<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0">
  <channel>
    <title>International Journal of Transportation Engineering</title>
    <link>http://www.ijte.ir/</link>
    <description>International Journal of Transportation Engineering</description>
    <atom:link href="" rel="self" type="application/rss+xml"/>
    <language>en</language>
    <sy:updatePeriod>daily</sy:updatePeriod>
    <sy:updateFrequency>1</sy:updateFrequency>
    <pubDate>Wed, 25 Oct 2023 00:00:00 +0330</pubDate>
    <lastBuildDate>Wed, 25 Oct 2023 00:00:00 +0330</lastBuildDate>
    <item>
      <title>In light of the automated fare collection data, how did the travel patterns of transit riders in Tehran change following COVID-19?</title>
      <link>http://www.ijte.ir/article_181837.html</link>
      <description>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.</description>
    </item>
    <item>
      <title>Machine Learning based Distributed Traffic Signal Control</title>
      <link>http://www.ijte.ir/article_232594.html</link>
      <description>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.</description>
    </item>
    <item>
      <title>Analyzing and Predicting Fatal Road Traffic Crash Severity Using Tree-Based Classification Algorithms </title>
      <link>http://www.ijte.ir/article_236022.html</link>
      <description>School transportation services operate in connection with the urban transportation network. The compatibility of the network&amp;amp;rsquo;s carrying and congestion capacity depends on the functional system of its activities across temporal and spatial dimensions to enable adaptive performance. 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.</description>
    </item>
    <item>
      <title>Preventing Motorcycle Accidents: A Multi-Institutional Model</title>
      <link>http://www.ijte.ir/article_236024.html</link>
      <description>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. The aim of this study is to present a multi-institutional prevention model for motorcycle accidents. This applied research used a mixed-methods approach, combining qualitative content analysis and quantitative descriptive-survey methods. In the 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.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). The organizational structure dimension had the highest impact, while comprehensive education had the lowest. All factor loadings were above 0.50 and statistically significant at the 95% confidence level. The prerequisites for a multi-institutional approach to preventing motorcycle accidents include developing an appropriate organizational structure, fostering inter-institutional communication, promoting multifaceted cultural development, implementing intelligent control systems, and providing comprehensive education. Emphasizing these dimensions and adopting an interdisciplinary approach to traffic management can lead to improved safety for motorcyclists.</description>
    </item>
    <item>
      <title>Estimating Urban Travel Times from Sparse GPS Data: A Practical ArcGIS-Python Framework </title>
      <link>http://www.ijte.ir/article_242871.html</link>
      <description>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 (sparse GPS data) due to limitations such 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.</description>
    </item>
    <item>
      <title>Investigation of the Factors Affecting the Unconfined Compressive Strength (UCS) of the Subgrade Soil Stabilized with Copolymers</title>
      <link>http://www.ijte.ir/article_247004.html</link>
      <description>Since transportation plays a crucial role in the economic and social development of a country and affects many aspects of life, it is considered as a vital artery there. Stabilizing the subgrade soil of roads improves their physical and mechanical properties and increases resistance to traffic load, moisture, and temperature changes. The goal is to extend the service life of roads, reduce maintenance costs, prevent premature failures, and enhance transportation. Most soils are stabilized with additives like cement, lime, and bitumen to improve their strength and durability, but these traditional stabilizers cause significant environmental pollution. Therefore, using environmentally friendly materials is important. This study examined the unconfined compressive strength (UCS) of the soil stabilized with styrene-acrylate and styrene-butadiene, as two eco-friendly emulsion copolymers, in dry and wet conditions and then in wet-dry and freeze-thaw cycles. The results were analyzed using the SPSS and Design-Expert software programs. It was indicated that increasing a pure polymer initially increases UCS, followed by a decrease. Also, moisture, wet-dry and freeze-thaw cycles reduce UCS. According to the independent t-test results, only the reduction of strength due to moisture was statistically significant. Using the equations proposed in this study, it is possible to estimate the UCS of the soil stabilized with the mentioned copolymers under different conditions and determine the optimal type and amount of polymers based on project requirements.</description>
