Tarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401Enhancing Pedestrian Trips in Urban Areas: A Macro-Level Approach (Case Study: Shiraz City)1929194521126110.22119/ijte.2024.409439.1642ENSalmanAghidi KheyrabadiFaculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, IranAmir RezaMamdoohiFaculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran0000-0002-5339-9807Journal Article20230731The focus on sustainable transportation and pedestrian-friendly urban environments has gained importance, emphasizing the need to prioritize pedestrians over cars in transportation planning. Pedestrian trip modeling poses several challenges, including predicting the number of pedestrian trips generated in specific areas, identifying the variables influencing walk-trip generation, and measuring their impact. Most researchers have developed trip generation models based on trip purposes rather than travel modes. Furthermore, some studies have used variables similar to those used for other travel modes to model walking trips. This study aimed to identify influential variables and measure their impact. Developing trip production models exclusively for walk trips, along with the corresponding variables, and addressing the challenge of zero-walk trips in many zones are regarded as innovations. Shiraz City was utilized as a case study, encompassing 325 pedestrian analysis zones, to model walk-trip production using linear regression. Walk trips, categorized into home-based and non-home-based trips, were estimated for the base year. The Herfindahl-Hirschman Index, access to land use, and car ownership at the neighborhood level significantly influence walk-trip production. An increase in car ownership reduces home-based walking trips and increases non-home-based ones. Additionally, a 1% rise in access to green spaces resulted in a 4% increase in home-based walking trips. These models can predict future walking trips and assess the impact of urban design plans on pedestrian activity. Prioritizing pedestrian-friendly transportation planning leads to more sustainable and people-centric urban areas.http://www.ijte.ir/article_211261_60c0a33ec74fd648d97a79d6ab401f9e.pdfTarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401Review on the Impact of Nanoparticle Additives on Fiber Adhesion in Ultra-High Performance Concrete for Corrosive Traffic Environments1947197221668910.22119/ijte.2025.468052.1669ENKarimOjaghiFaculty of Civil Engineering, University of Tabriz,Tabriz, IranFarhoudKalatehFaculty of Civil Engineering, University of Tabriz,Tabriz, Iran0000-0001-5192-9408Mohammad AliLotfollahi YaghinFaculty of Civil Engineering, University of Tabriz,Tabriz, IranJournal Article20241123Ultra-high-performance fiber-reinforced concrete (UHPFRC) is a cutting-edge material in traffic and road engineering, combining fibers and cement to deliver exceptional strength and durability. Distinguished by its fine-grained composition, UHPFRC forms microscopic pores that effectively impede the ingress of water, gases, and chlorides. With an optimized mix design, UHPFRC can achieve compressive strengths exceeding 200 MPa and tensile strengths surpassing 20 MPa, along with remarkable tensile performance encompassing both hardening and softening phases. The nanoparticle additives improve the adhesion of fibers. These attributes position UHPFRC as an ideal material for enhancing the stability and longevity of traffic infrastructure components. Despite these advantages, the widespread application of UHPFRC is constrained by the susceptibility of steel fibers to corrosion in wet and aggressive environments. This review article critically evaluates the influence of nanoparticle additives on the adhesion properties of fibers in UHPFRC under corrosive conditions. It addresses the challenges, limitations, and prospective applications of UHPFRC, offering valuable insights for design engineers to accurately estimate the ultimate bearing capacity of UHPFRC structures across diverse environmental settings.http://www.ijte.ir/article_216689_37537f3b38cc3ef3256cbee8b326d8b0.pdfTarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401Rural Crash Severity Modelling at Marginal Areas around Cities in Iran Using Ordinal Logistic Regression and Partial Proportional Odds Modelling Approaches1973199220823210.22119/ijte.2024.472865.1675ENHamidShamanian EsfahaniDepartment of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran0000-0001-5000-6687Seyed TeimourHoseiniAmin University, Tehran, IranRezaSakhaeiAmin University, Tehran, IranMajidEhsani SohiAmin University, Tehran, IranJournal Article20240811Proof from earlier investigations indicates that many rural crashes happen in marginal areas around cities. Therefore, Exclusive crash severity models should be developed to pinpoint the factors linked to the increased likelihood of injury and fatality in these segments of rural roads. For this purpose, a partial Proportional Odds (PPO) model alongside the traditional ones including ordered logit (OL) and multinomial logit (MNL) models was utilized in this study to develop crash severity models for these segments of roads. The authors applied rural crash data gathered from highways that lead to Isfahan for modelling. The PPO model outperforms the traditional models, as demonstrated by comparing developed models. Also, the results indicate that rural crashes are more likely to be severe when the average speed exceeds 95 km/h, in multi-vehicle type crashes, in overturn-type crashes, when the at-fault vehicle is a truck/trailer, and when the at-fault or not-at-fault vehicle is a motorcycle. On the other hand, severe crashes in marginal areas around cities tend to decrease when a foreign vehicle is at fault and when the driver of the at-fault vehicle is 30 to 40 years old.http://www.ijte.ir/article_208232_842a833adb2a5aed2fef99c3bf503c10.pdfTarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401A Model to Predict the Bus Dwell Time in Stations1993200822118810.22119/ijte.2025.487347.1678ENSeyed EbrahimAbdolmanafiDepartment of Transportation Engineering, School of Civil Engineering, Science and