Metro System Research Articles

Novel Approach to Optimizing Express-Local Metro Train Timetable Considering Multiple Train Stopping Patterns

A traditional hybrid operational mode of a metro system usually combines the express and local trains. The stopping patterns of express trains are generally assumed to be the same. To provide a diverse service, this paper aims to explore the train timetable optimization method when the express trains have different stopping patterns. A passenger-oriented timetabling model for reducing passenger waiting time is established, which is proved to be a quadratic programming problem. Then, an Interior Point Method is applied to obtain the best timetable. A case study based on the Guangzhou Metro Network is conducted, symbolizing different operation strategies. The results indicate that the proposed model can efficiently reduce the passenger waiting time by 16.8% and the number of stranded passengers by 15.9%. The practical implications of this research are significant, as it introduces a new approach to train timetable optimization that can be applied to real-world metro systems.

How do access and spatial dependency shape metro passenger flows

Spatial imbalances in metro ridership significantly reduce the overall efficiency of metro system. Understanding the factors that contribute to metro ridership is essential for developing targeted strategies to improve ridership equity and overall system performance. This study introduces novel spatial dependency indices based on spatial weight matrices and land-use function complementarity to explore how access and inter-station spatial dependency affect metro ridership, focusing on station-level boardings and alightings, as well as station-to-station flows. Using the data from the Xi'an Metro, the findings indicate that access to employment and residence from metro stations considerably enhances station-level boardings and alightings. Walking access emerges as a critical factor, especially in the context of station-to-station travel. Furthermore, the analysis reveals a complementarity feature within the metro system, where increases in boardings (alightings) at one station leads to a higher demand at others. Stations that serve areas with complementary land-use functions tend to attract more travel between them. These findings emphasize the critical role of access and spatial dependency in enhancing transit planning and system efficiency.

Analysis of Metro Users’ Perception Towards Attributes Related to Bicycle–Metro Integration: RIDIT and TOPSIS Model Approach

This study investigates the viability of incorporating bicycles into the Dhaka Metro system, a groundbreaking urban transit project for Bangladesh. As Dhaka’s inaugural metro rail network, the system signifies a substantial advancement in addressing urban congestion and enhancing transportation alternatives in one of the world’s most densely populated cities. The current design of the metro fails to accommodate bicycles, hindering efficient first- and last-mile connectivity. The investigation utilized data from 382 fully completed questionnaires, obtained through purposive sampling, about metro–cycle integration in Dhaka. The research employed RIDIT and TOPSIS analyses to rank the characteristics deemed most essential for bicycle–metro integration according to user opinions. Research indicates that secure bicycle parking, multi-modal ticketing, route comfort, and safety measures are the foremost objectives for commuters. The high emphasis on secure parking indicates the need for safe and accessible storage options that would make cycling a viable mode for reaching metro stations. A multi-modal ticketing system further enhances convenience, providing seamless transitions between transit modes. Journey comfort and the need to mitigate risks posed by motorized vehicles underscore the importance of safe and user-friendly commuting environments. While features like road and station design were ranked lower in priority, the study emphasizes that a well-integrated bicycle infrastructure is essential to ensure the metro system’s success. With these improvements, Dhaka’s metro system can meet the growing demands for sustainable and inclusive urban mobility, setting a precedent for future infrastructure projects in Bangladesh.

