Mass Transit Rail Research Articles

Geo-spatial analysis of transit planning for sustainable tourism development in Bangkok, Thailand

ABSTRACT In the contemporary urban landscape, the rail mass transit system assumes a crucial role in shaping city tourism, primarily attributable to its commendable efficiency in ensuring safety and optimizing travel times. A comprehensive understanding of this system becomes imperative for formulating strategies aimed at augmenting the tourism potential it facilitates. Consequently, this study employs rigorous spatial analysis, concentrating on tourist attractions and their accessibility levels within the Transit-Oriented Development (TOD) center and an area outside the TOD center (non-TOD). The empirical results of this investigation unveil that the distribution characteristics of a substantial proportion of tourist attractions manifest clustering tendencies (Z-score exceeding 1.65), particularly in areas synonymous with historical and recreational activities. In contrast, specific activities such as cultural and agricultural pursuits exhibit a random distribution characteristic (Z-score between −1.65 and 1.65). Notably, it becomes apparent that activities characterized by distinct distribution patterns also harbour varying potentials for accessibility. In essence, this scholarly endeavour contributes nuanced insights into the intersection of urban rail mass transit systems and tourism dynamics, shedding light on the intricate relationships between spatial distribution, activity characteristics, and accessibility levels within diverse urban contexts.

Exploring Spatial Accessibility to Urban Activities Based on the Transit-Oriented Development Concept in Pathum Thani, Thailand

Transit-oriented development (TOD) serves as a model for sustainable urban planning, integrating land use and transport planning. Successful implementation varies across specific geographic locations and has yet to be fully realized in the suburban areas of Thailand. This study empirically examined and searched for understanding of the enhanced accessibility to urban activities through the TOD concept by focusing on bus stops and rail mass transit. The study utilized a network buffer zone approach around transit areas as TOD measurement units, examining distances of 500 m, 1000 m, and 2000 m. Spatial analysis was applied to examine and understand the enhanced accessibility to urban activities through TOD by using network analysis, Getis-Ord Gi* hotspot analysis, and bivariate local Moran’s I. The results revealed that this area still has limited access to activities via public transport, particularly in the areas where activities are concentrated, especially in commercial, mixed-use, and residential zones. However, upon examining the relationship between access distance and the intensity of land use activities, it became apparent that within the network buffer zone encircling the transit areas, designated as transit-oriented development (TOD) measurement units, there exists a notable concentration and diversity of land use activities. Specifically, enhanced accessibility to the transportation system corresponded to increased activity density. Nonetheless, this correlation was predominantly observed at stations situated in more central areas, whereas stations located at greater distances exhibited a lower intensity and diversity of activities within the TOD zone.

Perceived service quality based on passenger and trip characteristics: A structural equation modeling approach

In order to improve public transit as a customer-oriented service, it is essential to evaluate service quality from the customers' perspective. Various groups of passengers perceive service quality differently based on their demographic and trip characteristics. In addition to a naïve market segmentation which is based on pre-defined groups, this study proposes a cluster analysis to identify groups with combined characteristics. This paper utilizes a customer satisfaction survey (CSS) to better understand the impact of several attributes on satisfaction perceived by different groups of passengers. 1028 valid survey responses are utilized from a case study that is a mass transit rail in Tehran, a less focused context in the literature. Structural Equation Modeling (SEM) is used to identify the most effective attributes in each group. The results indicate that different groups do perceive certain aspects of the service quality differently which underscores the necessity of undertaking a market segmentation analysis by clustering. Despite differences among groups/clusters, passengers will be more satisfied with a secure and convenient transit system. The findings from this study can be used to develop strategies for specific customer groups and evaluate factors that influence customer satisfaction of such groups.

