فصلنامه مهندسی حمل و نقل
سال دوازدهم شماره 3 (پیاپی 48، بهار 1400)

The concept of container unloading and loading in container ports for the purpose of unloading and loading is referred to as container allocation. This study assumes that the containers are transported between different segments of the port and must be allocated between the existing segments of the port for transport. The allocation is made to minimize costs. For a good and efficient modeling is written the relationship between the different sections.In this paper, the issue of the allocation of containers to ships, yards, customs, mainland and cranes is examined separately. Also, the problem of allocating ships to the berths is also studied. in both parts, the time of transportation and the capacity of the enclosures are limited in the problem. The literature review shows that the results obtained from solving this problem are not applicable in practice. After mathematical modeling, due to the NP-hardness of the problem, two innovative algorithms have been used to solve the problem. The first PSO method performs the assignment of ships to the dock, and then the second algorithm uses the GA method to allocate containers to different parts. Finally, the proposed algorithm is analyzed and compared. The results of the calculations show that the proposed algorithm has a very high performance in practice and in the real world.

Four-lane divided highways constitute a significant proportion of Iranian interurban road network. Capacity is one of the key features when examining traffic conditions on this type of roads which is affected by the driving behavior and local conditions governing these roads. An experimental research approach based on site observations was adopted. The objective was to examine and compare the performance of a number of internationally known methods that so far have been used for the capacity analysis of these roads in Iran, and to develop new models, if required. The other objective was to identify the major parameters that would affect the capacity of these roads. For this purpose, 32 suitable sites were identified and data describing their traffic, geometric and surrounding road environment were collected and analyzed. The results indicated that neither of procedures presented in the German, Indonesian and American Highway Capacity Manuals provided a close estimation of the capacity of this road type in Iran. The results provided from the two newly models developed in this study namely, a neural network model and a multivariate linear regression model indicated that these models produced more accurate results in comparison with those procedures, respectively. Finally, the results indicated that roadway width, lateral friction due to the activity and accessibility of the surrounding area, and combined effect of the grade length and steepness are the major factors affecting the capacity of this road types. The developed models could be used for the capacity analysis of this road type in Iran.

Variable-message signs (VMS) are traffic control devices providing drivers with information along their way. In view of emerging conditions such as the increasing social role of inter-city routes, formation of small communities along them, and the high speed of vehicles in these areas that deteriorates safety, this study aims to use a special type of variable-message sign to help reduce the speed of vehicles on a key road in the Iranian Mazandaran Province. In this study, using affordable and compatible speed sensors, the speed of vehicles was recorded before and after the installation of the variable-message sign, to measure its effect on the speed, using special speed sensors. The device was equipped with infrared speed sensors (PIRs), wirelessly connected to the sign using IOT technology, and the speed of passing vehicles is detected by these sensors, and displayed online on the variable-message sign screen. The effect of the variable-message sign was measured using the average speed, the 85th percentile speed, and the speed of vehicles in different distances, i.e. 50 m, 30 m, 20 m before the sign, on the VMS, 20 m and 50 m after the sign. The results showed a 7% decrease in the average speed of vehicles in general; and respectively 6.5%, 11%, 11.3%, 3.7%, 6.3%, and 5.3% decrease at 50 m, 30 m, and 20 m before the sign, on the VMS, 20 m and 50 m after the sign, compared to the speeds recorded before the installation of the sign. Moreover, the 85th percentile speed at 20 m, 30 m, 50 m before the sign, on the VMS, 20 m and 50 m after the sign decrease 6, 7, 7, 4, 3, 3, 3 km/h respectively.

Cracking of asphalt layers and pavements is one of the most common modes of failure in roads and highways, which can significantly increase the costof repair and rehabilitation. Since asphalt mixtures can behave as brittle materials at low temperature,brittle fracture and crack growth in pavements is usually observed at the surface of roads located in cold regions. Traffic loading (due to the weight of moving vehicles) and thermal stress (induced by daily or seasonal variations of field temperature), are two major parameters affecting nucleation and propagation of cracks inside the pavements. Reflective cracking is often observed in the overlays, and the growth of such cracks is an important problem in field. In this paper, a multi-layer asphalt pavement containing a reflective crack is analyzed and fatigue life, crack path and effective stress intensity factor are determined. Using extensive two-dimensional finite element analyses, the effect of modulus and thickness of overlay and existing asphalt layer on fatigue life of asphalt pavement were investigated. The results demonstrate that exceeding the thickness of overlay from a special amount causes abrupt increase in the fatigue life of asphalt pavement and also the HMA stiffness were the most influencing factors on the pavement fatigue life. Among the mechanical and geometrical properties of asphalt layers, overlay thinness has the most impact on the crack growth path. By increasing overlay thickness the crack grow path will have a smaller deviation from vertical direction.

