https://jte.sinaweb.net/ Quarterly Journal of Transportation Engineering en daily 1 Mon, 22 Dec 2025 00:00:00 +0330 Mon, 22 Dec 2025 00:00:00 +0330 https://jte.sinaweb.net/article_233077.html This paper presents a bi-objective single allocation p-hub median problem. We explore the tradeoff between the total cost (airline preference) and lost time cost for passengers (customer preference). Most papers focus on airlines and the network is established based on the viewpoint of airlines despite the importance of passengers. Poor level of service for passengers, lack of convenience and satisfaction may lead to network breakdown. The most important criterion in passenger dissatisfaction in hub-spoke network are scheduling delay and trip time delay because of non-direct flight. We attempt to consider both delays in the framework of constraints and the objective function. This paper consists of two objective functions. The first objective minimizes transportation costs of airline depending on the received services (short haul, medium haul, large haul) while the second objective minimizes the cost of lost time of passengers because of using the hub-and-spoke network. For calculating this cost, the time difference between direct path as the most ideal trip condition is compared with the most ideal nonhub-hub-nonhub path and multiply it by the value of time. We performed experiments using the well-known yearbook of tourism statistics data. We found the exact pareto frontier for 34 nodes in the Iran aeronautics network. https://jte.sinaweb.net/article_87487.html The use of hub-networks leads to decrease in costs and transfer time and consequently increase the system efficiency. Transport and logistic fields, communicative and technological networks are some applications of hub location-allocation. Regarding the vast Iran’s airspace, a hub location-allocation approach can be used to determine airport hubs in Iran to decrease transportation costs and optimize the system reliability. At first, a bi-objective model is introduced to minimize the costs and maximize the reliability. Thus, using of meta-heuristic algorithms to solve the multi-objective problem is inevitable. Then, a differential evolution algorithm is used to solve the presented model. To investigate the implementation of the proposed algorithm, the obtained results are compared with the obtained results of the ε-constraint method in a small-sized problem. The results show a low percentage error and gap. Then, the proposed algorithm is used to find the best hubs location for 15 international and important airports in the Iran Aviation Network. Finally, the obtained results show that Shiraz and Imam Khomeini airports are chosen as hub locations more than the other airports. Mehrabad and Mashhad airports stand on the next positions. https://jte.sinaweb.net/article_225987.html Traffic accidents are a leading cause of injuries and fatalities worldwide, with substantial economic, social, and health impacts. Iran ranks 113th out of 175 countries in accident rates, where these incidents are a primary cause of death. Analyzing factors influencing accident severity from human, environmental, road, and vehicle perspectives is crucial. This study aims to identify parameters affecting accident severity, focusing on vehicle type and driver's age, using data from Khorasan Razavi province and SPSS software. Results from multiple and binary logistic models show that young, adolescent, and elderly drivers significantly impact injury and fatal accident rates. Young drivers' high enthusiasm and risky behaviors, coupled with elderly drivers' decreased ability and reaction speed, contribute to this. Motorcycles and trucks have the highest probability of injury and fatal accidents due to rider vulnerability and their involvement in severe accidents. In contrast, buses and minibuses show reduced accident severity, likely due to strict controls on public transportation fleets. https://jte.sinaweb.net/article_86844.html Recently, utilizing the traffic simulation models have been known as an efficient traffic control and management tool. However, all traffic micro-simulation models require a car-following model so that the simulations would be performed based on it. Many car-following methods have been proposed yet, but all these methods have several number of parameters to calibrate, in a way a little variation over them creates considerable disturbance. In this paper a new car following model was proposed using the Multi-variate Adaptive Regression Spline (MARS) method that do not need any calibration stage. The proposed model inputs are leading vehicle velocity, relative velocity of leading and following vehicles and spacing between them and the output is the acceleration of the following car. As a result of this paper, a car following model with the Mean Squared Error (MSE) equal to 0.004 and the correlation coefficient (R) equal to 0.98 was achieved using the function estimation method through the MARS method. Finally, the MARS output was compared with the results achieved by the Helly linear model, the GHR model and the Gipps model. Based on micro simulation experiment it was shown that the proposed method was more accurate than those models. https://jte.sinaweb.net/article_232584.html By mixing washed natural sand or broken sand or a mixture of these two with pure bitumen, a material called asphalt sand is obtained, which according to the annual price index of road and bond or road management has the highest unit price among other types of asphalt such as binder and topka. Has dedicated itself. According to the general technical specifications of the road, if this asphalt layer is more than ten centimeters higher than the final layer, it has no bearing capacity and can be easily used to fill passive cracks. However, if this asphalt layer is placed at a level of less than ten centimeters compared to the final surface, it will find load-bearing conditions, which must be based on the requirements and regulations of publication 101, it is necessary to think of provisions for that excess of the non-load-bearing condition, which is usually due to the implementation of this The regulatory provisions will also incur costs due to the fact that, unfortunately, there is no item or additional price under the title of asphalt bearing sand in the price list, nor is there an explanation in the introduction of chapter 15 of the price list due to the reasons for the mismatch between the title of the publication and the items in the price list for that presentation. has been This research tries to evaluate this issue and examine this deficiency in relation to providing a solution and distinguishing the nature of the technical regulations and regulations of these two types of asphalt sand from each other on the one hand and proposing an analysis of the price and how to pay it from the road price list. Pay on the other hand. Finally, in addition to concluding and presenting laboratory results and analyzing the price of asphalt bearing sand, three correction methods are proposed under the headings of mountain and river - bearing and non-bearing - and predicting the additional price of mountain or bearing compared to the river and non-bearing row in the price index. https://jte.sinaweb.net/article_225988.html Identifying road accident hotspots enables better understanding of accident patterns for road safety experts to improve roads safety. This study as an applied research, analyzes road accidents to identify blackspots using clustering algorithms: Kernel Density Estimation (KDE), Local Moran's I, and K-Means. The Iranian Ministry of Roads and Urban Development's definition of blackspots was used as the reference for algorithms comparison and results validation. The study examined road accident data on the Mashhad-Bojnord road from 2019-2022. After extracting blackspots using the mentioned algorithms in raster format, their overlap with the reference blackspots was calculated. The KDE algorithm showed the highest match with the blackspots, with 82.55% and 70.96% overlap in forward and return directions, respectively. Analysis of blackspots and accidents distributions near settlements revealed that the highest accident density occurs in the first 30 kilometers of Mashhad city, between Farooj and Shirvan cities, 14 kilometers after Shirvan city exit in the forward direction, and the first 8 kilometers of Bojnord city. https://jte.sinaweb.net/article_79636.html In this study, 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. https://jte.sinaweb.net/article_221069.html The primary objective of this research is to conduct a comparative analysis of transportation systems and to develop strategies for specialized tourism transportation, employing the Meta-SWOT technique. A case study of the metropolitan areas of Mashhad, Tous, and Binālūd was conducted. Given that tourism is a vital component of sustainable development and a significant opportunity for cultural, economic, and social advancement in cities, transportation plays a pivotal role in attracting tourists and providing them with services. In this research, the resources of each mode of transportation in Mashhad were initially evaluated, and their specific objectives were identified and prioritized. Subsequently, the influential and key factors for the success of the project were identified, and weights were assigned to them based on the research findings. Furthermore, various modes of transportation were identified as competitors, and a competitive map was drawn among them. The findings indicate that private cars and taxis, with the highest scores, are the most significant competitors to the specialized tourism transportation system in Mashhad. Subsequently, a PESTEL analysis was conducted to identify factors that cannot be directly controlled. According to the findings, environmental factors related to social welfare, economy, and private sector participation have a significant impact on the project's success. Finally, optimal strategies for implementing a specialized tourism transportation plan were extracted, focusing primarily