Urban Public Transit Research Articles

Reposition optimization in free-floating bike-sharing system: A case study in Shenzhen City

In recent years, the free-floating bike-sharing system has attracted a large number of travelers for its convenience and non-pollution in the urban public transit. Although many researchers have been carried out, there still exist challenges in repositioning optimization to improve the operating efficiency in the bike-sharing system. This study introduces an improved repositioning model for the free-floating bike-sharing system and designs Non-dominated Sorting Genetic Algorithm II (NSGA-II) to conduct optimization. Firstly, the Gaussian mixture model (GMM) is adopted for clustering to obtain the stations in the free-floating bike-sharing system. Then, a multi-objective optimization model is established considering minimizing the total cost of the repositioning operation and maximizing the satisfaction degree of demands of the delivery stations. To solve the model, an improved NSGA-II is proposed, in which different ways of crossover and mutation operators are applied to maintain the diversity of the population. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the best compromise solution. Finally, using trajectory data from the free-floating bike-sharing system in Shenzhen City, we further compare the results with traditional Genetic Algorithm (GA). The comparison demonstrates that the proposed method is reasonable and effective in the reposition optimization for free-floating bike-sharing system.

Impact of Unplanned Long-Term Service Disruptions on Urban Public Transit Systems

Impact of Unplanned Long-Term Service Disruptions on Urban Public Transit Systems

Research on Optimization of Urban Public Transport Network Based on Complex Network Theory

The urban public transportation system is an important part of urban transportation, and the rationality of public transportation routes layout plays a vital role in the transportation of the city. Improving the efficiency of public transportation can have a positive impact on the operation of the public transportation system. This paper uses complex network theory and the symmetry of the up and down bus routes and stations to establish an urban public transit network model and calculates the probability of passengers choosing different routes in the public transit network according to passenger travel impedance. Based on passenger travel impedance, travel path probability and passenger travel demand, the links are weighed, and the network efficiency calculation method is improved. Finally, the public transit network optimization model was established with network efficiency as the objective function and solved by the ant colony algorithm. In order to verify the effectiveness of the model and the solution method, this paper selects areas in Nanguan District of Changchun City for example analysis. The result shows that the efficiency of the optimized network is 8.5% higher than that of the original network, which proves the feasibility of the optimized model and solution method.

Topology analysis of Lanzhou public transport network based on double-layer complex network theory

The network topology is the basis of studying the overall performance and dynamic evolution mechanism of network. In regards to the study on the topology of multi-layer complex networks, the current studies fail to consider the heterogeneity of edges and nodes in multi-layer complex networks, and such methods are insufficient when they are used to analyze the static characteristics of topology. Therefore, this paper based on the theoretical basis of the multi-layer complex network, establishes a two-layer public transit complex network model where urban rail transit and bus transit cooperate with each other, and by optimizing this two-layer public transit complex network model, further proposes an integrated public transit network model. According to the method of analyzing the static statistical characteristics of complex networks, and considering the heterogeneity of nodes and edges in multi-layer network, this​ paper gives the evaluation indicators of static statistical characteristics of multi-layer public transit complex networks. Taking the two-layer public transit complex network structure in Lanzhou as an example, this paper finds out the main factors affecting its network stability and efficiency by analyzing the physical structure characteristics of this two-layer public transit complex network in Lanzhou where urban rail transit and bus transit cooperate with each other, and then puts forward the network optimization suggestions from the point of view of optimizing key nodes by using the method of identifying key nodes with centrality. In this study, the coupling among heterogeneous public transit network layers and the static structure characteristics of multi-layer public transit complex network are studied from the perspective of network structure, to assist the traffic management department in finding out the problems of the road network for the management and improvement of the performance and efficiency of the network. This has a profound influence on the development planning of urban public transit system.

