JOURNAL OF TRANSPORTATION RESEARCH
Year:2011 | Volume:8 | Issue:3 (28)|Papers Count:7

Highway construction projects are conducted in an outdoor environment, and are therefore sensitive to various weather conditions, especially rainfall. Rainfall is regarded as a major risk factor, which often leads to partial or complete suspension of construction project operations. In this paper, a decision support system is developed for quantifying the impact of rainfall and temperature on highway construction schedules. The system incorporates a database that uses historical daily rainfall and temperature data alongside a knowledgebase that includes a fuzzy inference system, employing fuzzy rules acquired from experts in highway construction. As the monthly delays are random variables, probability theory is also applied for frequency analysis. This system can be useful in preparing realistic schedules for the preconstruction stage and in analyzing weather-related claims for the post construction stage. It can also be used in predicting the impact of short term weather forecasts in the real- time construction process. To demonstrate the usefulness of the system, it has been applied to the cities of Tehran and Gorgan in Iran, which have very different climates, and the results are compared and discussed. The results show how the differences in climate of these cities and the time and stage of construction are reflected in predicted construction delays.

In this research study, an Autoregressive Distributed Lag (ARDL) cointegration framework is applied over the time period of 1972-2009 in order to examine the short run and long run characteristics of gasoline demand in the transport sector in Tehran. The results indicate that the amount of gasoline consumed per car, per capita income and real price of gasoline are integrated of order 1. The ARDL bounds test also confirms that these variables are cointegrated. The long run income and price elasticity of gasoline demand are estimated to be 1.28 and -0.11 respectively. The short run income elasticity is estimated to be 0.78 based on an ARDL error correction model, while the short run price elasticity is found to be -0.11. The adjustment parameter is 0.61, which implies that a demand adjustment of around 0.61 takes place in any year. This means that around 95% of the demand adjustment occurs after three periods. It is hoped that these results will assist in prediction of transport fuel requirements and fluctuations, which is vital in an age where fossil fuel supply and demand must be carefully managed.

The purpose of this paper is to use an analytical method to generate fragility curves for a highway bridge in Tehran. The methodology adopted uses 3-D finite element models, nonlinear static and nonlinear time-history analyses. Due to the specific characteristics that near-fault ground motions possess and also phenomena such as forward directivity, the effects of such ground motions on highway bridges are compared to far-fault earthquakes using fragility curves in this research study. Because of the geometry and the skew of the bridge used in this study, it was subjected to a suite of strong ground motions in various directions to obtain a precise analysis. It was observed that the fragility curves are sensitive to the input angle, which is specifically the case for higher PGA levels. In addition, the fragility curves that were developed using near-fault records with forward directivity showed a higher probability of exceeding a specific damage state compared to far-fault records. It is suggested that the findings of this study would be used for analysis and risk assessment with regards to highway bridges in earthquakeprone regions.

The main goal of this research is to study, compare and evaluate the configuration of left-turns in highway intersections with the AHP method. To this end, the authors have used some case studies, for example the Imam Ali and Shahid Zeinoddin two-level crossing in order to investigate the technical and economic parameters to determine the optimum configuration of loop (clover) and direction, according to the most important criteria. Available space at the intersection, performance and topographical conditions of the region, comparative prices, constructions costs related to the intersection sand traffic volume passing through are indicated according to the principles of intersection design to determine the design speed, which is the most appropriate geometric design of intersections considering the various factors. After this stage, other parameters including economic conditions, space limitations, architectures and urbanism criteria are discussed. In the next section, with regards to providing the optimal left-turn configuration in a sample intersection project, the AHP (Analytic Hierarchy Process) method is introduced. Finally by using the Expert Choice software, all the information gathered and entered as input to the comparison process and superior to the various other options with regards to left-turn configurations will be measured with the AHP method.

Undoubtedly, the transportation sector is one of the key economic industries that have extensive previous and subsequent effects on other economic sectors. On the other hand, the activities of this sector are heavily dependent on oil products and their related industries. Due to this, the price of oil products affects the basic variables in the transport sector, one of which is employment. In this research study, the authors are going to investigate this vital issue and report on the effect that oil price increases have on employment in the transportation sector. This will be achieved by using the Auto Regressive Distributed Lag Method (ARDL). The results of this paper suggest that there is a long-term relationship between employment and oil prices. During this research study, the effect of energy prices on the employment in the transportation sector was also investigated by using the Vector Auto Regressive model (VAR). The results of this indicate that the effect of energy prices on employment determined by the ARDL method is validated. These results are vital in understanding the interdependency of factors in the transportation and oil industries, especially with regards to employment.

Transportation networks that are subject to daily hazards, such as traffic accidents, a rainfall, as well as damage related to natural disasters, such as floods and earthquakes, are therefore considered vulnerable. Different parameters, for example network capacity and shape alongside the vulnerability of network components, affect the network stability. Among these parameters, a form of network that can be stable for a large number of conditions is of particular interest. In this article, the effect of different indices on network topology will be studied and using genetic algorithms, a method for solving the problem of network topology design based on travel time, efficiency and stability indices will be introduced. For the purpose of network development, the effect of various network performance indices on the design of a network will be examined, and finally the results from using these indices alongside travel time index in the design of network will be compared. The findings show that network design based on travel time index is unable to yield a reliable network for traffic incidents in the long term, and network design based on reliability and travel time index yield a different network.

Applying an appropriate process for using the history of previous interactions with contractors in future relations with it has an important role in an organization’s success with regards to its outsourcing process. The present mechanism for contractor evaluation and selection is only based on inviting companies with some needed specification to the tender and then only focusing on their bid price, which causes many difficulties for organizations. However, if it is possible to take into account their past performance evaluations as one of the effective decision factors to invite contractors into future limited tenders, many of those problems will be resolved. Contractor evaluation is a Multiple Attribute Decision Making (MADM) problem, which uses numerous and complex criteria. In many cases, sub-criteria, which form main criteria, have dependencies and interrelations to each other. This makes it difficult to use conventional MADM methods, which are built based on primary assumption of criteria independence, in such a case. The purpose of this research is to rank contractors based on previous performance while considering the dependency between criteria. This study uses a hybrid fuzzy integral technique for modeling this problem and allows solving it within the situation of interrelated criterions. Here, the group analytical hierarchy process (AHP) technique is used to determine the weight of each criterion, Interpretive Structural Modeling (ISM) is employed to map out internal relationships among the sub criteria, and fuzzy integrals are used to obtain the fuzzy synthetic performance of sub criteria to form each main criterion. The results obtained from comparing this model with the conventional AHP method, both with and without considering interrelations among sub criteria have shown. There is a modification and rearrangement in ranking the contractors based on the proposed approach.