Journal of Transportation Engineering
Year:2018 | Volume:10 | Issue:1 (38) |Papers Count:10

Urban transportation network is an essential component of our daily life in modern communities. This network is vulnerable to natural and humanitarian disasters. Its degradation may lead to large negative impacts on the economic efficiency of the community. Repair and maintenance of highway bridges، as the most critical component of the network، comprises a large portion of total annual maintenance costs، and usually due to lack of unlimited budget، this money has to be spent based on the importance and/or priority of the bridges in the network. The current study aims to prioritize the critical bridges during normal traffic conditions in an urban transportation network. The rank of each bridge is based the difference in the total network travel time before and after that given bridge is eliminated from the network. The bridge that by its elimination causes higher travel time is considered more critical. Proper functioning of bridges in the city of Isfahan، through which Zayande-Roud river passes، is quite important. This proposed method is applied to 78 bridges in Isfahan traffic network. Comparing the result of this method with the ranking of the highest traffic volume bridges demonstrates that critical bridges are not necessarily the ones with the highest volumes. In other words، the importance of a bridge or a link in the network is more dependent on the number of substitute detours، when that bridge/link is closed، than the traffic volume of that bridge/link.

Airports are an important national resource which play a critical role in transportation of people and freight in regional، national، and international level. Therefore، it is essential to use an efficient ground access system in order to employ the full capacity of an airport. This study investigates the ground access mode choice model to Hasheminezhad International Airport of Mashhad. The purpose of this study is to study the current conditions of airport access، the effective factors influencing the passengers’ access mode choice and the weight of each parameter. The required data were collected by departure passenger using questionnaires. The questionnaire used for the purpose of this study was developed according to the stated preference method and orthogonal design. It required the passengers to reveal their choice behavior on the 5 kind of transportation system used to access airport including: private car (parking)، private car (drop off)، taxi، subway، and bus. The survey was carried out in the form of face to face interview during 9 days in fall 2016. Overall، 596 passengers participated in this study that 533 questionnaires were used for modeling purpose. Finally، multinomial logit models were estimated to predict airport access mode choice. The results indicated that in the current situation، taxi and private car (drop off) were the main chosen transportation mode by passengers. Additionally، bus as only public transportation has a very minor role in the passengers’ choice (about 2 percent). The results of modeling revealed that the passengers’ choice was significantly influenced by factors such: travel cost، income more than 25 mRial، education level، Age group of 36 to 52 years، gender، place of residence، number of luggage، and the crowd level of public transportation.

Evacuating people to the safe zones is the most crucial operation in many disasters. We have presented mathematical models in this paper، to combine the locational decisions with the max-flow problem in order to select the safe destination that maximizes the number of dispatched people، both for the static and dynamic cases. Existing frameworks for emergency logistics، address the evacuation process based on fixed and pre-determined destinations usually with a strategic perspective. The unpredictable and turbulent nature of a disaster may، however، disrupt the predictions. Furthermore، the primary goal in emergency situations is to dispatch people from the danger zone to a safe place، no matter where. A non-linear integer programming model is developed in this paper for selecting one destination in a capacitated network. We have also formulated the robust counterpart of the dynamic model in order to contribute the uncertainty of the capacity of routes during a disaster. The special structure of the model and its similarity to the max-flow problem let us develop exact algorithms and heuristics for the single destination location problem. The solution methods are based on combining a branch and bound approach with the existing algorithms for the max-flow problem. Our proposed heuristics use the idea of adding a super-sink to the network to generate upper bounds very fast. The exact algorithms as well as the heuristics are tested on randomly generated instances as well as a real world network. The mean and variance of their computation times are reported. They are compared according to their performance (gap to optimality) and their behavior amongst different categories of the graphs. We have also used the real data for Mitte-center berlin to implement our algorithms for an existing data set. The results of the algorithms for this case are also reported in the results section.

