Urban Public Transport Research Articles

Exploring Public Transportation Supply–Demand Structure of Beijing from the Perspective of Spatial Interaction Network

A comprehensive understanding of the relationship between public transportation supply and demand is crucial for the construction and sustainable development of urban transportation. Due to the spatial and networked nature of public transportation, revealing the spatial configuration and structural disparities between public transportation supply and demand networks (TSN and TDN) can provide significant insights into complex urban systems. In this study, we explored the spatial configuration and structural disparities between TSN and TDN in the complex urban environment of Beijing. By constructing subdistrict-scale TSN and TDN using urban public transportation operation data and mobile phone data, we analyzed the spatial characteristics and structural disparities of these networks from various dimensions, including global indicators, three centralities, and community structure, and measured the current public transportation supply and demand matching pattern in Beijing. Our findings revealed strong structural and geographic heterogeneities of TSN and TDN, with significant traffic supply–demand mismatch being observed in urban areas within the Sixth Ring Road. Moreover, based on the percentage results of supply–demand matching patterns, we identified that the current public transportation supply–demand balance in Beijing is approximately 64%, with around 18% of both excess and shortage of traffic supply. These results provide valuable insights into the structure and functioning of public transportation supply–demand networks for policymakers and urban planners; these can be used to facilitate the development of a sustainable urban transportation system.

Diseconomies of scale and subsidies in urban public transportation

Subsidization of urban public transportation systems is often motivated by economies of scale and second-best considerations such as an underpriced road alternative. We model a public transit line subject to frictions between users (in-vehicle crowding), users and vehicles (boarding and alighting delays), and vehicles (congestion). We derive the profit- and welfare-maximizing provisions of supply. We show that if demand exceeds a first threshold, the system enters a congested regime and service frequency decreases. Beyond a second threshold, the strong deterioration of service quality causes the transit line to operate under diseconomies of scale, calling for a Pigouvian tax instead of a subsidy. This finding, which goes against Mohring’s classical rule (1972), holds with an untolled road alternative, provided that the network structure remains constant. We estimate the model for the London Piccadilly line and find evidence of substantial diseconomies of scale during the morning peak, adding up to −1.49 £/trip for the observed provision of service quality (-0.61 £/trip at optimum). These results question current subsidy policies for the busiest transit lines.

A novel data-driven energy management strategy for fuel cell hybrid electric bus based on improved twin delayed deep deterministic policy gradient algorithm

With the prosperity of artificial intelligence in recent years, energy management strategies (EMSs) based on deep reinforcement learning (DRL) have become the mainstream approach to ensure efficient energy distribution of hybrid electric vehicles (HEVs). Moreover, in terms of developing sustainable urban public transportation systems, zero-emission fuel cell hybrid electric buses (FCHEBs) are more promising than hybrid electric buses (HEBs). Given that, this article proposes a novel data-driven EMS based on DRL to enhance the training efficiency of the proposed EMS while improving the fuel economy of an FCHEB. In this article, to optimize the power allocation of the FCHEB, an improved twin delayed deep deterministic policy gradient (TD3) algorithm combined with prioritized experience replay is innovatively formulated, and then a promising EMS based on it is proposed. Furthermore, to enhance the adaptability and improve the training efficiency of the proposed EMS, a stochastic training environment is established with massive real-world velocity data, and a pre-training method using the global optimal experience is designed. Simulation results show that the proposed EMS improves fuel economy by 5.87% compared with the EMS based on original TD3, reaching 97.15% of the global optimal dynamic programming method.

Decision support algorithm for intermodal transport networks: Urban aerial cableway systems

We propose a decision support algorithm to solve the service policy of urban cableway systems, which are used as a transport mode to address the First-Last Mile problem for intermodal urban public transport networks. Our work develops a stochastic discrete-event model for computing the queuing performance of the public transport networks and evaluates the effects on the passenger waiting time over a commercial working day, considering different service policies: (i) previous policy; (ii) current policy; and (iii) proposed policy. We provide an embarking procedure for urban cableway lines to aid transport operators in managing queues on platforms during rush hours. Finally, a set of large-scale Monte-Carlo simulations was conducted using a real multimodal network of a large-size metropolitan city (3.8 million inhabitants) to evaluate the effectiveness of different service policies.

