Journal of Transportation Engineering
Year:2017 | Volume:8 | Issue:3 |Papers Count:11

Decrease in traffic speed will result in freeway’s passing capacity, and this means decrease in performance level of service quality. Factors resulting in traffic speed decrease are categorized as permanent or temporary. Raining parse is one of temporary factors decreasing free flow speed. In this research effect of weather conditions (rainy weather) are surveyed as a temporary cause of decrease in capacity of freeway and on freeway’s free flow speed in Tehran-Qom freeway. So it can calculate the rain fall decrement index in the geographic region of Iran, (previously not calculated). If the time of traffic considered in design of freeway in the time of rain, by using decrement index the design capacity can be optimized. In this research. In the beginning rainy hour and non-rainy hour were identified and separated, and also hours with less than 0.01 millimeter of rainfall due to insignificant effects were ruled out and considered as non-rainy hour. Studies show that light rain has no significant effect on flow speed and capacity and in some points its effects are neglected. But in case of heavy rainfall due to decrease in driver's vision range and decrease in surface friction between vehicle's wheels and road surface, flow speed will be significantly less than light rain situation and the changes between free flow speed of in 2 different conditions, rainy hour and sunny hour would be calculated. And with use of multi regression analysis and validating data from statistics test, result would be evaluated. traffic data and weather data from the last 6 months of hijri shamsi year 1391 in Tehran - Qom freeway was gathered and results obtained also confirms that rainy weather will result in 3.5 to 8.9 % decrease in capacity and 4 to 10% decrease in free flow speed.

Determining the fleet size is one of the most important issues of the shipping industry. In this study, a mathematical model is proposed for the dynamic problem of determining the number of rail freight wagons in conformity with the real-world conditions and restrictions. In the proposed model, the demands for wagon and due time for start have been considered deterministic. In addition to the revenue, another objective function has been considered for more productivity which reduces the number of delays in responding the demands during planning. Also, in accordance with the actual conditions in a railway network, freight wagons have been heterogeneously taken into consideration. In the proposed model, the vehicle capacity constraints, vehicle delivery, and the line capacity have been taken into account for the first time. Here, specifying empty wagons in order to increase productivity of the available wagons in the network; as a result, reducing a large expense of fleet ownership and maintenance has been considered. After defining the problem in the form of a mathematical model, a method based on the multi-objective simulated annealing algorithm has been proposed to find the Pareto solutions. Finally, a numerical example has been given from the Islamic Republic of Iran's Railway Transportation Industry and the solution has been discussed.

This study considers a scheduling problem of combined arrival-departure aircrafts over multiple runways with a number of a parking spaces constraint that minimizes the total weighted tardiness. This phenomenon is modelled as a parallel machine scheduling problem with unequal ready time, target time and dead line. Additionally, sequence-dependent separation times on each runway are considered to prevent the dangers associated with wake vortex effects. Considering occasional occurrence of such restrictions at airports as well as planning a better deal with such issues, a mixed-integer programming (MIP) model is presented and solved by Lingo software to show its validity. A meta-heuristic algorithm, namely firefly algorithm (FA), is proposed to achieve acceptable results in a reasonable time. The performance of the proposed FA is evaluated through a comprehensive benchmark of instances. Furthermore, the computational results show that the performance of the proposed FA is satisfactory in terms of computational time compared with Lingo. Finally, the conclusion is provided.

GPS, among the various methods of traffic data collection has special popularity due to the low cost and wide access. The primary factor for reliability of determined parameters extracted GPS trajectories is the correct calculation of a vehicle location on a road segment, which is realized by a map-matching algorithm. High percent of GPS trajectories is taken from a variety of sources including mobile GPS, GPS equipped vehicles the, fleet public transport, and social networks are in low sampling rate between 2 to 6 minutes. So determining a suitable map matching algorithm to reduce data errors seems necessary. This paper aims to implement ST-matching and IVVM algorithms to match the GPS tracking data and extract traffic parameters and traffic map by matched trajectories. A special characteristics of ST-matching algorithm is to employ simultaneous spatial, temporal and topology analysis. IVMM algorithm not only considers the spatial and temporal information of a GPS trajectory but also devise a voting-based strategy to model the weighted mutual influences between GPS points. To evaluate these algorithms GPS trajectories with 2 minutes sampling rate of public fleet transport related to bus lines are used. ST-matching algorithm use only one point before each sampling point to match it there for the first point has not any before point, there is no the previous point, so the algorithm is highly dependent on the starting point. IVMM algorithm by modeling mutual influences between GPS points provides more effective and strong result. Distance Weight Function plays an important role in IVMM algorithm. By increasing the value of the parameter beta in Distance Weight function increases map matching accuracy. The obtained accuracy of the method of IVMM and the ST-matching is 88% 73% respectively. The results of this study show the IVMM algorithm outperforms the ST-matching method. Also In the face of U-turn IVMM gives better results.