on strategic alignment with tourist attractions, social welfare, and economic considerations. https://jte.sinaweb.net/article_90933.html In recent years, the number of fatalities due to such natural disasters as floods, earthquakes, storms and so on has been increasing. Large damage/fatality dimensions due to such disasters have caused relief to the affected areas and reducing the effects of disasters to be attended to. This necessitates proper management at the time of disaster which includes proper planning, organizing, directing and controlling the required activities. One of the most vital actions of disaster response phase is to provide necessary relief commodities of shelters. In this paper, a three-level network consisting of depots of vehicles, supply centers of relief commodities and shelters has been proposed for simultaneous routing and scheduling of transportation vehicles to distribute relief commodities. In relief commodities distribution operations, the possibility of getting service from each supply center by multiple vehicles, multiple depots for relief vehicles to start and capacity constraint for vehicles and commodities supplies have been intended to. The objective of the proposed model is to reduce the total time required by the transportation vehicles to reach the supply centers and shelters considering hard time windows. Next, to show the efficiency of the proposed model, we select the fourth region of Tehran city as a case study, run the model on it and present solution results. These results show that relief commodities supplies of supply centers affect total time of servicing. https://jte.sinaweb.net/article_232585.html Accurate control of longitudinal and lateral acceleration in unmanned vehicles is one of the key challenges in the development of safe and efficient autonomous systems. Given the rapid growth of autonomous technologies and the need to improve the performance of these systems in various road conditions, research in the field of intelligent control of these vehicles has gained special importance. In this paper, an innovative method for controlling the longitudinal and lateral acceleration of unmanned vehicles based on reinforcement learning is presented. The proposed method, by utilizing a disaggregated architecture, reduces the computational complexity and enables the use of more advanced reinforcement learning algorithms. In the initial stage, a single reinforcement learning agent is designed and trained to simultaneously control longitudinal and lateral acceleration. Then, in order to improve efficiency, the reinforcement learning agents are separated into two independent parts for longitudinal and lateral control, and trained separately. Simulation results show that this separation not only increases the convergence speed of the training process, but also significantly improves the accuracy of the control system's performance. Separating the agents results in a reduction of about 2 hours of deep network training time, a 38.2% reduction in average direction error and a 10.1% reduction in average distance error. These findings could help develop more advanced and safer control systems for autonomous vehicles and play an important role in improving the safety and efficiency of these technologies. https://jte.sinaweb.net/article_90941.html One ways to increase the willingness to use public transport, is greater coordination and integration between modes in the network. Using mass rapid transit is justifying when appropriate demand of them are provided by lower level networks such as feeder network. In this paper, the effect of changes in demand on the design parameters of the multimodal feeder network has been analyzed. According to complexity of mathematic approaches to solve public network design problems, we used a meta heuristic method, Ant Colony Optimization algorithm. The results show an increase in demand in the suburban areas has more effects on the functional parameters to CBD areas and total cost of system would be increased. Because of multimodal services, this is made possible to short-turn services in the network until the variable lines frequency decreased the user and operator costs and increased utility of modes. In the current case study, reduced demand of near and far area from rail route causing to improve about 7% number of route, 20% frequency, 2% total route length and their headway is decreased about 21% to base scenario. https://jte.sinaweb.net/article_221070.html The void of the asphalt mixtures is a crucial parameter in design and performance of asphalt mixes. Changes in this parameter after road construction under traffic and over time, cause changes in the performance of asphalt mixtures. Therefore, predicting the void of asphalt mixes in the roads under service is an essential requirement for assessing asphalt performance. In this research, an AAN-based model with the high accuracy of R2 =0.97 has been developed to predict the void of asphalt mixes using feed-forward Artificial Neural Networks (ANNs) with the Levernberg-Marquardt Back Propagation (LMBP) training algorithm. The LMBP algorithm is a dynamic technique that combines the speed of the Gauss-Newton method with the convergence guarantee of the Steepest Decent method. Furthermore, the method of adjusting the training parameters of the ANN models is presented to increase the possibility of achieving higher accuracies in the process of reinitializing the weights and retraining the ANN models. https://jte.sinaweb.net/article_91084.html Pavement evaluation is one of the most important criteria in pavement maintenance. Decision makers face with challenges in maintenance planning of road networks with regards to users increasing expectations. The key point is to rigorously evaluate pavement both in objective and subjective manners. This paper aims to develop a model to relate user satisfaction which is a subjective index with an objective index which is easy to calculate. The pavement condition index and pavement roughness have been studied to explore whether or not they have strong relationship with the user satisfactions. Manual pavement evaluation is conducted to compute the pavement condition index and a smartphone application is applied to calculate pavement roughness. In conclusion, pavement roughness shows the best correlation with user satisfaction, while the relationship between user satisfaction and the pavement condition index is not statistically significant. A section of 20 km of Imam Ali Highway is utilized as a case study to successfully validate the model. https://jte.sinaweb.net/article_228622.html Public transportation systems exhibit complex travel behaviors influenced by spatial and temporal factors such as passenger origins, time-dependent demand, and urban structural characteristics. Understanding these behaviors is essential for improving transportation planning and urban development. This study investigates zone-based travel trends in the city of Mashhad, Iran, using smart card data collected from bus and metro systems. Temporal travel patterns of passengers across 253 traffic zones were classified into three categories—morning, noon, and evening—using the K-means clustering method. Meanwhile, the Mean Shift clustering method was employed to examine spatial characteristics such as population distribution and urban development within each zone. The results reveal distinct clusters for both temporal and spatial dimensions, highlighting the complex relationships among travel trends, demographic factors, and land-use characteristics. Key findings include a strong association between residential areas and morning trips, commercial and educational centers with midday trips, and the connectivity of peripheral areas with adjacent residential neighborhoods. These results provide practical insights for urban planners and policymakers to improve transportation systems and land-use policies. https://jte.sinaweb.net/article_92649.html Increasing of tire inflation pressure in recent years is one of the main changes in truck loads characteristics which is highly effective on the interaction of tire and pavement. It results in the reduction of tire imprint surface area leading to the increase of pavement damage. Reinforcement of pavement using geosynthetic is one of the methods to overcome this problem. In this study, the effects of tire inflation pressure on the responses of a typical asphalt pavement reinforced by geosynthetic have been investigated. 3D Finite Elements method using ABAQUS has been utilized for pavement analysis and determination of pavement responses. Viscoelastic behavior was assumed for the asphalt layer and a method was developed for determination of the Proney’s series parameters for a typical asphalt concrete mixture used in Iranian pavements. Three types of geogrid with different elastic modulus has been utilized at three different positions in the pavement structure, and the effects of different tire pressures of 600, 750 and 900kPa on the two critical pavement responses of the horizontal tensile strain at the bottom of asphalt layer and the vertical compressive strain on the top of subgrade have been investigated. It is found that, the tire pressure is mainly affect the horizontal tensile strain of the asphalt layer and the compressive vertical strain on the subgrade is not significantly affected by the tire pressure. The results also show the optimum position of the geogrid for reducing the horizontal tensile strain of the asphalt layer is at the bottom of asphalt layer and that for reduction of the compressive strain on the subgrade is beneath the sub-base layer. it is also found that the performance of geogrid in reduction of the tensile and compressive strain is not affected by the tire pressure. https://jte.sinaweb.net/article_222298.html Many industrial companies utilize cross-docking as a logistics strategy to improve performance in costly distribution operations. In a cross-docking system, goods collected by vehicles are unloaded at inbound doors with minimal storage space and, after a short processing time, are reloaded at