http://www.ijte.ir/ International Journal of Transportation Engineering en daily 1 Thu, 01 Jan 2026 00:00:00 +0330 Thu, 01 Jan 2026 00:00:00 +0330 http://www.ijte.ir/article_236806.html Maintaining pavement friction under wet conditions requires surface textures that withstand traffic-induced polishing and wear. This study evaluates how the coordinated adjustment of maximum aggregate size (MAS), aggregate gradation, packing density, paste film thickness (PFT), and mortar film thickness (MFT) governs skid resistance in slip-formed concrete pavements. Twenty mixtures were produced with Modified Fuller–Thompson exponents (0.67, 0.55, 0.45, 0.35) at MAS = 9.5, 12.5, 19, 25, and 37.5 mm. Tests included slump and Box Test, wet packing density, PFT/MFT, compressive and flexural strength, EN 1338 abrasion, ASTM E303 British Pendulum Number (BPN), Mercury Intrusion Porosimetry (MIP), and Scanning Electron Microscopy (SEM) of the Interfacial Transition Zone (ITZ). The results indicate that mixtures with MAS = 19–25 mm provided the best overall balance—higher compressive and flexural strengths, BPN typically ≥ 65, and lower abrasion rates. The study indicates that coordinating packing density with PFT and MFT—within a compatible gradation—enhances mechanical properties as well as skid resistance. http://www.ijte.ir/article_236023.html Shuttle services have become an increasingly popular mode of transportation, particularly in areas where direct access to public transit is lacking. This study focuses on the utilization of shuttle services at Abbaspoor University in Tehran, Iran, and aims to identify the key determinants of students' willingness to use these services. A stated preference survey was conducted to gather data on student preferences, with the questionnaire divided into three sections: socio-economic information, travel behavior, and stated preference scenarios. The survey results were analyzed using a binary logit model to assess the impact of various factors on the adoption of shuttle service. Findings indicate that shuttle services are instrumental in reducing reliance on private vehicles and alleviating traffic congestion. The binary logit model results show that students who commute by metro are 33% more likely to use the shuttle, while car ownership decreases the probability of shuttle adoption by 9%. Moreover, increasing shuttle headways significantly reduces the likelihood of use: from –0.11 at 15 minutes to –0.42 at 60 minutes, underscoring the critical role of service frequency. The model achieved a prediction accuracy of 71% with a McFadden’s ρ² of 0.225, indicating a satisfactory fit.  The study provides valuable insights for the design and implementation of shuttle services in university settings, particularly in developing countries with limited public transportation infrastructure. The results underscore the importance of strategically located shuttle stops and highlight the role of shuttle services in enhancing accessibility, equity, and sustainability within the broader transportation ecosystem. http://www.ijte.ir/article_181129.html Roundabouts are recognized as effective traffic management solutions, offering advantages such as improved safety and reduced congestion compared to signalized intersections. However, exceeding the roundabout's capacity can result in decreased efficiency and safety. The capacity of a roundabout depends on various factors, including traffic flow rates, geometric design parameters, and traffic flow characteristics. This study investigates the influence of weaving length, entry radius, and exit radius on the capacity of a roundabout in Sanandaj, utilizing AIMSUN traffic simulation software. Statistical and computational methods are applied to analyze data obtained from parameter analysis. The findings emphasize that imbalanced dimensions and a limited perspective in transportation network design contribute to traffic congestion. Consequently, comprehensive consideration of geometric and behavioral aspects of users within the transportation network is crucial when designing roundabouts. This analytics-driven study provides valuable insights and patterns, enabling the development of original content that surpasses existing research, ultimately facilitating the identification of areas for improvement and effective decision making. http://www.ijte.ir/article_232592.html Traffic accidents and physical and financial casualties are a serious and global problem. The human, the road, the vehicle, and the environment are the four causes of traffic accidents, and among them, the most effective factor is the human factor. Therefore, in the field of traffic safety, social science studies, in particular, psychology and driver studies, are necessary. The main purpose of this study was to investigate the relationship between personality dimensions of Myers-Briggs personality test on high-risk driving behaviors and the number of accidents. The population of the study consisted of all Razi University students who hold a driving license. Using the Cochran formula, 361 samples were obtained and selected by the available sampling method. The research tool is a questionnaire consisting of three sections: demographic questions, a researcher-made questionnaire on high-risk driving behaviors, and a Myers-Briggs personality test. Confirmatory factor analysis and structural equations were used to confirm the research hypotheses and questions. Amos software was used for data analysis. Increasing Personality Preferences (Extrovert, Intuitive, Perceiver) Increases Risk Driving Behaviors, and with increasing personality preferences (Introvert, Sensor, and Judger) the number of risky driving behaviors decreases.  