Journal of Transportation Engineering
Year:2019 | Volume:10 | Issue:4 (41) |Papers Count:13

Possessing a considerable portion of the cost of any health system، blood supply chain is one of the most critical parts of the system. Accordingly، any improvement in the performance of a blood supply chain can result in significantly improved performance as well as cost of the health systems. To have an efficient blood supply chain، appropriate planning is of great significance. This paper puts forward a bi-objective mixed-integer linear programming model for designing blood collection، production، inventory control and distribution under uncertainty with the need for making both strategic and tactical decisions simultaneously over multiple periods of planning. Moreover، blood transshipment between regional blood centers is accounted for in this work. To deal with the proposed bi-objective model، the epsilon-constraint method is devised، and to capture demand uncertainty، a Light robust approach is applied. The usefulness of the concerned model and its solution technique، which is a combination of epsilon-constraint and Light robust methods، is then evaluated via a set of numerical examples، and also، the sensitivity analysis is provided. We close the research while comparing the performance of both deterministic and robust models based on the network total cost، a performance measure including both constraint violation cost (feasibility robustness) and objective functions (optimality robustness) under a specific realization. The results imply that the robust approach strongly outperforms the deterministic one.

Today، the greenhouse gas emission from industry and transport is the most important factors in the destruction of ecosystems and natural resources. One of the main sources of pollution is industries related to construction، maintenance and improvement of transport infrastructure. The production of cleaner asphalt needs to reduction of temperature in the asphalt mixture، without a reduction in mechanical performance levels. The reuse of Reclaimed Asphalt Pavement (RAP) in the production of new asphalt preserves natural resources and reduces environmental pollution. In this study، the use of RAP in producing hot and warm mix asphalt mixtures and effects of two additives (Sasobit and Zycotherm) was evaluated. The amount of RAP in the mixture was 50، and 75% and percentage of Sasobit and Zycotherm were 2 and 0. 1% respectively. The addition of Sasobit improves the compressibility and strength of asphalt mixture effectively، so the sample containing 75% of RAP had better compressibility and strength، but Zycotherm caused improvement of compressibility and considerable decrease in air void range and increase stability of mixtures containing 75% RAP. Generally، partial strength values of WMA with 75% RAP is not very different from HMA. Finally، TSR test results have increased along with the increase in the percentage of sub-asphalt materials ratio which shows low sensitivity to moisture in the recycled mix.

In this study، some mechanical properties of roller compacted concrete (RCC) containing recycled concrete aggregate (RCA) have been investigated. Different mixtures of RCC، in which the fine، coarse or fine and coarse fractions have been replaced with RCA have been made and their mechanical properties including compressive strength، flexural strength، elastic modulus and energy absorption have been evaluated. The compressive and flexural strength of the mixtures have been measured at the different curing ages of 7، 28 and 91 days، while the elastic modulus and energy absorption have been evaluated on the specimens cured for 28 days. Results show that the mixtures containing RCA have a slightly less compressive strength than the control mixture made of natural aggregate. The highest compressive strength was obtained for the mixture containing recycled coarse fraction and natural fines. The flexural strength test results showed that the mixtures containing recycled aggregates have a higher flexural strength than the control mixture، with the highest flexural strength for the mixture containing coarse RCA and natural fines. Furthermore، the ratio of flexural to compressive strength، which is used as an indicative of energy absorption، is higher for the mixtures made of RCA، with the highest for the mixture containing both fine and coarse RCA. The elastic modulus test results show that the mixtures containing RCA have a higher energy absorption than the control mixture، while their elastic modulus is less than the that of the control mixture. The lowest elastic modulus was obtained for the mixture containing both coarse and fine fraction of RCA. This research results show that RCA obtained from structural concrete is feasible to be used in RCC.

Evaluation of the road surface distresses is one of the most prominent phases of pavement management process. Over the past decade، a considerable number of researches have been carried out on developing automatic methods for distress detection most of which rely on computer vision and image processing techniques. One of the most important assets comprising computer vision systems is the image feature extraction algorithm. Textural features present more detailed information about the image regions characteristics compared to other features such as color and geometrical (shape) properties. In the past few years، multi-resolutional analysis approaches، such as wavelet transforms have provided an effective tool for fast and accurate image texture representation. In the present study، after acquisition of six different types of asphalt pavement distresses under controlled condition، in order to analyze their structures، three 2-D discrete wavelet transforms including Haar، Daubechies3 and Coiflet1 were utilized. In addition to aforementioned transforms، directional selective dual-tree complex wavelet transform was also applied on the distress images with the purpose of investigating the effectiveness of directional sensitivity increasement. After decomposition of the images by applying the abovementioned transforms، second-order statistics based on gray level co-occurrence matrix and higher-order descriptors based on gray level run-length matrix were employed، in order to characterize the wavelet frequency sub-bands texture.