Beyond synergies: understanding SDG trade-offs, equity and implementation challenges of sectoral climate change mitigation options

Mitigation actions needed to achieve the ambitions of the Paris agreement to limit global temperature rise to 1.5 °C or below 2 °C have to align with sustainable development. In the near term, this implies a better understanding of context-specific challenges in integrating sustainability with climate policies during the designing, planning, implementation and financing stages. Through a review of selected studies across regions, this paper draws out conclusions focussing on mitigation–sustainable development goal (SDG) trade-offs, with implications on costs and equity for different development contexts. Studies show that trade-offs depend on how the option is implemented and at what scale; mitigation options such as afforestation, biomass production and digitalisation are examples of this. Some options could also result in significant adverse environmental impacts as in the case of battery waste and raw material resources for electric vehicle (EV) or air pollution associated with compact urban development. We find the most important factors influencing equity include unequal access (e.g. urban green spaces and public transportation), high costs (e.g. EV) and financial constraints. Major knowledge gaps include (i) limited empirical evidence of SDG-related trade-offs associated with scaling up mitigation options, (ii) limited understanding of the extent to which benefits are experienced by different groups, (iii) an understanding of the extent to which local context was considered when assessing mitigation–SDG interaction, including the engagement of stakeholders and (iv) synergies and trade-offs associated with cross-sectoral policies. The paper recommends ex-post analysis of detailed and place-based cases that document how synergies and trade-offs emerged and how these were addressed.

Smart Passenger Center: Real-Time Optimization of Urban Public Transport

This paper introduces the Smart Passenger Center (SPaCe), MerMec's solution for real-time optimization of urban public transport. The proposed system, based on cutting-edge artificial intelligence technologies, provides real-time vehicle status information and passenger activity monitoring. All of the information acquired from the vehicles is used to optimize the performance of the vehicle fleet for real-time traffic management.The purpose of the paper is to explain the reasons and benefits of such Intelligent Transport System (ITS) with a deep understanding of its architecture and advanced functionalities.Additionally, a practical application of the data collected by SPaCe is proposed for the task of bus timetable optimization.The goal is to schedule bus trips in a way that maximizes multiple conflicting goals such as service quality and operating costs, based on real time collected data.The reported results show how the developed optimization system can support the decision-making process to balance the interests between passengers and public transport agencies.

The Role of DRT in European Urban Public Transport Systems—A Comparison between Tampere, Braunschweig and Genoa

Demand-Responsive Transport (DRT) is one of the most valid solutions to tackle the problems affecting public transport today, both in urban and rural areas. Despite its undoubted advantages, it still remains underdeveloped compared to its great potential. The purpose of this paper is to understand the role that on-demand transport plays in the strategic choices of public transport authorities (PTAs): to this end, this study examined the DRT services of three geographically distant European cities, in order to test different social, cultural and regulatory backgrounds, examining their main characteristics. Tampere, Braunschweig and Genoa were selected for the purposes of this work; data and information were collected by viewing the official websites of public transport companies and by direct contact via mail/telephone with the managers responsible for on-call transport. The data collected were then analyzed based on specific Key Performance Indicators (KPIs) identified in academic literature. The results of this paper show that the role of on-call service in the strategic decisions of PTAs depends on the cultural context of reference; some cities focus more on urban services, others on rural transport. In all three case studies examined, on-demand transport is an important aspect of local mobility and with wide room for growth.

A consumer surplus, welfare and profit enhancing strategy for improving urban public transport networks

We show that a novel pricing system can help resolve a series of perennial problems evident in the deregulated British urban public transport market that have impeded urban growth, access equality and environmental ambitions. A two-stage pricing system, with operators setting their multi-operator service ticket prices collusively in one stage and their single-operator ticket prices independently in the other, offers potential consumer surplus, profit and welfare gains over, what we characterise as, the free-market ‘Status Quo’. The proposed win–win pricing system can also support a larger number of operators and services with potential additional welfare gains. We also compare the proposed system against a multi-operator ticketing card (MTC) scheme, permitted in the UK under the Block Exemption. The Block Exemption allows collusive pricing on a limited basis but is due to expire and is under statutory review, making this is a timely contribution. We show, whilst the MTC offers higher welfare when all regimes provide the same number of services, the proposed system can support a larger number of operators in the presence of fixed costs, which can reverse the welfare ranking in its favour. A calibration exercise indicates the market may be operating in the region where the proposed system can dominate the ‘Status Quo’ in profit, consumer surplus and welfare terms and support a larger network than the ‘Status Quo’ or MTC with further welfare gains. The resulting higher public transport patronage may also offer further indirect benefits via reduced pollution, congestion and accidents. Improved transport efficiency may have urban density advantages, especially in Britain’s second-tier cities which do not tend to benefit from extensive public transit rail and underground networks, with associated agglomeration effects contributing to the current levelling-up priority. Given the salience amongst developed countries of the private aspect of urban public transport in Britain, along with an unresolved private vs public debate, this issue is of potential interest to urban planners and policymakers beyond the UK.

