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In Iran, oil products are the most valuable export, 30% of which (Crude Oil) is used domestically every year. Countries like Iran depend heavily on oil revenues. One of the main sectors for consumption of crude oil in Iran is the transportation Industry. This paper aims to measure and estimate fuel productivity in land transportation in Iran using available data from 1973-2003. The function of fuel productivity is estimated using time series analysis, and the co-integration with stationary variables have been accounted and analyzed. At this stage, initially the co-integration variables of the model are known, and then, the structure of the model and the number of optimal orders are identified. The next step however, determines the number of co-integration vectors of the model which eventually with some restrictions estimate the fuel productivity function within the land transportation sectors e.g. rail and road.

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Abstract: Car-Following models are integral parts of capacity analysis, safety research, traffic simulation, and developing advanced vehicle control systems. During the past six decades, various car following models have been developed. GHR is the most well-known stimulus based model, in which the stimulus is the relative velocity of vehicles. In this research, timeto- collision (TTC), as the stimulus, is proposed as a substitute for relative velocity in the GHR model. GHR model is calibrated based on the comprehensive and detailed data gathered in the NGSIM project on I-80 freeway. The Results of GHR model calibration based on the data obtained for the two stimuli indicated that coefficient of determination (R2) increased from 0.233 in the base model to 0.638 in the proposed model. In all, the results indicated that the application of TTC as the stimulus in the GHR model would improve the model's outcome.

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Air transportation has an important position among the other modes of transportation due to its significant impact in the economy and welfare of a society. Within the several components of air transportation market, flight network plays a fundamental role and considerably affects the airlines revenue. Improvement of the network system requires an accurate plan and programming. Hub-and-spokes are of further interest; as such networks reduce the operational costs, create proper ground for flight network development and extension, and help in competition. However, several models have been introduced for hub-and-spokes design purposes based on the diversity of the effective factors, decision-making variables and different forms of the network. Generally speaking, hub-and-spokes are categorized into two principal sectors: single allocation and dual or multiple allocations. Within a single allocation, traffic is accumulated in a single hub and then distributed to the destinations, while within a dual-allocation network, the gathered traffic at the first hub is again distributed to another hub before directing it to the final destination. This research presents a linear model for hub-and-spokes evaluation and planning, determining optimum flight routes and fleet assignment. The model considers both direct flights and hub connections, and outputs an optimum network based on the mixture of these two options. Sets of airport connections are so designed to well cover all the necessary inter-airport trips. This particular is done by utilizing hub-and-spoke system as the airport networks. To fulfill the requirements of the study location (Iran), in this paper, single allocation was selected to develop the models, meaning that just one hub has been considered in the modeling process. Inter-airport demands of the passengers were inputted in the network and the model works only for passenger transportation. The objective was to design the hubs so as to obtain an optimum network. In other words, the model is to suggest the best option with which the demand is handled cost-effectively. Trips are planned to be either direct or meeting a one-hub maximum. As the model is to minimize the cost, such variables as demand for variety of routes and type and quantity of the available aircrafts were included. The model was developed in two stages to ease the process. The first stage dealt with the target function and the fleet was assigned to the Abstracts 136 outputs of the stage one. Iran's internal flight network was chosen as the case of study to develop the model based on the country's geographical situation and available data. 59 airports were chosen as the total set of airports and trip origins. The number of hub candidates and destination airports were eight including Isfahan, Ahwaz, Bandar Abbas, Tabriz, Tehran, Shiraz, Kerman and Mashhad airports. Based on the availability, the data of five types of aircrafts were used in the model development. Lingo Version 8 has run the model using branchand- bound method to obtain accurate and reliable outputs. Up to eight hub networks were considered by the model and the model confirmed that with increase in the number of hubs, operational cost decreased. However, cost reduction had lower rate for the systems with six hubs and over. The results also suggested that the probability of stop in a hub rises for longer trips. Flights longer than 1.5 hours had to stop at one hub in three-, four-, five-, six- and eighthub networks. Four-hub network was found to be the optimum one due to having the shortest stop slot where fixed cost has been allocated for selecting an airport as the hub. The hubs of the optimum fourhub network are Tehran, Shiraz, Kerman and Isfahan airports. The results showed that demand is not the only effective factor in the selection of the hub; it means that another key factor, geographical positions, has effect and the airport with higher demand is not necessarily selected as the hub. Therefore, hub-and-spokes can enhance the efficiency of the airports with lower demands. As an example out of the results, passengers intended to use Isfahan and Kerman airport as their hubs in a four-hub network were more than the ones targeting Isfahan and Kerman airports as destinations. Analysis of the four-hub network cleared that, according to the current demand and operational costs of different aircrafts, large planes (e.g. Airbus 300) and small lpanes (e.g. Foker 50) will perform more flights in comparison the with other types. Using the model developed in this research, airlines will be able to forecast and plan their required fleet combination based on the demands.

