping, education, etc., according to the studies conducted in Tehran, 12% of trips are shopping purposes, which after the trip with the purpose of work. Therefore, by identifying factors affecting the creation of shopping trips, we can play a significant role in reducing transportation cost, reducing pollutant emissions, increasing user satisfaction, and contributing to the growth of sustainable development. In this research, considering the frequency of data in areas 2 and 5 of Tehran metropolis and calculations based on Cochran's formula, 1500 questionnaires were provided to the people of these areas. Finally, 1,000 questionnaires were collected from users in the field of e-commerce who had successful orders in online and offline services in the last 20 days of 2021. The results of the descriptive statistics of the interviewees showed that the largest share of people in the statistical population were single men in the age range of 18-35 years without owning a car and having a bachelor's degree with an income level of 10-15. Also in this paper we used the indicators of age, gender, marital status, car ownership, shopping cost, shopping time, product price, household income, employment status, and education level. It has been used as indicators affecting the type of shopping trip. In the next step, the results were evaluated and the travel type estimated. In order to compare the proposed method, MLP neural network, DT and KNN algorithms were used. The results showed that the deep model has the best performance with an accuracy of 95.63%. After that, there are neural network with 90.12% accuracy, DT with 86.49% accuracy and KNN with 80.16% accuracy.

The purpose of this research is to rank road transportation smart projects in terms of implementation time, cost and ease of implementation using the model of similarity to the ideal option. In this research, the experiences of intelligent transportation systems in other countries, as well as how to use them and applicable projects in the suburban axes of other countries, were examined. In this regard, according to the proposed methods and needs assessment, the possibility of using different projects of intelligent transportation systems in a main corridor of the country (Tehran-Imam Khomeini Port (RA)) was investigated. In order to determine the execution rank of the projects, the method of similarity to the ideal option was used, and according to the existence of 12 projects and 3 main criteria of the duration of the project, the ease of implementation, and the cost and benefits of the ranking was done. Some of the results obtained in this research are: According to the presented model, the most important priority in the existing axes was the issue of regional speed,

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.

In recent years, due to the increase in the population of growth and the expansion of cities, the need for transportation, especially public transportation, has become very important. Since people use different types of transportation (metro, bus, taxi, bicycle, private ride, etc.) every day, it is Crucial to deal with it, especially from the aspect of sustainability among experts, considering the situation strategic transportation of region 5 has tried to emphasizing the economic and social importance that public transportation has for its consumers, it has been tried to address the importance of indicators and their ranking in order to easily achieve sustainability through SUTI-ANP-PROMETHEE methods. The results showed that the situation of the 5th region of Tehran municipality is weaker than the average from the point of view of sustainable urban transport criteria. In fact, according to the weightings and the scores obtained from this survey and the t-test at the 95% confidence level, it showed that the score of region 5 in both approaches is less than 2.5 out of 5. Therefore, based on the ranking made in the promethee method, among the investigated indicators, the improvement of greenhouse gas emission indicators caused by transportation and cycling and walking routes has been emphasized in the transportation development program of Tehran Municipality's 5th district and should be to be prioritized.

Online and offline shopping trips affect various aspects of urban life, such as e-commerce, transportation systems, and sustainability. To evaluate the factors that influence shoppers' choices, we propose a hybrid machine learning model that combines a gray wolf optimization algorithm and a deep convolutional neural network. We apply this model to estimate shopping trips based on a survey of 1000 active e-commerce users in districts 2 and 5 of Tehran, who made successful orders in both online and offline services in 2020. The gray wolf optimization algorithm performs feature selection and hyperparameters tuning for the deep convolutional neural network, which is a powerful deep learning model for image recognition and classification. Our model achieves an accuracy of 97.81% with an MSE of 0.325 by selecting seven out of ten features. The most important features are delivery cost, delivery time, product price, and car ownership. In addition, comparing the performance of the proposed method with other methods showed that the proposed algorithm with an accuracy of 97.81%, the accuracies of the single deep learning model, MLP neural network, decision tree, and KNN models were 95.63%, 90.12%, 86.49%, and 80.16%, respectively. This study offers valuable insights for transportation planners, e-commerce managers, and policymakers. It aims to help them design effective strategies to reduce transportation costs, lower pollutant emissions, alleviate urban traffic congestion, and enhance user satisfaction all while promoting sustainable development.

