Rail Transit Planning Research Articles

Long-Term Passenger Flow Forecasting for Rail Transit Based on Complex Networks and Informer.

With the continuous growth of urbanization, passenger flow in urban rail transit systems is steadily increasing, making accurate long-term forecasting essential for optimizing operational scheduling and enhancing service quality. However, passenger flow forecasting becomes increasingly complex due to the intricate structure of rail transit networks and external factors such as seasonal variations. To address these challenges, this paper introduces an optimized Informer model for long-term forecasting that incorporates the influences of other stations based on complex network theory. Compared to the ARIMA, LSTM, and Transformer models, this optimized Informer model excels in processing large-scale complex transit data, particularly in terms of long-term forecasting accuracy and capturing network dependencies. The results demonstrate that this forecasting approach, which integrates complex network theory with the Informer model, significantly improves the accuracy and efficiency of long-term passenger flow predictions, providing robust decision support for urban rail transit planning and management.

State-dependent multi-agent discrete event simulation for urban rail transit passenger flow

Urban rail transit passenger flow modeling is the foundation of urban rail transit planning, design, and operation. The motivation of this paper is to accurately and efficiently simulate passenger flow dynamics in urban rail transit systems. To this end, we propose a State-dependent Multi-agent Discrete Event Simulation (SdMaDES). The state-dependence (or congestion-dependence) means that the service abilities (or travel times) of bottleneck facilities (e.g. platform screen doors and transfer corridors) are not constant and they interact with the congestion dynamics. Specifically, we first establish a modular Multi-agent Discrete Event Simulation (MaDES), which includes four types of modules (passenger, train, station, and network modules) and three types of agents (passenger, train, and station agents). The logical connections and event-triggering modes between the modules are analyzed and defined, and thirty types of events are designed. The state-dependence is then captured by an Improved Social Force Model (ISFM), which adds an autonomous obstacle avoidance mechanism. The ISFM reproduces passenger movement behavior within bottleneck facilities of urban rail transit systems at the microscopic level. These state-dependent functions or general rules are explicitly formulated by fitting the results of ISFM and are subsequently applied to the proposed MaDES model, resulting in the SdMaDES. This integration aims to enhance the accuracy of the simulation. We conducted a real case from the Chengdu Metro network. Some interesting results are found. (a) The maximum number of boarding passengers in a train carriage is a complex nonlinear function that is dependent on the state (density inside the train carriage). This challenges the linear function commonly utilized in most studies. (b) Compared to the actual data, the proposed SdMaDES model shows a cumulative error of 9.85% after data smoothing, while the conventional MaDES model exhibits a much higher cumulative error of 21.9% after data smoothing. (c) As the overall traffic demand level increases, the gap between the two simulation models’ results is getting wider and wider due to the amplified nonlinear impact of congestion.

Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport

In this paper, a cost-oriented optimization model of station spacing is presented to analyze the influencing factors of station spacing and layout near Shanghai Pudong International Airport. The Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm is used to cluster and analyze the high population density, and optimize the station layout in the southwest of Pudong International Airport. A spatial analysis of the land use and geological conditions in Pudong New Area is given. Combining the optimal station spacing, ideal location and spatial analysis, five routing schemes to Pudong International Airport are proposed. The DBSCAN and K-means algorithms are used to analyze the “PDIA-SL” dataset. The results show that the space complexity of the HDBSCAN is O(825), and the silhouette coefficient is 0.6043, which has obvious advantages over the results of DBSCAN and K-means. This paper combines urban rail transit planning with the HDBSCAN algorithm to present some suggestions and specific route plans for local governments to scientifically plan rail transit lines. Meanwhile, the research method of station layout, which integrates station spacing, ideal location and spatial analysis optimization, is pioneering and can provide a reference for developing rail transit in metropolises.

Urban Rail Transit Planning and Design Based on ARIMA Model and AnyLogic Software Station Pedestrian Flow Simulation

Urban Rail Transit Planning and Design Based on ARIMA Model and AnyLogic Software Station Pedestrian Flow Simulation

Optimization and Application of Communication Resource Allocation Algorithm for Urban Rail Transit Planning.