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In most cases, the place of producing and using hazardous materials is not the same and such materials should be transported from the production line to the consumption place. Because of the dangerous nature of such materials, safety indicators and criteria should be considered. More than 90% of hazardous materials transportation in Iran is by road. This shows the importance of attention to the safety factors. Although transportation departments or local governments are responsible for allocating acceptable paths that reduce risk, transportation companies usually look for some paths with lower travel times and fuel consumption. So many methods have been presented for designing the paths of hazardous materials transportation based on the trade -off between costs and risks of the transportation. Almost in all of them the national hazardous materials transport routing has been a decision for the matter in two levels, the government allocates a subset of the transport network to hazardous materials and the transportation corporations, choose their paths from this subset. However, the issue of justice in the distribution of risk is highly regarded in the states because feeling Injustice in received level of risk, might lead to public opposition to the routing of hazardous materials. Therefore in this research some routing models have been proposed. In the first mathematical model, we just consider the safety of paths and two major goals would be pursued. First we seek ways of minimizing risk in the whole studied path networks, and then this matter would be considered that the risk does not increase in each link more than certain amount, and in fact justice in the distribution of risk be established. This model was bi-level linear and transformed into a single-level mixed integer linear program by replacing the second level by its Karush–Kuhn–Tucker conditions and by linearizing the complementary constraints. Then we solve the MIP problem with a commercial optimization solver In the second model, in addition to the safety, the economic efficiency of the routes is considered. In fact, in this model, the results of the safety model will be used in a mathematical model with economic-safety approach. The real case study then has been used to evaluate mathematical In most cases, the place of producing and using hazardous materials is not the same and such materials should be transported from the production line to the consumption place. Because of the dangerous nature of such materials, safety indicators and criteria should be considered. More than 90% of hazardous materials transportation in Iran is by road. This shows the importance of attention to the safety factors. Although transportation departments or local governments are responsible for allocating acceptable paths that reduce risk, transportation companies usually look for some paths with lower travel times and fuel consumption. So many methods have been presented for designing the paths of hazardous materials transportation based on the trade -off between costs and risks of the transportation. Almost in all of them the national hazardous materials transport routing has been a decision for the matter in two levels, the government allocates a subset of the transport network to hazardous materials and the transportation corporations, choose their paths from this subset. However, the issue of justice in the distribution of risk is highly regarded in the states because feeling Injustice in received level of risk, might lead to public opposition to the routing of hazardous materials. Therefore in this research some routing models have been proposed. In the first mathematical model, we just consider the safety of paths and two major goals would be pursued. First we seek ways of minimizing risk in the whole studied path networks, and then this matter would be considered that the risk does not increase in each link more than certain amount, and in fact justice in the distribution of risk be established. This model was bi-level linear and transformed into a single-level mixed integer linear program by replacing the second level by its Karush–Kuhn–Tucker conditions and by linearizing the complementary constraints. Then we solve the MIP problem with a commercial optimization solver In the second model, in addition to the safety, the economic efficiency of the routes is considered. In fact, in this model, the results of the safety model will be used in a mathematical model with economic-safety approach. The real case study then has been used to evaluate mathematical