A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions

This systematic literature review (SLR) focuses on indoor environmental quality (IEQ) in passenger transport vehicles within tropical and subtropical regions. It specifically examines indoor air quality (IAQ), thermal comfort (TC), acoustic comfort (AC), and visual comfort (VC) of passenger vehicle cabins (PVCs) in auto rickshaws, sedans, trucks, bus rapid transits (BRTs), buses, trains, trams, metro systems, aircraft and ferries of tropical and subtropical regions. The SLR used the PRISMA approach to identify and review scientific studies between 2000 and 2024 on the IEQ of PVCs in the tropics. Studies reviewed were found in SCOPUS, Web of Science, Science Direct, and EBSCO databases including relevant citation references. Findings reveal a significant geographical imbalance in research, with most studies concentrated in tropical Asia (78.2%), while sub-Saharan Africa (8.2%), South America (11.8%), and Oceania (1.8%) are considerably underrepresented. In 113 studies, most addressed IAQ and TC but limited attention to AC and VC. Moreover, fewer studies have jointly addressed all the IEQ parameters, highlighting the need for a more comprehensive approach to IEQ for tropical PVCs. Several studies alluded to in-cabin commuter risk linked to PM2.5, PM10, carbon monoxide (CO), and volatile organic compounds (VOCs). These risks are exacerbated by traffic hotspots, poor ventilation, ambient pollution, overcrowding, and poor vehicle conditions. Additionally, thermal discomfort is compounded by extreme heat loads, inefficient HVAC systems, and high vehicle occupancy. Common gaps include a paucity of IEQ studies and inadequate IEQ regulations or adapted standards in developing tropics. Infrastructural and regulatory deficiencies have been identified, along with strategies for mitigation. Recommendations are for more holistic IEQ studies in the tropics, including exposure studies for emerging gaps in new indoor pollutants, integration of AI and IoT for sustainable ventilation strategies, and development of effective regulatory frameworks considering region-specific conditions. Finally, Policymakers are encouraged to establish localized IEQ standards, enforce regulations, and prioritize upgrades to transport infrastructure. The SLR findings emphasize the urgent need for targeted interventions in developing tropical regions to address disparities in IEQ, ensuring healthier and more sustainable transport environments that could be replicated across transport systems worldwide.

Evaluating the Accessibility of Pedestrian Sidewalks to Connect Public Transport: A Pilot Study in Valparaíso, Chile

The need to assess whether accessibility in urban mobility meets the required standards to provide a satisfactory experience for users is emphasized. The general objective of this research is to evaluate pedestrian accessibility in urban mobility, taking as a case study different access points such as the sidewalks and crossings between the trolleybus system and the EFE metro system in Valparaíso. Specific objectives have been set, including identifying the area to study and the elements to evaluate, designing an evaluation system, and applying descriptive and numerical methods for the assessment. The methodology used includes two approaches: the descriptive, which provides a detailed view of accessibility conditions in each evaluated area, highlighting aspects such as physical condition and compliance with regulations, and the numerical, which assigns quantitative values to the elements being assessed to establish a classification of accessibility levels. Additionally, a survey was conducted to obtain a subjective view of pedestrian preferences. Based on the above, evaluating pedestrian accessibility in urban mobility in Valparaíso allowed for identifying aspects that require improvement to ensure a satisfactory experience for users. Furthermore, it promotes the use of both transportation systems and provides recommendations for future research.

Comparison and Optimization of Rail Defect Detection Methods Based on Object Detection Model

Rail maintenance is an extremely complex but important component of a metro system. In response to the frequent occurrence of rail defects, the rail defect detection based on object detection is compared and optimized. First, the detection performance of the Single Shot MultiBox Detector (SSD) model and the Fast Region-based Convolutional Network (Faster R-CNN) model on rail defect are compared through model training and validation. Second, to address the issue of low defect visibility in images, the rail defect detection method combining the grayscale histogram equalization and the Faster R-CNN model is proposed. Finally, to address the issue of failed detections in rail defect detection, the Faster R-CNN model is improved by adding the Feature Pyramid Network (FPN) structure. Results show that the rail defect detection method using the Faster R-CNN model is more accurate, with the rail defects of mean average precision (mAP) is 75%. By performing grayscale histogram equalization, resulting in a 2-percentage point increase in the mAP0.75 of the rail defect detection based on the Faster R-CNN model. By combining the FPN with Faster R-CNN model, the mAP of small-scale defect detection is increased by 15 percentage points, and the AP of various rail defects is increased by 3, 13, 13, and 15 percentage points, respectively.