    </item>
    <item>
      <title>Effects of Aging and Rest Periods on the Self-Healing Properties of Asphalt Mixtures</title>
      <link>http://www.ijte.ir/article_236025.html</link>
      <description>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.</description>
    </item>
    <item>
      <title>An Optimized Operational Model for the Development of Micromobility Systems in Metropolitan Areas: A Case Study of Tehran</title>
      <link>http://www.ijte.ir/article_247416.html</link>
      <description>Micromobility has emerged as a flexible, low-emission alternative for short urban trips, attracting growing interest in densely populated cities. This study evaluates the financial viability of implementing a micromobility network in Tehran from the perspective of a private or institutional investor. Employing a discounted cash flow (DCF) model over a five-year planning horizon (2024&amp;amp;ndash;2029), the analysis considers only direct monetary flows, including capital expenditures (CAPEX), operating costs (OPEX), and revenue streams derived from trip-based fare structures. Demand is disaggregated by trip duration and monetized using calibrated fare multipliers aligned with real-world usage patterns. A real discount rate of 46.5% is applied, consistent with local economic conditions and infrastructure investment benchmarks. Results reveal that while the project operates at a deficit in its initial two years, it reaches operational breakeven in year three and achieves significant profitability thereafter, generating a cumulative net surplus of over 44 billion rial by the end of the analysis period. The findings underscore the financial feasibility of micromobility systems in emerging urban contexts and offer a replicable methodology for evaluating clean transport investments under inflationary and uncertain financial conditions..</description>
    </item>
    <item>
      <title>A Multivariate Test-Retest Approach for Verifying Self-Reported Speeding Behaviours among Taxi Drivers in Tehran</title>
      <link>http://www.ijte.ir/article_250423.html</link>
      <description>The aim of this study is to assess the repeated responses and verification of surveys using a one-way multivariate test-retest process with a four-week interval between measures for 120 taxi drivers in Tehran. The only independent variable includes the questioning stage. The items of a scenario-based questionnaire were considered as dependent variables. The null hypothesis posits no significant difference. The results were addressed using two testing approaches: variance testing and average testing. The results of the multivariate test statistics showed no significant variance difference in the answers between the first and the second test. The average testing including the contrast test also showed such a conclusion for the average measures in two stages. This means that factors which motivate speeding amongst taxi drivers were stable over a four-week period. In all these cases, the p-values were greater than 0.05, which indicates the non-significance of the difference between the responses in two stages, and as a result, accepting the null hypothesis. The added power in multivariate analysis results from the correlation between outcome variables and the use of cross-products.</description>
    </item>
    <item>
      <title>Evaluating the Effects of Speech-Based Auditory Warnings on Safe Driving Behavior among Young Drivers</title>
      <link>http://www.ijte.ir/article_250424.html</link>
      <description>This study evaluated the effects of speech-based auditory warnings on safe driving behavior in high-risk situations using a high-fidelity driving simulator. Utilizing a within-subject design, 36 young drivers navigated an urban scenario under two conditions: "with" and "without" auditory warnings. Warnings consisted of brief Persian voice messages (e.g., reduce your speed, hazard ahead) delivered at predefined critical moments before hazardous events. Behavioral and vehicle-related indicators including collisions, speed limit exceedances, velocity, braking intensity, accelerator pedal input, engine RPM, and seatbelt used were recorded via simulator logs and analyzed using paired statistical tests. The auditory warnings significantly enhanced safety metrics: mean collisions with vehicles, pedestrians, and fixed objects decreased by 80%, 76%, and 56%, respectively, while speed limit exceedances dropped by 53%. During critical events, warnings prompted lower speeds, reduced accelerator input, lower engine RPM, and increased braking intensity. Seat-belt compliance also improved; however, as no explicit seat-belt warning was provided and the condition order was fixed, this remains an exploratory finding. Overall, this pilot study suggests that speech-based auditory warnings can significantly improve key indicators of safe driving behavior among young drivers in simulated environments. Nonetheless, generalizing these short-term findings to real-world driving requires future research with randomized condition tracking and larger sample sizes.</description>
    </item>
  </channel>
</rss>