One of the most important parameters in assessing the satisfaction of passengers in a bus system is bus frequency or bus headway. In this study، optimization of the public transportation system’ s frequency has been investigated، which aims to determine time interval between the next buses for a set of public transport lines determined by their travel plans. Origin-destination demand and restrictions on existing bus fleets should be considered by results. In this way، a model (MILP) was proposed for a pre-existing model which originally formulated as a non-linear two-level formula. The proposed formulation is capable of solving the real optimality of small scale problems using the MILP technique. In order to solve large scale، a metaheuristic method has been proposed that its accuracy is estimated by comparing exact results. Both an exact and approximate approach have been tested using existing cases، thus، the public transportation system of Qazvin has been used as case study. Although its public transport system has 22 lines، an improvement of about 6% was achieved using this model. This shows that، even in small cases، there are improvements in system efficiency. Since the general improvement of Qazvin bus system was not possible after a considerable amount of runtime، an alternative solution approach was proposed in this study. Therefore، a tabu search method has been proposed، which results in a competitive comparison with the exact model.

One of the main pavement distress in regions with a significantly large amount of rain and snow is stripping of aggregates. In this research study، in addition to focusing on stripping formation، the main factors contributing to the severity of stripping and the ways to improve the durability of the asphalt pavement are investigated. The effect of different quantities of limestone filler، hydrated lime، and nanomaterials called Zychoterm as anti-stripping agents are investigated and optimal mix designs using these materials are provided. Since annual temperature variation of Ardebil province is larger than temperate regions، so this province is chosen as the case study of this research. Aggregate from three different mines، referred to as mine A، B، and C، are obtained and are investigated using C294 test. The stripping potential of dry and saturated asphalt specimens are tested based on AASHTO T283 using indirect tensile strength test. The results show the effect of aggregate type on the asphalt mixtures’ performance. Specifically، the asphalts mixes from aggregates of mine A and C have shown a significant improvement against stripping when mixed with 2% hydrated lime، 4% limestone filler، or 0. 1% Zychoterm. In contrast، using these additives in asphalts made from aggregate type B، which was limestone، did not show any increase in the TSR strength.

The main purpose of this study، Modeling، identifying key factors and investigating various data mining algorithms in traffic accidents in Iran، especially on urban roads. The following was extracted set of rules that can be effective in identifying key factors and their impact in reducing accidents. The data included 5099 records of traffic accidents on the Tehran-Qom road in Tehran during a four-year period. Each accident record consisted of 57 accidents related to accidents. In the pre-processing، the greedy search algorithm was used to find the best sub-set of factors. After the pre-processing، reduced records used. Finally، 8 characteristics، accident factor، type of collision، visual impedance، accident situation، road surface conditions، location geometry، direct causes and type of accident were investigated. To achieve the objectives of this research، seven different data mining techniques were used. 6 Data mining algorithms were used to predict and identify key factors using WEKA data mining software; These algorithms include: J48، PART، Logistic، Classification via Regression، Naï ve Bayesian and Multilayer Perceptron. Also، the apriori algorithm was used to extract the rules. The results showed that Perceptron and Part algorithms had the best performance among other algorithms to predict. Algorithm Naï ve Bayesian despite being in the range of acceptable has a weaker performance than other algorithms، both in model accuracy and coverage. Several of the most important factors of the set of rules were road accidents، flat and straight geometry، Lack of visibility barrier And attending the accident site.

A vehicle routing problem (VRP) is an important issue that has attracted great attention of researchers in recent years. This paper presents a competitive VRP to get short routes with the maximum sale by providing suitable services to customers before delivering the goods to other competitive distributors. To distribute the goods with a short lifetime، in which customers need a special device for keeping them، the arriving time to customers effects on a number of sales، in which classical VRPs are unable to calculate these kinds of assumptions. According to the real world، the arriving time of the competitors is uncertain because of customer demands، traffic، weather conditions، etc. A scenario-based approach is used to handle the uncertainty of the arriving time of rivals. The purpose of this paper is to solve this problem by optimizing the sale of products to customers before delivering the products to other competitor distributors in an uncertain condition by robust optimization. To evaluate the performance of the presented model، the improved differential evolution (IDE) algorithm is used. The related results in small and medium-sized problems are compared with the result obtained by an exact solution method. Additionally، in order to evaluate the performance of the proposed IDE algorithm، a few sample tests in large sizes are solved and their results are compared with other two differential evolution algorithms. The results show that the proposed IDE algorithm has a suitable accuracy and performance for solving the presented model.