This study is concerned about how the quality of perishable products can be improved by shortening the time interval between production and distribution. Since special types of food, such as dairy products decay fast, the integration of production and distribution scheduling (IPDS) is investigated. This article deals with a variation of IPDS that contains a short shelf life product; hence, there is no inventory of the product in the process. Once a specific amount of products are produced, they must be transported with the least transportation time directly to various customer positions within its limited lifespan to minimize delivery and tardy costs required to complete producing and distributing the product to satisfy the demand of customers to the limited deadline. After developing a mixed-integer nonlinear programming model of the problem, because it is NP-hard, an Improved Particle Swarm Optimization (IPSO) is proposed. IPSO performance is compared with a commercial optimization software for small-sized and large-sized problems. The model has developed as an Integer- nonlinear model and it solved by using an improved particle swarm optimization which is improved by 1-opt and 2-opt operator and is coded in Matlab program. The model has been investigated through the real data gathered from Pegah company and the outcomes has been compared to the previous order system. Computational experiments show the e ffi ciency and effectiveness of the proposed IPSO in terms of both the quality of the solution and the time of achieving the best solution.

In order to investigate the effect of nylon fibers on the performance of asphaltic mixtures, 12mm long nylon fibers in different contents of 0.1, 0.2 and 0.3% (by the weight of total mixture) were added to a typical asphaltic concrete. After determination of the optimum binder content of the mixtures, the volumetric properties of the mixtures containing different percentages of nylon fibers were analyzed. Then, the fiber reinforced mixtures were subjected to Marshall Stability, flow an indirect tensile strength tests. In addition, in order to evaluate the permanent deformation behavior of the mixtures, using UTM-10, dynamic creep tests were conducted under different stress levels of 200 and 400kPa, and at different temperatures of 40, 50 and 60°C. Dynamic creep curve, flow number and the creep strain slope (CSS) were used for analysis of the results. Then, the creep behavior of the mixtures was modeled using the three-stage model developed by Zhou et al. The resistance against moisture damage of the mixtures were also evaluated using the tensile strength ratio (TSR) and Marshall Stability ratio (MSR). The results showed that the mechanical properties of the mixture such as the Marshall stability, Marshall Quotient and the indirect tensile strength of the mixture can be improved by modifying with 0.1% of nylon fiber. Also, the moisture sensitivity of the mixtures decreases with increasing fiber content, up to the fiber content of 0.1%, after which, increases with increasing fiber content. The results of dynamic creep tests and modelling the creep curve using the three=stage model showed that the mixture containing 0.1% of nylon fiber has the highest length of primary creep region and flow number and the lowest creep stain slope, indicating that its resistance against the permanent deformation is the highest.

One of the important properties road pavement and safety is skid resistance. These properties are dependent on numerous factors, such as properties of pavement surface texture and materials used, weather conditions, seasonal changes and road surface contaminants. The aim of this study is to examine the effects of various contaminants on skid resistance of the pavement surface. The existence of contaminants, especially during the first rain after a drought period makes the wet road surfaces slippery and increases the risk of accidents. Some of these contaminants are natural, such as dust and quick sand on the desert areas and some of them are unnatural such as lube oil and rubber particulates produced by tire wear. So, in this study, dust, quick sand, lube oil, rubber particulates, soot and cool color traffic were chosen as contaminants. Asphalt samples were made in Marshall large formats using three continuous grading with Gyratory compression and then by British Pendulum Tester were tested at different temperature and humidity. Test results indicated that contaminants had distinct effects on skid resistance of asphalt pavements. It was also shown that under dry conditions, the minimum value of skidding is when the surface is completely covered with quicksand and under wet conditions; the value of skidding was declined on average of 49 to 55 percent by cool color traffic. Artificial neural network (ANN) and decision tree data-mining methods were employed to analyze the data were derived from the statistical model. Accordingly, it was shown that changes in the type of contaminants cause the greatest change in skid resistance.