outbound doors. The key operational logistics and transportation challenges in cross-docking include vehicle routing and scheduling, which significantly impact cost reduction and system efficiency. This study develops a multi-objective mathematical model for the routing and scheduling of capacitated heterogeneous vehicles with time windows. The objectives of the proposed model include minimizing transportation costs and reducing vehicle arrival times at the cross-dock. The role of the cross-dock as a consolidation and distribution hub is considered to optimize routing and scheduling decisions. To solve the proposed model and handle the problem’s complexity, the AUGMECON2 algorithm is employed. https://jte.sinaweb.net/article_92650.html Pervious concrete is increasingly used in the pavements and overlays subjected to heavy traffic and in cold weather regions. Typically, pervious concrete has little or no fine aggregate and has just enough cementitious paste to coat the coarse aggregate particles while preserving the interconnectivity of voids. In the present study, effect of nano silica additives on pervious concrete abrasion resistance is investigated. Five samples indicate the PPC, PCNS1, PCNS3, PCNS5 and PCNS7, which respectively represent plane pervious concrete, pervious concrete containing nano silica in the amount of 1%, 3%, 5% and 7% by weight of binder, have been evaluated. A total of 30 samples were prepared which 15 samples for testing compressive and 15 cubic cubes was for wear resistance. The results indicate that by increasing the use of nano silica in pervious concrete, compressive strength and abrasion resistance were also increased. The concrete containing nano silica in the amount of 5 % by weight of binder has the best abrasion resistance performance. Use of nano silica in the amount of 5% has a very good influence in enhancing abrasion resistance and compressive strength about 48% and 28% respectively. Other studies on microstructures between the cement mortar mixed with the nano-particles and the plain cement mortar showed that the nano-silica filled up the pores and reduced CaOH2 compound among the hydrates. Finally, the relationship between the indices of abrasion resistance and compressive strength of concrete is obtained, which indicates that the abrasion resistance of concrete increases with increasing compressive strength. https://jte.sinaweb.net/article_236801.html The main objective of the present research is to design a model for the formation of public attitude and intention to use electric vehicles (EVs), considering the role of sustainable transportation in Mazandaran Province. The research is applied in nature and employs a mixed-methods approach. In the qualitative phase, the Thematic Analysis method was used to design the research model, with data gathered through library studies and interviews with experts. The statistical population for this phase consisted of 17 experts in the fields of energy and automotive industry, selected using the snowball sampling method. In the quantitative phase, the Interpretive Structural Modeling (ISM) method was employed for leveling the research variables, and the Importance-Performance Analysis (IPA) method was used for analyzing the current situation and prioritizing the factors. The results indicated the presence of five comprehensive themes in the research model, which are: Consumer Lifestyle and Behavior, Market Dynamics and Industrial Competition, Social Acceptance and Environmental Sustainability, Policy-Making, Economics, and Financial Incentives, and Technological, Innovative Transformation, and Energy Infrastructure. Consumer Lifestyle and Behavior was identified as the theme with the highest priority and dependence (most impacted), while Technological, Innovative Transformation, and Energy Infrastructure was placed at the lowest priority and influence level (most influencing/driver). https://jte.sinaweb.net/article_92653.html This paper explores the effects of trip purpose on price elasticity of bus mode. Data for the research was collected through passenger field survey in the city of Isfahan. Nonlinear regression and nonparametric statistics were used for analysis. It was found that the most suitable function to explain the relationship between percentage of change in demand and percentage of change in fare is logarithmic. This implies that increase in the fare has a diminishing return to scale on demand. Average values of elasticities were calculated as (-0.33) for educational trips, (-0.27) for shopping trips, (-0.26) for commuting trips, (-0.66) for leisure trips, (-0.26) for cure and treatment trips, (-0.35) for returning-to-home trips, and (-0.54) for other trips. Highest values were observed for leisure trips and lowest values for shopping and commuting trips. Kruskal-Wallis and Mann-Whitney U test were employed to analyze the quity of elasticity values among trip purposes. Results show that differences are significant and therefore, trip purpose does have significant effects on the value of fare elasticity of transit demand. https://jte.sinaweb.net/article_92654.html This paper shows that besides personal attributes, trip purpose of the crowd does have an effect on the macroscopic characteristics of pedestrian traffic stream. In this research land use is used as a surrogate to trip purpose. Data was collected on pedestrian movements in religious ceremonies, leisure and shopping urban areas, and a university campus in Isfahan, Iran. Fundamental diagrams were calibrated for three land uses and it was found out that the most and least capacity belongs to the educational and leisure land uses, respectively. It was also found out that Greenberg model best fits the data for religious and leisure land uses. Traffic in educational land use was observed to have significant differences with two others in the way people interacted with each other. Values of capacity were compared to the Highway Capacity Manual (HCM) values which revealed that HCM overestimates the capacity of walkways in religious and leisure land uses. https://jte.sinaweb.net/article_92656.html Disorders in rail networks expand delays and reduce the reliability and stability of the schedule. Railway disruption management includes ways to manage the operations after the occurrences of unanticipated deviations from the original schedule. In this study, the temporary blockage of tracks in the rail network is regarded as a disruption. The occurrence time of blockage and its recovery time are given. In this paper, first the basic scheduling model with the objective of minimizing the total travel time of trains will be provided. The re-scheduling model is presented which is the extension of the basic model and the original schedule provided by the basic scheduling model will be used as an input for the re-scheduling model. The new plan includes a set of new departure times, dwell times, train running times and a set of new stops for trains on the rail network for passenger's praying. A heuristic approach was proposed to design the new plan within a reasonable time. To validate the model, the train re-scheduling model is tested for multiple disruption scenarios with different disruption recovery times on the Iranian rail network. The result indicates that the developed mathematical models have advantages in producing good recovery solution with respect to the time constraint. https://jte.sinaweb.net/article_92657.html Road traffic management consists on improving the traffic fluency on road networks, assigning dynamically the traffic flows, and reducing the number of traffic congestions states as well as their negative effects, i.e. blocking the emergency vehicles, delays, waiting time, drivers’ stress of emergency vehicles, air and noise pollution. the proposed algorithm consists in improving the traffic flow, i.e. the road network can support more vehicles without decreasing the average speed of vehicles, while taking into account the real-time road traffic information; and on the other hand, in reducing the number of traffic congestion situations by avoiding the massive use of the same road at the same time (i.e. providing the suggestion of itineraries with a lower travel times). This allows adjusting intelligently and promptly the road traffic in the network according to the real-time changes.This paper proposes a multi-agent system for path traffic management from swarm intelligence. The objective is to increase the quality of the entire path network, especially in case of congestions and jams, taking into account real-time traffic information and travel time of drivers to reach their destinations. https://jte.sinaweb.net/article_105954.html Providing a cost-effective solution to the two-fold problems of assigning locomotives to trains and train scheduling is of high importance for most railway companies. Due to high cost of deadheading locomotives and tardiness of trains, solving these two problems simultaneously has a significant impact on decreasing transport expenses in Iranian railways. The locomotive assignment problem is to assign locomotives to a set of freight rakes in order to provide the hauling of all freight rakes while maintaining minimum possible movements of deadheading locomotives and minimum coupling delay of freight rakes. In Iranian railways, passenger trains run across the network according to a fixed schedule. Scheduling freight trains is to determine the departure time, arrival time and the movement sequence of freight trains during the intervals between passenger trains in the way that they do not interfere with passenger trains’ schedule and at the same time minimum delay of freight trains occurs. In this paper the problems of locomotive assignment and train timetabling have been solved in two phases. In the first phase, locomotives are assigned to freight rakes using a genetic algorithm. In the second phase, the best locomotive assignment solution which is the output of the first phase is selected and a lower bound for arrival time of freight trains on their destination is calculated. Then freight trains are scheduled using