The construction and operation of China's rail transit system have entered a high-speed development stage, and the rapid increase of train speed and mileage has brought greater challenges to the safety and reliability of the rail transit system. Network planning evaluation is the key to the early decision-making of urban rail transit project, which directly determines the success or failure of the whole project. How to scientifically and reasonably evaluate the urban rail transit information resource network planning has become a difficult problem for many urban planners to solve. Therefore, this paper studies the optimization of the communication resource allocation algorithm and the comprehensive evaluation of its application for urban rail transit planning. In this paper, based on CVNN structure, the network prototype is an extension of RVNN structure. In the abstract, its processing unit is composed of a pair of real-number processors that can realize certain operations. HNN is a fully connected recurrent neural network based on the idea of the energy function, which is helpful to understand the calculation mode of HNN, and the research shows that HNN can solve many combinatorial optimization problems. In addition, the combination of neural network and genetic algorithm with simulated annealing mechanism can also bring new directions for research. On the basis of experimental analysis, it can be concluded that in general, the error reduction rate of the optimization scheme designed in this paper can reach 58.6% on average. In practical application, the accuracy of the optimal bit error rate is 52.4%.

Analysis of the Relationship between Beijing Rail Transit and Urban Planning Based on Space Syntax

Transportation infrastructure planning is one of the essential ways to achieve a carbon-neutral society in China’s future. With regards to sustainable urban development, the Green Low-Carbon policy for Transportation is set out in the 14th Five-Year Plan Outline 2021–2025. However, there are only a limited number of previous studies that systematically combined land-use planning and urban transportation evolution to clarify the structural issues in urban transportation optimization. In this study, we use traditional analysis and space syntax analysis to examine the relationship between the urban development of Beijing and the evolution of its rail transit transportation. After analyzing Beijing’s multi-center and multi-circle rail transit structure, it was concluded that the current division of labor in Beijing’s rail transit is unclear. Analysis using space syntax shows that connecting suburban centers using suburban railways improves accessibility better than subways. However, after analyzing the synergy between these factors, it is found that the application of space syntax needs to be analyzed in combination with the actual situation.

Risk Factors in Urban Rail Transit Planning: İstanbul Case

Literatürde raylı sistemlerin yapım ve işletme aşamalarına yönelik riskleri inceleyen çalışma sayısı sınırlı olmakla beraber özellikle 2019-2021 döneminde yaşanan COVID-19 salgını nedeniyle bu sorunun önemi daha fazla kavranmış ve bu yöndeki çalışmalar hızla artmıştır. Bu çalışmada risk analizi COVID-19 ile sınırlı tutulmamış raylı sistem yatırımlarının barındırdığı çeşitli riskler araştırılmıştır. İstanbul kenti çok sayıda ve farklı kapasitelerde raylı sistemine sahip olması nedeniyle örnek alan olarak incelenmiştir. Çalışmada raylı sistemlerin planlanması aşamasında öngörülen yatırım planı, finansman, yapım, yolcu sayısı öngörülerinin ne düzeyde gerçekleştiği, yanılmaları etkileyen risk faktörlerinin neler olduğu önce-sonra yöntemiyle araştırılmıştır. Araştırma bulguları İstanbul’da raylı sistemlerde yolcu talebinin pandemiden önce dahi tahminlerin altında kaldığını göstermektedir. Yolcu talebi tahminindeki sapmalar maliyeti karşılama süresinin uzamasına neden olmaktadır. Bu sorunun kaynağı daha çok ulaşım ana planlarının dayanağı ve girdisi olan arazi kullanımı, nüfus ve demografik girdileri ile ilgilidir. İkinci grupta yapımın gecikmesi, maliyetlerin artması ve gelirlerdeki azalmaya neden olabilen riskler yer almaktadır. Üçüncü grupta yer alan riskler ise pandemi ve benzeri koşullarda hareketliliğin kısıtlanması nedeniyle ortaya çıkabilmektedir, İşletme aşamasında karşılaşılabilecek kaza ve arızalar ise son risk grubunu oluşturmaktadır.

