فصلنامه مهندسی حمل و نقل
سال دوم شماره 2 (پیاپی 6، زمستان 1389)

From safety point of view, railroad- highway grade crossings are critical points in rail transportation system and are sites with specific characteristics in the elements of road transportation systems such as bridges and tunnels. Although, accident frequency in crossings is low in comparison with the accident frequency in roads, studies demonstrate that it is still very high compared to the low number of crossings and relatively high standard of railway safety. Identification of high risky grade crossings is a basic method to reduce harmful accident impacts and optimize resource allocation and quick improvement. Employing statistical models is a solution for identifying black spot crossings which are developed, based on the relationships between accidents and geometric design, control devices and traffic attributes. Despite developing such models for other road spots such as bridges and road intersections, no frequency prediction model for railway- highway grade crossings in Iran has been generated so far. The present study tries to develop a frequency prediction model using geometric and traffic grade crossing characteristics and the occurred accidents in the years 2002 to 2006. Average daily vehicle traffic, average daily train traffic, availability of gates, crossing location (rural or urban), train speed and highway pavements are significant and are introduced in Poisson model. Considering the estimated coefficient for each factor and expected changes in future, a new outlook of safety situation of grade crossings can be imagined. Use of this method is suggested for prioritization of grade crossing securing, prediction of future crossing situation with change of characteristics, resource allocation, etc. in Iran railway system.

In scientific research works, time domain and frequency domain methods have been widely used to detect damage and its location. By making attention to the capabilities of square time frequency representations in this study a new algorithm based on the representations was suggested for the first time to identify system and detect seismic damage in bridge piers. To evaluate the proposed algorithm, the analytical model of PEER-W180 Bridge was used. According to the method, before an earthquake event, some sensors were installed on top of the piers and vibrated the bridge by exciting force and recorded the bridge response signals. After the earthquake event which caused damages in the bridge piers, structural response signals of the piers were then recorded. Therefore the signals were processed using Reduced Interference Distribution, which is a time frequency representation, and dynamic characteristics were extracted. Then, by using the suggested threedimensional tensor method, the damage and its location were detected. The results show the ability of the proposed algorithm for system identification and seismic damage detection in bridge pier. The algorithm is an output-only method. Furthermore, there is no need to create and update an analytical model of an existing bridge. According to the results, the damaged pier was detected correctly using the proposed algorithm. In addition, maximum error in the probability of damage in the piers was calculated equal to % 6.1. Therefore, the results indicate the ability of the algorithm in detection the damage and its location.

Importance of transportation in development of countries and emphasis on productivity in the five-year development plans, are the most important reasons to do more research on the topic of transportation efficiency. Despite the importance of these two topics, less research with the extraction of performance measurement’s indicators in the transportation industry and emphasis of provinces during the development plan period have been implemented. In this research, to achieve this goal by using the 6 input and 6 output indices within the Third Development Plan and the first 3 years within the Fourth Development Plan, we consider the relative performance of the provinces in the cargo of transportation has been considered in this paper, by using the mathematical Data Envelop Analysis Model (DEA) and Susceptibility Model. The method used in this research is descriptive - analytic and the data are extracted from the valid census references. The results indicate that there is a high performance in Booshehr and Tehran Provinces and low performance in Kohgiluyeh and Boyer Ahmad Province, within the Third and Fourth plans. The number of inter –city vehicles is considered as a main input index and the number of passengers is considered as an output index, indicating the significance of both parameters in the performance of transportation system.

Due to maturation, the resilient modulus (Mr) of recycled mixes with bitumen emulsion and cement will increase upon curing. Therefore choosing a design Mr for these mixtures will be more complex than conventional hot mixes. Furthermore the Mr test apparatus is not accessible in many project plants and developing a model for estimating the Mr with an inexpensive and accessible method will be desirable. In this research using the results of indirect tensile strength (ITS) and Mr tests at different temperatures (-10, 5 and 25oC) and curing times (7, 28 and 120 days), two models have been developed for recycled mixture with bitumen emulsion containing type I and pozzolanic cements. Based on the results, first the relation between ITS and Mr in similar conditions (temperature and curing time) for each cement was correlated by a linear relation. Then by considering the effects of temperature and curing on Mr, the aforementioned models were modified for estimating Mr in different conditions.

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.

One of the most important points about gas stations is their suitable and appropriate location. The aim of this project is to determine the appropriate number and location of gas stations by utilization of mathematical programming model, in a way that these stations have the best services. In this research, the City of Mashhad was chosen as the study area. Mashhad is divided into 13 urban districts and 141 traffic zones. Mashhad city is selected for this project. Information and specifications regarding the traffic background of Mashhahd was collected and then organized within GISenvironment. Also on the basis of gas consumption in a particular period and considering some specific circumstances, the number of the required gas stations was calculated. In order to study the serviceability of the districts where the gas stations are built, the potentiality of each district was defined and calculated, using some specific scenarios. The mathematical site selection model was defined on the basis of the maximum serviceability potentials of districts and solved by Lingo Software, and the best serviceable districts were chosen. Finally the selective districts prioritization was presented in the framework of some assumed scenarios in GIS environment.

The traveling salesman problem (TSP) is a well-known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Despite this simple problem statement, solving the TSP is difficult since it belongs to the class of NP-hard problems. This means that no known algorithm is guaranteed to solve all TSP instances to optimality within reasonable execution time. Due to thedifferent nature of metaheuristics algorithms and the importance and application of TSP in different fields, in this paper the shortest Hamiltonian path is achieved between 423 Iranian cities by the two types of algorithms. for the first time Tabu search as a single-solution-based algorithm and memetic algorithm as a population-based algorithm is selected. To evaluate the accuracy and efficiency of the proposed algorithms, standard problems with size from 16 cities to 1060 cities have been used. Results demonstrate the performance and effectiveness of proposed algorithms. Java programming language to code algorithms has been used in this research. Parameters tuning for each algorithm is done separately and ultimately the best value for each parameter has been determined.Finally, the performances of each algorithm determined by quality of solution and CPU time and the results have been compared.