http://www.ijte.ir/ International Journal of Transportation Engineering en daily 1 Wed, 01 Jul 2026 00:00:00 +0330 Wed, 01 Jul 2026 00:00:00 +0330 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, and 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_250423.html 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. http://www.ijte.ir/article_253255.html Traffic accidents represent one of the major global challenges affecting public safety, have become a serious threat to public health, resulting in substantial human and financial losses for various countries each year. This study examines the spatial distribution of traffic accidents in the city of Zanjan. In this research, the spatial distribution pattern of accidents was examined using the Moran's I spatial autocorrelation method and spatial statistical analyses in a GIS environment. For this purpose, ten effective parameters were analyzed, including the type of road artery, speed limit, one-way roads, road width, population density, density of land uses, traffic intersection density, density of transportation axes, density of commercial and service land uses, and trip attraction intensity as influential factors in the occurrence of accidents. The results showed that these factors have a direct and significant relationship with road accidents in the city of Zanjan. The most significant impacts, in order, were from the parameters of one-way roads, road width, population density, density of land uses, intersection density, and trip attraction intensity. Additionally, the spatial pattern of accidents was generally clustered, and hazardous points were clearly identifiable. Based on these findings, recommendations for improving traffic safety in Zanjan have been provided, including geometric modifications of intersections, management of commercial and service land uses, adjustment of speed limits on busy streets, enhancement of traffic management, and implementation of immediate safety measures at accident-prone locations. This study can guide decision-making and planning to reduce accidents and improve urban safety in Zanjan. http://www.ijte.ir/article_247416.html 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 shared micromobility network in Tehran from the perspective of a private or institutional investor. Employing a discounted cash flow (DCF) model over a 2024–2029 evaluation horizon, the analysis considers direct monetary flows, including capital expenditures (CAPEX), operating expenditures (OPEX), and revenues generated through trip-based fare structures. Demand is disaggregated by trip-duration categories and monetized using calibrated fare multipliers aligned with duration-sensitive usage patterns. A real discount rate of 46.5% is applied to reflect local economic conditions and investment risk. The results indicate that the system operates below cost-recovery levels during the initial deployment years, but reaches operational breakeven in 2026, after which annual revenues exceed annual costs. By 2029, the model estimates total annual revenue of 49,279,481 million rials and total annual costs of 5,060,766 million rials, resulting in a final-year net operating surplus of 44,218,715 million rials, equivalent to approximately 44.22 trillion rials. These findings suggest that, under the assumed demand, pricing, and cost conditions, shared micromobility can become financially viable after the initial capital-intensive phase. The study provides a replicable framework for evaluating clean transport investments in emerging urban contexts characterized by inflation, demand uncertainty, and high operational risk. http://www.ijte.ir/article_253256.html This study presents a robust framework for assessing the seismic reliability of the Koohrang-III water transmission tunnel by accounting for the complex soil-structure interaction (SSI) phenomenon. A high-fidelity finite element-based numerical model was developed to simulate the tunnel’s dynamic behavior under various seismic loading conditions. To evaluate structural reliability, this research integrates the Response Surface Method (RSM) with the Hasofer–Lind algorithm, providing a computationally efficient approach to quantify performance. Six distinct strong ground motions were applied during nonlinear time-history analyses to extract critical design parameters, specifically the thrust force and bending moments. The results demonstrate that the tunnel’s structural reliability is highly sensitive to the analyzed loading parameters. Specifically, the thrust force exhibited the highest failure probability at approximately 37.5%, while the bending moment showed the lowest at roughly 2%. These findings highlight the necessity of reliability-based assessments in enhancing tunnel seismic safety protocols and optimizing structural design against earthquake-induced hazards. http://www.ijte.ir/article_250424.html 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 seat-belt use 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 or counterbalanced condition order and larger sample sizes. http://www.ijte.ir/article_252114.html Urban road safety is a cornerstone of sustainable development and quality of life, particularly in developing countries such as Iran. Conventional safety management in the country predominantly relies on crash statistics and reactive black-spot analyses. This study introduces a localized Human Factor Score (HF_Score) framework to enable proactive traffic risk management. Drawing on the conceptual foundations of World Road Association (PIARC) guidelines and tailored to the urban context of Iran, the framework integrates a quantitative HF_Score index with a field-based RSE_HF (Road Safety Evaluation based on Human Factors) tool. These components are designed to identify latent risks without the need for crash data by assessing the alignment