Impact of Urban Rail Transit Network on Residential and Commercial Land Values in China: A Complex Network Perspective

Urban rail transit can improve a city’s accessibility. However, high construction and operation costs restrict the development of urban rail transit. Value capture recoups the additional value that the investments of urban rail transit confer to local land and is considered to be an effective measure to alleviate this financial problem. Understanding the land value uplift effects of urban rail transit is essential for understanding value capture. This study applied a Space-P model of urban rail transit network based on complex network theory and demonstrated the influence of urban rail transit network characteristics on residential and commercial land prices. The model was tested with eight metropolises in China, using the 2003 to 2022 timeframe as the context. The results showed a significant positive correlation between the number of nodes and the land prices, the average clustering coefficient was highly positively correlated with the land prices, and there was a significant negative correlation between the average path length and the land prices. This study provides theoretical support for value capture, is beneficial for urban rail transit planning, and supports improvements in the development quality of urban rail transit networks.

Discussion on Problems and Methods of Urban Rail Transit Planning

<span lang="EN-US">My country’s economy is gradually developing, and the demand for transportation between cities is increasing. Therefore, the construction of urban rail transit is a hot topic in transportation. Many related scholars and researchers have studied it through a lot of practice and have formed a lot of research results. This article analyzes the problems existing in the planning, design and construction of urban transportation rail transit, and proposes some corresponding solutions, hoping to provide references for the development of my country’s transportation industry.</span>

Influence of Rail Transit on Development Patterns in the Mountain Mega-Region with a Surprise and Implications for Rail Transit and Land-Use Planning

Between 2020 and 2050, all states comprising the Mountain Mega-Region (MMR—Arizona, Colorado, Nevada, New Mexico, and Utah) will be among the top 10 fastest growing U.S. states. They also have among the nation’s largest shares of land area in federal, state, public, and tribal land ownership. This has led to concentrations of populations in their metropolitan areas. Indeed, in 2020, the metropolitan areas of more than one million residents—Albuquerque, Las Vegas, Phoenix, Salt Lake City, and Tucson—comprise more than 70% of their states’ populations. With rapid growth combined with land constraints, many of these metropolitan areas are using rail transit systems to help meet transportation needs while also influencing development patterns in intended ways. If they are effective, these rail transit systems will: (a) create commercial real estate rent premiums; (b) attract jobs; and (c) attract households to areas near rail stations. We report the effectiveness of MMR rail transit systems in each of these respects. We also present a surprise: Contrary to conventional wisdom, it is households with children that locate closest to rail stations than single persons and childless households. We reason that improved planning is needed to meet the market demand for development throughout the half-mile circle around transit stations in the MMR’s metropolitan areas. If this can be done, all development in these MMR metropolitan areas may occur near rail transit stations.

Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network

This paper proposes an evaluation method based on a T-S fuzzy neural network for evaluating the speed grade of public-transport lines in the context of large-scale rail-transit planning and construction in Hangzhou. The six-dimensional data of morning peak/evening peak average speed, average speed at peak, average station distance, proportion of dedicated lanes, and nonlinear coefficients were selected as input data for the neural network to output the operating speed grade of bus lines. Improving and optimizing the membership function of the Takagi–Sugeno (T-S) model improves its predicted result accuracy compared to a traditional T-S model. The line data of 28 typical trunk lines or expressways in Hangzhou were used as an example; the results demonstrate that the speed grade evaluation method based on an improved T-S fuzzy neural network can effectively and quickly evaluate the speed grade of Hangzhou public-transportation lines. This paper presents a novel analysis and method for large-scale rail-transit planning and evaluation of urban public-transport lines. The aim is to provide practical instruction for the subsequent optimization of public-transportation lines in Hangzhou.