another genetic algorithm. Using the applied method, the results of 30 test problems of simultaneous locomotive assignment and freight-train scheduling are presented. https://jte.sinaweb.net/article_92662.html Standard references used for the design and analysis of walkways; assume that pedestrian stream is unidirectional. But in reality, the pedestrian stream is bidirectional. In this paper, the main question is whether the main features of the pedestrian stream in uni and bidirectional mode are the same? So, in this paper, the effect of making flow bidirectional in the main flow characteristics and pedestrian behavior are investigated. The investigation is based on both experimental and empirical data that were extracted from videos taken from Isfahan sidewalks. Results show that, in same density, the pedestrian mean speed in bidirectional flow is more than unidirectional flow. Mean speed difference in two type of flow becomes more considerable when densities are more than 0.6. The mean speed in majority and minority pedestrian group in bidirectional flow with unequal directional ratio is compared. The results show that density of the people walking in the same direction have more effective roll rather than counter flow density in each pedestrian speed. In high densities, the pedestrian try to walk in the trajectory that pedestrian walk ahead of him to reduce conflict. It leads to lane formation. In this paper, these lanes are studied in different densities and ratios. It is observed that number of the lanes increased in bidirectional flows. Using empirical data, fundamental diagrams are drawn for uni- and bidirectional flows. Analyzing pedestrian speed in all sidewalks shows that speed entropy in unidirectional flow is more in comparison to bidirectional ones. https://jte.sinaweb.net/article_92664.html One of the important properties of roads related to road pavement and safety is skid resistance. These properties is dependent on numerous factors, such as properties of pavement surface texture and materials used, weather conditions, seasonal changes and road surface contaminant. In this study the effects of various contaminants on skid resistance of the pavement surface were investigated .The presence of contaminants, especially during the first rain after a drought period makes 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. In this study, dust, quick sand, lube oil, rubber particulates, soot and cool color traffic were chosen as contaminants. Asphalt samples using three continuous grading with Gyratory compression were made in Marshall large formats and by British Pendulum Tester were tested at different temperature and humidity. It was proved that contaminants affected skid resistance of asphalt pavements distinctly. It was also shown that in the dry conditions, the minimum value of skidding is when the surface is completely covered with quick sand and in the wet conditions; the value of skidding was declined on average 49 to 55 percent by cool color traffic. The data were derived from the Statistical model, were analyzed by decision tree and artificial neural network. It was shown that changes in the type of contaminants cause the greatest change in skid resistance. https://jte.sinaweb.net/article_92665.html This article reflects the findings of a study on the impacts of countdown timers on safety and performance of traffic at signal controlled intersections. Parameters such as late-stopping ratio, early start ratio, number of red light violations and number of accidents were examined to consider safety impacts of these timers. Additionally, saturation flow rate, saturation headway and start-up delay parameters examined to compare traffic performance at 6 intersections where the countdown timers where left on and then switched off. Data required for this purpose were provided from the video recordings of video surveillance cameras. Comparison between the timer on and off situations showed that the number of red light violations reduced by about 1.16% , when the timer was on , The number of accidents showed no clear variation and early start ratio increased by about 1.7% when the timer was on. However, Mann-Whitney test based on a 95% Confidence interval showed that there is no significant difference in these parameters. Late-stopping ratio on average reduced by about 2.34% when the timer was on and Mann-Whitney test results showed that there is significant difference between the two situations. . Investigation on start-up delay parameter indicated that there is a significant difference between the two situations. In this regard, start-up delay of all the intersections increased by about 22.8% when the timers were off. The t test for analyzing saturation headway and saturation flow rates indicated that there is no significant difference between the two situations. https://jte.sinaweb.net/article_92666.html 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 2to6 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 provide 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. https://jte.sinaweb.net/article_92668.html Evaluation of the effects of polypropylene additive on moisture damage properties of asphalt mixtures abstract: Different methods are used for reducing the effects of moisture damage in asphalt mixtures. Hydrated lime and amin-materials are conventionally used as anti striping additives. The polymeric materials have basic properties and they might reduce the acidic properties of binders. Hence, the effects of one polymeric material named Polypropylene (PP) additive were investigated on the moisture damage of asphalt mixtures. For this purpose, different asphalt mixtures were fabricated using granite and limestone aggregates as well as 0, 2, 4% PP additives. Indirect tensile strength tests were applied on 1, 3 and 5 freeze–thaw conditioned mixtures based on AASHTO T283 standard method. Also, surface free energy tests were used for determining adhesion properties of base binder, modified binders and aggregates in different conditions. Obtained results showed that PP improves the strength of asphalt mixtures in wet and dry conditions. In general, it seems that the use of PP up to 4 percent decreases the moisture sensitivity of asphalt mixtures. Also, the results of surface free energy tests showed that PP increases the free energy of adhesion. Thus, adhesion properties improve between asphalt binders and aggregates. https://jte.sinaweb.net/article_92669.html The need to reduce the use of cars and the use of public transport should be the main goal of transport management policies. One of these policies is to determine the city's central zone and receive a toll from passengers arriving at this zone. Two different methods including stated preference and revealed preference are used. In this research, the aim is to create the possibility of modeling the pricing policy of the city's central zone and to study the results before the implementation and review the effect of improving the public transportation system on it. The stated preference method is used to examine the effect of the pricing policy of entering the zone in terms of improving the public transportation system. In this regard, modeling has been done with discrete multi-choice logic models for more precisely modeling, this modeling is done by business trips and shopping trips. To do this research, data collection was carried out through personal interviews with personal vehicle users for the purpose of travel trips and shopping trips, respectively. Interviewees (182 different drivers) interviewed by questions about travel characteristics, socio-economic features and their options in terms of pricing policies for personal vehicle access. The values of variable coefficients for entering the PRICE zone in the Utility Function of Multiple Logit models are equal to -0.00033 and -0.00032 for business and hopping trips respectively, and their elasticity are -0.6394 and -0.6350, indicating that the increase of price has the greatest effect on business trips. https://jte.sinaweb.net/article_119610.html Satisfying the healthcare needs of patients at home have so many advantages in today’s world. Providing an orderly series of health services both decreases the costs and speeds up healing of patients. For instance by replacing hemodialysis with peritoneal dialysis which can be done at home, patients feel more comfortable and the medical expenses would be lower. In this paper a periodic robust vehicle routing mathematical model with simultaneous deliveries and pickups and soft time windows to serve peritoneal dialysis patients at home is developed. The model is built according to the issues and problems seen in dialysis center of Hasheminejad kidney center. It has been tried to consider realistic assumptions in the model design, such as the uncertainty in the travel time of the vehicle. Having the sensitiveness of providing timely healthcare service in mind, a method should be applied to face the uncertainty in time which guarantees minimum risk. Results show that the presented robust model at the worst condition or in other words at the maximum uncertainty level has no constraint violations. It means that by using this model the chance of providing timely health service would be enhanced. https://jte.sinaweb.net/article_120392.html The effect of cement as a filler in reducing the moisture sensitivity of hot mixed asphalt Abstract Moisture is one of the most important reasons of asphalt stripping. The removal of moisture effects on hot mixed asphalts is one of the most important problems in pavement engineering; one solution to reach this goal is the use of different kinds of additives during mixture procedure. Portland cement can be used as a substitute of filler in hot mixed asphalt. In this paper the results of a research program conducted to evaluate the effect of cement in reducing the moisture sensitivity of asphalt are presented. The experiments of this research are designed to assess the effect of long term humidity conditioning on hot mixed asphalt. The results indicate that the effect of cement in reducing the