Partnerships in Urban Mobility: Incentive Mechanisms for Improving Public Transit Adoption

Problem definition: Because of a prolonged decline in public transit ridership over the last decade, transit agencies across the United States are in financial crisis. To entice commuters to travel by public transit instead of driving personal vehicles, municipal governments must address the “last-mile” problem by providing convenient and affordable transportation between a commuter’s home and a transit station. This challenge raises an important question: Is there a cost-effective mechanism that can improve public transit adoption by solving the last-mile problem? Academic/practical relevance: In this paper, we present and analyze two incentive mechanisms for increasing commuter adoption of public transit. In a direct mechanism, the government provides a subsidy to commuters who adopt a “mixed mode,” which involves combining public transit with hailing rides to/from a transit station. The government funds the subsidy by imposing congestion fees on personal vehicles entering the city center. In an indirect mechanism, instead of levying congestion fees, the government secures funding for the subsidy from the private sector. We examine the implications of both mechanisms on relevant stakeholders. These two mechanisms are especially relevant because several jurisdictions in the United States have begun piloting incentive programs, in which commuters receive subsidies for ride-hailing trips that begin or end at a transit station. Methodology: We present a game-theoretic model to capture the strategic interactions among five self-interested stakeholders (commuters, public transit agency, ride-hailing platform, municipal government, and local private enterprises). Results: By examining equilibrium outcomes, we obtain three key findings. First, we characterize how the optimal interventions associated with the direct or the indirect mechanism depend on: (a) the coverage level of the public transit network; (b) the public transit adoption target; and (c) the relative strength of commuter preferences between driving and taking public transit. Second, we show that the direct mechanism cannot be budget-neutral without undermining commuter welfare. However, when the public transit adoption target is not too aggressive, we find that the indirect mechanism can increase both commuter welfare and sales to the private-sector partner while remaining budget-neutral. Finally, we show that, although the indirect mechanism restricts the scope of government intervention (by eliminating the congestion fee), it can dominate the direct mechanism by leaving all stakeholders better off, especially when the adoption target is modest. Managerial implications: Our findings offer cost-effective prescriptions for improving urban mobility and public transit ridership.

Transit Assignment Modeling Approaches based on Interval Uncertainty of Urban Public Transit Net Impedance

Transit Assignment Modeling Approaches based on Interval Uncertainty of Urban Public Transit Net Impedance

Exploring the resilience assessment framework of urban road network for sustainable cities

Urban space for new transportation facilities cannot meet the increasing traffic demand. Afterward, scholars gradually increased attention to the resilience evaluation of urban road networks. Therefore, we proposed a resilience assessment framework of the urban road networks, including the resilience performance index, the robustness index, and the recovery index. Then we simulated the cascading failure based on a nonlinear load-capacity model with two capacity control parameters: α and β. Results show that the intersection-based attack has the most significant impact on resilience, and resilience is positively correlated with the node degree of the attacked intersection. The increase of α and β could enhance the resilience, and the urban road network achieves the best resilience performance when α=0.3,β=0.5. Compared with the deliberate attack strategy, the resilience performance under the random attack strategy is more robust. This research can provide the foundation for optimizing urban road networks and multi-mode urban public transit networks.

What should we do to enhance your loyalty if you are (dis)satisfied with public transit service?

Within a highly motorized context, urban public transit (PT) agencies have been trying to find effective ways to increase PT ridership, which is important in ridership retention and attraction. This study is designed to examine how perceived service quality, perceived value, corporate image, satisfaction, and complaints interact to influence passengers’ loyalty to PT, on the basis of a passenger segmentation approach according to the extent to which passengers are satisfied and dissatisfied with PT, i.e., a cross satisfaction-and-complaints classification approach. A four-step analysis procedure consisting of exploratory factor analysis, structural equation model, latent class cluster analysis, and multigroup SEM, is proposed. Passengers are segmented into three subgroups, each profiled by distinctive feature associated with passengers’ satisfaction and complaints about PT service. The multigroup analysis reveals significant differences about the relationships between factors of interest across the three subgroups. It is expected that the results would provide useful implications for transit agencies to enhance the passengers’ loyalty, where customized marketing measures and strategies towards groups holding diverse satisfaction and complaints with PT are necessary.