The role of transit accessibility in influencing the activity space and non-work activity participation of different income groups

Improved accessibility by transit service constitutes a critical component in removing spatial barriers in daily mobility for disadvantaged groups. However, the effects of transit accessibility on the daily mobility and activity participation of different social strata remain inconclusive. This study investigates the role of transit accessibility on the activity space of three income groups in Hong Kong. The results show that the availability of transit stations and network accessibility by mass transit rail (MTR) are significantly linked to the spatial extensiveness of activity space of the higher- and medium-income commuters, while bus plays a more important role for the daily mobility of the low-income group. Concerning non-work activity participation, the low-income non-commuters appear less affected by the availability of MTR stations than the other two groups, suggesting a potentially lower ability of using MTR to carry out different daily activities. Our findings offer some in-depth insights into the possible social inequality of using transit service, thereby contributing to a more nuanced understanding of the relationship between transit accessibility and mobility in relation to economic status. Policy recommendations to alleviate transport disadvantage and improve social equity are proposed.

Hazard identification and risk assessment of Abuja rail mass transit

Abstract Due to multiple advantages in terms of capacity, safety, dependability and punctuality, rail mass transit plays a vital role in easing urban traffic congestion. In addition, rail mass transit is environmentally friendly. Even though it is beneficial to passengers in urban areas, security issues have become increasingly serious in recent years. To improve the safety and dependability of the rail mass transit system to some extent and limit the loss to a bare minimum, it is necessary to identify and evaluate the hazards connected with rail mass transit in the early stages of the system's operation. Against this backdrop, this research employs a risk matrix approach to examine the dangers connected with Abuja's rail mass transit system (ARMT). The questionnaire is designed and delivered to 100 participants, including personnel and passengers, to get their perceptions of hazards at the ARMT. The questionnaire is the initial step in the research process. The four safety variables discussed in this study are human error, equipment design failure, environmental conditions and management. Human error is the most significant factor covered in this research. Understanding the source of risk stemming from these four safety variables at the early stages of rail mass transit operation can significantly improve the system's overall safety and reliability, which can be paramount. According to the findings of the investigations, human-related activity is the most significant possible cause of risk at that ARMT, with a high level of risk portrayed by the data.

Data-driven multi-output prediction for TBM performance during tunnel excavation: An attention-based graph convolutional network approach

A deep learning-based multi-output prediction model is developed to better understand and more accurately estimate tunnel boring machine (TBM) performance in each segment ring during the deep excavation under complex underground environments. The novelty lies in the development of a new deep learning approach named att-GCN, which feasibly integrates the graph convolutional networks (GCN) and scaled dot-product attention mechanism to improve model performance and interpretability. It is proved that our proposed att-GCN model is outstanding in significantly enhancing the prediction performance and effectively capturing the influence between monitoring points. As a case study, the proposed method is validated in a Singapore Mass Rail Transit (MRT) construction project, where seven features associated with the TBM machine are input for att-GCN training and testing. Experimental results reveal that the att-GCN model can exhibit a powerful capability in simultaneously predicting two targets named penetration rate (y1) and energy consumption (y2), reaching the mean absolute percentage error (MAPE) value at 15.475% and 15.173%, respectively. In terms of prediction accuracy, att-GCN is superior to some state-of-the-art algorithms, including deep neural network (DNN), random forest (RF), and support vector regression (SVR). Moreover, an online-learning version of att-GCN is designed. When the objective value is gradually known and fed into att-GCN during the tunneling procedure, the model can yield more impressive performance under the MAPE of 8.504% (y1) and 7.934% (y2). Accordingly, the real-time estimation of TBM performance based on the time-varying monitoring data provides valuable evidence to realize the intelligent control of TBM tunneling, which can ultimately improve construction efficiency and reliability.

