Interaction between URT and Urban Spatial Structure

Rational planning for the underground space development in subway station areas, in coordinate with the urban rail transit development, has positive impacts on the sustainable development of cities. This paper induces the space syntax method for calculating the quantitative accessibility index of the urban rail transit and detects the coordination between urban underground space use intensity and rail transit system of the 7 selected subway lines in Tokyo. The results show that the station areas with higher accessibility index are the same sort with higher underground space use intensity. This means that the space syntax method is suitable and feasible for calculation of the quantitative accessibility index of subway lines. The higher the accessibility index is, the more underground space will be needed potentially in future. The areas with high accessibility of subway lines and low intensity of public underground space develop are the key districts under potential exploitation of underground space.

The sustainability appeal of urban rail transit

As the scale of development continues to expand, carbon emissions of urban rail transit (URT) in China have gradually increased each year, posing certain pressure on the carbon emission reduction efforts in the URT industry. To evaluate the current status of low-carbon development in the URT industry, this paper first constructs an annual carbon emission accounting model for URT that considers both the construction and operation processes. Based on this model, the annual carbon emissions of URT in China from 2015 to 2023 are calculated. Furthermore, based on decoupling theory, the relationship between carbon emissions and industry development in URT is explored from both the construction and operation aspects. The results show that: (1) From 2015 to 2023, the total carbon emissions of URT in China increased significantly from 14.425 million tons to 24.7072 million tons. The proportion of carbon emissions from construction is higher during the study period, but the growth rate of carbon emissions from operation is faster. (2) The order of carbon emissions from URT in different regions from largest to smallest is: East > West > Central > Northeast. (3) During the study period, the carbon emissions from URT construction in China were weakly decoupled from the operational lines. (4) There was an expansive coupling relationship between carbon emissions from URT operation and passenger transport turnover in China. These findings can provide some guidance for the sustainable development of the URT industry.

With the rapid development of urban rail transit, the traditional urban rail wireless network based on fixed infrastructure is not in a position to meet the increasingly complex communication demand. At the same time, Ad Hoc network, as a special wireless mobile network, is developing rapidly. Applying this self-organized networking architecture to the urban rail vehicle–ground communication network can overcome the problems existing in the traditional urban rail communication system. The routing protocols that can achieve low delay and highly reliable data transmission are important in the urban rail transit scenario. Therefore, combined with the wireless Ad Hoc network and the characteristics of the urban rail transit scenario, this paper proposes a dynamic addressing hybrid routing mechanism based on static configuration. Using an improved AODV routing discovery algorithm and then writing the routing table into the router in advance for static configuration not only reduces network overhead but also prolongs the network’s lifetime. It also saves the delay of routing discovery. Then, the cluster head node dynamically monitors the link status, dynamically finds the path when the link needs to be replaced, and selects different update paths according to different types of communication services. Finally, each algorithm’s network performance parameters, like the routing discovery overhead, residual link lifetime, packet delivery rate, throughput, and end-to-end delay, are analyzed and compared.

The construction and circulation of railways, especially urban rail transit, change the travel patterns of residents along the lines and provide convenience for residents in outer suburbs to enter the city center. At the same time, urban rail transit will likely have an impact on the social structure and types of residents in the area. This paper explores the urban gentrification caused by railways in mainland China, covering the old city renovation plan, demolition along the subway line, subway line terminus, and other perspectives. The findings show that with the development of urban rail transit, land prices in the area will increase and communities will become gentrified, which means possible crowding out of low-income citizens. This article intentionally explores the relationship between the subway and gentrification.

Urban rail transit, as a green, environmentally friendly, safe, and efficient mode of transportation, plays a crucial role in urban sustainable development. However, the influencing mechanism of build environment factors on rail transit ridership still needs to be further investigated. Also, the interaction effects between these factors have not been considered. This study aims to explore the relationship and impact of built environmental factors on metro ridership. The research employs the Multiscale Geographically Weighted Regression (MGWR) model to analyze the temporal and spatial effects of built environmental factors on the rail transit ridership. The GeoDetector model is utilized to investigate the interactive effects of these factors on rail transit ridership. The Shanghai Metro ridership data and built environment data are applied to validate the model. Based on data analysis results, we found that Food & Beverages and Accommodation services, respectively, have the greatest impact on metro ridership on weekdays and weekends. Furthermore, the interaction effects between other variable and Land use diversity significantly enhance rail transit ridership, validating the promoting effect of land use diversity on metro ridership. By proposing recommendations for relevant urban planning and policy formulation, we can foster the sustainable development of urban rail transit.

Different types of stations have different functional roles in the urban rail transit network. Firstly, based on the characteristics of the urban rail transit network structure, the time series features and passenger flow features of the station smart card data are extracted. Secondly, we use the principal component analysis method to select the suitable clustering variables. Finally, we propose a station classification model based on the two-step cluster method. The effectiveness of the proposed method is verified in the Beijing subway. The results show that the proposed model can successfully identify the types of urban rail transit stations, clarify the function and orientation of each station.

N ow urban rail transit (URT) plan in China has some problems such as inconsistent with urban overall plan (UOP) and urban transportation plan (UTP). According to such condition, trinity system of UOP, UTP and URT plan is advanced, among which URT plan should be focused on and its system structure is researched on from URT development strategy plan and URT overall plan, and URT overall plan is analyzed from network plan and network control plan. Therefore, URT plan is studied and good plan can produce good URT construction so that healthy and sustainable development of URT can be achieved.

