Tehran Metro Research Articles

Discovering the optimal distance between spatial orthogonal tunnels: A dynamic analysis using Tehran metro as a case study

Discovering the optimal distance between spatial orthogonal tunnels: A dynamic analysis using Tehran metro as a case study

The New Norm, a reality or a fiction? A longitudinal passenger satisfaction study on the persisting effects of COVID-19

The concept of the "new norm" implies a shift in societal behavior, and the COVID-19 pandemic is suspected to have long-term effects on customer perceptions of public transportation service factors such as crowdedness and cleanliness as mentioned in the literature. To assess the existence of a new norm in passenger behavior, a six-wave longitudinal customer satisfaction survey was conducted, comprising four waves before the pandemic and two waves after, in addition to an interview panel survey. Employing the SEM-MGA approach, we modelled the longitudinal sample, utilizing a confirmatory factor analysis framework grounded in passenger satisfaction literature specific to the Tehran metro. A MGA model was introduced, and the Importance-Performance Analysis was employed to identify alterations in the significance and execution of satisfaction factors across each survey wave and model. Three main factors of cleanliness, crowdedness, ventilation, were examined to assess the new norm. Each factor consistently emerged as a significant factor in passenger satisfaction, pre and post-COVID-19. In conclusion, our findings indicate that the COVID-19 pandemic did not have an observable long-term impact on public transportation passengers' perceptions of cleanliness and ventilation. This suggests that authorities may consider returning to pre-pandemic operational practices to conserve valuable resources. Moreover, our study underscores passengers' adaptability and the system's reversion to pre-pandemic norms in this regard.

EPB-TBM cutterhead torque and thrust modelling in rock tunnels through an analytical method and TSFS model

The analysis of cutterhead torque and thrust force is of utmost importance in the selection of a proper tunnel boring machine (TBM) and in achieving optimal operation of the earth pressure balance (EPB) machine for a specific project. This study focuses on the analysis of cutterhead torque and thrust force using data collected from the recent metro project of Tehran, specifically the southern extension of Tehran metro line 6, (TML6-SE). To assess the impact of geotechnical and operational parameters on the measured torque and thrust, a database consisting of 457 data points was established. The excavation of a significant portion of the project took place in a dense and robust limestone using a refurbished EPB machine with a diameter of 9.19 m, initially designed for soft ground excavation. To complete this section of the tunnel, the cutterhead was equipped with disc cutters instead of rippers. Consequently, existing theoretical models for estimating torque and thrust of an EPB machine were modified to accommodate the hard rock boring process. Additionally, the Takagi-Sugeno fuzzy system (TSFS) was utilized in this study. The results of the models yielded quantitative conclusions, and the comparison between the measured and predicted target parameters demonstrated high accuracy. This study contributes to the understanding of the influence of various parameters on the performance of EPB machines in hard rock boring conditions, as well as providing insight into the potential adjustments needed in theoretical models for predicting cutterhead torque and thrust force. The proposed models showed satisfactory and reliable accuracy, with all models having an R2 value above 0.7 and loss function values nearing zero.

The positive impact of transit-oriented-development characteristics on Metro Station usage: A case study of Tehran's metro stations and TOD index calculation

Transit-Oriented Development (TOD) facilitates the creation of more walkable cities. To implement TODs, urban planners need a mechanism to delineate TOD levels so they can envision future planning trajectories. This study offers an approach to developing scores for TODs within Tehran, a metropolitan area with metro stations and Bus Rapid Transit that facilitate public transportation usage. TODs exhibit distinct characteristics when compared to other areas within a city. Furthermore, TODs vary in their levels of integration across transit, commerce, and residential, necessitating policies specific to each TOD. The main objective is 1) To identify the factors that best define TODs for metro stations and 2) To develop a TOD index to measure the TOD score. We used three different spatial units of measurement to define a range of metrics to identify how effective TODs work with different characteristics. The spatial units include: 1. Thiessen polygons 2. the walkable distance of the transit nodes and 3. Thiessen polygons without the walkable distances. The main criteria we used are travel behavior, walkability, accessibility, transportation inclusivity, network attribute, trip generation rate, and land use. The metrics are weighted based on the correlation results with the usage rate. A Negative Binomial regression was developed to find the metrics that are significantly influential on the usage rate of the metro stations. Results indicate that all criteria except the land use are significantly correlated with the usage rate of metro stations.