Building Architecture of Intelligent Control System for Urban Rail Transit System

The increase in the volume of passenger transportation in megalopolises and large urban agglomerations is efficiently provided by the integration of urban public transit systems and city railways. Traffic management under those conditions requires creating intelligent centralised multi-level traffic control systems that implement the required indicators of quality, comfort, and traffic safety regarding passenger transportation. Besides, modern control systems contribute to traction power saving, are foundation and integral part of the systems of digitalisation of urban transit and the cities. Building systems solving the traffic planning and control tasks is implemented using algorithms based on the methods of artificial intelligence, principles of hierarchically structured centralised systems, opportunities provided by Big Data technology. Under those conditions it is necessary to consider growing requirements towards software as well as theoretical design and practical implementation of network organisation.This article discusses designing architecture and shaping requirements for developed applications and their integration with databases to create a centralised intelligent control system for the urban rail transit system (CICS URTS). The article proposes the original architecture of the network, routing of information flows and software of CICS URTS. The routing design is based on a fully connected network. This allows to significantly increase the network bandwidth and meet the requirements regarding information protection, since information flows are formed based on the same type of protocols, which prevents emergence of covert transmission channels. The implementation of the core using full connectivity allows, according to the tags of information flows, to pre-form the routes for exchange of information between servers and applications deployed in CICS URTS. The use of encrypted tags of information flows makes it much more difficult to carry out attacks and organise collection of information about the network structure.Platforms for development of intelligent control systems (ICS), which include CICS URTS, high computing power, data storage capacity and new frameworks are becoming more available for researchers and developers and allow rapid development of ICS. The article discusses the issues of interaction of applications with databases through a combination of several approaches used in the field of Big Data, substantiates combination of Internet of Things (IoT) methodology and microservice architecture. This combination will make it possible to single out business processes in the system and form streaming data processing requiring operational analysis by a human, which is shown by relevant examples.Thus, the objective of the article is to formalise the principles of organising data exchange between CICS URTS and automated control systems (ACS) of railway companies (in our case, using the example of JSC Russian Railways), URTS services providers, and city government bodies, implement the developed approaches into the architecture of CICS URTS and formalise principles of organisation of microservice architecture of CICS URTS software. The main research methods are graph theory, Big Data and IoT methods.

Construction of Virtual Simulation Experimental Teaching Resource for Urban Public Transit

In order to enable students to better grasp the urban public transit operation process and its evolution mechanism, it is necessary to carry out the construction of the virtual simulation experimental teaching resources of urban public transit. Guided by the construction goal of “experimental skills, innovative ability and scientific research quality”, and the education concept of “students-centered philosophy”, this paper expounds the main content of the construction of virtual simulation teaching resources of urban public transit from three aspects of the teaching system, experimental items, and management system. In addition, the key technologies of virtual simulation platform construction are introduced briefly. The construction of the virtual simulation platform, on the one hand, can ensure that the students can better carry out basic experiments, comprehensive training and innovative practical activities through the virtual simulation experiment platform; on the other hand, can provide an important reference for the construction of similar virtual simulation experiment teaching resources in other transportation-related majors.

Productivity Growth of Urban Transit Agencies in the U.S.

ABSTRACT This article assesses the productivity of US urban public transit using data of 45 largest bus agencies and 32 rail agencies from years 2007 through 2017. The study shows that both bus and rail transit agencies have experienced declining cumulative productivity growth during the study period. The Malmquist productivity index was decomposed into technical efficiency change and technological change components and the findings indicate that, for bus transit agencies, outsourcing or purchased transportation is associated with negative efficiency change. Although purchased transportation has a positive effect on technological change for bus transit, the effect is not significant. The results suggest that transit agencies that seek to partner with shared-mobility service providers or to integrate shared-mobility with transit service must address challenges that hinder transit efficiency, and that transit technology has yet to keep up with technological progress in urban mobility.