The impact of the Bangkok metro expansion via Big Taxi GPS probe data

Urban rail investments in megacities aim to reduce congestion and related externalities. This study investigates the impact of Bangkok’s metro expansion on taxi trips using GPS-based data from 2017 to 2019. A rigorous approach to processing and analyzing the extensive traffic data in a difference-in-differences estimation framework shows that the metro expansion decreases taxi trips by approximately 32.2%, compared to areas not served by the metro system. This effect persists for catchment sizes of 300, 500, and 800 meters and increases over time. Bangkok’s 19 new metro stations result in an annual climate benefit of approximately 0.17–0.34 MtCO2-eq yearly or 0.21–0.42% of Thailand’s transport sector emissions. Excluding private vehicle trips from the analysis, this is a conservative estimate of total climate savings. Multi-decadal CO2 emission savings are valued at around $1 billion, supporting the need for climate funding for transit systems in rapidly growing cities in developing countries.

Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies

Introduction: With the rapid urbanization of modern cities, metro systems have become indispensable for efficient mobility. However, the increasing demand for public transportation has led to rising energy consumption, posing significant challenges for operational sustainability. Current energy management strategies in metro networks rely on static models and centralized systems, which often fail to adapt to real-time fluctuations in energy demand, leading to inefficiencies and wasted resources. Methods: This paper proposes an innovative approach to optimizing energy demand in metro systems by integrating Artificial Intelligence (AI) and the Internet of Things (IoT). By leveraging real-time data collected from IoT sensors deployed throughout the metro network, we apply machine learning algorithms such as Random Forests and Neural Networks to dynamically predict energy demand. These predictions enable metro operators to adjust energy consumption in real-time, thus improving overall system efficiency and reducing operational waste. Our approach was validated using data from the Parisian metro system through extensive simulations. Results: The results of simulations demonstrate significant improvements in energy efficiency. Optimized energy demand management led to a reduction in wasted energy during metro operations, particularly through the utilization of regenerative braking systems. Conclusions: Our findings suggest that integrating AI and IoT technologies into metro systems significantly improves energy efficiency by enabling dynamic energy demand prediction and real-time adjustment of energy consumption. The proposed system is scalable and adaptable, making it suitable for application in metro networks globally, thereby enhancing energy efficiency and supporting sustainable transport initiatives.

Blockchain-Powered Energy Optimization in Metro Networks: A Case Study on Electric Braking

As urban populations continue to expand, the need for efficient and sustainable metro systems has become increasingly pressing. Traditional energy management methods, while somewhat effective, often fall short in fully utilizing the potential of regenerative braking systems within metro networks. These conventional approaches, which rely heavily on centralized control and energy storage systems, encounter scalability, security, and transparency limitations. Additionally, inefficient management of energy recovery data can result in significant energy losses and higher operational costs. In response to these challenges, this study proposes a blockchain-based solution utilizing Proof-of-Work (PoW) algorithms to optimize energy recovery, particularly during electric braking in metro systems. The developed model securely and transparently validates energy recovery events in real-time, eliminating the need for centralized oversight. By customizing the PoW algorithm, we achieved a balance between computational efficiency and strong security, making this solution scalable and practical for large metro networks. Initial simulations demonstrated a 12-15% improvement in energy recovery efficiency and a 10% reduction in operational costs compared to traditional systems. Furthermore, the comparison between net energy gains and the energy expended by the PoW process highlights the transformative potential of blockchain technologies in metro transportation, offering a pathway to more sustainable and environmentally friendly urban mobility solutions.

