Transit Network Research Articles

Origin–destination matrices from smartphone apps for bus networks

The knowledge of passenger flows between each origin–destination (OD) pair is a main requirement in public transport for service planning, design, operation, and monitoring, and is represented by OD matrices. Although they can be determined by traditional approaches (e.g., surveys, ride-check counts, and/or smartcard-based methods), the availability of new technologies and the proliferation of portable devices triggers an emerging interest in building OD matrices from the apps of bus operators. This research proposes the first framework for the estimation of OD matrices on transit networks by processing smartphone app call detail records (SACDRs). The framework is experimentally tested on a sample of 30 workdays of an Italian bus operator. The results are represented by easy-to-read control dashboards based on maps, which help quantify and visualise the OD matrices in the metropolitan area of Cagliari (Italy). The experimentation shows that the framework can properly estimate the number of trips for both origin and destination w.r.t. OD matrices built from household surveys: the mean absolute error is on average lower than five movements for 90% of the origins and 85% of the destinations.

Cluster-based Bayesian approach for noisy and sparse data: application to flow-state estimation

This study presents a cluster-based Bayesian methodology for state estimation under realistic conditions including noisy data from sparse sensors. The proposed approach is interpretable and, building upon previous work on transition networks, explicitly accounts for experimental noise within the data-driven framework by means of data clustering. Experimental measurements are exploited, beyond model training, to quantify the degree of uncertainty (noise) for each trained state. Such noise levels are eventually associated with probability distributions that, when combined with Bayes’ theorem, allow us to perform real-time state estimation. The proposed methodology is tested on two cases of challenging flows generated by an accelerating elliptical plate and also a delta wing experiencing gusts. Results specifically indicate that the proposed approach is robust against the number of clusters, enabling state estimation with a significant order reduction, notably decreasing the computational cost while preserving estimation accuracy. Based on the present findings, the proposed data-driven approach can be employed for realistic state estimation in nonlinear systems where noise, sensor sparsity and nonlinearities represent a challenging scenario.

Identifying Station Importance in Urban Rail Transit Networks Using a Combination of Centrality and Time Reliability Measures: A Case Study in Beijing, China

Time reliability (TR) is a critical factor that affects the efficiency and service quality of the urban rail transit network (URTN). However, previous studies have not incorporated TR into the evaluation of URTN station importance, focusing instead on basic centrality measures. Therefore, this paper proposes a new metric of station-based TR for evaluating and ranking URTN station importance. The new metric in combination with traditional centrality measures was used by the weighted Technique for Order of Preference by Similarity to Ideal Solution (weighted TOPSIS) to identify the combined significance level of individual URTN station importance and rank them accordingly. To investigate the performance of this method, we exploit deliberate attacks on the top-ranked stations through different methods. A case study of Beijing’s URTN during the morning peak hour showed that the proposed method is generally a better indicator for identifying station importance in maintaining network connectivity. The case study also demonstrated the feasibility and validity of the model. This study can provide recommendations for the planning and operation of rail transit systems and can inform the effective design of station protection strategies.

Optimizing Transit Network Departure Frequency considering Congestion Effects

This paper introduces a bilevel programming model for optimizing transit network departure frequency. In the upper-level model, user satisfaction is reflected by considering congestion effects in the cost function. The lower-level assignment model simulates passenger travel behavior more realistically by incorporating congestion effects. This problem is solved by a heuristic gradient descent algorithm, where an approximation of the gradient is obtained at each iteration by using sensitivity analysis for transit equilibrium problems. The effectiveness of the proposed model and algorithm is demonstrated through two test examples, one of which involves a real-world scenario comprising over 130 transit lines. Numerical results conclusively indicate that the incorporation of congestion effects in the proposed model leads to improved transit system performance and enhanced user satisfaction.

Analysis of the Mechanical Behavior and Joint Shear Capacity Optimization of Glued Keys in Segmental U-Shaped Bridges

This paper presents an in-depth analysis of the mechanical behavior and joint shear capacity optimization of segmental U-shaped bridges, with a focus on the application of precast segmental techniques in the construction of U-beam bridges widely used in urban rail transit networks. This study further explores the roles of key position distribution and size in the overall stability and service behavior of such structures. Considering the critical case study of the Colombia Bogotá Metro Line 1 project, finite element modeling was carried out using ABAQUS 6.14 to simulate concrete material behaviors and to evaluate the stress–strain relationship in accordance with the concrete plastic damage model and existing standards. This research identifies the significant contribution of keys in minimizing deformation and enhancing shear capacity, demonstrating the pivotal influence of shear key design on the mechanical behavior of segmental bridges. By calculating the shear capacity under different cases, this study provides recommendations on key distributions and dimensions that optimize joint shear capacities, indicating that augmenting key size within the web plate section decisively reinforces the bridge’s mechanical resilience.