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Falling avalanche is one of incidents that may happen during cold months of winter in Iran. This event may lead to closure of some main roads of the country. Road closure is a challenging issue, particularly on roads connecting Tehran capital to the northern cities. Detecting avalanche prone locations on roads is usually conducted by data gathering, surveying and investigating aerial photos. Field investigation usually requires collecting regional data including slope stability, geology and number and repetition of road traffic. In this study importance of each parameter was determined By an AHP method. After interviewing experts, importance of each parameter was determined pair wise. Final weights for each parameter were also determined using Expert Choice software. Searching for important contributing parameters and methods for measuring risk of avalanche in mountainous roads in the literature, main parameters of falling avalanche were selected and used in this study. It is obvious that many of recognized parameters should be considered in every effort of measuring danger. That is why such parameters are similarly used in most methods. The most important reference for categorizing the methods of risk measuring was guidelines on preventing falling stones and avalanche published by US National Institute of Highways and the Main Office of Highways. In these guidelines, traffic  repetition is taken as an important factor increasing the risk after a falling event happens. This study framed the experts’ opinions and optimized risk analysis with regards to local geotechnical and geologic conditions in Iran. Experts selected the snow depth, hillside slope, vegetation condition on hillside and number and repetition of the road traffic. Importance of parameters were calculated as 44.1% for traffic number and repetition, 19.1% for the hillside slope, 17.2% for vegetation, 15.6% for snow depth and 4% for traffic rate. These parameters were selected as the factors contributing in avalanche. In continue each parameter was rated in a four level category (very high, high, medium and low). Model of avalanche danger calculates the avalanche risk in every point in a road network and all roads can be evaluated in terms of the danger of potential avalanche. For example the model was applied on Karaj-Chalus highway connecting Alborz to Mazandaran provinces. This highway is an important arterial between the capital and the northern cities. Using the method, 15 dangerous avalanche prone locations were determined and prioritized. They are located at 65, 73 and 60 km from Karaj. Preventive efforts should be taken for maintaining these locations and keeping them safe against potential avalanches

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Capacity of a road facility as an important characteristic in transportation and traffic studies is defined as the maximum rate of flow that could be held by that facility, which has been supposed to have a constant and certain value. This assumption, although necessary for most traffic studies, has also caused some problems, like that of demand exceeding capacity in many road facilities. Researchers have recently shown that capacity is not necessarily the maximum flow rate held by a facility. They have also demonstrated that capacity has a stochastic nature rather than a constant and deterministic value. Stochastic approach to capacity is more complicated and comprehensive. In this approach, capacity is treated as a random variable generated from a population, and having corresponding distribution function. Knowing more about breakdown phenomenon, as transition from acceptable to unacceptable flow, plays a key role in this approach. To obtain breakdown flow rates, threshold speed as the quantitative measure is used to distinguish congested and non-congested flow rates. Flow rates occurring immediately before decrease of average speed below the threshold speed, are regarded as breakdown flow rates and their value in addition to non-congested flow rates are used to estimate the distribution function. Product Limit Method with analogy to life time data is used to estimate non-parametric function. The main advantage of this method is that it considers censoring data. In capacity estimation, if a time interval is followed by a breakdown, it will be regarded as uncensored interval; if it is non-congested it will be regarded as censored interval, meaning that capacity of the road is bigger than incoming demand. If it is located in a congested area, it would not be used in the estimation process. Two common parametric estimation methods are (OLS) ordinary least squares and (MLE) maximum likelihood estimation. Since binary data is used to estimate capacity distribution function, the ordinary least squares method is not useful with such data. Maximum likelihood estimation with a presumption about the type of distribution is used to estimate the parameters. Distribution function with the maximum log-likelihood value would be the function that has most likely produced the sample, and is known as the capacity of the freeway. In this paper, both non-parametric and parametric capacity distribution functions of Tehran-Karaj freeway as the oldest and the busiest freeway in Iran, serving and average of 100,000 passenger cars a day, are estimated. Threshold speed is found to be respectively 70 km/h and 75 km/h in two sections under investigation located in the direction to Karaj. Based on the data gathered for four months by traffic cameras; and refining to meet standard criteria, a sample of 229 and 169 breakdowns were detected at each section. Different distribution functions are fitted to the data, and with trial about different kinds of functions, Gumbel distribution is found to be the best distribution fitting the observed data.