Evaluating the robustness of attributed dynamic bus-metro networks based on community reconstruction

Despite significant advances in applying complex network theory to analyze the robustness of public transport systems, one still cannot seamlessly incorporate complex topological structures into existing algorithms, network modelling remains inaccurate, and high-level features of public transport systems cannot be captured effectively. Moreover, the identification of community structures with dynamic transfer relationships between bus and metro systems requires well-designed formulas and sophisticated computer codes. This study aims to evaluate the robustness of bus-metro networks based on community reconstruction. Firstly, we constructed an attributed dynamic bus-metro network, considering the socio-economic environment of the public transport system and the dynamic transfer relationship between bus stops and metro stations. Secondly, we introduced the community reconstruction approach, proposed a robustness estimation model, and designed community-based strategies for node and edge attacks, which are ComNA and ComEA, respectively. Finally, taking a real-world bus-metro system in Xi'an as a case study, this research evaluates the system's robustness under various attack strategies and analyzes the impact of dynamic transfer relationships on robustness. The results reveal that: (1) The performance of public transport networks exhibits varying trends under different attack strategies. Notably, the bus-metro network demonstrates enhanced robustness to random attacks compared to targeted attacks. (2) Community-based attack strategies are more effective than traditional methods in dismantling public transport networks. (3) Enhancing the transfer capacity at metro stations significantly improves the overall robustness of public transport systems. These results are of critical importance for improving the robustness of public transport systems.

Optimization of Energy Involved in Rolling Stock of a Sub-Urban Rail Transport System

Objectives: This research is based on the real-world study of Mumbai Metro, which focuses on enhancing the efficiency of metro rail systems by optimizing the timetable to synchronize train movements. The primary goal is to minimize total energy consumption by maximizing the exchange of regenerative-braking energy. Methods: Mumbai Metro Rolling Stock is having regenerative braking systems, allowing surplus energy regenerated during braking to be transferred to other trains in the same electrical rail section. To achieve this optimization, a graphical method is used to coordinate the time synchronization of the braking train arriving at a station with the accelerating train departing from the same or different station. This coordination ensures that regenerative-braking energy is effectively utilized and distributed among trains within the system. By quantifying the energy savings resulting from synchronization, this model provides an incentive for implementing more efficient train scheduling practices. The application of this model was demonstrated through the design of schedules for the Mumbai Metro. The implementation resulted in measurable energy savings, showcasing a clear correlation between train movement synchronization and reduced energy consumption. Importantly, this optimization strategy does not compromise overall passenger service quality and can be implemented with relatively low investment costs. In conclusion, adjusting the timetable in force based on principles of time synchronization and energy optimization has the potential to yield considerable energy savings for metro rail systems. Findings: This research emphasizes the importance of strategic train scheduling in maximizing the efficiency and sustainability of public transportation networks using regeneration of electrical energy. By implementing the optimized timetable, could lead to approximately a 5.03 % increase in regenerative energy utilization which would save 2.2 % in total energy consumption. Novelty: This study introduces a novel method to assess energy cooperation between trains using timetable optimization because this is the first real-world study of its kind conducted on any Indian metro system in which if one train is in braking mode then another train in the same electrical section should be in motoring mode so as to avoid the losses of the regenerated energy. Keywords: Optimization, Headway, Dwell time, Coasting period, Traction energy

A Lifestyle-Based Perspective on the Mobility Choices and Preferences of Urban Travelers

This study investigates how lifestyle factors influence mobility choices within the metropolitan area of Thessaloniki, which is the second largest city in Greece. The primary objective is to understand the interplay between lifestyle attitudes and preferences for sustainable mobility options. This research utilizes data from a comprehensive survey conducted among Thessaloniki’s inhabitants, identifying four distinct attitudinal clusters shaped by lifestyle characteristics and general attitudes toward recycling, energy conservation, social distancing, and other factors. A two-step clustering approach combining hierarchical and k-means methods as well as Chi-square and Kruskal–Wallis tests were employed to investigate whether life attitudes are correlated with revealed and stated mode choices as well as beliefs, perceptions, and feelings related to the current and future public transport systems and micromobility options in the metropolitan area of Thessaloniki. The findings reveal significant variations in mobility choices across the identified lifestyle segments with environmentally conscious segments showing a higher propensity for sustainable modes of transport. Additionally, differences are observed in perceptions and intentions regarding micromobility and the future mass transit system within the region, suggesting that when introducing a new metro system that is expected to promote a shift toward public transport, segment-specific approaches are necessary for raising awareness and increasing trust to the new mode.