Problems and Countermeasures of Urban Rail Transit Construction in China

In the 21st century, the over dependence on cars in China’s urban development has led to a series of problems, which have seriously affected the development of contemporary cities. The problem of communication has become the bottleneck of the development of many cities in China. Therefore, the rise of urban rail transit is an inevitable trend. The construction and development of rail transit is an effective way to solve urban diseases, such as traffic congestion, traffic pollution, poor green travel environment and difficult parking. In the period of great development opportunity of rail transit, it is necessary to discuss how to scientifically plan urban rail transit system, promote urban intensive development and improve urban traffic conditions. Combined with the current situation of rapid development of urban rail transit in China, this article analyzes the main problems existing in the development of urban rail transit at present, and puts forward the guiding ideology and main countermeasures for the development of urban rail transit in the future: do what you can and develop steadily to effectively avoid the hidden dangers brought about by blind development; further strengthen the scientific nature of urban rail transit planning and maintain the seriousness of planning; further improve the investment and financing mode of urban rail transit. Some suggestions are also put forward for the key problems to be solved in the near future.

Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China

Understanding the relationship between the rail transit ridership and the built environment is crucial to promoting transit-oriented development and sustainable urban growth. Geographically weighted regression (GWR) models have previously been employed to reveal the spatial differences in such relationships at the station level. However, few studies characterized the built environment at a fine scale and associated them with rail transit usage. Moreover, none of the existing studies attempted to categorize the stations for policy-making considering varying impacts of the built environment. In this study, taking Guangzhou as an example, we integrated multi-source spatial big data, such as high spatial resolution remote sensing images, points of interest (POIs), social media and building footprint data to precisely quantify the characteristics of the built environment. This was combined with a GWR model to understand how the impacts of the fine-scale built environment factors on the rail transit ridership vary across the study region. The k-means clustering method was employed to identify distinct station groups based on the coefficients of the GWR model at the local stations. Policy zoning was proposed based on the results and differentiated planning guidance was suggested for different zones. These recommendations are expected to help increase rail transit usage, inform rail transit planning (to relieve the traffic burden on currently crowed lines), and re-allocate industrial and living facilities to reduce the commute for the residents. The policy and planning implications are crucial for the coordinated development of the rail transit system and land use.

Evaluating the relationship between rail transit and industrial agglomeration: An observation from the Dallas-fort worth region, TX

Recent studies have suggested that rail transit not only facilitates urban growth but also promotes urban agglomeration. Yet research that links industrial agglomeration with rail transit is scant—what types of industries are likely to cluster near rail stations? To what extent can rail transit access be seen as having an influence on industrial agglomeration? And how do these interactions vary as rail transit proximity increases? To answer these and related questions, we investigate the relationship between industrial agglomeration and rail transit in the Dallas-Fort Worth metropolitan area using the Longitudinal Employer Dynamics (LEHD) employment data from 2014 at the census block level. First, we use the Local Indicator of Spatial Association statistics (LISA) tests to identify industrial agglomeration patterns within the study area. We then use logistics models to reveal the relationship between rail transit proximity and industrial agglomeration. Our study finds that the impacts of rail transit on industrial agglomeration, in terms of magnitudes and signs, are mixed across industries. The varying results suggest that the benefits of rail transit access exhibit considerable demand from certain industry sectors including the manufacturing, knowledge, and services industries, while exerting weaker forces in pulling agglomeration in its immediate environs among other industries (including the retail trade sector). In practice, these results are useful for justifying evidence-based rail transit planning.

AESTHETIC APPROACH TO GREEN TRANSPORTATION PLANNING IN TOURISM WITH DESIGN FACTORS

Green transportation technology has become a new paradigm in transportation engineering fields over the whole world. Most attention, however, has been paid to mitigate greenhouse gases or energy consumption, seldom reported pro-environment design in aesthetic aspect. It is well known that a proper design of train enhances traveler satisfaction and contributes to demand increase in public transportation. Hence, aesthetic factors should be considered significantly. However, a difficult problem for reflecting aesthetic aspect is that there is no clear design standard for railway to reflect aesthetic features. This paper aims to suggest aesthetic factors to be guidance of rail transit planning in tourist attractions. We begin by defining a term ‘aesthetic in railway system’ based on literature and empirical review. In this paper, the definition is divided into two complementary views: (I) Sight-seeing mechanism from inside to outside. (II) Vehicle exterior design harmonized with surrounding environment. Based on the definitions, design factors are suggested: window size, speed, routes, type of track, color, and size of train system. Each factor is explained with its standard. A result of evaluating rail transit with the factors shows that wireless tram is the most suitable transit for tourism. Limitations and improvements of the study are also suggested.