GL-Net: Semantic segmentation for point clouds of shield tunnel via global feature learning and local feature discriminative aggregation

has gradually become the first choice of modern urban public transportation due to its advantages of safety and high-efficiency. Shield tunnel is an important type of subway tunnel, and its structural stability and safety play an important role in subway operation. The shield tunnels are prone to problems such as water leakage and tunnel collapse, which affect the safe operation of subways. Efficient monitoring methods are required to detect the status of subway tunnels. The data collection and accurate segmentation of key components of shield tunnels are the basis and key to the automatic monitoring of subway tunnels. This research presents a novel semantic segmentation method of three-dimensional (3-D) point clouds of typical structural elements (e.g., longitudinal joint, circumferential joints, bolt hole and grouting hole) in shield tunnel based on deep learning. In this method, we focus on how to make the network learn robust global features and complex local distribution patterns. Further, we propose a global and local feature encoding block (namely GL-block) to discriminatively aggregate local features while learning global representation. After multiple encodings by the GL-block, we design a global correlation modeling (GCM) module to establish a global awareness of each point. Finally, a weighted cross-entropy loss function is designed to solve the problem of unbalanced number of samples in each category of shield tunnel. In the experiments, we make a dataset of shield tunnel point clouds with a length of about 1,000 m collected by CNU-TS-1 (DU et al., 2018) mobile tunnel monitoring system, and use the dataset to train and test the segmentation ability of our method on the typical structural elements of shield tunnels. Experiments verify the effectiveness of our method by comparing with the other state-of-the-art 3-D point cloud semantic segmentation methods, and our method has an mIoU score of 73.02 %, which is at least 14.54 % higher than the other compared state-of-the-art networks. Also, we further verify the adaptability of our method to different tunnels and different laser scanning equipment, such as FARO, Leica and Z + F, and achieve very advanced performance.

Links between the Energy Intensity of Public Urban Transport, Regional Economic Growth and Urbanisation: The Case of Poland

The article concerns the verification of links between the energy intensity of public urban transport, regional economic development and urbanisation in the light of sustainable development challenges and club convergence processes. Three research questions were formulated in the article: (1) Does the regional economic development of voivodeships affect the energy intensity of public urban transport? (2) Does urbanisation shape energy consumption patterns in public urban transport (and are there agglomeration effects)? (3) Does the level of urbanisation of voivodeships depend on their regional level? The study covered 16 subregions of Poland from 2010 to 2020. A spatial dynamic exploration of the relationships between energy intensity patterns of public urban transport and the phenomenon of urbanisation and regional economic development was carried out. Panel models of vector autoregression and panel causality testing were used. The influence of the economic development of regions and the level of urbanisation on energy intensity patterns of public urban transport was confirmed. The link between economic development and the process of urbanisation was identified. An additional effect was noticed (novelty knowledge), i.e., there is a delayed club convergence between voivodeships in the area of energy intensity of public urban transport, regional economic development and urbanisation (polyconvergence).

Citizens’ perception analysis of public transport and smart technologies in the Brazilian capitals during the SARS-CoV-2 pandemic

Amidst the consequences of the SARS-CoV-2 pandemic, the overall trip decrease and public transport modal share contraction pose a critical dilemma towards urban mobility. Through a questionnaire in Brazilian capitals, the present article considered (1) the citizens’ safety perception of urban mobility and public transport before and during the pandemic, (2) an estimated perception of the post-pandemic, (3) perception of safety regarding both traditional and smart measures, and (4) the concern about data use and privacy. Findings indicated an increase in private cars (41%) and ride-sourcing services (442%) use and a decrease in public transport modes during the pandemic, with an expectation of a post-pandemic modal split following the same pattern. According to respondents, most measures implemented resumes to traditional individual ones, without a systemic approach or smart initiatives. About the latter, a contrasting result was obtained, where there is a high safety perception if implemented with a low security perception over data use and privacy. In this sense, operators, public authorities, city planners and users must observe systemic sanitary measures, regulatory laws and transparency over data use and privacy, democratic and inclusive decision-making processes to address urban vulnerabilities and ensure safe public transport during and after the pandemic.

Access to Inclusive Urban Public Transport System in Bangladesh: The Case of Dhaka City

This article examines the state of people’s access to the inclusive urban transport system in Dhaka and suggests strategies for improving access to the transport system. By adopting an exploratory approach, both quantitative and qualitative tools of data collection were employed to gather primary data through questionnaires and key informant interviews (KIIs). The findings reveal the lack of passengers’ trust and satisfaction in terms of the availability, accessibility, accommodation, acceptability and affordability of public buses for the vulnerable groups in Dhaka city. To make the transport system accessible and inclusive, suitable vehicles need to be introduced with additional resource commitments along with sensitive training and public awareness to respect and support vulnerable groups to access transport systems with ease in Dhaka and similar cities.