water susceptibility of asphalt strength is time dependent and anti stripping effects in early stages after mixture is not considerable.The results reveal that cement has a suitable long term moisture sensitivity reducing effect which can be attributed to the time dependence of chemical reactions. Keywords: Hot Mixed Asphalt, Portland Cement, Moisture Sensitivity, Additives, strength, time dependency https://jte.sinaweb.net/article_119373.html Public transportations have the most important role in the development of modern societies. So the existence of traffic in the modern societies caused different kinds of problems and difficulties in these societies. However the rail transport has a positive effect on the passengers’ movements and even goods. It is necessary to examine different factors of this type of transport such as travel convenience, time of travel and the amount of energy consumption in order to enhance its performances. One of the best methods in the reduction of energy consumption process is implementing the optimized profile of train speed. There are a variety of algorithms and methods based on the energy efficiency. This thesis aims at finding a linear hypothetical model with selective data considering dynamic motion of train including slope of the track and examining 3 stations with the lowest and highest slope , with 3varibales (1,3and5) using imperialist competitive algorithm (ICA) in MATLAB and programming coding in M file to get optimized speed profile which results in less fuel consumption. Finally the results taken from ICA and genetic method will be compared with regard to the number of recourse to the cost function and convergence speed. https://jte.sinaweb.net/article_88369.html In this paper, using the concept of game theory, we propose an attacker-defender (AD) model to investigate the vulnerability of a rail transportation network against malicious attacks. The idea emerged in this paper is rooted in the consequences (especially the traffic and transit operational consequences) of the terrorist attack on 17th Khordad, 1396, to the building of the Parliament of Iran and the closure of the station connected to it (i.e. Baharestan metro station). The purpose of this study is to provide a methodology for identifying the most critical metro station in a situation where there is no possibility of boarding or alighting passengers at that station. The model presented in this study is a two-stage optimization problem that is defined as a game between the attacker and the users. In this paper, after formulating the problem, a solution algorithm is devised to dealing with the problem. as result with this formulation the most likely station exposed to attack is identified. https://jte.sinaweb.net/article_79655.html Various parameters include personal or human behavioral factors, environmental factors, road geometry and vehicle characteristics causing traffic accidents. However there has been little empirical examination of the relationship between urban form and pedestrian accidents. Therefore, this study examined the effect of different urban form parameters on pedestrian crashes by considering city block, street network and land use for the city of Mashhad in Iran during time period of 3 years (1391-1393). To do so, we developed a geo_statistical database of crash incidence and urban form parameters. Required raster layers with 20 m pixel size, have been prepared in a spatial database containing 111,537 pixels. Finally the data were entered into SPSS software and modeling has been done. The results of the study indicate that with increasing distance from commercial land use, the number of pedestrian accidents decreases. In organic zones the higher number of accidents has been occurred than grid networks. Also larger blocks, indicated significantly lower pedestrian accident rates than the other block group acreages. https://jte.sinaweb.net/article_79657.html The 22% share of taxis in urban passenger trips, in a city like Tehran, addresses the major role of the TAXI operation system compared to other competitive transport modes. Despite the apparent difference in the model of taxi operation in Iran compared to other countries, adequate researches have not been taken to assess how to increase the efficiency of operation of Taxis. Among the different functions of TAXIs, shuttle TAXIs could be addressed as one of the important ones. The result of this situation is that in the cities of Iran, the time spent by passengers is greatly wasted until the completion of the taxis' capacity during non-peak hours, and hence the decrease of the level of utility of taxis for passengers. Similarly, at peak hours, TAXIs engage in heavy traffic during these hours, causing long wait times for travelers to access a shuttle TAXI. The present study suggests that if regular scheduling for TAXI movements and changing the way taxis work from time response to time scheduled, then increasing the utility of this user for demand could also increase the income of active shuttle TAXIs. Results indicate that by inserting the proposed time table the income of each driver would be increased up to 21% whereas the average waiting time of passengers to get the TAXI at origin/destination stations would not be worsened meaningfully (average waiting time would decrease 26 seconds at Sadeghieh station and increases 14 seconds at the university station). https://jte.sinaweb.net/article_88169.html In addition to low-temperature cracks and fatigue cracks, the high-temperature rutting is one of the main failures of asphaltic mixtures. In previous research, in order to investigate the rutting potential for hot-mix asphalt, it has been underestimated that these mixtures are non-homogeneous combinations of aggregate materials, bitumen and voids, and the macro-structural parameters such as rut depth are often used to evaluate the mechanical performance of the mixture, while the aggregate arrangement and parameters such as contact length seem to play an important role in the rutting performance of the mixture. In this paper, using image processing (iPAS2 software) on the cut samples, the contact length of aggregates and its effect on the rutting performance of 16 types of mixture (two types of grading, two types of bitumen, two types of aggregate and two types of filler) is analyzed and evaluated. The rutting performance of the mixture is investigated using dynamic creep and wheel tracking tests. The results show that the rutting performance is dependent on the contact length of aggregates in the asphalt mixtures, and in this sense, the analysis of asphalt mixtures provides very useful information which can be used even as a control tool in the design of asphalt mixtures. https://jte.sinaweb.net/article_77225.html A Location-Arc Routing Problem (LARP) is a practical problem, while a few mathematical programming models have been considered for this problem so far. To the best our knowledge, it is the first time that a mixed non-linear bi-objective programming model is proposed for a multi-period LARP with time window and risk of robby valuable product. In the proposed model, vehicles can meet the customer for delivery or receive product. 22 standard problems are solved with the ε-constraint method, MOPSO, MOBA, MODA and NSGA-II. The computational results are shown the efficiency of the MODA on indicators of multi-objective problems for solving them. The deviation of the MODA objectives with the ε-constraint at the extreme is equal to 1.32% and 0.45% average. The proposed model is used for solving the location problem of the treasury of a bank as a case study. The case study is a node routing problem with nearby nodes that has transform to arc routing. According to the rules, experts have selected 13 treasuries between 18 candidates, that the Pareto boundary provided by the MODA for the 10 case studies. https://jte.sinaweb.net/article_90944.html The performance of unbound granular layers, such as base and subbase, is evaluated by various methods. Non-destructive test equipment such as LWD is an appropriate method that, in addition to increasing the speed and accuracy in comparison with destructive methods, evaluates the structural properties of unbound granular material properly. The most important output parameter of the LWD is a modulus that influences various factors such as inherent and massive properties of unbound granular material. In this research, the LWD modulus was determined in different conditions using aggregates based on Grain No. 5 of 234 code. For this purpose, compaction, moisture content, stress level and saturation level were selected as factors affecting the unbound granular material modulus. Using the response surface method, the intended experiments were designed. The results of the experiments showed that the compaction-moisture model has a better interpretation than compaction-saturation and moisture-saturation models, and the interaction of compaction and moisture has a significant effect on the LWD stiffness modulus. Also, the results showed increasing in the modulus of LWD in the form of exponential correlation due to increasing of LWD weight. Finally, the compaction-moisture model was compared with other similar models and it was found that the coefficient of determination of the proposed model is significantly higher than other models and, unlike other models, has a compaction-moisture parameter explaining the interaction effect of compaction and moisture on the LWD modulus. https://jte.sinaweb.net/article_119374.html The large number of parameters in urban networks, makes them one of the most complicated problem in the real life and affects traffic and transportation engineering and urban design. The large number of parameters forces problem solvers to ignore lots of them. Eigenvector centrality measurement is a powerful tool that provides many valuable information from a large network for urban planners and managers, but has two drawbacks; 1) the eigenvector centrality measurement is not able to calculate the centrality values for a network withmore than one parameter (namely multi-layer network), 