Analysis and Calculation of Maximum Operation Speed and Average Distance between Stations for Regional Rail Transit Planning

Regional rail transit eases downtown residents gathering,improves living conditions,and develops satellite towns.Maximum operation speed and average distance between stations play an important role in transportation efficiency and function orientation.There are no specific specifications for planning regional rail transit in China,and foreign specifications are inapplicable.The paper researches the relationship between maximum operation speed and average distance between stations of regional rail transit,and calculates the matcing values of the two.Taking Beijing R1 line as an example, the paper determines maximum operation speed and average distance between stations through traction calculation and dimensionless evaluation model,and verifies each indicator.Each determined value is consistent with the R1 line planned value by comparing.The research provide decision support for future planning of regional rail transit.

Research on the Common Rail Transport System Building in Integration System of Urban Rail Transit in Hohhot

Based on the impact analysis of common rail transportation on urban rail transit and comprehensive consideration of Hohhot, including passenger flow characteristic analysis and related product design principle, this paper studies the impact of common rail transport system on the urban rail transit and describes the product design of common rail transport system of Hohhot in two aspects: common rail train stop plan and the nature of the passenger flow, which is dedicated to provide relevant theoretical basis for the rail transit planning and construction of Hohhot in the future. Key words: the integration of urban rail transit; common rail transport; product design; Hohhot

Wavelet Neural Network-based Short-Term Passenger Flow Forecasting on Urban Rail Transit

Accurate forecasting of short-term passenger flow has been one of the most important issues in urban rail transit planning and operation. Considering the shortcomings of traditional forecasting methods, and in order to improve forecasting accuracy of passenger flow, this paper presents a wavelet neural network (WNN) for short-term passenger flow forecasting. One real urban rail transit station with large and significantly changed passenger flow is chosen to be the example. The proposed method and BP neural network have been compared with the results, which show that the WNN model has more advantages. The WNN model features higher learning speed and drastically less convergence time, showing that it is meaningful in practical application. Furthermore, the calculated relative errors using BP neural network are nearly in the range [-0.4, 0.3] and the calculated relative errors are in the range [-0.25, 0.1] using the WNN, which demonstrate the superior accuracy of using this approach. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3096 Full Text: PDF

Analysis and Countermeasures Research on Planning Environment Impact Assessment (PEIA) of Urban Rail Transit Planning in China

Based on the analysis and summary of 19 PEIA cases of urban rail transit (URT) planning, this paper pointed out the major problems on PEIA of URT in practice, such as the depth of environmental impact prediction was inadequate, Optimal comments to URT Planning were not operational, and Public Participation was not representative etc. In response to these problems, this paper put forward some suggestions on both of regulating the technical means of PEIA for URT and improving the capacity of PEIA technical personnel. It could be helpful to improve the scientificity and practicity of PEIA for of urban rail transit planning in China.

Characteristics and Reliability Analysis of the Complex Network In Guangzhou Rail Transit

Researching for the characteristics and reliability of urban rail transit network by using complex network theory has certain significance on rail transit's planning and efficiency improvement. In this paper, the topological structure of the Guangzhou urban rail transit network was made by space L and space P methods. The network characteristics, such as average path length, clustering coefficient and degree distribution were selected in each method. Then the network's reliability was discussed, and the results show that the Guangzhou rail transit network at present is classified as a random network. When suffered from selected attack, the average travel length and the global efficiency are increasing; the local efficiency keeps the same. As long as most of the stations work well, the entire rail network structure is relative stable.