Drive-by Environmental Sensing Strategy to Reach Optimal and Continuous Spatio-Temporal Coverage Using Local Transit Network

Monitoring environmental features, such as air pollution, carbon dioxide emissions, noise, and heat, gives cities key data-driven insights to advise sustainable policies and city design. However, given the high variability of the environmental data, achieving good spatio-temporal resolution and coverage remains a major challenge. Even in well-monitored cities, such as Amsterdam, environmental sensors are usually placed in very few fixed locations, implying limited spatial coverage and an inability to adapt to changes in the urban environment. As cities evolve, they experience shifts in pollution sources, and fixed sensors might not adequately capture these changes without a costly and time-consuming reconfiguration process. To monitor the environmental qualities of Amsterdam’s roads, we present a “drive-by” sensing solution for a structured network of vehicles, meaning that sensors are designed to be deployed on buses and tramways, the trajectories and schedules of which are known. We propose a deployment strategy that combines the available fleets to reach optimal spatio-temporal coverage for different environmental features. For example, by optimizing the deployment of sensors on public transit vehicles, our proposal significantly enhances the monitoring of pollution-sensitive areas in Amsterdam. Depending on the desired spatio-temporal granularity and noting that one vehicle only hosts one sensor, the required number of sensors to be deployed on the structured network varies between 43 and 142, with the latter achieving the finest possible resolution.

Inequality and spatial mismatch in the urban labor market: Evidence for the Curitiba metropolitan region, Brazil

Accessibility plays a fundamental role in improving urban economic equity, especially for disadvantaged communities. In many metropolitan areas of Brazil, accessibility relies on infrastructure unequally distributed, creating barriers to access opportunities in the urban labor market. This paper aims to identify sources of spatial mismatch and measure its effects on the labor market of the Curitiba Metropolitan Region (CMR), in Brazil. First, we measured the spatial imbalances of households and jobs by income classes and their effects on the spatial dissimilarity of accessibility to job opportunities. Second, we use econometric tools to evaluate how accessibility to the formal job sector affects individual earnings in the CMR labor market by wage quartile. We find evidence of strong spatial segregation for the poorest individuals from public transit network and from the formal job sector. The econometric results show there was roughly no accessibility premium for individual earnings for the poorest workers and positive effects for the richest workers in the CMR labor market. This set of empirical evidence suggest a spatial concentration of urban amenities that enhance economic inequality for the CMR.

Resilience-based post-disaster repair strategy for integrated public transit networks

The resilience of public transit systems has become a critical issue due to their essential role in urban mobility. However, the challenges of repair selection and sequencing in integrated public transportation networks (IPTN) have not been fully explored. Therefore, we propose a bi-level resilience-based repair strategy optimisation (RRSO) model to investigate the optimisation of resilience in IPTN. To consider trip selection and account for cascade failure processes, a lower-level traffic assignment model was integrated into a single-layer RRSO model. In the traffic assignment model, perceived travel time reflects the traffic impedance of public transportation. Additionally, to assess the performance of the RRSO model under emergency repair conditions, random variables were introduced to represent uncertain factors in the traffic environment. Finally, the results demonstrate that the RRSO model outperforms standard empirical repair strategies. This study provides theoretical insights into the management of urban public transportation.

Competing or complimentary: Modeling transit ridership at route-level considering inter-route interdependencies

Transit routes in a network are often interdependent. Two or more transit routes complement or compete based on their spatial and temporal overlaps. Two routes complement each other if riders get to transfer from one route to another at a station. Two routes compete if they serve a common geographic stretch, giving the riders an option of choosing either one of them for their travel. When a new route is introduced by the transit agency, ridership on the existing routes changes too. Thus, it is important to assess inter-route relationships and their effect on transit ridership at route-level for better predictions. This research develops a route-level transit ridership model that is capable of capturing the effect of inter-route relationships in a transit network in addition to commonly used explanatory variables. Route-level ridership data were collected from the transit agency of the city of Gainesville, Florida (USA). For the city of Gainesville, model results showed that routes that share up to nine transit stops in a stretch have complementary relationship. However, when the number of common stops increases to 10 or more, routes start to compete. With every 10% increase in the supply of the routes that share ten or more transit stops with the subject route, logarithm of the monthly ridership on the subject route decreases by 0.96%.