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 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.

Crash prediction models (CPMs) are a valuable tool in transportation planning studies that enable safety and its changes to be investigated in future decisions. The main goal of this study is to develop the CPMs based on the trip distribution step from the common four-step demand models, which is called the crash risk distribution in this study. In order to, the Negative Binomial formulation with a log-link function is used. The frequency of severe crash in the city of Qom, Iran, including the total number of fatal and injury crash among each origin-destination (OD) pair of traffic analysis zones (TAZs) as a dependent variable, and explanation variables, including the traffic-related and trip distribution results, have been used for model calibration. Traffic-related data include the vehicle kilometers traveled, experienced travel time with vehicle, and average vehicle speed between each OD pair of TAZs. The results of trip distribution include the trip distribution by purposes of work, education, shop, and personal. Model calibration and validation results show a significant relationship between the mentioned variables and the frequency of severe crashes. Hence, the developed model predicts the number of severe crashes in future years based on increased trips distributed among TAZs. Therefore, with the help of this model, it is possible to identify and prioritize trips with high-risk origin-destination in terms of safety, and the impact of different travel demand management scenarios on safety can be evaluated.

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 increasing growth of traffic on urban roads and the excessive attention to the design of cars on roads have reduced the role of pedestrians and cyclists and increased the number of accidents on local streets. Thus, traffic engineers and urban planners can take a long step toward improving the comfort and quality of life in neighborhoods and human-centered cities by developing and designing roads based on increasing the safety of pedestrians and cyclists. Traffic calming can be set as strategies that can be effective in achieving the above goals. In this study, one local area without traffic calming is selected, and then using the PTV Vissim Microsimulation model, we evaluate narrowing and traffic circle performance on it. Simulation results show us narrwong is better than traffic circle because of greater impact on deceleration, less emission and fuel consumption.

One of the most important elements in traffic engineering is the pedestrian, which has not received much attention. Walking has a prominent place in the urban transportation system because a significant portion of inner-city travel is done on foot. As a result, there is a need to identify the factors affecting pedestrian accidents and to analyze the accident statistics of recent years. A total of 350 questionnaires were distributed to employed pedestrians. In this study, the findings were analyzed using factor analysis and SPSS software. About 50% of The purpose of the trip  is for shopping, 25% for study and work, and another 25% for leisure activities. So shopping is one of the most important reasons to walk. The Pedestrian Behavior Questionnaire (PBQ) included 3 categories of questions, the first category was classified into four main factors, the second category into three factors and the last category into three factors. The first factor, Errors has a positive  correlation and significant relationship with the first factor (dysfunction)in the third category. The second factor in the first category questionnaire group, aggressive behavior, has a has a positive  correlation and significant relationship with all factors in the second category, In other words, lack of strategy and control, rejection of feelings, failure of goals leads to increased aggressive behaviors. The second factor in the first questionnaire, lapses, this behavior increases with sleep disturbance or inappropriate sleep, which has a high level of significance and reveals the importance of this issue. In positive behaviors, there is a positive correlation between proper sleep and the cause of positive behavior, and in violent behaviors, there is a negative correlation between the cause of sleep. This means that poor sleep has increased this factor.