between roadway design and users’ perceptual–cognitive capabilities. The framework was developed through qualitative content analysis and thematic analysis, resulting in cognitive evaluation forms and checklists. Due to its high implement ability and low cost, it is well-suited for application in Iranian urban environments and aligns with the principles of the global Safe System approach. From a policy perspective, it can serve as a complementary safety metric in roadway design, urban project evaluation, and geometric modifications. The study further recommends institutionalizing the framework through national standardization, capacity building, and expert training programs. Findings highlight the importance of enhancing tolerance to human error and creating environments consistent with users’ cognitive expectations to achieve long-term reductions in urban traffic crashes. The proposed framework represents a foundational step toward both theoretical and operational transformation in urban road safety policymaking in Iran. http://www.ijte.ir/article_252115.html Traffic management in a smart city is important in several aspects. From wasting people's time in traffic, which causes financial and mental harm to them, to increasing air pollution, which can directly affect their physical health and have destructive effects on the environment. Providing a mathematically based system in which drivers can choose the optimal driving time, drive at the highest speed and the lowest pollution on the street, can be a good help to traffic management in a smart city. The presented Modified Best-Mean-Random (MBMR) algorithm is a population-based metaheuristic designed to optimize multi-criteria traffic parameters (e.g., traffic volume, speed, pollution) on Stadhouderskade street in Amsterdam. The performance of the proposed MBMR algorithm was benchmarked against three competitive metaheuristics—GWO, MOEA/D, and BES—based on accuracy, stability, and computational efficiency. MBMR achieved the highest accuracy with a 39.02%, 21.88%, and 34.21% improvement over GWO, MOEA/D, and BES, respectively. In terms of stability, it consistently outperformed all other algorithms, showing a 55.56% to 63.64% reduction in standard deviation across multiple runs. While its execution time was marginally higher than GWO by 2.4 seconds, it remained notably faster than MOEA/D and BES. These results confirm MBMR's capability to deliver precise, stable, and computationally efficient solutions, making it a robust candidate for real-world multi-objective optimization tasks. http://www.ijte.ir/article_253257.html This study presents a comprehensive spatial analysis of traffic accidents on Iran’s road network from 12019 to 2023, utilizing advanced machine learning techniques to identify and classify accident hotspots. The research employs a two-stage clustering methodology: DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for geographic hotspot identification, followed by K-Means clustering for risk stratification. Analysis of 82,157 validated accident records revealed 923 significant hotspots, with 16 critical risk locations, 440 high-risk zones, and 467 moderate-risk areas. The study incorporates temporal features, weather conditions, road characteristics, and collision types to provide a multi-dimensional understanding of accident patterns. Results indicate that approximately 21.6% of clustered accidents occur on holidays, and 9.3% occur under adverse weather conditions. The top critical hotspot, the Farouj-Shirvan corridor, recorded 239 accidents with an EPDO score of 1,334, predominantly involving rollover collisions. The findings demonstrate the effectiveness of density-based spatial clustering combined with multi-dimensional risk assessment in identifying high-priority locations for traffic safety interventions on Iran’s road network. http://www.ijte.ir/article_254369.html Representing traffic and transit interactions in multimodal transportation networks is essential for obtaining link travel times and transit operating conditions. Achieving a consistent equilibrium between traffic and transit networks is important because inaccurate representation of modal interactions may lead to unreliable evaluations of multimodal transportation strategies. However, existing static traffic and transit assignment approaches often rely on predefined or sequential interaction procedures, where the convergence of traffic and transit states is not explicitly assessed. As a result, these approaches may require unnecessary iterations or terminate before achieving consistent network conditions.This study develops a convergence-based link-level traffic and transit assignment framework that iteratively exchanges information between traffic and transit assignment models until a convergence criterion is satisfied. The proposed approach incorporates transit-generated passenger car equivalent flows into traffic assignment and updates transit operating characteristics, including travel time, dwell time, and headway, based on revised traffic conditions.The proposed framework converged in both case studies and demonstrated that traffic and transit interactions vary across link types and operational conditions. The results indicate that transit operations can influence network conditions beyond transit-served links. Sensitivity analyses further confirm the robustness of the proposed convergence procedure under different transit supply and demand conditions, with the private vehicle network showing greater sensitivity to public transport demand on lower-demand lines and dwell time playing a more influential role on higher-demand lines.The proposed approach provides a computationally efficient, link-level framework that can support transportation planners in more accurate evaluation of multimodal infrastructure and operational strategies.