Cross-dock is a logistic strategy with the aim of reducing inventory and increasing customer satisfaction. It is described as process of moving goods from suppliers to customers through cross-dock centers without or with little storage, and products must be collected to cross-dock centers before being shipped to customers and after consolidation, freights are delivered to customer with outbound vehicles. This research considers location-routing problem with cross-dock throughout a multi-echelon supply chain by integrating suppliers, cross-dock centers and costumers. In this problem, cross-dock center, vehicle, supplier, costumer, and product are multiple. Also, cross-dock centers and vehicles have limited capacity, split pickup and delivery are allowed, and vehicles are heterogeneous and have constraint for product type shipping. The aim of the model is to minimize the sum of the opening costs of cross-dock centers and the distribution and operational costs of vehicles. This problem arises from the perishable food products distribution industry. For the problem, an integrated mixed integer nonlinear programming model is proposed. Since the problem under study is NP-hard, a particle swarm optimization algorithm is presented to tackle larg-sized problems. Also, a lower bound is developed for the problem. In order to show the performance of the introduced algorithm, different test problems with small, medium and large sizes are provided randomly and solved by the proposed approaches. Computational results show the high performance of the proposed algorithm.

Transportation demand management (TDM), refers to an approach which tends to more efficient use of transportation resources of a city. Typically, car use reduction is said to be the main goal of this approach to avoid congestion problem. A part of daily car usage in cities is due to commuters’ long trips. It is a crucial issue to attract people out of their cars in long trips because of the high proportion of such trips in vehicle-kilometer traveled as a proxy of transportation emission. This study focuses on managing the demand of long car trips which their destinations are in the central part of the city of Tehran. Therefore, three push policies (i.e., increasing fuel cost, increasing parking cost, and cordon pricing) and two pull policies (i.e., transit time reduction and transit access improvement) are investigated on 240 commuters who their workplaces are in the central part of the city and their driving distance is more than 8 kilometers. Adopting an approach named multi-instrumentality, design of this study is enhanced by considering TDM policies’ interactions. By developing a behavioral mode choice model in form of multinomial logit, significant transportation related variables are discovered and interpreted, respectively. The application of model regarding to the effect of cordon pricing policy on car usage is also presented.

Public transportation network design is one of the most complex issues in transportation engineering where researchers usually apply simple heuristic methods to solve the complicated problem. Route generation algorithm is one of the heuristic methods that use the shortest path between high transit demand O-D pairs and expand the shortest path, called route generation algorithm, to cover more transit demand. In this paper, the expanding route generation algorithm has been revised in order to consider restrictions on minimum route travel time and length to the primary route generation algorithm. The proposed algorithm for route generation has been coded in a computer programs and used for transit network design in Sioux Falls test network. The results show that the algorithm reduces the number of transit routes in the test network by 70 percent and route overlaps length by one-third compare with the previous route generation algorithms used for transit network design on Sioux Falls.

To allocate resources at the national level and ensure the safety level of roads, cost calculation can help determine the size of the problem and demonstrate the economic benefits resulting from preventing such injuries. In the current study, the cost of road traffic injury fatalities and non- fatalities was estimated by willingness to pay method using Bayesian analysis. In a cross sectional study fatal and non- fatal injuries cost was estimated. Totally 782 road users were randomly selected and investigated. The research questionnaire was prepared based on the standard for WTP method (Contingent value (CV), stated preference (SP), revealved preference (RP) model) considering perceived risks, especially in Iran, and its validity and reliability was determined. The research questionnaire was collected along with four scenarios for passengers, pedestrians, vehicle drivers, and motorcyclists. Mean age of the subjects was 33.4±9.9 years old. Men and women constituted 89.3% and 10.7% of the studied population.47.2% of these people had an accident record themselves and 51.4% had an accident record in their families. In sum, fatal and non- fata injury cost was 1, 171, 450, 232, 238, 648 IRR equivalents to 39, 048, 341, 074. Willingness to pay demonstrated an increase in risk reduction at the age of 35 and 55 years old. Findings obtained from Bayesian model showed that willingness to pay had a significant relationship with age, medium and high monthly income, logarithm trip mileage, daily payment for reducing mortality risk, payment for time reduction,, bus, minibuses and car drivers and occupants. GNI of road traffic injuries in Iran is higher than the global average. It seems that the measures for reducing traffic injuries in Iran have not been sufficient, the result of which has been the existing traffic injuries volume in the country.