Examining China’s Intervention in Nigeria’s Transport Infrastructure

For a country with over 200 million people and a severe infrastructural deficit, the reality is that Nigeria has no wherewithal to meet the demand for fixing its transport infrastructural deficit, alone, without external financing and technical assistance. With the rising constraint on public resources and fiscal space, it is obvious that the government alone cannot provide the resources necessary to address the transport infrastructural deficit in a country like Nigeria. Hence, the importance of China’s intervention in reducing the transport infrastructural deficit. This study examines the nature of transport infrastructure in Nigeria, the causes of the infrastructural deficit in Nigeria and further identifies some Chinese transport infrastructural projects and investments in Nigeria and their impact. This study employed both qualitative and quantitative research methods by collecting and analyzing both quantitative (closed-ended) and qualitative (open-ended) data. The present study found a huge infrastructural deficit in Nigeria transport sector. The study identified corruption among other causes as the main cause of infrastructural deficits in Nigeria. Some of the major BRI infrastructural projects in Nigeria identified in this study include: Abuja Rail Mass Transit Project, Nigeria Railway modernization project (Abuja to Kaduna section), Nigeria Railway Modernization Project (Lagos-Ibadan Section), and Abuja Airport terminal project among other. The paper concludes that there is a deliberate effort to fix the severe transport infrastructural deficit in Nigeria evident in the cooperation between the Nigerian and Chinese Governments. And the Chinese intervention in Nigeria’s transport infrastructure has been largely impactful and beneficial to Nigerians. Keywords: Infrastructural Deficit, Transport Infrastructure, Sino-Nigeria Relations, Infrastructural Development, Chinese Investments DOI: 10.7176/EJBM/14-2-02 Publication date: January 31 st 2022

A Survey on Formal Specification and Verification of Smart Mass Transit Railway Interlocking System

Nowadays interest in Smart Mass Transit Rail has grown-up to a large extent in a metropolitan area as the need for urban mobility has increased steadily. The reliability of software being used in such mass transit rail is crucial for us, specifically when software crashes may lead to catastrophic loss of human life and assets. For example, when we travel by metro it is essential for us that the interlocking system software controlling the metros are accurate so collisions and derailment are prevented. The reliability and safety of such interlocking systems are made on the precise functional requirements specification and verification respectively. Therefore, the precise functional requirements specification and verification of such interlocking systems represent a challenge in an active research area, so in this paper, we survey various articles in this field and discuss their consequences.

Procuring urban rail transit infrastructure by integrating land value capture and public-private partnerships: Learning from the cities of Delhi and Hong Kong

Worldwide, the private sector has actively participated in delivering transport infrastructure assets in cities. Typically, Private Participation in Infrastructure (PPI) approaches have been used to deliver urban rail transit (URT) systems. Public-Private Partnership (PPP) agreements or variants thereof have been the procurement method of choice by governments. However, PPPs have been unable to provide governments with value for money and concessionaires with sufficient operating revenues. The corollary, in this case, has meant that governments have been drawn to consider alternative forms of financing to procure and support the economic viability of a city's URTs. Land value capture (LVC) has been identified as a potential finance mechanism that can be integrated with a PPP to ensure its economic success. There are, however, only a limited number of cities that have integrated LVC with a PPP to successfully their URT projects. In this paper, an exploratory case study approach is used to learn from the experiences of Delhi Airport Metro Express and Hong Kong's Mass Transit Rail. Consequently, we develop a conceptual model that integrates land value capture and PPPs that can assist policy-makers with the procurement of their rail infrastructure. The implications of our developed model for procurement policy are presented.

Inference of activity patterns from urban sensing data using conditional random fields

The study of human activity–travel patterns for urban planning has evolved a long way in theories, methodologies, and applications. However, the scarcity of data has become a major barrier for the advancement of research in the field. Recently, the proliferation of urban sensing and location-based devices generates voluminous streams of spatio-temporal registered information. In this study, we propose an approach using the linear-chain Conditional Random Fields (CRFs) model to learn the spatio-temporal correspondences of different types of activities and the inter-dependencies among sequential activities from training dataset such as the household travel or time use surveys, and to infer the hidden activity types associated with urban sensing data. The performance of the CRFs model is compared against the Random Forest (RF) model, which has been used in a number of existing studies. The results show that the linear-chain CRFs models generally outperform the RF counterparts with respect to classification accuracy of activity types, in particular for those travelers having more outdoor daily activities. The proposed methodology is demonstrated by reconstructing the activity landscape of the surrounding area of a major Mass Rail Transit station in Singapore using the transit smart card transaction data. The inferred activities from the transit smart card data are expected to complement the ground surveys and improve our understanding of the interactions of different components of activities/travels as well as the relationship between urban space and human activities.