Research Branch, IAU, Tehran, Iran0000-0003-0812-3059DavodKhaliliDepartment of Transportation Engineering, School of Civil Engineering, North Branch, IAU, Tehran, IranHamidrezaMazaheriDepartment of Transportation Engineering, School of Civil Engineering, Science and Research Branch, IAU, Tehran, Iran0000-0003-4686-4579Journal Article20241110The focus of this research is to develop a bus dwell time model based on formulas presented in the Highway Capacity Manual (HCM) and Transit Capacity and Quality of Service Manual (TCQSM). The dwell time model proposed in this paper not only includes factors like the number of boarding and alighting passengers, but a number of secondary factors like crowding in the bus, crowding in the station, roadway congestion, bus type, the status of bus lines, the number of alighting passengers, the number of boarding passengers, level of service of the station before passengers alighting, level of service at the bus before passengers alighting, bus type, level of service at the bus after passengers alighting, the number of bus lines passing through the station, the average headway of bus lines, and level of service of roadway are considered and taken into account in our proposed model as well. Furthermore, the developed model is validated using data collected from bus lines in Tehran, Iran. The model validation demonstrates that it has relatively good accuracy (85%) to estimate the bus dwell time. Moreover, the sensitivity analysis on the developed model indicates that increasing the number of alighting passengers and crowding at the bus has a greater effect on the dwell time than any other factors. Decrease in level of service of roadway, increase in the number of boarding passengers, crowding at the station, and decrease in the average headway of bus lines are the other important factors respectively.http://www.ijte.ir/article_221188_6332546f04186d5ca48665c9f72eba65.pdfTarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401Evaluating the Effectiveness of Burr Mixtures for Travel Time Reliability Analysis2009202321669010.22119/ijte.2025.489786.1681ENMojtabaRajabi-BahaabadiCivil engineering department, Yazd university, Yazd, IranJournal Article20241120Travel time reliability plays a key role in travelers' decision-making processes and serves as a significant indicator for evaluating road performance. The initial stage of enhancing travel time reliability involves measuring it, which guarantees on-time arrivals and minimizes travel costs. A thorough understanding of travel time distribution is required to accurately measure travel time reliability. Traditionally, travel time has been represented using unimodal distributions. However, recent studies have indicated that travel time distribution is often multimodal. Failing to accurately model travel time distribution can lead to overestimation or underestimation of travel time reliability, resulting in suboptimal solutions in practical applications. This study mainly focuses on examining the effectiveness of six different mixture distributions, namely Burr mixture, Gamma mixture, Inverse Gaussian mixture, Log-normal mixture, Normal mixture, and Weibull mixture, in modeling travel time reliability. The Bayesian information criterion is utilized to compare and select the best model for representing travel time distribution. The results of this study indicate that the Burr mixture model can characterize the travel time distribution more accurately compared to its alternatives. Furthermore, the results show that using burr mixture distributions leads to more accurate estimations of travel time reliability measures compared to single distributions.http://www.ijte.ir/article_216690_2888b8911336de3d92dca0aeaff73048.pdfTarrahan Parseh Transportation Research InstituteInternational Journal of Transportation Engineering2322-259X12420250401Evaluation of Safety Measures on the Highways of Isfahan Province Based on before-and-after Studies using the Experimental Bayes Method2025203722118910.22119/ijte.2025.504189.1686ENMohammadaliSalavatiPhD Candidate in Civil Engineering, Transportation Planning University of TehranJafarJamiliPhD Candidate in Civil Engineering, Transportation Planning University of TehranJournal Article20250202Isfahan Province, Annually, experiences around 650 fatalities and 5,000 injuries due to traffic accidents, with a troubling 20% increase in these figures each year. Alarmingly, half of the traffic-related deaths occur during transport or while receiving medical care. The escalating number of vehicles, coupled with the rapid expansion of transport networks, has led to a significant rise in the frequency and severity of traffic accidents globally, a challenge particularly pronounced in Iran. This phenomenon has resulted in increasing human and economic losses. In light of these circumstances, the effectiveness of safety policies and preventive measures in Isfahan necessitates the implementation of scientific methods to evaluate interventions aimed at rectifying accident-prone areas, in accordance with international road safety standards. This study endeavors to compare various before-and-after evaluation methodologies. Utilizing the experimental Bayes method, it assesses safety measures implemented at 15 high-accident sites as part of the Safety Improvement Plan for Isfahan Province (e.g. widening the speed limit lane before the round place, installing detector for indicating safety signs, pavement rehabilitation of the speed lane, blocking inappropriate exits and creating parking lots, etc.). The analysis, grounded in experimental observations, aims to provide a robust foundation for future decision-making by transportation managers, planners and engineers. The findings from this assessment reveal that the interventions at the identified sites resulted in a notable 45% reduction in accidents, with a confidence level of 95%. This significant impact validates the appropriateness of the measures undertaken, highlighting their effectiveness in enhancing road safety in the province.http://www.ijte.ir/article_221189_89bf876c74cf8bf7cdf195692aa4cff1.pdf