Spatial Coupling of Mass Transit Networks and Business Centers in China's Megacities: A Complex Network Theory Approach

Different from traditional urban rail transit network, urban rapid rail transit network planning is system planning in a greater region with multi-level, multi-factor and multi-objective planning. The significance of an evaluation index system of urban rapid rail transit network planning has been shown in urban rapid rail transit development. Based on the analysis of an evaluation index system of urban rapid rail transit network planning in different cities and the “3E” principle (Economy, Environment, Equality) that was used in Metropolitan and Comprehensive Transportation planning, the evaluation index system of urban rapid rail transit network planning is reorganized. Grey incidence analysis method is carried out to evaluate the latest urban rapid rail transit network planning in Chengdu of China and the best one of five plan alternatives is selected. Results show that the “3E” principle is much more guidable for the evaluation index system, and Grey incidence analysis method is much more effective. Through this article, for the real practice of urban rapid rail transit network planning in Chengdu of China in 2010, scientific decision support is provided and shows high-grade results.

The Urban Rail Transit (URT) network possesses the features of multi-route and big volume of passengers. To study the route choice behavior and volume control of passengers is a bridge to match the capacity supply and passenger demand in URT network. It’s also a crucial problem proposed by the networked operation of URT. We analyze systematically the effect factors of passengers’ route choice behavior and related research on passenger volume control in URT network, as well as the updated representation of URT network and nature of passenger demand. Then we set up the integrated calculation formula for general travel cost in URT network. afterwards, we summarize the classical research method for route choice behavior, including its main study procedure, the search and identify method for effective routes, logit model, probability distribution model, multi-agent simulation and calculation of the match probability by using big data e.g. AFC data. Importantly, we propose the framework for joint comprehensive prediction of passenger route choice behavior and volume control in URT network based on big data, which displays the mind map of passenger-flow-based prediction control and intelligent decision for future study. This review has great theoretical and practical meanings in improving the service efficiency and quality of URT, so as to balance the load of each line and station in URT network, as well as to reduce or eliminate the passenger waiting time for those being left behind because of congestion.

Urban rail transit stations are the key nodes of urban rail transit network. Identifying and analyzing land use characteristics around urban rail transit stations can significantly contribute to urban rail transportation operation and management. Therefore, a visualization method of land use characteristics around urban rail transit stations based on POI is proposed in this paper. In the proposed method, first, the Voronoi diagram is used to determine coverage of urban rail transit stations and each POI is put in a coverage area based on their physical location. Then, topic-oriented hierarchical POIs of each urban rail transit station are extracted based on skyline idea. Finally, the land use characteristics around an urban rail transit station are visualized based on the extracted hierarchical POIs. We carried out two case studies and a quality evaluation. By using realistic data from Beijing rail transit in order to validate the method proposed in this paper. Results show that our method can clarify various situations of land use of urban rail transit stations and may provide support for the application of transportation model technology.

Large-scale activities, holidays, and emergencies often cause a significantly large burst of passenger flow demand in some urban rail transit (URT) stations in a short time, called large passenger flow (LPF). The LPF will propagate through the entire URT network of the city. The impact of the frequent occurrence of LPF on network service levels is crucial and unpredictable. This article describes an analysis of how this LPF propagates through the entire network inspired by how radionuclide imaging is done in clinical medicine. In this study, with LPF of URT as the research object, a propagation model of LPF in URT based on AFC data, train operation data, and URT network topology data was developed, which was inspired by the concept of radionuclide imaging in clinical medicine. In the condition of obtaining the list of passenger route selection ratios, the dynamic propagation state matrix of the LPF in the network is solved. The contribution value matrix of the LPF was proposed to evaluate the impact of the LPF on the URT network. Considering the LPF in Chengdu East Railway Station, China, as an example, the propagation effect of LPF in the Chengdu Metro network was analyzed, and the effectiveness of the proposed model was confirmed.

