Publisher: Tarrahan Parseh Transportation Research Institute   (Total: 1 journals)   [Sort by number of followers]

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Intl. J. of Transportation Engineering     Open Access   (Followers: 2)
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International Journal of Transportation Engineering
Number of Followers: 2  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2322-259X - ISSN (Online) 2538-3728
Published by Tarrahan Parseh Transportation Research Institute Homepage  [1 journal]
  • A probabilistic density approach for evaluating factors contributing to
           injury severity (Case study: Borujerd-Khorramabad Rural Highway)

    • Abstract: Accordingly, an examination of accident road factors based on the probability density seems necessary. Thus, this paper first aimed at using principle components analysis (PCA) as a statistical prioritization tool for identifying the main and sub-main factors that contribute to injury severity on Borujerd-Khorramabad as a four-lane rural highway during the years 2015 to 2017. Secondly, the multivariate Gaussian probability model was used as a probabilistic density approach to estimate the probability density based on the relationship between factors that contributing to injury severity and the Pearson correlation. The results obtained through PCA indicated that factors contributing to injury severity were ranked in terms of eigen values and rotated component matrix. Findings from the PCA model showed that OS, PSL, AADT, SL, R, and S, as 6 important factors affecting the accident occurrence relevant to injury severity. The results of the probability density also showed that the relation between operating speed with posted speed limits, and the relation among segment length, operating speed and radius are considerable due to increasing the probability density of accident occurrence. Moreover, AADT with operating speed and operating speed with slope and radius have significant effects on the probability density of occurring accidents. The results of the present study show that applying a multivariate Gaussian probability model helps to estimate the probability density of the accident occurrence of factors contributing to road accidents based on their values.
       
  • Identification and prioritization of road project risks Using the Failure
           Modes and Effects Analysis Method in a Fuzzy Environment

    • Abstract: A dynamic, efficient transportation network is an important index of a country's development and currently, major parts of infrastructure projects-related credits and budgets are allocated to road construction projects. Since several risks divert such projects, during their construction, from their main goals, proper risk identification and management are necessary to better implement infrastructure and road construction projects. As risks are changeable factors that differ from country/region to country/region, this research has reviewed the literature and used the experts' opinions to identify the most influential ones in Iran to eliminate or reduce their effects on the time and cost of road construction projects. To this end, a questionnaire was designed to identify the risks and prioritize them using the failure modes and effects analysis method in a fuzzy environment; defuzzification was done by the MATLAB Software. Scores of the risks revealed that: 1) inflation (increased material price), 2) late financial provisions, 3) deficiency, failure, or defect of equipment/machinery, and 4) Maps and specification changes of more than 25% with respect to the values specified in the general conditions of contract due to the employer’s incorrect studies/estimation of the project, were identified as the most important risks of road construction projects.
       
  • Study of Urban Taxi-related Accident Analysis Using the Multiple Logistic
           Regression and Artificial Neural Network Models

    • Abstract: In this research, factors affecting the severity of property damage only (PDO) and injury/fatal accidents were examined using taxi-related accident data from March 2015 to March 2021 in urban sites of Rasht city. The multiple logistic regression and artificial neural network (ANN) were applied to recognize the most influential variables on the severity of accidents. Results indicated that the multiple logistic regression in the backward stepwise method had a prediction accuracy of 88.54% and R2 value of 0.871. Moreover, the regression analysis revealed that the wet surface condition, night without sufficient light, rainy weather, Kia Pride taxi and lack of attentions increased the severity of accidents, respectively. The most important result of the logit model was the significant role of environmental factors, including slippery road surface, unfavorable weather as well as poor lighting condition, and also indicated the dominant role of poor quality of vehicles along with human factors in increasing the severity of accidents. Comparing the correct percentage of prediction in the multiple logistic regression and ANN model, the results showed that ANN model performed better so that the prediction accuracy of ANN was 95.8%.
       
  • Sustainability Analysis of Urban Transportation Network Based on the
           Determination of the Relative Importance of Evaluation Criteria

    • Abstract: There is rising agreement that transportation systems are perfectly capable of linking economic development, environmental integrity, and social quality of life. Meanwhile a wide range of research clearly shows that transportation systems are unsustainable in most of the cities and urban areas. In practice, there are numerous transportation systems which are able to pose serious threat to the environmental, social and economic aspects of future generations. Therefore, a truly sustainable urban transportation network is definitely one of the most pressing need of cities and urban centers, particularly in developing countries. Thus identifying the evaluation criteria and determining their importance are critical. While most researches have only focused on economic or environmental aspect of transportation systems, in this paper, by considering economic, social and environmental dimensions, the evaluation criteria for evaluating the sustainability of urban transportation network have been discerned. Furthermore, a framework based on a goal programming model for Best Worst Method (BWM) has been proposed to evaluate and prioritize sustainability dimensions and evaluation criteria. In order to demonstrate the utility of the proposed model, it is employed to a real-world case study of transportation in Yazd, one of the most important cities in Iran and the first Iranian historic city. The results of this study are applied to evaluate, prioritize and select real transportation projects. Moreover, it is demonstrated how the proposed framework could assist urban managers in analyzing sustainability of existing instances, formulating effective strategies, evaluating and selecting coherent policies or even constructing projects to accomplish sustainability goals.
       