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  Freeways have a particular role in urban transportation networks due to their high capacity compared to other facilities of lower hierarchical classification. Although these facilities do not have any at-grade junctions and are of the highest mobility and least access classification, their flow control can help general urban traffic condition. Traffic control strategies are thus of particular importance to urban transportation. Ramp metering of urban freeways and highways is one of the efficient traffic control policies that can alleviate traffic congestion by restricting on-ramp flows to the main stream. A main challenge of this policy is the determination of optimal flow rates of the on-ramps leading to optimal flow rate of the main stream. In this paper, a linear programming model is developed considering the capacity constraint of the main stream and the constraints of queue length of ramps. Although the queue length of the on-ramps increase due to the ramp metering strategy by holding up vehicles on these ramps, the travel time of the main stream as the main body of traffic whose traffic condition is of higher importance, decreases due to the increase in the speed of this stream caused by the drop in vehicle density. The main objective of this paper is the implementation of a mathematical programming model developed for a rather congested case study in Tehran; and the analysis of its challenges and impacts. This model takes into account the maximization of flow in the transportation network while flow conservation and capacity constraints are not violated. In the field survey, flow rate data of about 15000 vehicles west-bound of Shahid Hemmat highway segment from Modares freeway to Shahid Chamran off-ramp were gathered for three hours. This segment includes five on-ramps and four off-ramps whose flow rate data along with that of the main stream was collected on a Tuesday in summer 2011. The data was collected through video recording and then obtaining the necessary variables like flow rate data by re-watching the films carefully and counting the vehicles. Although very time and budget consuming, but this survey method made possible the data collection phase to be valid and reliable. Flow rates for 5 minute time intervals for all the ramps and the main stream were obtained to comprise part of the research data base. Capacity, as a model parameter, was predicted for the segment under study. Results of the mathematical programming optimization model indicate that level of service of the segment under study increases from F to E and that the speed in the main stream increases between 18 and 24 kilometers per hour and that travel time in this segment has a decrease of nine minutes. Results of the optimization model indicate that freeway traffic performance can be optimized by careful management of on-ramp monitoring and control realized through ramp metering strategy, emphasizing quantitatively and scientifically the importance and necessity of detailed traffic data and its analysis for the betterment of traffic conditions through merely management techniques which do not require much time or budget to use the existing facilities more efficiently. .

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In this article has been tried to find a new solution for fleet assignment to BRT network through scheduling assigned fleet to routes. Vehicle scheduling in each route is done with regard to passenger waiting time at stations and in consequence assigned vehicle dispatching model is related to the first station at each route. In designing the model, it has been tried to develop it in a way that it can be extended and be useful on a worldwide scale. The proposed model for Tehran BRT network has been developed by lingo software with data acquired from the Tehran municipality transportation department and the results analyzed. One of the important finding in this research is that a necessity of using buses with high capacity in BRT systems.

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The destination choice problem is an essential element in transportation planning processes. The problem is to find the probability that a person traveling from a given origin will choose a destination among many available alternatives. The focus of this paper is the destination choice of non-work (shopping purpose) trips, as part of the transportation planning process, in particular in trip- based and activity- based models. In general, destination choice models are estimated and applied at the traffic zone level, although the actual destination is an elemental alternative inside a traffic zone. Therefore, the number of explicitly modeled choice alternatives is usually the number of traffic zones. Most destination choice models assume a Multinomial Logit (MNL) form for the problem. The Multinomial Logit is not capable of accounting for unobserved similarities among alternatives, since the covariance matrix of the MNL model has only elements in the diagonal. The purpose of this paper is to investigate alternative destination choice model structures, focusing on structure equation models. The non-work destination choice problem is studied in spatial choice modeling. The literature concerned with spatial choice models covers several disciplines and important insights can be found in spatial behavior and spatial interaction models. Trip distribution models are expressed indirectly in terms of behavior models and this issue in trip generation and trip distribution is bolder. Considering new approach to transport planning (activity- based) and modeling behavior of passengers, the activity location choice is more attended and usually discrete choice models are used. Many studies describe zonal utility (simple decision structure) by using land- use and socioeconomic variables and thus cannot describe individual behavior in disaggregate level. For describe more accurate of individual utility, recent studies, have used simultaneous choice process concept and in other hand few studies used structural equation models and latent variables in describe choice of activity location. Investigating of individual features in activity location choice by using of structure equation models considered in recent studies. Considering the importance of determining activity location in activity- based approach, use of exogenous and explainer variables are bolded. Variable in classic destination choice models firstly are supposed independently and secondly have less attention to psychological and personal feature of passengers. Considering these two points, the power and efficiency of representation of behavior are reduced. Studies on the consumer behavior in shopping centers, showed that in addition to observable demographic and socio-economic variables, latent individual variables like to psychological variable, Attitude lifestyle and shopping orientation are important and must be attendant (complex decision structure).the idea of applying these variables in modeling the individual clothes shopping destination choice by using structure equation models was sourced from ethology studies on customers of shopping centers (novelty of paper). In this paper 213 sample are collected by internet- based questionnaire and individuals socio- economic, attitude, lifestyle and shopping orientation were asked. This integrated model is able to correctly predict the 42 percent of observation in which destination number 1 (Bazar of Tehran and Plasko shopping center) has the highest percent correct.