Pedestrian dynamics on narrow pavements in high-density Hong Kong

IntroductionThe investigation of pedestrian dynamics is important as cities continue to develop facilities for high volume foot traffic. Important insights into speed-density relationships, flow patterns, boundary effects and critical states have been derived from experimental studies. Extending these studies to real settings enables us to see how these relationships apply in settings with heterogeneous populations, complex trip purposes and undirected spatial behaviours. Hong Kong offers the opportunity to examine pedestrian dynamics in conditions of relatively dense pedestrian traffic on narrow pavements. MethodsData were collected from a sample of 24 street environments, varying in pavement width and pedestrian flow. Individual trajectories of 356 randomly selected individuals were extracted from video records. Pedestrian speed was related to the following independent variables: pedestrian volume, pavement width, effective width and shops. Speed was also related to lateral displacement and position. Lane formation and counterflows were measured. To examine how the street environment compares with the free-flow conditions of wider, dedicated corridors, speed was measured for 356 randomly selected individuals on 7 corridors in the mass transit rail (MTR) system. ResultsDisplacement, effective width, number of shops and sex of the individual account collectively for 13.7% of variance in speed, while pedestrian volume was not significant. There is a slight tendency to righthand movement in bi-directional flows, with the rate of counterflow negatively related to dominant flow density. ConclusionsWalking speed on Hong Kong streets is constrained by shopping activity, obstacles and reduced spatial dimensions. Walking speed is maintained through lateral displacement, with higher speeds at the outer edge of the bounded space. People walk significantly faster in unconstrained conditions of the MTR.

Visualization Method of TOD Development Process Based on Big Data

With the rapid development of urbanization and motorization in China, the urban problems such as low-quality land spread and low efficiency of transportation are becoming increasingly prominent. It has become an effective method to solve the traffic and environment problems by using TOD theory, while mass rail transit has become the best carrier of TOD model. TOD is a powerful means to optimize land use, traffic development and urban planning, which provides a possibility for the organic combination of land use and traffic development. This paper mainly studies the visualization method of TOD development process based on big data. In TOD model of urban development guided by public transport, this paper studies and analyzes the planning points of TOD mode, and also studies the advantages, disadvantages, opportunities and threats of urban rail transit(URT) to prove the reliability of TOD development process. This paper studies the scale algorithm of rail transit network, and also analyzes the environmental pollution caused by various traffic modes and the land use ratio of TOD types by chart analysis. The experimental results show that the most important vehicle in cities is automobiles, while the energy consumption of Metro light rail is only 0.84, carbon dioxide emissions are 1.21 and noise pollution is 0.42. The pollution caused by it is the smallest, which is worth expanding. In terms of the proportion of type land, residential land is the core of neighborhood, accounting for 62.5%, while urban TOD is mainly used for core land, accounting for 55%. In the type land, different types of land use main functions are different.

Efficiency of Railway Transport as a Sustainable Mode of Transport in Nigeria: A Study of Rail Mass Transit in Lagos and its Environs.

Efficiency of Railway Transport as a Sustainable Mode of Transport in Nigeria: A Study of Rail Mass Transit in Lagos and its Environs.

Building Mass Rail Transit in Kuala Lumpur: Is its Good Transport Economics?