Investigating and Measuring Radon Gas Concentration in Tehran and Alborz Metro Stations

Abstract Humans are regularly exposed to various types of radioactive radiation and, of course, to Radon-222 over the course of their lives. According to the report of the United Nations scientific committee on the effects of atomic radiation in 2000, the average human is estimated to be exposed to about 4.2 mSv of radioactive radiation each year, 52% of which is caused by inhalation of radon gas. The radon gas is one of the most important elements that is emitted from the decay of natural uranium and radium in the earth. Therefore, the concentration of this gas can be higher in enclosed spaces, especially underground locations, and it is important to measure the amount of radon gas radiation in these underground stations. In this research, a domestically manufactured environmental meter for radon gas was used to measure the concentration of this gas in different Tehran metro stations. In general, all 42 subway stations of Tehran and Karaj cities were measured at continuous time intervals during the spring season. On average, trace amounts of radon gas were observed in all the stations, but high concentrations of radon gas were measured at some stations, such as Tajrish and Ghaem stations in the northern Tehran-Karaj plain due to underground water resources, fault type and distinct geological structures. According to the US Environmental Protection Agency (EPA) standard, the maximum permissible amount of radon gas concentration in the air is 148 Bq/m3, while the average amount was 156 Bq/m3 at Tajrish station. This amount is above the permissible limit and can therefore be considered hazardous to health. Geologically, the Meydan-e-Azadi (Azadi square) station on line 4 located in the center of Tehran also revealed a near high radon concentration due to bedrock that it mainly has been consisted of calcite. Consequently, measures for better ventilation and easier air movement are required in such stations.

Correlation of Work Fatigue and Mental Workload in Train Drivers: A Cross-sectional Study.

Evidence suggests that train drivers experience a high level of fatigue and mental workload. The present study aimed to assess overall, physical, and mental fatigue levels and their correlations with the mental workload in the metro train operation. Study Design: A cross-sectional study. This study was conducted on all 1194 train drivers in the Tehran Metro. The train drivers completed the Samn-Perelli Fatigue Scale and the Fatigue Assessment Scales at the beginning and end of the shift. In addition, they completed the National Aeronautics and Space Administration Task Load Index in the middle and at the end of the shift. Correlation and regression analyses were performed on the data to test the study hypothesis. Overall, physical, and mental fatigue levels increased significantly at the end of the shift compared to the onset of the shift (P<0.001). The mental workload and related dimensions were significantly increased at the end of the shift compared to the middle of the shift (P<0.001). Mental demand was the most important workload problem among the train drivers. The highest correlation was found between overall workload and time pressure (R=0.68, P<0.001). The mental workload had a significant correlation with work fatigue in the train drivers. Control measures should be focused on the mental workload and related dimensions, especially mental demand and time pressure.

Prediction of earth pressure balance for EPB-TBM using machine learning algorithms

Face stability control of excavation with earth pressure balance machine (EPB) approach is the best available method to reduce the ground deformation and settlement of surface structures in a tunneling project in urban areas. In the present paper, several models have proposed through a statistical method, including feed-forward stepwise regression (FSR) and machine learning techniques such as support vector machine (SVM), Takagi–Sugeno fuzzy model (TS), and multilayer perceptron neural network (ANN-MLP), to provide a predictive strategy for EPB machine during the tunnel excavation. For this purpose, a monitoring dataset of machine performance parameters including advance speed, screw conveyor speed, screw conveyor torque, thrust force, and cutterhead rotation speed from Tehran Metro Line 6 Southern Extension Sector (TML6-SE) has been compiled. Then, the relation between the performance parameters and target values were investigated to analyze the available inputs and offer a new equation using the FSR. Moreover, evaluation metrics and loss functions were utilized for the evaluation of the developed models’ efficiency. The results proved the significance of the presented methods in this paper that could be used to predict the earth pressure balance operation with high efficiency.