Energy plays an important role in production and service systems. Among energies، in today’ s world، natural gas has become as one of the effective ones. The optimal relation between different echelons of chains and goods transfers is among important challenges of supply chains. Maritime transportation and cargo ships routing is one of the common methods for freight transportation in fossil fuels supply chain such as gas. In this regard، a mathematical model is presented for a three-echelon supply chain consisting of origin and destination of intermediate tankers. In order to design the optimum routes in a LNG supply chain، a transportation system is considered with intermediate tankers Also، in this model the optimal values of transported gases to tankers and destinations are determined so as to minimize storage cost while satisfying demands. Since the proposed model is NP-hard، Simulated Annealing and Differential Evolution algorithms are employed to solve the model. To demonstrate the efficiency of the proposed algorithms، the results are compared with the results of GAMS software for small-size problems. Then، the two meta-heuristics are compared for large-sized problems. The results show that DE obtains better solution in reasonable times.

The aim of this paper is to propose a model to forecast human and cargo air transport demand in Iran aviation industry. Using multiple regression method، the effects of geographical، economic، social، and competitive aspects were investigated within two separate models for passengers and cargo. Accordingly، we gathered data for 594 active air routes in Iran air network between 2009 and 2012 from Iranian airport holding company. One advantage of the proposed model in comparison to pervious researches is the exclusion of frequency of flight variable. This variable restricts the ability of forecasting the models due to its high correlation with demand for travel. Therefore، models that include with frequency of flight variable are not efficient for forecasting demand. Additionally، the comparison of forecasting results and real demand for 2013 indicates the accuracy of forecasting model. Moreover، the results show that because of plenty of differences and erratic distribution between effective variables around the country، modeling should be specific to each city. This means that a general model for all cities is not appropriate and leads to an inaccurate forecasting، so we investigated separated models for metropolises of Iran to consider special situation of them. Also، defining dummy (Binary) variables in modeling of special cities helps to increase fitting of model to real observations. We can incorporate special situation of some cities into model by means of these variables. Therefore، one of the methods to conquest the inconsistency between cities of Iran is applying dummy variables to simulate conditions of special cities.

Modeling and simulation are widely used in the transportation network. In fact، by using this technique، a pre-built system will be analyzed after and before launching. Petri nets are useful tools for modeling and analyzing complex networks such as railway network. In this paper، using colored petri net concept، the main elements of a railway track and signals is modeled including turn out، track segment، end segment، junction and etc. In this model، the place is intended as block similar to railway and to show that block is busy by train، it is used the arc to each place. The supervisory control is designed to supervise train input and output to yards and stations، safety and non-blocking requirements in such a way that not only proposed railway network is not blocked but also safety is guaranteed. In this regards، some arcs is intended whose conditions have the role of supervisory control and also Normal and Express trains are considered in railway network as color token in petri net model. It is analyzes the petri net model by CPN Tools to satisfy logical (safety and non-blocking) and operational requirements of network. So Availability Tree is provided by state space graphs results to verify non-blocking in train operations and satisfying safety requirements. Then Best Integer Bounds Analysis is provided to verify safety operation requirements in signaling railway blocks. Finally The Best Upper Multi set Bounds Analysis in CPN Tools is implemented to verify the maximum number of Token(Train) detection in each place (block) in order to verify that the express train is never guided to waysides.

The United Nations Generel Assembly introduced the decade 2011 to 2020 as a decade of reducing the traffic fatalities. This organization، in different resolutions، has urged all the countries to pay their especial attention to reduce the road accidents. The speed factor plays a key role in reducing the risk of the road accident; and one of the deterrence factors for unauthorized speed of cars is the traffic enforcement camera of the traffic police NAJA. In recent years a major increase in use of such devices for reducing violocations and accidents in suburban and urban highways is observed. The aim of this study is to analyse the effectiveness of traffic enforcement cameras of the taraffic police in the Tehran-Karaj highway. This is performed using data mining techniques such as modeling with through time series and regression. First، using descriptive analysis، we study the process of violations along with the number of active cameras in the highway. In the inferential analysis step، we analyse the violations by modeling time series and non-liner power regression. In applying assessment data، the models fitted by time series had less prediction errors then their equivalent regression models. In the prediction of year 1393، the violation rate has reduced by 32% in Tehran-Karaj highway، compared to the violations in the same period of 1392. This observation along with other analysis results shows the effectiveness of cameras in the period of study. The results of analysis and mining of traffic enforcement camera data can be used in improving urban management and planning with the goal of reducing violations and accident.