  • A New Holistic Crashes Prediction Model based on Zero-Truncated data for
           Intercity Four-Lane Highways Curves

    • Abstract: This study is aimed at exploring the effect of some recognized and new candidate variables of horizontal curves on crash frequency in four-lane highways using zero-truncated crash data. The present study has considered the related variables for 45 curves of four-lane intercity highways during a three-year period (2018-2020). The standard Poisson distribution is a benchmark for modeling Equi-dispersion count data and could not express Under-dispersion zero-truncated data. The modeling was performed using Poisson, Negative Binomial, Zero-Truncated Poisson, Zero-Truncated Negative Binomial, and Conway-Maxwell Poisson (COM-Poisson) regression. The results revealed that the COM-Poisson regression distribution could effectively fit the model Under-dispersion zero-truncated Crashes data. According to the results, using the consistency and self-explaining variables as a useful approach for the estimation of crash frequency in four-lane highway horizontal curves was evaluated.
       
  • A data mining approach to gain insight into traffic violations of young
           drivers in developing countries

    • Abstract: In developing countries, the population of younger adults is relatively higher. In addition, the frequency of traffic violations, committed by young drivers, is considerable. Consequently, annually a large portion of road crashes is recorded among this age group. This paper aims to study the traffic rule violations of young drivers in Iran. Focusing on the behavior of young drivers and understanding the mechanisms that affect the occurrence of violations among this group of drivers can be helpful to promote traffic safety. For this purpose, 567 drivers in the range of 18 to 40 years old have been studied. Then, different data mining approaches such as descriptive analysis, correlation analysis, multinomial logistic regression (MLR), and Random Forest (RF) were used to provide insight into traffic violations of young drivers, and to propose potential countermeasures to decrease this issue. Results indicated that driving over speed limits, red-light running, and angry driving are the most frequent violations. The frequency of using mobile phone while driving, as a source of distraction, has been found to be highly correlated with other violations. As the frequency of previous traffic fines, the number of days with access to private cars, and the frequency of previous crashes increase, more diverse types of violations with high frequencies are expected in the future. In addition, the frequency of risky violations was found to be higher among men and those with lower education levels.
       
  • Evaluating the Acceptance of a More Strict Plate Control Policy among
           Motorcycle Riders in Tehran

    • Abstract: Dramatic growth in motorcycle usage coupled with the riders’ high-risk driving behavior calls for a reform in motorcycle monitoring schemes in developing countries. In Tehran, Iran, about one million motorcycle license plates are registered in the city, of which more than 35% are unreadable, proving the existing monitoring schemes fall short in regulating motorcycle operations. A more Strict plate control (MSPC) is proposed to address the issue. While there is no question about the necessity of this policy, Tehran policymakers are concerned about the acceptance level of this policy. This study investigates its acceptance among motorcyclists, the major potential opponent population, in Tehran. To this end, 400 riders have been surveyed. Data analysis shows that subjective factors, such as driving behavior and attitudes, highly impact acceptance. Also, aggressive riders are more likely to disagree with the policy, but most motorcyclists do not disagree with a More Strict Plate Control (MSPC) Policy.
       
  • Optimal Increase of Single-Line Railway Route Capacity by Developing a
           Train Management Schedule Technique

    • Abstract: Rail transportation plays a significant role in the movement of commodities and passengers. The progressive demand for transporting passengers and commodities with limited capital available to develop rail infrastructure challenges the rail system ability for transportation by trains. There are two general ways to improve capacity in a route, including new investment in infrastructure and improving the performance of existing lines.In the present study, time management was used to increase the capacity of existing railways. A new rescheduling model is proposed in this research to overcome some of the current constraints called “Optimal increase in the capacity of lines.” This model uses the conflict solution technique and timetable compaction and can be used for one, two, and multi-line routes. A case study was conducted for part of a single-line BADROOD-ISFAHAN route, in which significant results were obtained.After process1, more than 25 initial timetable schedule conflicts were resolved in both Same Orders and Order Free approaches. After process 2, the OPTIMAL INCREASE model could compress the timetable by almost one hour and improve maximum dwell times (from 61to30 min) and total dwell times (from 271to168 min) of trains at stations. The total duration of the timetable was increased by almost 20 minutes. After process3, the OPTIMAL INCREASE model provided approximately 36minutes shorter timetable duration (better capacity utilization). Also, the results show that the duration of timetabled developed was slightly increased, mainly due to the sizable reduction in maximum dwell time from 61 minutes to 10 minutes.
       