Due to simplicity, economy, and the positive effects on traffic parameters and characteristics related to personal and social health, active travel modes can play an important role in intra-city movements. However, with the outbreak of the Covid-19 virus, people's travel mode choice behavior changed. In other words, some people have changed their travel modes due to concerns about being infected with the virus, which can lead to a change in their travel modes in the long term. As one of the most vulnerable groups in the Covid-19 virus epidemic, students, with a significant share of their travels in intra-city movements, should be given more attention. Therefore, it is necessary to examine how the behavior of students' active travel choices will change as a result of the Covid-19 virus epidemic. To do this, a sample of 267 boys and 546 girls was used based on a study-based questionnaire in Qom in 1399. The results of logit models (choosing and not choosing active travel modes) by gender (girl and boy) and time position (before and after the Covid-19 virus epidemic) showed that the parameter of the goodness of fit (McFadden) for all models is greater than 0.16 and less than 0.27. In other words, the independent variables in these models can significantly show the changes in the dependent variable. The results showed that the characteristics of the student household, the parents' travel mode on work trips, and the perception of the distance between home and school affect the utility of choosing active travel modes before the Covid-19 virus epidemic. Also, the perceptual variables of the student parents towards the Covid-19 virus epidemic were significant only in the model for boys. Moreover, having a large family is the only variable with a positive effect on the choice of active travel modes and increases the probability of choosing active travel modes by up to 20%. Also, having more than two passenger cars at home has the most negative effect on the dependent variable and reduces the probability of choosing active travel methods by 31%.

Today, pedestrian streets are important elements in urban space that can speed up the non-motorized movement. Development of pedestrian streets is one of the basic strategies to reduce the harmful environmental consequences of motor vehicles, increase the safety of pedestrians, and improve the urban environment. Recently, City of Qom has faced up many economic, social and environmental degradation problems that need to be rehabilitated and recreated. Regarding the issues, one of the ways to increase the presence of pedestrians in cities is to select pedestrian locations appropriately that optimize the routes between the trip origin-destination. In order to facilitate this importance, identifying and prioritizing the factors affecting the choice of pedestrian location based on trip purposes in the City of Qom is vital. Thus, the goal of this study is to promote walking using the factors influencing the location of pedestrian streets. In order to reach the goal, the present study firstly employs the transport and landuse data and information of the city of Qom as a cultural and religious center of the country based on the trip attraction data in 2018. Secondly, it identifies the relationship between factors affecting location of pedestrian streets using the structural equation modeling (SEM) based partial least squares (PLS) method. Therefore, the results of PLS method revealed that factors such car ownership, household, population, income, and area have a positive effect on pilgrimage, recreational, and shopping trips. Finally, variables such as car ownership and students have the most and the least effects on trips and the choice of pedestrian location, respectively.

 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.

The issue of transportation is one of the issues that has always been an integral part of the country's macro and strategic plans due to its connection with the country's macroeconomic and social infrastructure and the interaction between them. Examining and analyzing the opinions of those involved and stakeholders in the field of road transport for policy-making in this sector is the most important indicator of external road transport evaluation, which shows important issues such as evaluating delays and the impact of travel time on system utility. The study method is the design of a questionnaire, although part of it is apparently a pairwise comparison questionnaire (fuzzy AHP), but in the initial layer, the classification of variables of this questionnaire has been done with the help of rotating analysis included, which is a new method. In the first part, the inquiries from the passengers were made directly in the terminals of the west, east, south and Beyhaqi of Tehran due to the restrictions in four consecutive days and in the other twenty selected terminals with the help of local representatives. The system is optimized and improved with the help of suggested solutions. The most important results obtained from weighting are the indicators that have been considered for evaluation and pairwise comparisons; Dynamics of incentive policies (categories 1-0.27); System traffic performance (category 2-0.26); Safety (categories 2-0.39), welfare services (categories 1-0.21) and intelligent systems (categories 2-0.16). Therefore, from the results of weighting, it can be seen that the dynamics of incentive policies and policy types can with a high coefficient of micro and macro indicators to increase the share of public road transport and also focus the users' proposed solutions to increase the share of transportation. The general approach has been to policy-making, optimizing travel time, increasing the level of safety and quality of services that interact with the comparison method. Priority is given to the implementation of infrastructure projects in the field of public road transport, development of intra-terminal and in-terminal welfare services complexes, development and modernization of intelligent transport infrastructure, and acceleration of fleet modernization.