Air pollution and energy shortage as serious crises، made researchers and industrialists trying to find suitable solutions with the aim of energy management. Electric transportation loads ( especially، electric vehicles and urban metro systems )، are considered as the major consumers of energy for the electric network. Since the mentioned vehicles، have time overlap with the peak demand of main electric network at the peak time consumption، the feeding procedure has negative impacts on the upstream grid. One of the best solutions is reusing the huge regenerative energy of braking trains. The regenerative energy could be taken to consideration as a distributed generation in electric transportation system as well as the distributed generations of power systems like solar energy resources. Therefore، in this paper an integrated configuration comprised of the urban metro system، charging station for electric vehicles، photovoltaic panels، and energy storage as an interface for energy exchange is introduced to alleviate the problems. The priorities of power consuming، supplying، charging or discharging are defined by a smart energy management system. This system imposes the economic and technical constraints to power flows. By considering this method the profitable consequences are imminent. Supplying the loads by the smart configuration leads to energy management and consequently the reduction of the operation and infrastructure expenses and decreasing the negative impacts on the upstream network by optimizing the model of energy consumption from economic and technical points of view.

OOne of the reasons of drivers' disinterest towards changing travel mode is that driving is a habit for them. The importance of the fact reveals more when transportation demand management (TDM) policies are implemented to reduce car-use. As in most efforts the aimed reduction in car-share won't achieved، researchers believe that the better we understand the factors affecting the mode choice behavior، the better we could estimate travel demand management policies' outcome. This paper pays attention to two groups of commuter drivers to the central business district (CBD) of Tehran، one with strong driving habit (who drive to work/school daily) and the other who just drive some of the week days to work/school. Using binary logit models، it shows that mode choice behavior of people with driving habit is different from others with no strong habit، when both groups face a TDM policy package. It also uses the results to suggest some relevant policies to increase mode shift from car for each of the two groups separately. Models show that commuters with driving habit do not change their mode in response to transit service improvement strategies، while others with no strong driving habit do so. According to the literature a defect in driving habit may cause commuters to think of other modes، so the present research suggests to eliminate the yearly pass to CBD to make such a crack in driving habit of the owners of the pass and make them to think over using other modes rather than driving daily.

The main purpose of this research is providing a model to use technological innovation capabilities in social and economic dimentions of sustainable transport. Today، sustainable development cannot be achieved without sustainable transport. Advances in technology have also played an important role in accelerating the pace of innovation. Technological innovation increases the amount of money that can be obtained from a given amount of labor and capital. Many research shows that a combination of strategies is needed to achieve sustainability goals. This is an applied research in terms of research method and descriptive-survey. In the context of sustainable transport، focusing on environmental issues and degrading them through the use of machines، reducing natural resources and overuse of oil derivatives are importatnt. The statistical population of the study، including managers، assistants and experts in the field of transportation from active companies in Iranian Transportation system، in the spring of 2017، was 43 companies and includes 145 personnel. Analysis was carried out based on data collected from 108 targeted personnel based on the Cochran formula with relative stratified sampling from the target population. The required information was collected using a questionnaire; analyzed by Statistical softwares. The research findings show that social factors are more related to the concepts of social learning، organizing and learning organizations in addition; economic factors are more related to improvement of the marketing process، optimal resource allocation and production process.