Spatial relevancy between the moving car and Points of Interest (POIs) in an urban traffic network is one of the important parameters which determine the relevancy of objects to the moving user. This paper introduces a flexible framework using fuzzification of spatial relationships. The objective of this approach is the determination of a model which is sensitive to the position, direction and velocity of the moving user based on fuzzy customized RCC. The proposed approach is implemented in a scenario of tourist in regions 3, 6 and 11. The tourist is guided from hotel/the origin to the POIs/destination. The experimental results demonstrated the efficiency of the algorithms based on the accuracy and satisfaction of the user.This paper has presented a Fuzzy Spatial Relevancy Algorithm for user-centered systems that guarantees the adaptation of the guiding navigation applications to new spatial contexts.    Adaptation of the application to the user context is based on the Voronoi-based Continuous Range Query and Fuzzy RCC with five main spatial relationships. In this way, this paper innovated model for spatial relevancy, which is sensitive to the position and direction of moving user with three contributions:(1) definition of fuzzy spatial regions for the user and his/her preferred entities, (2) customization of RCC8 relationships for urban user-centered wayfinding systems and (3) implementation of the proposed model for a scenario of a tourist wayfinder with two enhancing operators and evaluation of the algorithm. In this research the tourist guide is equipped with a PDA or Laptop system and a tool for positioning system like GPS. The tourist could execute this program in his/her device and receive the expected context-aware service conveniently. The experimental results show that the proposed approach could detect spatial relevant contexts at the right position at the right time with a high level of satisfaction.

This study investigates the effect of using waste engine oil (WEO) on some engineering properties of hot mix asphalt concrete containing different percentages of reclaimed asphalt pavement (RAP). Different percentages of WEO, namely 0, 5, 10 and 15% (by the weight of asphalt binder) have been added to the mixtures containing 25, 50 and 75% (by the weight of aggregates) of RAP and the volumetric properties, Marshall stability, flow, Marshall quotient and dynamic creep properties of the mixtures have been investigated and comparedwith control mixture without any waste material. Results show that the addition of RAP into the mixtures increases the air voids content, while, the air voids content decreases with increasing WEO content. Also, the optimum binder content of the mixtures was found to increase with increasing RAP content and decrease with increasing WEO content. In addition, the Marshall quotient of the mixtures decreases with increasing RAP content. The Marshall quotient of the mixtures containing 50 and 75% of RAP increases with increasing WEO. Dynamic creep test results show that the resistance against permanent deformation of the mixtures increases with increasing RAP content. In addition, the resistance against permanent deformation decreases with increasing WEO content. With the same RAP content, the highest resistance against permanent deformation is achieved by adding 10% of WEO. Results of this research show that, using waste engine oil as a rejuvenator of aged asphalt, enables to use up to 75% of waste asphalt in production of new asphaltic concrete.

If the geometric design of a road is in a way that it has to pass through areas with weak and problematic soil layers or borrow materials are located far away from project sites, stabilization of pavement improvement operations should be performed to construct pavement layers, especially its subgrade level. Generally, stabilization method of soils is divided into chemical and mechanical procedures, and simultaneous geosynthetic materials can be used. Nowadays, nano materials are proposed in order to improve geotechnical properties of soils in terms of bearing capacity. The present study was aimed to investigate the capability of nanoclay particles and the application of polypropylene fibers in the clayey soil of Eslami Island near Lake Urmia to construct layers in pavement. In the first step, nanoclay particles with 5 and 10 percentages were mixed with soil, and then the curing process was carried out in 7, 14, and 28 days. In the second step, polypropylene fibers were added to the clayey soil in 0.4, 0.8, and 1.6 percentages. Finally, the optimal values of polypropylene fibers and nanoclay particles simultaneously mixed with soil specimens and, similar to the first step, curing operations were carried out. To this end, laboratory tests containing compaction, uniaxial strength, direct shear, and California Bearing Ratio (CBR) in dry and saturate conditions were executed according to ASTM standards. Furthermore, swelling values in the improved specimens at saturate positions were estimated. The findings revealed that optimum combination was obtained at 5% of nanoclay blended with 0.8% of polypropylene fibers in specimens undergoing a 28-day curing process since this condition was found to upgrade the stabilization of soil specimens in terms of compressibility, bearing capacity, strength, and reduction of swelling potential.