2) It does not return true values for some features. In this paper, we address to solve both drawbacks of eigenvector centrality measurement to use in urban network related problems. Two validation factors to evaluate the proposed method is innovated; similar layers and similar nodes validations. The proposed method passes two validation factors. Two case studies are solved to show the application of proposed method in urban related problems include traffic light phasing and detecting the central part of Shiraz city by two features; like length and link width. Experimental results and case studies, show the efficiency and reliability of proposed method. https://jte.sinaweb.net/article_113746.html In this research paper, a new method is proposed to solve the traffic light phasing problem which distributes the traffic in the network and increases the efficiency of urban traffic networks. The method manages the traffic light phasing by local variables and control the entire traffic of network by common variables between neighbor junctions. The contribution of this paper, is scheduling traffic lights using eigenvector centrality, avoiding regular phasing cycles and global traffic control. This method is based on eigenvector centrality method and a matrix which is called “Junction Matrix”. The junction matrix includes the relation between a junction, its connected links and its neighbor intersections. The efficiency and reliability of the proposed method is evaluated by simulating 5 traffic scenarios over two networks. The networks are generated based on cell transmission model with two different sizes and two way links. Two indicators, “the number of jammed cells”, and “MFD”, are used for evaluation goals. The simulation results indicates the improvement in traffic light phasing problem by the proposed method. https://jte.sinaweb.net/article_154265.html 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. https://jte.sinaweb.net/article_206430.html With the development of industry and the increase in the movement of goods in the world, the role of rail transportation has become more colorful than before. The main weakness of rail transportation compared to road transportation is its network delays. One of the main causes of delays in the rail network is the delay in unloading and loading. In this research, first, the factors affecting the time of train unloading and loading operations and its appropriate solutions have been investigated. Then, according to the results of the studies, the focus is on reducing the time of unloading and loading operations in the container rail terminals. To reduce operation time, a mathematical model based on mixed integer programming is proposed. In addition to the exact solution of the proposed model, the model has been solved with meta-innovative algorithms of particle swarm and colonial competition in various dimensions. Finally, by comparing the performance of the particle swarm algorithm with the colonial competition algorithm, the result was that the particle swarm algorithm performs better than the Imperialist Competitive Algorithm for larger problems. Using the model provided in container rail terminals, it is possible to schedule the sequence of tasks for cranes, trucks and other equipment in a short period of time and provide them to the terminal operators on a daily basis. https://jte.sinaweb.net/article_206431.html Buses are the most common and widely used means of public transportation and in Tehran, on average, 2 million and 100 thousand trips are made daily using this mode. Because drivers of these vehicles are engaged in repetitive activities on a daily basis, they are highly prone to burnout. Burnout can severely affect drivers' performance and affect their behavior and driving style. In this study, the relationship between burnout and driving style of Tehran city bus drivers has been investigated. Data were collected using self-reported questionnaires in collaboration with the Tehran and Suburbs Bus Organization and the collected data were analyzed using SPSS software. The results show that the incidence of burnout can increase the tendency to negative and dangerous driving styles and reduce the tendency to positive and safe driving styles. In this study, for each of the driving styles associated with burnout, a multiple regression model was presented in which the driving styles as a dependent variable and the dimensions of burnout as independent variables. https://jte.sinaweb.net/article_213831.html Discovering patterns among traffic crashes has always been a focus for various researchers. By identifying correlations between these incidents, they aim to propose strategies to prevent crashes. With the increase in crashes and, consequently, the number of injuries and fatalities in recent years, analyzing crashes and uncovering their relationships has become essential. Therefore, in the present study, we delve into the analysis of rural traffic crashes in Isfahan province using correspondence analysis and multiple correspondence analysis, through which hidden patterns among these crashes are identified. Initially, we employ correspondence analysis to explore the human factor in crashes, which plays a role in over 90 percent of crash occurrences. Three meaningful categories are identified, representing a novel aspect of this research. Subsequently, we apply multiple correspondence analysis to analyze the crashes. The results reveal that the crashes in Isfahan province can be broadly categorized into four groups. Notably, the model developed in this study exhibits significantly higher accuracy compared to models used in previous studies. This research introduces the use of correspondence analysis and multiple correspondence analysis models for the first time in crash data analysis, providing a new tool for analysts and researchers. https://jte.sinaweb.net/article_213832.html This comprehensive study investigates the complex factors influencing high-risk driving behaviors and crash likelihood among commercial vehicle drivers. Based on the research findings, perceived social acceptance of high-risk driving was positively associated with subjective norms regarding such behaviors (0.63). These subjective norms, in turn, had a strong positive relation with pro-high-risk driving attitudes (0.70). Conversely, negative beliefs about the consequences of high-risk driving were negatively associated with attitudes toward those behaviors (-0.54). Personality traits like extraversion and psychoticism showed moderate positive relationships with accepting attitudes toward high-risk driving (0.42). Personal acceptance of high-risk driving behaviors itself strongly predicted positive attitudes (0.77).The driver's affect and mood state negatively impacted risk perception (-0.62), with lower perceived risk associated with increased intention for high-risk driving (-0.74). Compliance and enforcement actions positively influenced perceived behavioral control over risky acts (0.50), which then positively predicted deliberate engagement in those behaviors (0.60). Notably, attitudes emerged as the strongest predictor of behavioral intentions (0.75), with cautious attitudes relating to safer intended behaviors, and risk-accepting attitudes associating with riskier intentions.The findings highlight the importance of targeting multiple factors to promote safer commercial driving, including core beliefs about the consequences of high-risk behavior, perceived social norms, personal acceptance of risky practices, relevant personality effects, and accurate risk assessments. https://jte.sinaweb.net/article_213834.html Marine transport rising along with demand and supply abundance disclose the vital role of this mode in global supply chain which made the ports as important logistic hubs of this chain. Therefore, an efficient plan for improving services and optimal use of port equipment in the competitive condition is essential. The current study aims to utilize algorithms for optimizing the seaside operations problems scheduling in Shaheed Rajaei port in Iran. To this aim, Mixed Integer Linear Programming models were used for modeling the berth allocation, quay crane assignment, and quay crane scheduling with two integrating approaches. The models were validated by GAMS and a combination of Particle Swarm Optimization with Dynamic Programming methods were used for estimating the near optimal solutions. The objective function minimizes the imposed costs related to difference of berthing location from best location, difference of end service time from determined departure time, number of assigned cranes, and number of crane setups in every vessel. According to results, the deep integrated model with the developed QCSP algorithm that solved with PSO performed better than the functional integrated with combined methods. Findings could be helpful in costs management in studied port. https://jte.sinaweb.net/article_232586.html Although motorcycles provide less safety for their users, their use has been widespread, especially in developing countries, due to fundamental advantages such as lower ownership and operating costs compared to cars. However, motorcycle accidents account for a high share of deaths and injuries in urban traffic accidents. Studies show that the use of standard helmets is the most effective way to reduce these injuries. However, the main challenge for policymakers in the areas of health and traffic is the low willingness of motorcyclists to wear helmets. Accordingly, in the present study, by using questionnaires completed by Yazd motorcyclists and using the dual logistic regression method, the factors affecting the use or non-use of helmets were examined and the intensity of their effect was measured. After confirming the validity and reliability, the questionnaires were designed and categorized based on 10 factors. The findings showed that in general, three groups of factors, including motorcyclist attitudes, helmet characteristics, and the level of enforcement of traffic laws, play a role in the decision to use helmets. In particular, "low awareness of the laws" had