According to the results people with personality preferences (extrovert, intuitive, and Perceiver) have the highest number of high-risk driving behaviors and the number of crashes As well as people with personality preferences (Introvert, Sensor, and Judger), they have the least number of high-risk driving behaviors and the least number of crashes. http://www.ijte.ir/article_231025.html The form of urban networks plays a crucial role in the efficiency of traffic flow. Small deficiencies in the geometric design or spatial distribution of arterial networks can disrupt traffic continuity, reduce operational efficiency, and lead to increased congestion in urban transportation systems. The distance between roads with different functions is one of the most significant parameters affecting traffic in urban networks. Therefore, in this study, a radial-circular network was designed with primary arterial roads at varying distances (800 and 1200 meters) and building densities ranging from 100% to 250%. Using AIMSUN software, the network was simulated, and traffic parameters were extracted. Subsequently, a predictive model was developed using multiple regression analysis, with primary arterial road distance as the dependent variable and building density and traffic parameters as independent variables. The results indicated that the final model achieved a distance prediction accuracy of 0.949 for primary arterial roads. The variables of density (with a negative influence), stop time, operational speed, and queue length had a significantly greater impact on predicting the functional distance of primary arterial roads. Specifically, higher building density is associated with a decrease in the optimal spacing of these roads, whereas longer stop times and greater queue lengths contribute to increased spacing requirements. Moreover, an increase in land use density and the functional distance of roads leads to a higher increase in vehicle queue length, particularly in the three-ring network with a distance of 800 meters between roads. Additionally, as similar values increase, the stop time of vehicles also rises. http://www.ijte.ir/article_181837.html The spread of COVID-19 caused some problems in public transportation. The pandemic created new challenges for developing countries like Iran, where public transportation is already plagued by many problems. As a result of COVID-19 concerns, it was speculated that unpredictable travel patterns would result. Based on Automatic Fare Collection data, in which passengers use a smartcard to enter a stop, this study evaluates this speculation. The dataset includes one month of transactions for each of the three COVID-19-related years (2019, 2020, 2021) in Tehran, the country's capital. By using time series clustering, it was found that a new pattern of travel has emerged. Before vaccination, most origins were in the eastern part of the city; whereas, in the new era, most of the origins are in the western part of the city.The peak hours have also undergone a significant change. Prior to the pandemic, the peak hour occurred between 7 and 8 o'clock in the morning, and demand reduced until the evening peak hour, but as a result of the new pattern, demand did not decrease significantly after 8:00:00, which resulted in new peak hours.It is anticipated that these changes will have a domino effect on Tehran's transit system as a whole.The system may not be able to handle the changes in behavior, as it was designed to deal with pre-pandemic behavior patterns. There is a need for rescheduling to resolve the problem. Additionally, the government should develop a long-term plan for restoring public transportation demand to its pre-pandemic level. http://www.ijte.ir/article_232593.html The hub location problem in public transport focuses on strategically placing transport hubs to enhance service delivery and operational efficiency. Rising urban populations and transportation demands necessitate effective public transport systems. The challenge is to identify optimal locations for new hubs while balancing objectives like minimizing operational costs and minimize maximum passenger travel time. This study proposes a bi-objective model that selects potential hub locations from an interurban public transport network using the Multi-Criteria Decision-Making (MCDM) method of TOPSIS. The first objective is to minimize transportation costs, hub construction costs, and route creation costs, while the second aims to minimize maximum passenger travel time. Given that this problem is NP-hard, the Lagrangian Relaxation (LR) algorithm is employed for medium and large network sizes, with computational results provided. The proposed method is validated using Mandl's and Sioux Falls network data, which are standard benchmark datasets in transportation and network optimization. Results indicate that the algorithm effectively determines optimal hub locations. This approach can be adapted for specific parameters, bringing the problem closer to real-world conditions and uncertainties. http://www.ijte.ir/article_232594.html Optimizing traffic flow remains a central objective in transportation research. With the continuous growth in vehicle numbers, the limited scalability of existing infrastructure, and the inherently nonlinear, dynamic, and stochastic nature of traffic systems, signal control at road junctions has become an increasingly complex control challenge. Traditional signal control methods are predominantly rule-based, designed for deterministic environments, and often fail to adapt to real-time traffic variations and unexpected disruptions. This study proposes a distributed traffic signal control framework built upon a Machine Learning (ML) paradigm utilizing Reinforcement Learning (RL). Owing to their non-model-based architecture and computational efficiency, RL-based methods exhibit strong adaptability to changing traffic conditions and robustness against environmental uncertainties. In the proposed system, each junction is independently managed by an autonomous learning agent capable of interacting with its environment, refining its control policy over time, and making localized, real-time decisions. Simulation results demonstrate the effectiveness of the proposed approach, with vehicle queue lengths and average waiting times reduced by 35% to 66.4% on roads leading to the junctions, compared to conventional rule-based systems. These findings highlight the potential of distributed, learning-enabled control strategies in achieving scalable, adaptive, and efficient urban traffic