Kuala Lumpur city is hoping to join the public transport club of elite capital cities. Public transport especially of the rail-based system provide mass transportation for urban dwellers in a city. Most major cities in the world have good LRT or MRT systems in place for their citizens. Kuala Lumpur also wish to join these group of successful cities. In 2010 the federal government of Malaysia declared that the MRT line 1 and 2 will be built to increase public transport use in Kuala Lumpur. In July 2017, the MRT line 1 was completed. This paper reviews whether the MRT system is, after all, a good investment economically from the transport point of view.

Efficiency of Railway Transport as a Sustainable Mode of Transport in Nigeria: A Study of Rail Mass Transit in Lagos and its Environs.

This paper compacts with the notion of the relevance of railway transportation in the Nigerian economy. Assessments, Issues, challenges and operational rail-line in Nigeria. Specifically, the impact of railway in Lagos (Rail Mass Transit) The study also highlighted factors that may affect or retard the relevance of railway transportation in the Nigerian economy and solutions propounded. The paper presenter researched for the paper with reliance on textbooks, internet websites and operational case study since there is a dearth of material in the subject area most especially data from the pre-colonial period in Nigeria railway operations. Also, the researcher relied on secondary data from Nigerian Railway cooperation for his SPSS analysis. At the end of the paper, the presenter proposed a number of recommendations for efficient operations of railway service in Nigeria. Significant among is government improvement of infrastructure and enabling environment as well as privatization or commercialization of railway operation as the government does not have the political will and motivation to invest in a capital intensive project like a railway.

Predlog opštih zahteva za projektovanje objekata urbanih šinskih sistema

Predlog opštih zahteva za projektovanje objekata urbanih šinskih sistema

Synchronized optimization of last trains’ timetables in mass rail transit networks based on extra dwell time

Synchronized optimization of last trains’ timetables is purposed to improve the connecting effects of last trains by coordinating the arrival and departure times of trains at transfer stations. Due to the great complexities of transfer relationships, it is more and more difficult to solve this problem. In this paper, in order to reduce the number of unable transfer passengers, an optimization model of last trains’ timetables is proposed by determining the departure time and extra dwell time. And we minimize the difference between last trains’ actual departure time and the optimized ones for the convenience of rolling stocks daily maintenance. Possible optimized solution is investigated through a case study in Beijing subway by using the tool of CPLEX. The results indicate that the volume of unable transfer passengers is reduced by 15.0%, and the number of coordinated trains is improved by 8.9%.

Piano transductions: music, sound and noise in urban Taiwan

ABSTRACT While scholars have drawn attention to the production of space through sound, there has been less attention given to the interchange between multiple co-existing environments. This paper examines how the sounding of one place informs and produces the sounding of another by focusing on Western art music as it is multiply negotiated by urban residents in Taipei, Taiwan. Building upon Stefan Helmreich’s provocation on the transductive quality underlying immersive soundscapes, this paper looks at how various instantiations of piano playing in apartment buildings, on municipal garbage trucks and on the Taipei Mass Rail Transit System produce expectations for sonic space in a relational, rather than isolated, context. By analysing a grassroots campaign to regulate household piano practice, this paper shows how cultural expectations for the sounding of one place is spatially and ontologically produced in relation to adjacent auditory environments throughout the city. Contributing to discussions for a sounded anthropology, this paper addresses how residents navigate diverse auditory environments and calls for ethnographic attention to the movement between, not only within, sounded spaces.

On pedestrian traffic management in railway stations: simulation needs and model assessment

Abstract Mass transit rail stations make up complex systems in which passenger flows have significant influence on operations and traffic conditions. Are there pedestrian simulators that can effectively contribute to the management of crowd flows? To answer this question, an assessment grid is built to address scientific principles as well as operational and organizational needs. The scientific principles encompass real-world features to be described, especially causalities to reproduce. The grid is applied to several commercially-available software (including PTVVisWalk, Legion, Anylogic, MassMotion and SimWalk) as well as to research-sourced pedestrian simulators.

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents' Exposure to Urban Greenness.

Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size.