Reducing passenger waiting time and energy consumption for metro timetabling: A robust optimization approach

Urban subway scheduling is a quite complicated task as any small fluctuation could disturb the entire system. Subway companies need an efficient scheduling system that best serves passengers and optimizes the utilization of resources. They need, therefore, to include real-world problems in their schedule through non-deterministic modeling. A robust optimization approach is applied in real-world data to propose an optimum train schedule that minimizes passenger waiting time and maximizes electrical energy converted from kinetic energy. Three high, normal, and low travel demand scenarios are considered to optimize train running-time duration in all three interstation movement categories, namely acceleration, coasting, and braking. To find the optimal solution, a genetic algorithm (GA) model has been applied to real data from a subway line in Tehran Metro.

Evaluation of foam application in providing required conditioning for EPB hard rock TBMs

AbstractUtilizing the earth pressure balancing technique on hard rock tunnel boring machines (TBMs) is an efficient way to overcome engineering geological hazards that disrupt the application of these machines. Considering that geomechanical and engineering geological conditions of soil and rock are dramatically different, proposing a suitable conditioning design for earth pressure balance (EPB) hard rock TBMs requires particular attention to the characteristics of the excavated material and ground conditions. In this paper, foam application providing a favourable support medium for EPB hard rock TBMs is evaluated based on the experience of the Tehran metro line 6 southern expansion sector project, using laboratory and actual data. TBM muck, with different water contents, was used as the test specimen after granulometry correction. The trend of changes in the workability of foam conditioned mix was obtained by performing 350 slump tests. The pressurized permeability cell test (PPCT), a testing device capable of applying high water pressures to the conditioned material, was used to evaluate the impermeability of workable mixes. Results indicate that although foam can efficiently increase the workability of dry and moistened specimens, the presence of a separated liquid phase in the test specimen disrupts its application; moreover, foam conditioned mix is permeable even against low water pressures.

Investigation of noise annoyance and audiometric results of Tehran subway workers and their relation to noise exposure

Introduction: One of the most important sources of pollution is the noise generated by traffic and transportation, especially the urban railway system (metro), thus this study aimed to assess the noise exposure of Tehran Metro employees and its relation with noise annoyance and audiometric results of employees.&#x0D; Materials and methods: Measurement was done by using a TES-1351B sound level meter recommendations for all employees which consists of the staff of the station affairs and the staff of the administrative department. A self-reporting questionnaire on workplace noise annoyance were distributed to the employees and then audiometric were used to measure the employees' hearing level.&#x0D; Results: The average noise exposure in platform workers was 79.3±10 dB and in control room workers was 56.5±6.9 dB. A significant difference was found between the average noise exposure in the employees of the two groups (control room-platform) (p-value=0.001). Based on the results, noise in the work environment was significantly more annoying for people working in metro line 1 than in line 6 (p-value=0.025).&#x0D; Conclusion: These results show that in general, due to the sound pressure level of 10% of the platform employees being higher than the permissible limit and the increase in the level of noise annoyance of the employees at the frequency of 8 kHz, it is necessary to plan and adopt administrative and technical-engineering measures to reduce the level of noise pollution to about it seems necessary to allow the standard.&#x0D; &#x0D;

Estimating Maximum Surface Settlement Caused by EPB Shield Tunneling Utilizing an Intelligent Approach

To control tunneling risk, the prediction of the surface settlement rate induced by shield tunneling using earth pressure balance plays a crucial role. To achieve this, ten independent variables were identified that can affect the amount of settlement. The nonlinear relationship between maximum ground surface settlements and ten influential independent variables was considered in artificial neural network (ANN) models. A total of 150 genuine datasets derived from the Southern Development Section of the Tehran Metro Line 6 project were used to train, validate, and test ANN techniques. Hence, the ground surface settlements of the mentioned project were predicted by the most accurate back propagation ANN technique. Ultimately, the importance level of different influential parameters on ground settlement at tunneling is relatively determined based on the results of the optimal neural network. The results used in this paper to evaluate the relative importance of each variable involved in the rate of ground surface settlement demonstrate that the parameters of grout injection and permeability equivalent to the proportions of approximately 16.91% and 5.07% have the highest and lowest impact, successively.