Boosting a Regular Bicycle into a Low-cost E-bike for Public Urban Transportation

Boosting a Regular Bicycle into a Low-cost E-bike for Public Urban Transportation

Satisfaction of Istanbul Citizens with Urban Public Transportation

Transportation is one of the most challenging urban subsystems to transform in an environmentally friendly and futuristic way. Many city dwellers use a variety of modes of transportation. An efficient and sustainable urban transportation system must include many modes of transportation for a single trip. Intermodal combinations are essential for urban transportation efficiency. Public transportation and commuting are essential elements of multimodal travel. In urban areas, a mix of bicycles, vehicles, and public transportation is prevalent, while in rural areas, car, and public transportation are more prevalent. By examining the characteristics that lead customers to prefer water transportation over Metrobus and Marmaray, we hope to gain a better understanding of how the Asian and European sides of Istanbul are traversed. The number of participants in the "Maritime Transportation Satisfaction Survey" was 2,343. During this period, a model was built using the survey item "frequency of use" (dependent variable). Numerous survey examines and evaluation methodologies were utilized to determine the effectiveness of this strategy. The study examines the intermodal travel motivations and the evaluation of transportation options by multimodal users. For a successful urban transportation system, urban planning must take into account multimodal travel behavior and user expectations. There are initiatives to improve water transportation in Istanbul. Conventional maritime transportation is inadequate from start to finish. An integrated route optimization method is needed to increase the efficiency of maritime transportation. We believe that by strengthening maritime transportation links will increase water consumption. Before the coronavirus pandemic, 2,343 maritime carriers were evaluated on March 8, 2020. (Different surveys were conducted among the passengers of City Lines, Private Motors, Metrobus, and Marmaray to compare their choices and reasons.) SPSS will be used for data analysis. Multivariate Statistical Analysis relies on Multinomial Logistic Regression and Discriminant Analysis models, both of which use the K-fold and Leave-one-out criteria to decide which attributes are valid in the regression model and which are valid in the discriminant approach. The Hosmer-Lemeshow test criteria yielded a p-value greater than 0.05 for MLR characteristics.

Optimization of Urban Public Transportation Considering the Modal Fleet Size: A Case Study from Palestine

We introduce a simple yet efficient approach to optimize the modal fleet size of urban public transportation services, considering both user- and operator-oriented factors. This is envisaged to enhance the potential for achieving sustainable urban transportation systems and, eventually, opportunities to create sustainable cities. The presented constraint optimization approach can be described as follows. First, the expected passenger demand and the cycle time for the public transportation service are estimated. Next, the desired constraints and parameters, such as those related to the headway and seat supply, are determined. Finally, the optimal combination of different vehicle classes and the number of trips satisfying all the defined constraints are determined. The case of an urban area in a developing country is considered. The resulting solution determines the optimal numbers of public transportation trips and vehicles, by mode, required to meet the expected passenger demand, provide a high-quality service with acceptable headways for passengers, and, at the same time, reduce the service providers’ costs as well as the environmental impacts. It is also concluded that a fleet composed of different modes can better facilitate the achievement of the optimal solution for passengers and service providers compared with the one-mode fleet.

Women's access to urban public transport: Toward addressing policy constraints in combating sexual harassment

Women's physical harassment in public transport (PT) and public spaces is a pervasive and pressing issue across the globe. In developing countries, women's easy access to public transport and harassment-free travel in urban areas have been hindered by a combination of factors. These include gender stereotype behavior, sociocultural stigma, poor transport settings, and a male-dominated transport sector. As a result, women often face numerous acrimonious experiences in their everyday mobility. In light of these issues, this study seeks to analyze existing literature to gain a deeper understanding of how gender roles and women's positions in society shape travel behavior, as well as explore how gender-responsive policy interventions can effectively ensure an inclusive urban transport system for female commuters in developing countries. Through qualitative narrative analysis of previous research, the study aims to frame a conceptual relationship framework, which focuses on identifying micro to macro-level constraints and emphasizes the importance of gender-responsive policy interventions. The study expects that this framework will provide insight into how gender-responsive transport policies and women's participation in the transport sector can address constraints in transit environments. Furthermore, this study will assist in initiating measures to correct the gender-blind approach and provide a solid basis for policy advice in the arena of public transport and gender.

Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro

The collaborative development of conventional buses and urban metro has become an important research topic for the priority development of urban public transport. The topic of collaborative optimization of feeder bus route design and operation is studied in this study. The objective function is to minimize the total travel time of passengers and the operation cost of feeder buses. The improved particle swarm optimization (PSO) algorithm is used to solve the collaborative optimization model, and the effectiveness of the model and algorithm is verified through the case study. The research shows that it is feasible in model construction and algorithm to carry out collaborative optimization of feeder bus route design and operation. Compared with the multiple-to-one (M to 1) mode, the multiple-to-multiple (M to M) mode can better satisfy the needs of passengers from different places of departure and destinations to achieve a more reasonable and realistic goal. The case study is based on two metro stations and 16 feeder bus stops on Fuzhou Metro line 2 to obtain two bus routes and a corresponding operation scheme. Under the same topology road network, the operation time of the improved PSO algorithm is much shorter than the DFS algorithm, the total cost error of the feeder bus is 0.04%, and the departure frequency error is 4.6%, which is within the reasonable error range. Therefore, the collaborative optimization model proposed in this study is feasible and effective in optimizing the feeder bus routes and operation.

Modern Collective Transport. The Impact of Public Policy on the Implementation of the EU Legislative Objectives on the Example of Poland

Urban policy is driven by current trends and ideas. In the 20th century, it was mainly based on modernist views and the most important element of the transport planning policy at that time was the use of the private motor vehicle (car). As a result, transport policies in the 20th century were focused on large-scale road projects, while public transport was marginalized. However, this approach changed drastically at the turn of the 20th and the 21st centuries. Nowadays, the main emphasis is put on environmentally and user-friendly public transport. However, public urban transport often fails to meet the needs of the society. What are the reasons why urban public transport is still not as effective as it should be? The author of this article points in this respect to the poor policy of public bodies responsible for the provision of transport services for the society rather than to the poor quality of the transport law. There are two main areas for improvement - public service planning (defining the service) and cost-effectiveness of providing transport services. The author of the article proposes specific solutions in this regard.

SUMMIT: A multi-modal agent-based co-simulation of urban public transport with applications in contingency planning

In this article, we present SUMMIT (Singapore Urban Multi-Modal Integrated Transport Simulator), a multi-modal agent-based simulation platform for public transport calibrated using real world mobility data sets from Singapore. SUMMIT uses a co-simulation approach in order to model multiple modes of public transport in tandem with commuters seamlessly transitioning between different mode simulations. This is implemented through a message passing framework codenamed Fabric (Fast, Agent-Based, Reproducible, Integrated Co-simulation) which helps to align and synchronise the simulation as it transitions through the different simulation time steps. Three stand-alone simulators, each modelling a key mode in the Singapore public transport system, namely train, bus and taxi, are integrated with a commuter control model, which simulates the commuter behaviour and takes care of commuters’ transfer between different modes. We present one application of SUMMIT in public transport contingency planning, where train services are disrupted in multiple lines of Singapore Mass Rapid Transit (MRT) network. Different scenarios are simulated and key performance indicators are compared to help planners evaluate the efficacy of mitigation measures. The results show that bridging bus services, a commonly used mitigation measure, are effective in reducing crowd sizes within the train stations. However, we demonstrate that bridging buses could also result in worsening of commuters’ travel time due to over-demand for these buses. Our results also show early dissemination of information to commuters during a train service disruption could reduce the negative impacts of the disruption event significantly.

Advanced rail transportation infrastructure as the basis of improved urban mobility: research into Sydney as a smart city

ABSTRACT This research evaluates the advanced rail transportation infrastructure as the foundation of sustainable urban mobility. Sydney's rail transportation was evaluated as a smart city. To undertake this evaluation, twelve of Sydney’s inner municipalities were selected within Sydney's urban area – a 35 km radial distance from the CBD. To further examine Sydney's rail transportation evaluation, CITYKeys, being the smart city framework, was utilised. CITYKeys was carefully evaluated and two of its domains, transportation indicators and improved urban mobility & public transport were thus adopted. This research has two key findings. Firstly, Sydney, as a possible smart city, possesses three primary smart transport procedures: Green practice, Transformation and Model Integration. Subsequently, Sydney's new advanced rail transportation infrastructure aligns with CITYKeys public transport indicators. Secondly, Sydney Metro not only provided a significant technological advantage for the city's suburbs but also enhanced its urban mobility. This study contributes to the field of sustainable urban mobility by advocating the alignment between advanced and innovative rail transportation infrastructure and smart cities. Such findings will support transportation scholars in acquiring a better understanding of the need for advanced rail transportation infrastructure for smart cities.