The surge of the operational energy consumption has become a major challenge for the sustainable development with the rapid development of urban rail transit. Traction energy used to provide kinetic energy for the train during operation is about 50% in the total energy consumption of the urban rail transit, so the energy saving potential is considerable. Traction energy between train stations is determined by the driving strategy of the train, therefore, studying energy-efficient train driving strategy to reduce traction energy consumption has a great significance to achieve an environmentally friendly transport system. This paper designs a simulation software of energy-efficient train driving strategy based on the numerical algorithm to optimize energy-efficient train driving strategy with energy allocation. The simulation software can calculate energy-efficient train driving strategy according to any input line data, vehicle condition, and running time. The performance of simulation software is verified through the simulation of the actual data of Yizhuang line in Beijing.

Under the background of the rapid development of urban rail transit in China, the development demand of urban underground space has also greatly increased especially in the rail transit station areas. In this paper, taking the high-speed railway station area of Xuzhou Metro Line 1 as an example, the underground space development demand evaluation is conducted by considering the principle of urban underground space stock planning, the local underground space development conditions, as well as the special planning of the local urban constructions. Using the Analytic Hierarchy Process (AHP), a specific weight indicator scale is employed after the rationality of different weight indicator scales being compared. And then the weight indicator of different function types, i.e., commercial, parking, road, etc., are calculated and laterly utilized to forecast the recent development demand of underground space in the station area. Moreover, the steps to forecast the underground space development demand in rail transit station area are proposed, which can provide a reference for the forecasting of underground space development demand in the urban rail transit station areas.

With the rapid development of urban rail transit, the energy consumption of trains is increasing dramatically. The shortage of electrical energy is becoming more and more serious. In this paper, a novel method is proposed to better use regenerative braking energy for energy saving. A ‘time slot and energy grid’ model is set up to analyze the utilization of regenerative energy among trains. Based on this model, an energy efficient strategy that integrates train dispatch with train control is designed. The running time of trains in sections, the dwell time of trains at stations and the headway can be adjusted to find the global optimal solution for energy saving. The operational data of Beijing Changping subway line and Beijing Yizhuang subway line are used in simulation to illustrate the effectiveness of the proposed method in different scenarios. Simulation results show that our approach can significantly improve the utilization of regenerative braking energy and minimize the energy consumption in different scenarios when compared with the existing method.

A synergistic energy-efficient planning approach for urban rail transit operations

This chapter discusses urban transport issues, policies, and initiatives in [The Urban Transport Crisis in Emerging Economies: An Introduction/Australia]. Consistent with the other case studies, it covers the following set of issues: Urban land-use patterns and spatial structure; Trends in transport use and mobility; Urban transport problems; Urban transport governance, decision-making, and financing; Proposed urban transport solutions and implementation issues; and Other country-specific issues. The object of this framework is to allow for a comparative analysis across the case studies. This book discusses urban transport issues, policies, and initiatives in 12 of the world’s major emerging economies—Brazil, China, Colombia, India, Indonesia, Iran, Mexico, Nigeria, Russia, South Africa, Turkey, and Vietnam—countries with large populations that have recently experienced large changes in urban structure, motorization, and all the associated social, economic, and environmental impacts in positive and negative senses. It documents the worsening transport crisis and differences among these countries in their urban transport and land-use systems. It includes chapters on each of these 12 countries, focusing on one or more major cities per country. In order to present the case studies in a more comparable way, all chapters follow a common format. Each chapter covers the following set of issues: Urban land-use patterns and spatial structure; Trends in transport use and mobility; Urban transport problems; Urban transport governance, decision-making, and financing; Proposed urban transport solutions and implementation issues; and Other country-specific issues. The object of this framework is to help to identify new explanatory factors that may be overlooked in research limited to single cities or nations. By including cities and countries across all continents, the aim is to identify useful lessons on how to achieve urban sustainability goals across the globe.

The dynamic evaluation method of urban rail transit sustainable development has been established. Through the thorough analysis of urban rail transit sustainable development's each influencing factor, the paper established the evaluation index system for urban rail transit sustainable development. Based on the analysis of urban rail transit development state vector structure, the paper proposed the dynamic evaluation model of urban rail transit sustainable development by using the grey system theory. The Wuhan rail transit system was studied as the example. The study results confirm the method is practical and feasible. The model is helpful for policy-makers to formulate improvement measure and management method for urban rail transit sustainable development.

Accurately understanding the travel demand of urban rail transit (URT) systems is crucial for effective operational management. Despite the recognition that the diversity in human activity patterns results in different travel demands, few studies have thoroughly investigated the heterogeneity among passengers and its impact on URT ridership. This study utilizes smart card data collected from the Beijing Subway to categorize passengers into four groups: tourist passengers, flexible commuters, regular commuters, and life‐oriented passengers, based on their spatiotemporal travel patterns. Furthermore, a Multiscale Geographically Weighted Regression (MGWR) model is employed to examine the relationship between station‐level ridership of URT and its determinants, including the built environment and station properties, for each passenger group. The results indicate that the influence of these determinants on station‐level ridership varies across passenger groups and spatial scales. For instance, regular commuters exhibit lower sensitivity to accessibility on workdays, whereas those unfamiliar with the URT network are more concerned about the bus accessibility in pedestrian‐ or bicycle‐unfriendly areas. Notably, for tourist and life‐oriented passengers, the stations significantly affected by population density are concentrated in areas with a higher proportion of elderly individuals. Conversely, for flexible and regular commuters, these stations are predominantly situated in areas associated with internet technology and scientific research. These findings are valuable for policymakers in designing strategies tailored to different passenger groups to balance trip demand and capacity, thereby improving URT services and promoting a sustainable urban environment.