  • Motivational Factors of Bicycle Sharing in a Car-dependent City: Evidence
           from Tehran, Iran

    • Abstract: Creating motivational factors is a way to increase bicycle use in a city where its share in transportation is low. The current study evaluated factors that could motivate an increase in shared bicycle demand. Results of a survey conducted in Tehran were used to identify the most influential factors. Next, Aimsun software was used to perform a simulation on two major streets in the city to assess the following scenarios: 1) without bicycles, 2) with bicycles and other vehicles, and 3) with bike lanes. The results showed that the entry of shared bicycles into the streets decreased the density of motor vehicles. On Jomhouri St, the density of motor vehicles decreased from 16.39 veh/km for without bicycles scenario to 13.52 veh/km for construction bike lanes. A downward trend also was observed for Keshavarz Blvd., with a decrease of 14.21% from scenarios one to three. The construction of bicycle lanes as a means of increasing public interest in sharing bicycles can have a positive effect on reducing traffic congestion.
       
  • Intelligent Air Traffic Management Methods, case study: a proposed deep
           learning method for Mashhad airport air traffic management

    • Abstract: Air traffic management (ATM) is a set of management, analytical, and operational techniques and tools, which are used to optimize the traffic flow and exploit the existing flight system capacity. However, one of the challenges in ATM use is the prevention of flight delays. Several methods such as data mining, artificial neural network evolutionary algorithm, and fuzzy logic are available in the ATM field. but the complexity level as the number of the available categories for classification increases, making it impossible to use these algorithms in air traffic management. This study is aimed to comprehensively evaluate the techniques applied in ATM and assess the tools and criteria in this context. also, show that the artificial neural network(ANN) and long short term memory(LSTM) algorithms are most frequently used in ATM.then a hybrid deep learning model for Mashad airport air traffic management systems was proposed. our results demonstrate that Among various clustering algorithms, K-means and deep learning methods are more efficient and widely used. Evaluation criteria such as accuracy rate, delay, The Root mean square error (RMSE) and mean square error(MSE) are more commonly applied in air traffic system evaluation.
       
  • Experimental Study of Mechanical Properties of Slag Geopolymer Concrete
           Under High Temperature, Used in Road Pavement

    • Abstract: Providing the mechanical properties of concrete used in road paving is of great importance. In the current study, Granulated Blast Furnace Slag (GBFS) based geopolymer concrete (GPC) was used with 0-2% polyolefin fibers (POFs) and 0-8% Nano Silica (NS) to improve its structure. After curing the specimens under dry conditions at a temperature of 60 °C in an oven, they were subjected to Tensile Strength, Modulus of Elasticity and Ultrasonic Pulse Velocity (UPV) tests to evaluate their mechanical properties. all tests were performed at 90 days of age under ambient temperature (20 ℃) and temperature (500 ℃). The addition of NS enhanced the whole properties of the GBFS-based GPC. Addition of up to 8% NS to the GPC composition at 20% temperature improved the modulus of elasticity test results by 13.42%, tensile strength by 15.19% and UPV by 11.58%. Addition of up to 2% of POFs to the composition of GPC improved the tensile strength up to 11.76%, modulus of elasticity 07.05% and UPV drop up to 12.02%. Applying high heat to GPC samples reduced the modulus of elasticity by up to 42%, tensile strength by up to 21% and UPV by up to 46%. The effect of heat on the drop in results in control concrete is more than GPC. In the following, by conducting the Scanning Electron Microscope (SEM) analysis, a microstructure investigation was carried out on the concrete samples. In addition to their overlapping with each other, the results indicate the GPC superiority over the regular concrete.
       
  • Investigation of porous asphalt surface parameters used in traditional
           texture passages

    • Abstract: Permeable pavement, including porous asphalt, is one of the best management practices in urban stormwater control, which is an effective way to protect brick and mud from rain runoff. The aim of this study is to investigate the relation between parameters related to the surface texture of porous asphalt with evaporation and permeability as two critical properties of porous asphalt. For this purpose, laboratory samples were first made. By performing permeability and evaporation measurement tests in an innovative way, the amount of permeability and evaporation of porous asphalt with different gradations was determined. Then, with image processing and an English pendulum device, parameters related to the surface texture of the samples such as surface porosity, fracture of surface aggregates, and slip resistance were measured. Their effect on evaporation and permeability was investigated. The results indicate that with finer gradation, the amount of surface porosity and angle and visible fractures of aggregates in the sample surface is reduced by about 27% and 48%, respectively. Also, the results of the slip resistance test show that in the dry state, the friction decreases by about 11% as the gradation becomes more significant, and in the wet state, the larger the texture, the more slip resistance is about 32% higher. Based on the results presented in this study, With the relationships presented in this study, it is possible to estimate the permeability and evaporation of porous asphalt by measuring the parameters related to the surface texture, which are relatively easier and faster to measure.
       
 
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Publisher: Tarrahan Parseh Transportation Research Institute   (Total: 1 journals)   [Sort by number of followers]

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Intl. J. of Transportation Engineering     Open Access   (Followers: 2)
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Heriot-Watt University
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Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


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