Route choice modelling is a critical aspect of analysing urban rail transit (URT) networks and provides a foundation for URT planning and operation. Unlike in a free-flow road network, the consideration set for route choice decisions in a URT network does not depend purely on the physical connectivity of the network and decision makers’characteristics. Instead, it is also contingent on the train schedules. This paper delves into the evolution of research on route choices in URT networks, encompassing both probabilistic route choice modelling derived from utility maximisation theory and logit curve with physical connectivity, and retrospective route choice modelling based on travel time chaining along with comprehensive transport data. The former is noted for its conciseness, simplicity, and interpretability in real-world applications, even though the methodologies may not be cutting-edge. The latter incorporates dynamic temporal information to understand activities of passengers in URT networks. Enhancements of each genres are also examined. However, these improvements might not fully address the inherent limitations of models relating to a dependency on the quality of parameters, experience of experts, and calculation efficiency. In addition, novel research adopting contemporary data mining techniques instead of classical models are introduced. The historical development of research on URT network route choices underscores the importance of amalgamating independent information networks such as surveillance networks and social networks to establish a comprehensive multi-dimensional network. Such an approach integrates passenger attributes across networks, offering a multi-dimensional understanding of passengers’ route choice behaviours. Our review work aims to present not only a systematic conceptual framework for route choices in URT networks but also a novel path for transport researchers and practitioners to decipher the travel behaviours of passengers.

Capacity index of Urban Rail Transit (URT) Network plays an improtant role in rational utilization of system capacity and operation management. A definition and calculating method of the capacity of URT Network was first proposed according to the features of URT network and route choice behavior of rail passengers in this paper. Several aspects of influencing factors of URT capacity were analyzed. A bi-level programming model was presented to optimize the URT capacity besides the system utility. Upper level of the model aims at maximizing the total OD flow through the URT network, and the lower level model is one kind of Fisk Equilibrium model. A new kind of impendence function relevant to the lower level model was put forward in consideration of practical traveler behavior. Genetic algorithm technique was applied to solve the bi-level programming model on the premise that the bi-level programming problem be converted into a single-level programming which was achieved by reformulating the lower-level problem model to its equivalent Karush-Kuhn-Tucker conditions. Effective crossover and mutation operators were proposed to enhance the convergence of the Genetic algorithm. A simplified network of Beijing URT was designed and numerical examples were conducted to prove that the proposed model and algorithm are feasible and valid in calculating the capacity of such network.

The vulnerability of an urban rail transit (URT) network is an index that reflects its ability to cope with risks. However, existing URT network vulnerability studies have paid less attention to station track layout and passenger choice behavior, both of which significantly affect the consequences of a disruption incident. In the present study, we first analyze an actual scenario of URT section disruption and passenger behavior during an incident. Then, we propose two section vulnerability indexes that quantitatively evaluate the effect of a URT section disruption from two aspects: detour delay and loss in passenger flow. To make the application scenario of this method more realistic, the track layout and depot location are taken into account. By considering the relationship between train routing and the sections, a concept of “dominant section” is put forward to make the calculation of the vulnerability indexes more efficient and can be used for a simultaneous multi-section-disruption scenario. Finally, a case study of the Beijing Subway network is provided. The results show that disruptions in only a few critical sections can significantly affect the URT network passenger flow. Disruption of only 3% of the sections can lead to 80% passenger-flow loss, which reflects the high vulnerability of URT networks. The method proposed in this paper can provide support for the evaluation of URT network performance.

Behavior-Adaptive Sync-Flow Framework: Integrating frequency setting and passenger routing in oversaturated urban rail transit networks

A new global method for identifying urban rail transit key station during COVID-19: A case study of Beijing, China