The present study attempts to optimally model the daily temporal traffic accidents on Karaj-Qazvin freeway, as one of Iran's accident-prone roads between 2009-2013, using two methods of Time Series and Artificial Neural Network, based on spatial information system. Temporal patterns of road hazards are obtained from temporal traffic accident data (sample size equals to 1097) by taking into account trend and periodic components, model type and order, Autocorrelation and Partial Autocorrelation Functions. In the former method, the dependence of time domain and the order of temporal model were calculated and in the latter method, different architectures of Multilayer perceptron (MLP) (a Feedforward Artificial Neural Network) were implemented to determine the most optimum diagnostic performance. Characteristic indices, coefficient of determination and accuracy were used to evaluate the network and ARCGIS and MATLAB software were used to calculate the two models in different scenarios. The results indicate that the Artificial Neural Network model, with coefficient of determination and root mean square error 10.71, can estimate the rate of daily accidents somewhat better than the Time Series method and Partial Autocorrelation with coefficient of determination and root mean square error 14.31. It should be noted that the modeling of daily traffic accident data using Artificial Neural Network model and Partial Autocorrelation, has not yet been presented in similar studies and research.

Researches show that online services change the transportation system status by changing people's travel behavior. Shopping as one of the main trip purposes is the subject of many studies and increasing online shopping in today's world made the study of the side effects of emerging option a new subject of interest. According to usual trips related to shopping, i.e. search trips and actual buying trips, the present study tries to identify the effective factors on online search and online shopping of digital goods in Tehran and studied the effects of socio-economic variables, internet usage, type and price of purchased digital goods, and trips information on the utility of adopting online search and online shopping. Also the effect of three attributes of price discount, delivery cost and delivery time of the goods on the choice of online search and shopping was investigated. A 324-record database gathered online was used. Final models for both online search and for online shopping were binary logit. The results show that some socio-economic characteristics besides some online sale options are effective in choosing both online search and shopping. It is also revealed that some factors like the household's car number, price discount and the family income in the range of 2 to 5 million tomans per month, simultaneously affect the choice of searching and shopping online/ in-person positively. On the other hand, both delivery cost and delivery time of the goods have negative effects on online search and online shopping.

Passenger Car Equivalent (PCE) is a metric applied to represent the impact of different classes of vehicles on mixed flows by expressing it as the number of equivalent passenger vehicles.  The review of previous studies on PCE for signalized intersections showed that PCE was not determined by flow regime and the control delay, which is an essential indicator of performance of signalized intersections, was not employed to estimate PCE. Moreover, constant values has been considered for PCE and impacts of related variables on PCE has not been studied so far. The purpose of this study is to determine PCE of buses crossing signalized intersections for under-saturated, over-saturated, and near-saturated regimes using control delay and investigate the influential factors affecting PCE. Five intersections in Mashhad were studied and the methodology of Highway Capacity Manual (HCM2016) was used to compute control delay. The results show that in saturated regime, due to the instability of the flow, PCE has the highest value and in the under-saturated regime, due to the freedom of operation of passenger cars and their avoidance of being placed behind the buses, the amount of PCE is slightly greater than 1 and buses are nearly comparable to passenger cars. PCE was calculated for different traffic volume scenarios, percentages of buses, and green split and three linear models were estimated for each of the aforementioned regimes. The coefficients of determination of these models (R2) are very good and above 0.85. Traffic volume and green split are respectively the most influential variables.

urban planning is one of the necessities That needs to be addressed by expanding cities and urban populations. Among the data needed for such studies, the urban road network such as the network of passages has particular importance. Unique features of volunteered geographic information such as comprehensive coverage and daily updates make the volunteered dataset Identified as a suitable dataset for studies. But due to the heterogeneous quality of this dataset, it is necessary to evaluate its quality parameters and verify the quality of the dataset. Therefore, in this paper, according to the necessity of evaluating the quality parameters for volunteered geographic information and the high importance of positional accuracy and the lack of a comprehensive study in previous studies in order to compare positional accuracy criteria, it seemed necessary to conduct a comprehensive study on positional accuracy assessment methods to identify the strengths and challenges of each approach. Analyzes on positional accuracy evaluation criteria resulted in inappropriate Mean Distance Criteria in indistinguishing between positional accuracy of special situations and the advantage of the Hausdorff distance over the incremental buffer distance in higher processing speed. According to this criterion, the volunteered data set of Tehran city in areas 11 to 14 were evaluated as 2.5 meters, indicating the desired volunteered data quality of these areas. Also in the second set of evaluation methods due to high correlation (0.87) of completeness parameter and positional accuracy, this study recommends evaluating the completeness of two VGI and valid data sets in order to prevent possible errors. In this group of methods, the criterion of Buffer analysis was selected as the appropriate method due to the unpredictability of specific situations and the positional accuracy of the Tehran VGI dataset with a 5 meter radius was 0.781.