Safety consideration in transportation planning requires macro-level safety indicators. This is possible using various variables in macro-level safety studies. Using macro variables lead to easier and less costly accident predictive models. In this study, the predictive model of accident frequency obtained using macro level variables. Independent variables include, total length of the road network, the ratio of the length of roads network across functional classification (principal arterial, minor arterial, collector and local) to the length of all the roads, ratio of length of the bus lines to the total length of road network and density of the intersections in a Traffic Analysis Zone (TAZ). Accordingly, information of 16137 accidents in 96 TAZ collected. Then, the TAZs prioritized based on safety using Empirical Bayesian Method and TAZs with the highest Potential for Improvement (PI) found. Based on the results, increasing in length of the road network and the ratio of the length of road network across minor arterial in a TAZ, increases the chance of an accident occurred in that TAZ and a higher ratio of collector roads and local roads decreases the number of accidents in the TAZ. In this regard, the ratio of collector roads has the least and the ratio of local roads has the greatest impact.

Traffic accidents between two cars when overtaking on undivided rural roads are considered as one of the unpredictable events. They reduce road safety and cause severe head-to-head accidents or deviations. It can be overwhelming with appropriate suggestions and solutions to reduce the interaction between the two cars and decrease the number of drivers’ accidents and fatalities. This study tried to identify the effective factors, especially those associated with the natural behavior of drivers, in the overtaking process. In order to collect the required information, 6 undivided rural roads in the northern province of Iran (Mazandaran province) were selected as the study sites; thirty participants were considered for driving and their performance and behaviors were studied using three in-car cameras .Finally, by examining 34 factors in the driving behavior of participants from video X-ray and data extraction from camera films, 327 inter-vehicle interactions were recorded. By analyzing the recorded videos, the data for each variable were recorded as numeric codes in Excel software. After data collection, the dual logit model in SPSS software was used because of the bi-directionality of the target variable (Overtaking or not overtaking). Prior to data modeling, dependent variables were examined and the related variables were removed from the modeling process. Next, the data were modeled in three simultaneous, forward, and backward methods and by evaluating the models, the concurrent model was selected as the best model for the obtained data. Accuracy of 89% in this study showed that male gender, driving distance, and listening to music increased the chance of overtaking drivers. Also, distance to front vehicle, driver-talk time, vehicle speed, poor pavement surface, and lack of knowledge of safety in overtaking time reduced the likelihood of overtaking.

Damages caused by the rapid growth of personal vehicles in metropolises are unbearable and any increase in these vehicles will cause traffic jams, which is a major cause of delays at intersections. For this reason, the researcher has attempted to make suggestions to address this problem. The present research is applied in terms of its objective, the required data of which are collected using field studies. HCS software is used to calculate service level after extracting delay, volume, and capacity variables and importing these specifications and prescriptions. Afterwards, a brief comparison between intersections is performed. Findings show that there is a high volume and consequently delay at all intersections examined in Isfahan Hakim Nezami Street, indicating low service levels of these intersections. Therefore, it can be concluded that the increase in delay at city intersections results in a very poor performance of the transport system and the city passageways blockage. Synchronization of intersections is a very optimal way to get rid of this problem.

This research is conducted in order to develop transportation management methods based on limited resources to reduce social exclusion in rural areas, (Case Study: Ilam city). The research population consisted of all villages in Ilam city and also the chairmen of councils or village administrators and experts on the subject of rural transport research of which the 3 expert in the sector allocation of resources were used.. The research method is descriptive in nature, and survey in terms of applicable methods. Questionnaire was considered to be the data collection tool and to analyze the data, the descriptive statistics (mean, median, standard deviation) and inferential statistics (correlation, regression analysis, path analysis) were done using the software Excel and Lingo. The results show that with the development of credit obtained 65% assigned by assuming that spending rural transport, can only be used between 25 holistic village 12 statistical research village (model output) has been implemented and the rest will be postponed to future years.