Discussion on Optimization of Public Transportation Network Setting considering Three-State Reliability

In order to be environment-friendly, relieve traffic congestion, reduce pollution, and be green and sustainable, the optimization and development of public transportation, as the subject of people's long-term research, has always been shining. With the emergence of shared transportation, public transportation systems face more challenges. In order to better connect with bike-sharing, car-sharing, and other modes of transportation, public transportation will carry out important reforms, among which the optimization of line network is one of the most important tasks. The traditional bus route design is mainly based on the “four-stage” method model, which is mainly based on the investigation and analysis of the existing traffic system and land use. Through the work flow of “evaluation, calibration, and verification,” the network balance optimization model is used to get the bus travel allocation prediction model. In this paper, the optimization problem of public transit network is studied from the point of view of the reliability of public transit network. It is proposed that public transit network can be abstracted into series-parallel system and parallel-series system model from the three states of normal, short-circuit failure, and open-circuit failure and is analyzed and discussed through the hypothesis experiment. The research of this paper will provide a new perspective for the optimization of public transit network, complement the traditional methods, and support the optimization and reliability improvement of urban public transit network. More reliable bus networks and other modes of transportation, such as walking, bike-sharing, and rail, will become more suitable for people to get around.

Impact of Side Friction on Travel Time Reliability of Urban Public Transit

Travel time reliability is the key aspect that indicates the quality of urban public transit service. The studies on travel time reliability of the public transit system in Indian traffic conditions are few. Also, the impact of side friction elements on travel time reliability has not been considered in the previous studies. Hence, the present study aims to quantify the different types of side friction elements and analyse their impact on the travel time reliability of the public bus transit system. The field data consisting of side friction elements, traffic volume, and travel time of public bus transit have been collected and extracted at two different road sections (divided and undivided) in the Mysore city (Karnataka, India) during weekdays and weekends. The data are grouped into static and dynamic side frictions. An approach has been proposed to represent different types of side friction elements with a single index called the Side Friction Index (SFI) using relative weight analysis. Travel time reliability is represented using measures such as Buffer Time Index (BTI), Planning Time Index (PTI), Travel Time Index (TTI) and Reliable Buffer Index (RBI). The impact of side friction on travel time reliability was found to be sensitive to traffic volume, and hence the thresholds for different traffic volume levels have been determined using K-means clustering method. It was observed from relative weight analysis that the static side friction has a higher weightage (0.509 and 0.327 for the undivided road and divided road respectively) than the dynamic side friction elements in describing the variation of travel time. The impact of side friction on reliability measures at different traffic volume levels has been studied and found to have a non-linear (exponential) relationship. The impact of SFI has been observed to be higher on TTI and PTI in comparison with BTI. The study outcomes show that the impact of side friction on TTI and PTI is sensitive to traffic volume, especially at higher traffic volume level and impact of side friction on BTI is less, especially at medium traffic volume level. The inference from the study shows that the impact of side friction elements varies with respect to the type of road (divided and undivided), traffic volume levels, different days of week (weekday and weekend), and different time periods of day.

Build it and they will cycle: Causal evidence from the downtown Vancouver Comox Greenway

This study evaluated changes in cycling trips before and after the construction of an urban greenway in Vancouver, Canada. Urban cycling has gained in popularity as a healthy and environmentally friendly mode of transport. Carsharing is also on the rise globally, and it has the potential to disrupt urban mobility, including cycling and public transit. In this study, we hypothesized that cycling trips will increase after the opening of the greenway for residents living within 300 meters of the greenway compared to those living further away. We also posited that carsharing membership would have a positive impact on cycling uptake. Data were drawn from a three-year natural experiment study (2012–2015) of the Comox-Helmcken Greenway (“Comox Greenway”) in Vancouver. An experimental-and-control design was employed to compare pre-post differences in cycling trips for residents within 300 m of the greenway (experimental group, n = 239) and those further away (control group, n = 285). The opening of the greenway resulted in a 251% increase in cycling trips for the experimental group compared to the control group. Ethnically white subjects reported 130% more cycling trips than non-white subjects, and those aged 65 and older reported 79% fewer cycling trips than younger age cohorts. Carshare membership reduced the number of cycling trips after the greenway opening. Results suggest that greenways could be an effective strategy to boost urban cycling, and that carsharing programs may have a countervailing effect on cycling. The findings support recent initiatives to reappropriate road space in urban areas for cycling and walking due to the COVID-19 pandemic.