management. http://www.ijte.ir/article_236022.html School transportation services operate in connection with the urban transportation network.The compatibility of the network’s carrying and congestion capacity depends on the functional system of its activities across temporal and spatial dimensions.This study aims to examine the rhythmic structure of private school transportation services in Zanjan city and their role in generating and reproducing traffic within urban networks. The research employs a qualitative-exploratory methodology with an applied focus. Data were collected from a sample of over 200 school transportation services using interviews and observations.The collected data were analyzed and categorized using a rhythmic interpretation approach, considering variables such as movement patterns, routing, traffic nodes, origins and destinations, temporal characteristics, routes, spatial occupation, and functional amalgamation, and implemented in a Geographic Information System (GIS). The findings indicate that the functional structure of private school transportation services in Zanjan operates at the urban scale and is dependent on the origin-destination system of residences and schools. The results show that the functional rhythm of these services in central city schools peaks in the afternoon, whereas in peripheral areas it peaks in the morning.The main arterial and primary road networks serve as the framework for the movement and traffic system of these services, operating proportionally to residential weights and traffic nodes. Consequently, the study concludes that the functioning of private school transportation services in Zanjan is based on regional and urban traffic patterns. Given the size and spatial scale of the city, the flows of these services exhibit relatively long temporal and spatial intervals. http://www.ijte.ir/article_236024.html Background: As urban traffic becomes increasingly dense, the use of motorcycles has increased in metropolitan areas. Given the multifaceted nature of traffic accidents, there is a pressing need for constructive interaction among the various institutions involved in managing motorcycle traffic safety.Methods: This applied research used mixed-methods approach, combining qualitative content analysis and quantitative descriptive-survey methods. In qualitative phase, the statistical population consisted of experts and managers from organizations related to motorcycle traffic safety. Participants were selected using non-probability purposive sampling until theoretical saturation was achieved. In the quantitative phase, the statistical population included 9,223 individuals selected via convenience sampling. The statistical population in the quantitative section consisted of Judicial Experts, Traffic Accident Experts from the Iran Highway and Traffic Police Department, Traffic Police Headquarters of Iranian National Police, the Ministry of Roads and Urban Development, and the Civil Affairs Department of the Ministry of Interior, who were selected based on their availability. Sampling in the qualitative section was conducted purposefully based on criteria, while in the quantitative section, it was done using stratified random sampling proportional to the size of each stratum in the total population, resulting in a sample size of 384 individuals according to the Morgan table.Findings: The multi-institutional prevention model includes the following dimensions: organizational structure (t = 26.894), inter-institutional communication (t = 25.251), multifaceted cultural development (t = 25.392), technical factors (t = 12.436), and comprehensive education (t = 10.281). All factor loadings were above 0.50 and statistically significant at the 95% confidence level. http://www.ijte.ir/article_236025.html Aging of asphalt mixtures is one of the main causes of reduced durability and performance in flexible pavements. The self-healing ability of asphalt materials plays an important role in extending their service life. This study examines the impact of short-term and long-term aging, using two standard methods (R30 and NCHRP), as well as the influence of different rest periods on the self-healing capacity of asphalt mixtures. Specimens were prepared with PG 64-16 binder and siliceous aggregates, and self-healing was assessed using three indicators: stiffness ratio difference, fatigue life ratio, and failure rate. The results show that longer rest periods significantly improve self-healing indices. Samples aged with the R30 method generally performed better than those aged with the NCHRP method, while unaged samples consistently exhibited the highest self-healing potential. The findings suggest that employing multiple indices provides a more complete picture of asphalt mixture behavior, and systematic comparison of aging methods can serve as a valuable guide for optimizing materials and designing long life pavements. http://www.ijte.ir/article_242871.html Accurate estimation of travel time across urban road networks is essential for effective traffic management, efficient route planning, and the development of intelligent transportation systems (ITS). In practice, GPS data is recorded at low sampling frequencies due to such limitations as data storage and transmission costs. The low frequency of data poses significant challenges for traditional travel time estimation techniques, which often rely on continuous trajectories. To address this issue, the present study proposes a practical framework for estimating travel times at both the link and route levels using sparse GPS data. The methodology is implemented using Python scripting within the ArcGIS environment. A case study using GPS data collected from Tehran, Iran, is conducted to assess the performance of the proposed framework. The estimated travel times are validated against high-frequency GPS records, demonstrating that the approach yields accurate and reliable results despite the data sparsity. The integration of Python within ArcGIS enhances automation and makes the proposed framework both effective and accessible for real-world transportation analysis and planning.