Two-stage optimization for site selection and resource allocation of metro rescue stations

Metro systems serve as the backbone of modern urban transportation, with elevators being critical facilities within metro stations. Aiming at the problem of elevator emergency rescue in urban subway, a two-stage optimization model of location selection and resource allocation is proposed. In the first stage, based on the distribution and coverage of metro stations, we construct a Minimum Site Selection Model and a Maximum Coverage Model with a Fixed Number of Rescue Stations. Utilizing a mixed-integer programming approach, we determine the optimal layout for rescue stations, ensuring that the minimum number of stations covers all target locations. In the second stage, we develop a resource allocation model that optimizes the distribution of limited resources among rescue stations by balancing utility and cost. To address this nonlinear mixed-integer programming problem, we conduct a comparative analysis of the efficiency and effectiveness of five heuristic algorithms in resource allocation. The results indicate that Particle Swarm Optimization (PSO) and Tabu Search (TS) achieve the highest benefits under a concentrated resource allocation strategy, while Genetic Algorithm (GA) and Ant Colony Optimization (ACO) perform well in balanced resource distribution. This research provides theoretical support for emergency management in urban metro systems.

Last train schedule optimization for metro systems considering minimum adjustment cost under elastic passenger demand

ABSTRACT Optimizing the last train schedule is challenged by the elastic nature of passenger flow and the immutability of the schedule once announced to the public. The elastic passenger demand is first mathematically described, and an optimization method is proposed to minimize the adjustment to the last trains while maximizing the accessible passengers within the metro network. Linearization techniques are then employed to transform it into a linear programming form. The proposed method is verified through a real-world case study, which indicate an 8.4% increase in accessible passenger flow on a weekday with adjustments required for only 3 lines and 10 stations’ last train times. In a special event scenario, a 9.8% is achieved with adjustments to 2 lines and 8 stations’ last train times. The results suggest that for existing metro systems, judiciously adjusting the last train times can effectively enhance the overall level of nighttime operational service.

Metro train rescheduling approach during the transitional period

ABSTRACT Metro systems will inevitably be affected by train delays. Train delays during the peak to off-peak transitional period potentially lead to passengers being stranded. To address this problem, this study develops a train rescheduling model that comprehensively considers train delays, service cancellations, and the passenger service quality. The rescheduling strategy of adding temporary train services is particularly considered based on operational characteristics during the transitional period. Next, the model is transformed into a mixed-integer linear programming (MILP) model using linearization methods. To improve computational efficiency, a two-stage approach is proposed. Finally, numerical examples based on practical data from the Beijing Metro Yizhuang line are conducted to verify the effectiveness and efficiency of the proposed approach. The computational results show that the model proposed in this study can reduce the number of stranded passengers during the transitional period, and the two-stage approach can obtain high-quality feasible solutions in a short time.

A Study on Evaluating Impact of Environmental Concern on Intention to Use Eco Friendly Public Transport

In India, eco-friendly public transportation such as electric buses, metro systems, and ride-sharing schemes is progressively growing to lower emissions and ease traffic in cities. Reduced air pollution, fewer greenhouse gas emissions, better public health, and more sustainable urban mobility are all advantages of eco-friendly public transportation that help create a cleaner and healthier environment. Concern for the environment is a reflection of people's knowledge and concern for environmental issues, which shapes their decisions towards sustainable practices. This study is motivated with the focus to promote sustainable urban mobility in India by determining how environmental concerns affect the intention to use eco-friendly public transport. The technique used in the current study is Structural Equation Model. The findings of the study indicated that there is a significant impact of environmental concern on intention to use eco-friendly public transport.

How does shared mobility impact metro-based urban commercial travel accessibility and Equity?