the greatest deterrent role. After that, "physical problems with helmets", "dissatisfaction due to heat" and "weakness in law enforcement by the police" are in the next ranks. Also, factors such as "misperception about the low probability of an accident", "misbelief about the effectiveness of helmets", "high cost of helmets" and "fear of social judgment" also had a significant negative effect on helmet use, although with less intensity. https://jte.sinaweb.net/article_232587.html The railway transportation industry, as one of the vital transportation infrastructures, is experiencing a profound transformation towards digitalization and utilization of Industry 4.0 technologies. This research was conducted with the aim of prioritizing key factors affecting digital maturity assessment in the railway industry. In this study, first, through an expert panel including 15 specialists in the railway industry and Industry 4.0 technologies, eight main dimensions were identified including advanced Industry 4.0 technologies, cybersecurity and digital risk management, sustainability and environmental compatibility, practical applications and performance improvement, indigenous infrastructure and technical readiness, knowledge management and human capital development, digital economy and new business models, and digitalization challenges and obstacles. Then, using the Fuzzy Best-Worst Method, these dimensions and indicators related to each dimension were prioritized. The results showed that the advanced Industry 4.0 technologies dimension with a weight of 0.285 is in the first priority. In this dimension, the level of artificial intelligence utilization in operational processes with a weight of 0.312 was identified as the most important indicator. The calculated fuzzy consistency indices were less than 0.10, indicating the validity and reliability of the results. The findings of this research can be used as guidance for managers and policymakers in the railway industry in resource allocation and strategic planning for digital transformation. https://jte.sinaweb.net/article_236800.html The current study aims to investigate the role of psychological factors affecting the tendency and behavior of choosing public transportation for university trips. In order to investigate the psychological factors affecting the choice of travel mode, the theory of planned behavior was used. Since universities are attractive for travel and the study of student travel and the growth of travel modes for them will have a wide impact on society, in the present study, 398 questionnaires were completed by students from Isfahan University and Isfahan University of Technology. The structural equation modeling method was used to examine the relationships expressed in the theory of planned behavior. The results showed that individuals' attitudes toward public transportation have the most direct and significant effect on individuals' tendency and intention to use public transportation. After that, attitudes toward personal transportation have an inverse effect and subjective norms have a direct effect on the willingness to use public transportation. Accordingly, it was suggested that students' attitudes should be changed through appropriate education and advertising, and that by strengthening people's understanding of the benefits of public transportation, people should be led towards improved public transportation. https://jte.sinaweb.net/article_236802.html Lane changing is one of the most critical driving maneuvers, playing a significant role in both traffic safety and flow efficiency. The aim of this study is to develop and compare machine learning models for short-term prediction of drivers’ lane-change behavior on freeways. For this purpose, high-resolution microscopic data from the Next Generation Simulation (NGSIM) dataset were utilized, and two predictive models—Long Short-Term Memory (LSTM) neural networks and Support Vector Machines (SVM), were designed and evaluated. Predictions were performed for time horizons ranging from 1 to 5 seconds prior to the lane-change maneuver in order to assess the effect of prediction horizon on model performance. Evaluation metrics, including Mean Squared Error (MSE), Recall, and F1-score, were applied to assess model accuracy. The results indicate that the LSTM model significantly outperformed SVM across all evaluation criteria and achieved the highest accuracy with the lowest error in short-term horizons (1–5 seconds). Furthermore, statistical analysis revealed that lane-change maneuvers were more frequent in the right lanes of the freeway. The findings of this study can contribute to the design of advanced driver-assistance systems (ADAS) and the development of accurate predictive algorithms for semi-autonomous and autonomous vehicles. https://jte.sinaweb.net/article_236803.html This study quantifies the effects of the structural components of in-cabin music on driving performance and physiological arousal in a within-subject design with 50 licensed drivers. Fifteen music scenarios, derived from a fractional factorial plan manipulating three structural variables—emotion conveyed by the music, tempo, and playback volume—were implemented in a driving simulator; scenario order was counterbalanced with 5-min inter-scenario breaks. The physiological index was recorded from a GSR sensor as skin resistance (SR) and mapped to a unified metric Arousal Index = −z(log SR); performance measures included driving errors, mean/variability of speed, lateral lane deviation, and reaction time. Music-attitude profiling via PCA confirmed data adequacy and, using k-means, yielded an optimal K = 5 attitude typology. Clustering on performance–physiology features revealed four stable driver response types (K = 4; Silhouette = 0.463): (1) low errors/low arousal, (2) medium errors/medium arousal, (3) high errors/high arousal, and (4) low errors/high arousal. Within-subject tests showed significant differences across musical conditions (Friedman for errors: χ² = 24.33, df = 2, p < 0.001; for SR/Arousal: χ² = 22.11, df = 2, p < 0.001); Wilcoxon pairwise comparisons with Holm correction indicated robust contrasts for happy ↔ anxiety-inducing and sad ↔ anxiety-inducing music across both domains (p ≤ 0.003), while happy ↔ sad differed only in SR/Arousal (p = 0.021). Findings indicate that music-induced arousal modulates both behavioral safety and physiological state, and that inter-individual heterogeneity is decomposable into stable response types. https://jte.sinaweb.net/article_244128.html Road traffic accidents are a major public health issue in Iran, causing considerable fatalities and socio-economic losses annually. Given travel pattern changes during special periods such as Nowruz (Persian New Year), this study analyzes differences in traffic accidents during Nowruz and non-Nowruz periods across all Iranian provinces, using seven years of data (2016-2023). It examines variations in the share of urban and rural crashes and identifies key patterns involving vulnerable road users, particularly pedestrians and motorcyclists. Results show that during Nowruz, fatal crashes on rural roads are, on average, three times more frequent than those on urban roads, a pattern that remains relatively stable in non-Nowruz periods. Furthermore, the pattern of crash fatality locations is nearly similar in both time periods, in which while most deaths occur at the scene of crashes in rural areas, most victims are more likely to die after being transported to the hospital in urban areas. While the percentage of rural accidents increases during the Nowrouz, the rate of urban accidents is higher in some provinces. Additionally, pedestrian crashes in certain provinces, particularly in Alborz and Kermanshah, account for a significant proportion of accidents. While motorcycle crashes are more prevalent during the non-Nowruz period, provinces such as Qom and Tehran have high rates of these crashes. This research indicates that different provinces have unique characteristics in terms of accident occurrences, highlighting the need for informing appropriate strategies to the specific conditions of each province and road type, especially during both regular and holiday periods. https://jte.sinaweb.net/article_244129.html Understanding the behavioral patterns that influence motorcyclist accidents plays a significant role in developing traffic safety programs. The objective of this research was to investigate the relationship between motorcyclists' behavioral factors and the rate of accidents and near-miss incidents among riders in Isfahan. The standard "Motorcycle Rider Behavior" questionnaire was revised, with several items added to suit Iranian conditions. After data collection, Exploratory Factor Analysis identified four main factors: "Risky, Showy, and Impulsive Behaviors", "Intentional Violations", "Non-adherence to Safety Equipment Principles," and "Perceptual and Cognitive Errors". To evaluate the impact of these factors, two count regression models namely, "number of accidents in the last two years" and "number of near-miss incidents in the last three months," were developed. The results indicated that in both models, all behavioral factors were significant. However, the "Intentional Violations" and "Risky, Showy, and Impulsive Behaviors" factors had the greatest impact, with standardized coefficients of 0.8 and 0.6 in the first model, and 0.49 and 0.44 in the second. Among the 24 behaviors examined, "Failure to use turn signals" and "Changing lanes without checking mirrors" (with an average score of 3.3 out of 5) were identified as the most common high-risk behaviors. Behaviors such as "Using a mobile phone," "Failure to observe the speed limit," "Overtaking from the right," and "Weaving between lanes" (with an average score of 2.9 out of 5) ranked next. The findings of this research can be used to develop educational interventions, oversight measures, and policy-making for enhancing the safety of motorcyclists. https://jte.sinaweb.net/article_244130.html The international road transport industry, as one of the core pillars of the global