Safety of urban highways is one of the most important issues in traffic management of big cities, which is typically influenced by several factors including implementing specific lanes and stations of public transit. This study evaluates the safety effects of implementing a Bus Rapid Transit (BRT) lane on frequency of crashes in urban highways. In this study, 14 treatment sites were selected for a before-after study and 40 reference sites in terms of geometric and traffic similarities were selected for development of Safety Performance Functions (SPFs). Crash data for three years before and three years after implementing the BRT lane were used to evaluate the effectiveness by the means of Empirical Bayesian (EB) method. Only mid-block crashes were involved in the analysis. The Crash Modification Factor (CMF) was estimated 0.87 at a 95% confidence interval that reduces the total number of crashes By 12.58%. The Empirical Bayesian (EB) method because of eliminating the Regression-To-Mean (RTM) effect can precisely estimate the number of crashes and effective factors in reducing them. The EB method estimated the expected frequency of crashes using both predicted and observed frequencies. The range of crash reduction varied between 1.25 to 65.6 percent.

The field and purpose:

The identification of the impact of various means of travel in the event of severe accidents can lead to improved trends of long-term urban transport planning. the present research is reviewed to study the relationship between different vehicles in the event of severe urban  accidents. The purpose of this research is to estimate severe accidents at the level of urban traffic areas in order to use it in trend of transport planning that have been neglected in previous studies. For this purpose, for the first time, from the share of different vehicles travel has been used as independent research variables.

severe accidents data as well as separate travel data related to 2008 in Mashhad city is used for performing research. Also, in this study, two generalized linear modeling methods with logarithmic transformation and negative binomial distribution, and weighted geographic  regression were used.

According to the results obtained from the generalized linear model with logarithmic transformation and negative binomial distribution, respectively, bus services, school services, motorcycles and personal vehicles have the greatest impact on the event of urban severe accidents in Mashhad. Also according to results obtained from weighted geographic regression model, respectively, bus services, pedestrians and personal cars have the greatest impact on the event of sever accident in Mashhad city.furthermore, according to both methods used, The presence of more taxis in traffic areas has reduced the number of sever accidents in those areas. Therefore, due to the relationship between the sever accidents rates and the share of different vehicles travel, using the method presented in this research and applying management policies can reduce the severe accidents.

Safety conscious transportation planning is a new strategy in proactive approaches towards crashes. This approach requires specialized tools at macro-level to account for the safety implications of transportation policies and plans at an aggregate level. The purpose of his paper is to develop Aggregate (macro) Crash Prediction Models (ACPMs) that are concurrent with the trip generationstep of the four step demand modeling technique. The concept of Crash Generation Model (CGM) is introduced based on trip frequencies generated by purpose in each urban Traffic Analysis Zone (TAZ) utilizing a logarithmic transformation in a generalized linear model with the assumptionof a negative binomial error structure. CGMs may be used for immediate checking of the impact of future trip generations on crash frequencies in comprehensive transportation planning studies (i.e. ability to forecast crashes at each time-step trips are being forecasted). They will help safety planners develop travel demand management scenarios and simultaneously assess their perceived impact on the overall safety of the urban areas. The models prove an effective step towards incorporating safety into long-range transportation planning. It is shown that there is a significant relation between crash frequencies and trip frequencies by purpose per TAZ.

Road users, including drivers and pedestrians, have an indispensable role in accidents. Traffic enforcement which explains the proper performance of uses, can change drivers behavior and improve traffic condition. Due to high traffic accidents in our country, it is necessary to use experiences of other countries in this field. Writers in this article review the effects of traffic enforcement on traffic safety in European countries. Studies shows that proper traffic enforcement can reduce the risk of accidents up to 10-50 percent.