Smart Trip Prediction Model for Metro Traffic Control Using Data Mining Techniques

In the urban rail transportation industry, collecting various data, including the number of trips, the number of fleet breakdowns, the number of breakdowns of railway lines, etc., contributes significantly to future planning and optimization of resources and costs. We are faced with big data analysis due to the daily production of large volumes of data in the urban rail transport industry. This study aims to find a trip prediction model for Tehran Metro to do trip decision-making. This paper provides a brief introduction to knowledge discovery from failure databases and presents the data mining methodology. The relevancy of data mining for a trip prediction model will be depicted. In this sense, considering the relevance of data collected on the metro control center and intelligent trip prediction, this paper presents a functional architecture of a predictive trip model using data mining techniques. Data Mining will identify behavior patterns, allowing a more accurate early detection of faults in the daily operation. This research has investigated three situations, including delayed trips, incomplete trips, and canceled trips, using actual data recorded over the past four years, including non-programmed failures and their impact on trips. A model with more than 90% (90.48%) accuracy suggests a trip status forecast on this line. Also, the research has used Rapid Miner software and the Decision tree technique in data mining and its rules. Also, the kappa index of 0.792 is calculated for the validation model. Therefore, the proposed model enables the prediction of three types of incomplete traffic, delayed trips, and cancellation of trips due to emergency failure at the time of the operation of the Tehran Metro.

A Train Scheduling for Energy Optimization: Tehran Metro System as a Case Study

Energy efficiency is one of the main issues in designing and operating different electrical systems. Energy-saving in electrical railway systems is an important concern due to the high amount of used energy. In order to find optimum energy consumption, different methodologies shall be examined. In addition, various affecting factors should be determined, and suitable solutions should be adopted. This paper illustrates that proper train scheduling is one of the effective approaches to optimize the system energy. Accordingly, comprehensive modeling is proposed considering different affecting factors such as the slope of different lines, the speed limits in each section, the time limit between the arrivals of trains to each station, and different modes of operation such as motoring and braking. Using the proposed model, an optimization problem with the objective function of energy-saving is solved. To evaluate the effectiveness of the proposed method, the proposed scheduling scheme is applied to Line 2 of Tehran Urban & Suburban Railway Operation Company. Based on the results, using the proposed scheme causes a 3.2% energy-saving compared to the existing train movement schedule in the same line. The proposed train movement scheduling program is proceeding to the last verification steps and will be used as a part of Tehran Metro navigation system in the near future.

Monitoring of urban subway lines subsidence Using satellite radar interferometry method (Study area: Part of Tehran Metro Line 7)

Monitoring of urban subway lines subsidence Using satellite radar interferometry method (Study area: Part of Tehran Metro Line 7)

Do rail transit stations transform hosting neighbourhoods? Comparative evidence from high-income and low-income neighbourhoods in Tehran

The potential roles of rail transit investment have been extensively investigated in urban development and management processes. Applying the difference-in-differences model based on a longitudinal data set (2006-2016), this article presents comparative analysis of the surrounding neighbourhoods of four Tehran Metro Rail System (TMRS) stations in order to explain how neighbourhoods can be differently affected by the development of railway stations. The four areas include both high-income and low-income neighbourhoods. The results show that the northern high-income neighbourhoods and the southern low-income neighbourhoods have been transformed heterogeneously in terms of their sociodemographic compositions, housing characteristics, land uses and renewal.

Efficiency of different methods for calculating the mechanized tunnels face pressure considering an earth pressure balance

Different methods for calculating and estimating a safe face pressure were proposed by researchers, which have some advantages and disadvantages. In each of these methods, some related parameters such as soil geotechnical parameters, dimensions of the tunnel, and geological conditions are used. In these methods, using a series of mathematical or empirical functions, the face pressure is calculated. In this study, the face displacements were obtained using the finite difference numerical FLAC3D, the COB (Netherlands Underground Science Center) empirical, and the Leca and Dormieux (1990) analytical methods. The impact of the COB method on different ground stiffnesses is studied and evaluated. The reference case of this research is the Tehran Metro Line 6 tunnel (excavation radius: 4.6 m).