By the population growth and the increasing need in new transportation infrastructure، especially railway، and with the attention to the reduction of natural materials، using the recycled aggregates (RA) from construction and demolition waste (CDW) is spreading around the world. One of the most important resources of RA is oil contaminated concrete of oil platforms and wharves which are exposed to sea water. In this paper، first of all، the cubic samples of oil contaminated concrete with different percentages of oil contamination including 1%، 2%، 4% and 6% were built. The curing of the samples was done in the sea water (Oman sea-Chabahar coast/Iran). Then the samples were broken and crushed under experimental conditions. In the rest، the recycled oil contaminated aggregates were sieved and the possibility of the use of them as the granular aggregates of sub-ballast layer according to AASHTO and ASTM was investigated. Gradation، Atterberg limits، maximum dry weight and optimum moisture content، sand equivalent، California Bearing Ratio، Los Angles abrasion value and water absorption tests were done on RA. To assess and compare the "Railway Track Superstructure General Technical Specifications" Code (Code No.: 301) were considered. The experimental results show that RA with different contamination percentages have all of requirements that represented by code recommendations. So، it is possible to use of contaminated RAs as sub-ballast layer.

Recognizing the pattern of movement and the traveling mode is one of the most important issues in the field of urban analysis and transportation management. Disadvantages of the traditional method such as the questionnaire is the lack of availability and cost. So، after the emergence of new technologies، communication tools such as mobile phones are used to collect and analyze traffic data. The Wi-Fi network has been considered by intelligent transportation systems due to high availability and low cost. In this research، users in the specific area are classified into three categories using the Wi-Fi scanner. Pedestrians، passing cars and users who stop in the area for long time. This classification has been made using the extraction three features on the users' Wi-Fi signals and using an adaptive network-based fuzzy inference system (ANFIS) model. The results show that the proposed model for using the subtractive clustering method in the first layer of ANFIS to determine the initial membership function of the features has been able to classify the three categories with a accuracy of 84%، and the precision and recall of the user's detection Which used cars in this area، was 75% and 90%، respectively.

One of the most important parts of the driver reaction is detecting hazard in prominent time. A hazard is detected in the right time if it is completely visible for the driver. There are various hazard types such as fixed obstacles، pedestrians، and animals that some of them cross the road. Right-time hazard detection and the post-reaction is of high importance in accident prevention. It is assumed، in this paper، that increasing crossing speed of hazards affects the driver's hazard detection. Different driver types including novice، low-experienced، and experienced drivers are chosen and various environmental scenarios are also designed. The eventual suggested model is Fuzzy Sugeno that estimates relation between the driver's detection score and the hazards' crossing speed. The results show that hazards' crossing and also increased crossing speed raises drivers' detection score and decreases reaction time. The increasing slope of the drivers' detection score diagram in relation with hazards' crossing speed in different conditions is 2% to 50%. The results are useful in training and hazard perception and detection tests، especially، for novice drivers and also، in making fixed and low-speed crossing hazards recognizable.

Abstract Today، with the increasing production rate and importation of vehicles in Iran، identifing of vehicle registration plate recognition systems seem necessary. This factor has caused traffic control vehicle traffic by human staff seem impossible. If use of these systems are compatible with the country's environmental situation، they causing a significant reduction of costs for traffic controlling. Meanwhile، the huge amount of the vehicles have caused other traditional procedures are not applicable. Due to atmospheric and climatic conditions of the country، creating an efficient system compatible with a variety of environmental conditions and optical precision is essential. The system must have high diagnostic accuracy in distinguishing characters have vehicle registration plates. Therefore، given the importance of this paper is an attempt to solution to improve the ability to detect and predict farsi vehicle registration plate characters to be created. In this paper، the database contains 600 color images of vehicles in the country the size of 680 x 480 is used. In this study، in addition to the existing challenges to provide guidelines for improving forecasts in various stages. The advantages of the proposed method in addition to high precision، flexibility and the ability to implement in the real world as well as the ability to work under ambient conditions and atmospheric lighting can be named. Some problems that can be caused administrative problems in this regard will be occurred that must be resolved in the next steps. Usually there will be resistance by some factors involved that must be solved by interacting.

Warm mix asphalt (WMA) is a mixture with a mixing and compaction temperature 30– 40 degree less than conventional asphalt mixture. Lower product temperature of WMA leads to increase use of this but this temperature reduction has raised concerns about rutting and fatigue performance. The object of this study is to in to investigate the effect of type of warm mix additives on moisture susceptibility and rutting resistance. For this purpose، limestone and steel slag، two type of filler and Zycotherm and Asphalten-B as warm additive were used for samples preparation and evaluating performance. Indirect tension، resilient modulus and Dynamic creep tests were performed on prepared samples for evaluating the effect of aggregate type، filler and additives on moisture susceptibility and rutting resistance. Results indicate that mixture containing Asphalten-B improve the performance of WMA as compared to HMA in ITS، MR، rutting by 10، 15 and 5%، respectively and in moisture susceptibility، asphalt mixture contain Zycotherm can increase the moisture resistance by about 10%. Also، result show that asphalt mixture containing steel slag aggregate and cement filler the highest durability and rutting resistance.