supply chain, is facing challenges in terms of competitiveness and customer relationship management. In this context, identifying and clustering key customers based on value creation criteria represents an innovative approach to enhancing efficiency and strengthening companies’ competitive advantage. However, the multi-layered dimensions of customer value creation have received limited attention from researchers. Accordingly, the purpose of this study was to identify and cluster key customers in industrial markets based on value creation criteria. This research is considered a mixed-method study. In the qualitative phase, customer value creation criteria were elicited, while in the quantitative phase, the customer lifetime value (CLV) of key industrial customers was first calculated using a formulated equation, and subsequently, clustering was performed based on the elicited criteria. In the qualitative section, the sample consisted of 14 experts selected through purposive non-probability sampling. In the quantitative section, purposive and convenience sampling was employed to calculate the CLV of key customers, involving 42 companies. The K-Means method was then applied for clustering. The findings revealed that key industrial customers were grouped into three clusters: (1) Golden Low-Interaction Customers—customers with high revenue per transaction but fewer transactions compared to other clusters; (2) Silver Growth-Potential Customers—customers with a high number of transactions and continuous engagement, generating moderate revenue yet demonstrating a high renewal rate; and (3) Bronze High-Interaction Customers—customers with the highest number of transactions but very low revenue. https://jte.sinaweb.net/article_244131.html Enhancing the quality of public transportation while simultaneously minimizing the total person delay (including both private-vehicle and transit passengers) constitutes a core objective in modern urban traffic management. A key approach to achieving this dual objective is the implementation of Intermittent Bus Lanes Priority. A novel and adaptive method for implementing this strategy is proposed in this study, and its performance is evaluated via microscopic simulation of a 5.5-km corridor containing seven signalized intersections in Isfahan using Aimsun Next. Two comparative scenarios were modeled for this corridor: (1) the existing condition with a dedicated bus lane, and (2) the proposed Intermittent Bus Lane Priority Strategy. The existing traffic volumes under normal and saturated flow conditions, along with various bus headways, were examined to enable a more detailed assessment of the impacts of intermittent priority under different traffic states and bus operational conditions. The primary performance indicator used for evaluation was the total passenger delay across the entire simulated transportation network, which was considered a comprehensive metric of overall system efficiency. The results demonstrate that the proposed strategy significantly improves network efficiency, reducing the Total Person Delay by up to 24.4%. Furthermore, under saturated traffic conditions, the car delay decreases remarkably by up to 28.2%, despite a slight trade-off observed as an increase in bus delays, ranging from 4% to 13.9. The study's findings indicate that, given the current infrastructure in the country, this approach holds significant potential for achieving substantial improvements in the efficiency and performance of urban transport networks. https://jte.sinaweb.net/article_245409.html Urban street design is closely interrelated with land use; each land use has its own trip attraction and generation. Any change in land use characteristics can alter travel patterns. Mixed-use land uses are considered important due to their high trip generation and attraction. In this paper, the CODAS model has been used to evaluate the traffic safety impacts of mixed-use land uses( its ability to provide double-check control of the results). By combining different functional classes and different land use groups, twenty mixed-use land uses in the city of Tehran were selected and examined. After categorizing the criteria related to land use and the street, the combined Shannon entropy and Best-Worst Method (BWM) was used to weight the criteria. According to the results, the highest weight in the land use section belongs to "building floor area" (0.324), and in the street section to "accident severity index" (0.226). Subsequently, street segments containing these land uses were ranked in terms of traffic safety using the hybrid CODAS model. This study is based on the combination of the considered land uses. According to the results, mixed-use land uses with construction group D located adjacent to the highway functional class have a higher safety risk, followed by group C adjacent to highway roads. The results of this research can be used for prioritizing and improving the safety of mixed-use land use areas, allocating safety budgets in the respective areas, and implementing the Code23 of the National Building Regulations regarding traffic requirements for buildings. https://jte.sinaweb.net/article_245410.html Road safety and accident reduction remain among the most critical transportation challenges worldwide. A comprehensive analysis of accident risk and an evaluation of the safety performance of safety management units play a crucial role in the formulation of safety policies and the effective allocation of resources. The objective of this study is to identify relevant risk indicators and develop a composite index for the comprehensive assessment of accident risk across safety management units. Iran’s provinces were selected as the case study. In this research, risk indicators were categorized into three main groups: general risk, traffic risk, and road risk. The indicators were evaluated based on available data, and the provincial Composite Risk Index (CRI) was calculated using the mean values of the three indicator categories. The standard deviation of the indicators was analyzed to assess the stability and homogeneity of the risk conditions within each province. The results indicate significant variation in CRI values across provinces. Provinces such as Markazi was classified as high-risk, whereas Khuzestan was categorized as low-risk. Furthermore, the analysis of standard deviation revealed considerable variability in certain provinces, including Tehran and Sistan-Baluchestan, highlighting the importance of accounting for data dispersion in risk analysis and decision-making processes. The methodological framework proposed in this study, along with the application of the CRI composite index, provides a robust tool for ranking and comparing management units. It can serve as a foundation for prioritizing preventive interventions and optimizing the allocation of limited resources in the pursuit of improved road safety. https://jte.sinaweb.net/article_245514.html Identifying key components of urban transportation networks to enhance resilience, reduce vulnerability, and optimize traffic flow is a fundamental issue in transportation planning. In this study, an analytical framework based on graph-theoretical centrality concepts and matrix–tensor structures was developed to determine and prioritize the relative importance of network components. To this end, three incidence matrices—route–street, street–intersection, and route–intersection—were defined, and a three-dimensional tensor was constructed to represent the multilayer relationships of the network simultaneously. Degree, betweenness, and eigenvector centrality measures were then computed based on these structures and integrated through normalization and weighted aggregation. The proposed framework was implemented on the benchmark Nguyen–Dupuis network consisting of 13 nodes and 38 links. The results indicated that nodes 6, 11, and 5 exhibit the highest composite centrality values, and selecting the top five nodes covers 92.3% of the network routes. Sensitivity analysis further revealed that the tensor-based criterion can highlight inter-layer nodes that are not identified by classical methods. The findings suggest that the combined use of incidence matrices and tensor structures provides deeper insight into the functional organization of transportation networks and can support more effective strategies for maintenance prioritization, alternative route design, and system resilience enhancement. https://jte.sinaweb.net/article_245605.html In response to the necessity of traffic analysis at oversaturated intersections with non-lane-based vehicle behavior, this study proposes a framework comprising pre-processing, frame stabilization, georeferencing, and vehicle detection and tracking for the automated estimation of intersection performance measures. To this end, vehicle detection and tracking were performed on imagery from the Tohid intersection in Tehran using the YOLOv8 model and the ByteTrack algorithm, respectively. A mean Average Precision (mAP@0.5) of 0.961 for the detection model indicated its high accuracy. Subsequently, intersection performance indicators were calculated and analyzed based on the extracted trajectories and field data. The analyses reveal a functional imbalance across the intersection arms; specifically, the East and West arms face discharge challenges, recording low average exit speeds (15 and 22 km/h, respectively) and limited entry saturation flow rates per unit width (327 and 317 veh/h/m). In contrast, the North and South arms demonstrated better performance, with higher exit speeds (32 and 23 km/h, respectively) and adequate entry saturation flow rates per unit width (567 and 535 veh/h/m). However, delays exceeding 80 seconds at all entries and the degradation of the overall intersection Level of Service (LOS) to grade F indicate critical conditions and the necessity to revise the geometric design or signal timing. The findings of this study demonstrate that the proposed framework provides an efficient platform for estimating traffic variables and analyzing the performance of signalized intersections.