Souq Waqif Neighborhood as a Transit-Oriented Development

In a rapidly developing nation such as Qatar, the prime aspect of growth is directed toward delivering social, economic, and environmental coherence in its neighborhood development. Qatar's current fast economic growth and the physical transformation of its built environment compromises social and environmental aspects. However, if applied suitably, these transformations can enhance these compromised aspects while increasing economic prosperity. Such transformations include major urban public transit systems currently under construction for the 2022 FIFA World Cup and 2030 Qatar National Vision (QNV-2030), which aims to connect the center of Doha to several megaprojects and transit villages around major metro stations. The main goal of projects such as the Doha Metro System is to reduce the number of vehicles on the road networks while providing a “stress-free” transition experience. Therefore, the pursuit of transit-oriented developments (TODs), as part of an integrated transportation and land use strategy, will aid in the revitalization of urban neighborhoods in terms of both social and environmental aspects, while allowing for economic prosperity. The main challenge for urban planners is to design the metro stations and accompanying facilities to be well integrated into the urban context of their surroundings, thus reducing traffic through the design of mixed-use, compact transit villages. This study aims to explore the extent to which the new metro station can be interconnected with the spatial form of the built environment of the Souq Waqif neighborhood. This research study argues that efficient integration of land use with balanced transportation will contribute to creating a more livable environment with reduced automobile dependence while aiding the economic context. The research design includes qualitative data based on theoretical studies to assess the principles of TODs and the extent of further implementations that can be employed for the Souq neighborhood to become a TOD.

Activity-friendly neighbourhoods can benefit non-communicable and infectious diseases

ABSTRACT Walkable, activity-friendly neighbourhoods are recommended for their benefits for non-communicable diseases, environmental sustainability, and economic performance. But how do activity-friendly neighbourhoods function during infectious disease pandemics like COVID-19? The spread of COVID-19 in some of the world’s dense cities has raised concerns about the risks of urban density and public transit. However, there are several pathways by which dense, mixed-use neighbourhoods with transit access and recreation facilities can reduce the risk of both infectious diseases and non-communicable diseases. Reducing health inequities is a core value for public health, and we comment on strategies for equitably creating activity-friendly communities.

Passenger Flow Forecasting in Metro Transfer Station Based on the Combination of Singular Spectrum Analysis and AdaBoost-Weighted Extreme Learning Machine.

The metro system plays an important role in urban public transit, and the passenger flow forecasting is fundamental to assisting operators establishing an intelligent transport system (ITS). The forecasting results can provide necessary information for travelling decision of travelers and metro operations of managers. In order to investigate the inner characteristics of passenger flow and make a more accurate prediction with less training time, a novel model (i.e., SSA-AWELM), a combination of singular spectrum analysis (SSA) and AdaBoost-weighted extreme learning machine (AWELM), is proposed in this paper. SSA is developed to decompose the original data into three components of trend, periodicity, and residue. AWELM is developed to forecast each component desperately. The three predicted results are summed as the final outcomes. In the experiments, the dataset is collected from the automatic fare collection (AFC) system of Hangzhou metro in China. We extracted three weeks of passenger flow to carry out multistep prediction tests and a comparison analysis. The results indicate that the proposed SSA-AWELM model can reduce both predicted errors and training time. In particular, compared with the prevalent deep-learning model long short-term memory (LSTM) neural network, SSA-AWELM has reduced the testing errors by 22% and saved time by 84%, on average. It demonstrates that SSA-AWELM is a promising approach for passenger flow forecasting.

Reuse of Abandoned Railways Leads to Urban Regeneration: A Tale from a Rust Track to a Green Corridor in Zhangjiakou