The integration of shared mobility services, such as bike-sharing and ride-hailing services, with metro systems enhances the effectiveness and convenience of urban mobility. Various transportation modes significantly impact the accessibility and equity of commercial travel for the purpose of shopping, entertainment, tourism, and catering, due to the diversity of options, destinations, and origins. This study, based on the primary urban regions of Chengdu in 2023, employs the Gaussian two-step floating catchment area model, Gini Index, and Lorenz curve to examine the effects of shared mobility on the accessibility pattern and spatial equity of commercial services. It shows that the bike-sharing-metro travel mode enhances overall commercial accessibility, whereas the ride-hailing-metro travel mode has a substantial impact on accessibility distribution. Additionally, the commercial accessibility distribution pertains to the arrangement of commercial establishments in short-distance travel, whereas it exhibits a central hub and peripheral locations for long-distance travel. While the equity of commercial services improves effectively, metro transportation remains situated at the core of the transportation mode. The creation of the metro transit-oriented development should thoroughly assess the impact of shared mobility on the station area and prioritize the equilibrium between urban commercial and residential sectors.

Short-term Subway Passenger Flow Prediction based on LSTM and ARIMA Model

With the acceleration of urbanization, urban traffic problems have become increasingly severe. To alleviate urban traffic congestion, the development of public transportation has been greatly emphasized. As a convenient and rapid means of urban travel, the metro has become the preferred choice for citizens, leading to significant passenger flow pressure. Therefore, it is crucial to forecast passenger flow in advance. This paper utilizes passenger flow data from Chengdu Metro Line 1 from May to September 2019 to conduct a study. LSTM and ARIMA models were constructed to simulate the actual passenger flow data. The prediction performance of both models shows that the trends simulated by these models fit the original data well, verifying their applicability in passenger flow forecasting. Furthermore, it was found that the LSTM model outperformed the ARIMA model among the constructed models in this paper. Accurate metro passenger flow forecasting can help relevant departments manage the metro system more effectively, thereby improving passenger travel efficiency and safety.

Energy Efficiency Improvement on Railway Lines: An Overview

ABSTRACTGreater efficiency in the consumption of energy in the transport sector would mean lower emissions of CO2 and other gases and particles, which contribute to climate change. One of the ways to reduce the impact that the transport sector has on climate change turns out to be the achievement of services with a more efficient consumption of energy per passenger‐km or t‐km transported. Energy consumption has been an ongoing concern in the railway sector practically since its inception. There has always been an interest in finding solutions to reduce it, such as improvements in rolling stock design and the use of regenerative braking which will not be analyzed in this article, and optimal train movement, operation and timetabling, and infrastructure design. This article analyses the existing methodologies that allow the improvement of energy efficiency, and we verified that the developed studies focus more on LRT and Metro systems, and existing infrastructures, namely Urban Rail Transit, characterized by high levels of traffic and energy consumption. However, regarding the analysis of conventional railway infrastructure characteristics and design from an energy efficiency point of view, we found that less has been done relative to strategies to improve energy efficiency.

Life between Stations: A visualization of non-metro trips and associated station pairs in Hong Kong

Trip chains, consisting of multiple interconnected trips serving different functions and/or purposes, occur commonly among urban residents. Non-metro trips (NMTs) between a pair of metro stations as parts of trip chains predominantly carried by metro systems have received little attention in the existing scholarship and practice. They contribute, however, to “Life between Stations” (LbS)—various activities engaged in by metro riders and other urban residents around or between stations. LbS affects residents’ level of satisfaction for trip chains, sense of belonging, and even overall quality of life. But for a given city, where do those NMTs occur more frequently and how long are the durations? Using the 12-weekend metro smartcard swipe records in 2019 in Hong Kong, we defined, quantified, and visualized NMTs and associated metro station pairs in a real-world setting. We found that (a) the NMTs and LbS occurred between as many as 179 metro station pairs, involving 84 out of the 95 local metro stations, (b) the NMTs and LbS varied across the station pairs and/or metro lines, and (c) commercial and densely populated areas saw more than elsewhere. These findings shed light on efforts undertaken to better understand and improve LbS of metro riders.