Today, roads are considered among the main assets of each country so there is a need for a specific mechanism for their preservation and maintenance. Hence, the pavement management system, as an effective tool for decision-making and identifying effective and economical strategies, is used in pavement evaluation and treatment and also in maintaining roads in acceptable levels. In order to implement this system, having access to accurate measurement of different pavement indices, is vital. The goal of this study is identifying the effect of pavement distresses on the roughness and establishing a correlation between the two parameters to be used for evaluating the International Roughness Index (IRI) and roughness growth rate. In order to do this, using the Laser Crack Measurement System (LCMS), the roughness index and pavement distresses are measured in 10-meter length sections with lateral resolution of 1mm in several arterial roads of Iran. After the preliminary analyze of the LCMS output, pavement distresses with higher impact on roughness were identified and then, using artificial neural network (ANN), a correlation was established between IRI and pavement distresses. The relationship showed a correlation coefficient of 0.70. Putting this model into use, is a low-cost approach for road agencies to evaluate the roughness index as well as the roughness growth rate based on pavement distresses in network level. This in part would lead to better policy making and more efficient maintenance and treatment activities.

Today, sustainable development infrastructures are of particular importance in all aspects of urban management. The transport of goods is directly related to the lives of citizens, therefore, policy making and planning in this area, must be based on sustainable development. From the point of view of sustainable development, inter-urban load has various dimensions of the impact on the lives of citizens, that three economic, social and environmental indicators being its main features. In this study, firstthe sub-indicators of the sustainable development formula was weighted by distributing the questionnaire among experts and were selected four effective strategies. Then, these strategies were questioned by the drivers’ questionnaire and driver behavior was predicted after implement of each policy. In order to examine the simultaneous effectiveness of policies,16 scenarios were applied in the network. Also, the coefficients of the sustainable development model were calibrated to be considered as the criterion for decision-making for the implementation of goods transportation management policies. The results show that implementing the strategy of building 4 docks in the four corners of the central core of the cityis considered as the best single strategy. By analyzing the results of the questionnaire by AHP method, the weight of each indicators and sub-indicators was determined and the environmental index is the most important, and also in the environmental section under the indicator of greenhouse gas emissions, in the economic sector, under the index of travel time, added and in the social sector the total number of accidents Most Important.

In the last decades intelligent transportation systems are considered more than ever as a feasible method to control the traffic. The intelligence of this system can greatly reduce human error in crashes. Parallel parking system, car turning and automatic intellignet car are the important systems in this area. In this paper, an important factor of accidents has been discussed to reduce damages of crashes. At first the laws of car precession have been obtained according to traffic police laws and car nonholonomic constraint. Then, multiple paths and car decision capability system have been designed to access an intelligent control system. In this research design a fuzzy decision system is a novel way to decrease the accidents. Finally car dynamic analysis and MATLAB simulation have been compared to show the usability of designed intelligent precession system. Results of this paper with reasonable error illustrate the effectiveness of proposed control system.

Improving the safety of rail transport requires collecting, categorizing and analyzing accident statistics in order to assess and determine the factors affecting rail crashes. HRGCs (highway railway grade crossings) are high-risk areas for all rail lines in the world. Therefore, it is very important to study the factors affecting the formation and severity of railway traffic accidents. The use of statistical models, including the logit model, based on traffic, geometric and accident history, is one of the methods for identifying incident points that, despite the creation of such models for other points such as bridges and road junctions, the prediction of accidents in Iran HRGCs has not been addressed properly. Therefore, in this paper, for the first time, by determining the severity of accidents as a response variable using the Logit model and using data related to the road accidents of Iran Railway Network between 2009 and 2013, the factors affecting the severity of the road accidents can be achieved to reduce the severity of rail accidents and the resulting destructive effects by eliminating these factors. Finally, by using these data the result was that allowed intersections that are not blocked, passenger trains, motorcycles, very high road traffic conditions and high speed trains were known as factors of increasing the severity of accidents and on the other side, the proximity to railway stations, freight trains and agricultural machinery were known as factors of decreasing the severity of accidents.