While high-speed train systems have accelerated mobility in China during the twenty-first century, the train systems of normal speed have gradually been replaced and abandoned, resulting in a "rust belt" in some Chinese cities. The reuse of abandoned railways provides a way to rebuild urban public transit based on the traditional tracks, and is also a way to transform towards urban regeneration of the surrounding neighborhood. Previous studies discussed the possibilities of three perspectives of reusing the abandoned rails: as a new transportation route, as a place for tourism and commerce and as a green corridor for the public. As a case study, this paper selects Zhangjiakou City, which is the terminal of the first railway routes built by Chinese, and explores methods of transformation from rail to urban rail transit. Under the background of the Beijing Winter Olympics of 2022 being partly held in Zhangjiakou City, the old North station and a 10-km rail between the North and South Station have been abandoned since 2014. This paper suggests conversion of the railway into an urban tram to meet the increasing commuter flow between the old and new city center. Additionally, transformation of the abandoned railway located in the city center will also trigger the urban space regeneration by increasing more urban functions and promoting urban public space. This research might shed light on other cities with similar transforming transportation facilities by analyzing the reuse possibilities of Beijing-Zhangjiakou Railway in Zhangjiakou City.

Partnerships in Urban Mobility: Incentive Mechanisms for Improving Public Transit Adoption

Problem Definition: Due to a prolonged decline in public transit ridership over the last decade, transit agencies across the United States are in financial crisis. To entice commuters to travel by public transit instead of driving personal vehicles, municipal governments must address the ``last mile'' problem by providing convenient and affordable transportation between a commuter's home and a transit station. This challenge raises an important question: Is there a cost-effective mechanism that can improve public transit adoption by solving the last mile problem? Academic / Practical Relevance: In this paper, we present and analyze two incentive mechanisms for increasing commuter adoption of public transit. In a direct mechanism, the government provides a subsidy to commuters who adopt a ``mixed mode, which involves taking public transit and hailing rides to/from a transit station. The government funds the subsidy by imposing congestion fees on personal vehicles entering the city center. In an indirect mechanism, instead of levying congestion fees, the government secures funding for the subsidy from the private sector. We examine the implications of both mechanisms on relevant stakeholders. These two mechanisms are especially relevant because several jurisdictions in the U.S. have begun piloting incentive programs in which commuters receive subsidies for ride-hailing trips that begin or end at a transit station. Methodology: We present a game-theoretic model to capture the strategic interactions among five self-interested stakeholders (commuters, public transit agency, ride-hailing platform, municipal government, and local private enterprises). Results: By examining equilibrium outcomes, we obtain three key findings. First, we characterize how the optimal interventions associated with the direct or the indirect mechanism depend on: (a) the coverage level of the public transit network; (b) the public transit adoption target; and (c) the relative strength of commuter preferences between driving and taking public transit. Second, we show that the direct mechanism cannot be budget neutral without undermining commuter welfare. However, when the public transit adoption target is not too aggressive, we find that the indirect mechanism is budget neutral, and it can increase both commuter welfare and sales to the private sector partner. Finally, we show that, although the indirect mechanism restricts the scope of government intervention (by eliminating the congestion fee), it can dominate the direct mechanism by leaving all stakeholders better off, especially when the adoption target is modest. Managerial Implications: Our findings offer cost-effective prescriptions for improving urban mobility and public transit ridership.

Improving the On-Vehicle Experience of Passengers Through SC-M*: A Scalable Multi-Passenger Multi-Criteria Mobility Planner

The rapid growth in urban population poses significant challenges to moving city dwellers in a fast and convenient manner. This paper contributes to solving the challenges from the viewpoint of passengers by improving their on-vehicle experience. Specifically, we focus on the problem: Given an urban public transit network and a number of passengers, with some of them controllable and the rest uncontrollable, how can we plan for the controllable passengers to improve their experience in terms of their service preference? We formalize this problem as a multi-agent path planning (MAPP) problem with soft collisions, where multiple controllable passengers are allowed to share on-vehicle service resources with one another under certain constraints. We then propose a customized version of the SC-M* algorithm to efficiently solve the MAPP task for bus transit system in complex urban environments, where we have a large passenger size and multiple types of passengers requesting various types of service resources. We demonstrate the use of SC-M* in a case study of the bus transit system in Porto, Portugal. In the case study, we implement a data-driven on-vehicle experience simulator for the bus transit system, which simulates the passenger behaviors and on-vehicle resource dynamics, and evaluate the SC-M* on it. The experimental results show the advantages of the SC-M* in terms of path cost, collision-free constraint, and the scalability in run time and success rate.