Importance – Performance Analysis (IPA) of metro service attributes during the COVID-19 pandemic

BackgroundThe study of user satisfaction with public transport services is of key interest for enhancing public transport ridership. However, the elevated risks of virus transmission on public transport associated with COVID-19 have resulted in a shift towards private vehicles. This issue is of concern to policymakers due to reduced levels of public transport use and increased private vehicle trips. Thus, it is relevant to re-evaluate attributes impacting user satisfaction during the COVID-19 pandemic to understand how this compares to related research undertaken before the pandemic. MethodologyThrough a survey of 507 Tehran Metro users, the structural patterns among 33 metro service attributes were determined using Exploratory Factor Analysis (EFA). A service quality model of the Tehran Metro service (including cleanliness, ventilation/temperature, congestion, operation hours, ticket, information, reliability, and safety) was then designed using Confirmatory Factor Analysis (CFA). Attributes and latent constructs were classified using Importance – Performance Analysis (IPA). FindingsAttributes associated with general congestion in the metro, the performance of the metro during peak hours, cleanliness, and temperature/ventilation were found to be among the most influential attributes during the pandemic. ConclusionBefore the COVID-19 pandemic, time and cost effectiveness were key attributes affecting the choice of travel mode. Due to the outbreak of the virus, safety and health have been identified as the main attributes affecting the choice of travel mode. In this research, with a case study of the Tehran metro, it was found that there is a shift in attributes affecting service quality towards cleanliness, congestion and temperature/ventilation. As a result, a range of policies is needed to deal with the effect of COVID-19 on metro services. These include: increasing the number of metro services, reducing the time interval between metro services, improving air conditioning, and regular cleaning of vehicles. Policymakers can use the results of this study to improve user satisfaction with metro services and increase ridership levels during the pandemic.

Rail transit station and neighbourhood change: A mixed-method analysis with respect to neighbourhood context

While increasing evidence suggests a determining role of urban rail transit in shaping and transforming cities and neighbourhoods, empirical studies on the simultaneous development of rail infrastructure and neighbourhood change are scarce. This paper attempts to evaluate the neighbourhood changes around rail transit stations as well as provide a possible explanation of how neighbourhoods can be differently affected by the presence of rail stations. Based on a longitudinal dataset (2006–2016) and using a mixed-method approach, a comparative analysis of six stations of the Tehran Metro Rail System is conducted between the high-income neighbourhoods and low-income neighbourhoods of the city. The Difference-in-Differences analysis yields that the northern high-income neighbourhoods and the southern low-income neighbourhoods of Tehran have experienced a heterogeneous model of changes in terms of demographic, housing, and land-use factors. In addition, the semi-structured interviews indicate that the heterogenous estimated changes in neighbourhoods around the case-study stations could be explained by the contextual factors of the northern and southern host neighbourhoods in Tehran including socio-cultural changes (social factors), land-use changes (physical factors) and the need for public transportation (transportation factors).

Identifying and Prioritizing the Risks of Urban Rail Transportation Networks with Emphasis on Resilience (Case Study: Tehran Metro)

Identifying and Prioritizing the Risks of Urban Rail Transportation Networks with Emphasis on Resilience (Case Study: Tehran Metro)

Socio-spatial transformation of neighbourhoods around rail transit stations: an experience from Tehran, Iran

While increasing evidence suggests that rail infrastructure plays a structuring role in shaping and transforming cities and regions over time, empirical studies on the simultaneous development of rail infrastructure and socio-spatial transformation of surrounding neighbourhoods, especially at a local scale, are scarce. The main aim of the article is to evaluate the transformation of neighbourhoods around rail transit stations, as well as provide a possible explanation of how neighbourhoods can be differently affected by the presence of rail stations. Based on a longitudinal dataset (2006–16) and using a Difference-in-Differences (DID) model and Multivariate Analysis of Variance (MANOVA), a comparative analysis of the Tehran Metro Rail System (TMRS) is conducted between high-income neighbourhoods and low-income neighbourhoods of the city. The results yield that the northern, high-income neighbourhoods and the southern, low-income neighbourhoods of Tehran have been transformed heterogeneously in terms of socio-demographic factors, land-use conditions and renewal processes. The findings also indicate that the mixed estimated transformation of neighbourhoods around TMRS’s stations could be explained by the contextual factors of the northern and southern study settings in Tehran, including land-use characteristics and socio-economic factors.