Urban rail transit (URT) systems are critical to modern public transportation services. Unfortunately, disruptions in URT systems can lead to dysfunction and threaten sustainable development. This study analyses URT network sustainability from a vulnerability perspective. Two network attack scenarios, including random attacks and intentional attacks, are designed to assess different kinds of disruptions to URT networks. Under random attacks, nodes are randomly removed from the network. In contrast, under intentional attacks, key nodes are identified and removed based on topological metrics and passenger flow volume. Then, URT network vulnerability is evaluated by quantifying the changes in network efficiency and structural integrity under the network attacks from a spatio-temporal point of view. The real-world case of the Shanghai URT system from 1993 to 2020 is used to illustrate the vulnerability in the evolution of the URT system. The results indicate that the URT network is increasingly fault-tolerant and structurally robust over time. The URT network is more vulnerable to intentional attacks than to random failures. Additionally, there are significant spatial differences in the vulnerability of Shanghai URT network. Stations in the central activity zone (CAZ) are more fault-tolerant and robust than stations located outside of the CAZ. Furthermore, stations with large centrality and greater passenger flow volumes and lines with many key nodes and greater passenger flow volumes, are vulnerable to disruptions in the URT networks. This study provides a new index to comprehensively quantify node centrality; it also fills a research gap by analysing the vulnerability of URT networks based on both longitudinal and spatial patterns. Finally, this paper highlights significant practical implications for the sustainable development of URT networks, as well as the sustainable development of public transportation services.

Collaborative rescheduling of train timetables to relieve passenger congestions in an urban rail transit network: A rolling horizon approach

Land use of urban central rail transit station core area is an important part of the TOD model research, which is of great significance to urban agglomeration and sustainable development. Base on the characteristics of “Node-place” in the rail transit station area, this paper constructs a land use database framework in the station core area, and determines the land use index factors according to the cases field investigation and data analysis. By comparing the features of BP artificial neural network and depth neural network, this paper builds two technical routes: “Land use prediction simulation of station core area based on BP artificial neural network” and “land use planning scheme of station impact area based on deep neural network”. This paper explored the interdisciplinary method of using artificial intelligence (AI) technology to study the land use of urban central rail transit station core area and designs the technical route, which is of great significance to promote the efficient use of urban land in rail station area and the sustainable development of cities.

During the rapid development of urbanization, many huge cities are in the sensitive period that adjustment of urban spatial structure should be brought about with transport. Through dissecting Shanghai URT's development process, the interaction between URT and urban spatial structure is focused on in this paper. On the one hand, URT and urban spatial development form are mutual restricted; on the other hand, URT will promote the benign development of urban space, to form a layout of bead-shaped radial axis, and to avoid the negative overspread of a pie-type mode. For the oversize cities (such as Shanghai, Beijing, Guangzhou, etc) with strong economic power, after completing of URT' network layout in central areas, traditional mindset of transport planning should be changed, and the mode of TOD (Transit Oriented Development) should be adopt, thereby to achieve the object of coordinate development between a URT's network and a urban spatial structure in a city. Road area capita is lower in many major cities of our country, and service level of road is far below the traffic demand of motor vehicles. With a rapid growth of ownership of urban motor vehicles, traffic jams in Beijing, Shanghai, Guangzhou, Shenzhen, Wuhan and other major cities got worse. During 2010 in Beijing, the heavy congestions on Mid-Autumn Festival and National Day showed a warning sign that Beijing's road system serviceability couldn't afford the rush hour traffic demand. Therefore, developing of public transport, especially the URT (urban rail transit) system with features of mass transit, high speed and high efficiency, is the inevitable choice of solving major cities' traffic problems, and has showed a principal measure to form a perfect urban spatial structure with lower traffic congestion under the condition of limited urban land and transport resource. URT is safe, reliable, fast, and low-pollution. Due to the characteristics of high volume, fast and timely, it can provide the good accessibility of areas along the line and ensures people to travel further in as short as possible time. In other hand, it provides a strong transport support for the adjustment of the major cities' space layout and the expansion of urban built-up areas. Evolution of urban spatial form is the incorporated evolution of land and transport. Reference from the valuable experiences of development of urbanization

Timetable synchronization of the last several trains at night in an urban rail transit network

This paper firstly analyzes composed elements of the urban rail transit(URT) network, on basis of which the line and the station’s abstract models are built. An integrated impedance function model is designed to describe the network. Besides, the K-shortest path finding algorithm based on Floyd(KSPF) for path finding problem is designed. With the above model and algorithm, URT Network Digital Management System(URT_DMS) is developed. Taking Beijing URT network as an example, this paper gives out three paths between Wangjing station and Military Museum station. Compared with commercial software, the result shows the proposed model is valid.