Systematic review and research gaps on wildfire evacuations: infrastructure, transportation modes, networks, and planning

ABSTRACT Wildfires pose significant threats to communities, requiring robust pre-event planning for efficient evacuations. Transportation systems are crucial for these efforts, yet global research gaps persist, especially those related to transportation assets and transportation modes beyond privately owned automobiles. This study conducts a systematic review of four under-researched areas – infrastructure, modality, networks, and planning – to build a more comprehensive understanding of wildfire evacuations. Initial research is emerging in these domains, related to post-fire debris flows, air and transit evacuations, network analysis, and shelter planning. However, systematic analyses, evidence, and recommendations remain lacking. This includes wildfire's direct impact on transportation infrastructure, multi-modal evacuations, routing strategies, and community-driven evacuation plans. We underscore the need for empirical evacuation strategies to foster resilience for wildfire-threatened communities, offering valuable context-specific insights, identifying key actions, and highlighting ongoing research gaps.

Integrated charging scheduling and operational control for an electric bus network

The last few years have seen the massive deployment of electric buses in many existing transit networks. However, the planning and operation of an electric bus system differ from that of a bus system with conventional vehicles, and some key problems have not yet been studied in the literature. In this work, we address the integrated operational control and charging scheduling problem for a network of electric buses with a limited opportunity charging capacity. Operational control is carried out through speed control of the vehicles and bus holding at the terminal. We propose a hierarchical control framework to solve this integrated problem, where the charging and operational decisions are taken jointly by solving a mixed-integer linear program in the high-level control layer. Since this optimization problem might become very large as more bus lines are considered, we propose to apply Lagrangian relaxation in such a way as to exploit the structure of the problem and enable a decomposition into independent subproblems. A local search heuristic is then deployed in order to generate good feasible solutions to the original problem. This entire Lagrangian heuristic procedure is shown to scale much better on transit networks with an increasing number of bus lines than trying to solve the original problem with an off-the-shelf solver. The proposed procedure is then tested in the high-fidelity microscopic traffic environment Vissim on a bus network constructed from an openly available dataset of the city of Chicago. The results show the benefits of combining the charging scheduling decisions with the real-time operational control of the vehicles as the proposed control framework manages to achieve both a better level of service and lower charging costs over control baselines with predetermined charging schedules.

Review of Optimized Feeder Vehicle Systems in Developing Countries

With the population growth and changes in travel patterns, transportation demand in urban cities continue to increase rapidly. Since it is a cause for higher traffic densities, poor parking facilities, air pollution and road accidents, transport planners have to provide a system, which can ensure safe and comfortable mobility to all users as well as suppliers’ perspectives. Therefore, developing an affordable and efficient public transportation network is a critical goal for developing countries seeking to address urban mobility challenges. Feeder vehicle systems, which provide the first and last mile connectivity to the passengers, offers an opportunity for creating a system capable of meeting multiple needs of users and operators. It is an effective public transportation system that already operates in developed countries. It offers immense potential for improving accessibility and reducing congestion. However, the implementation of effective feeder system in developing countries is fraught with challenges due to uncoordinated transit networks, infrastructure limitations, and budget constraints. This paper presents a critical review of recent planning methodologies and selected decision support systems for optimizing feeder transport services.

Transporte orientado ao desenvolvimento urbano

Abstract Transportation networks play a vital role in the development of cities and access to opportunities. Transportation planning, however, has yet to recognize its role in promoting inequalities. This work aims to discuss the concepts of centralization and accessibility and present a paradigm for planning transit networks based on the understanding that transit demand contains an endogenous component: by increasing accessibility, transit systems encourage part of the demand they seek to meet, leading to a circular causation cycle. It is proposed, then, that the planning of transit networks should be strongly associated with the discipline of urban planning, considering the existing demand and the design of the city that one wants to build.

Metro Train Stopping Scheme Decision Based on Multisource Data in Express-Local Train Mode

Metro Train Stopping Scheme Decision Based on Multisource Data in Express-Local Train Mode

Stochastic fast charging scheduling of battery electric buses with energy storage systems design

Under the background of urban green and low-carbon economic development, battery electric buses (BEBs) together with fast charging technologies are considered as an effective way in promoting carbon emissions reduction and improving energy efficiency. However, challenges arise during daily peak periods, at which BEB charging activities cause increased operation costs and substantial stress on the power grid. To fill the gaps, this work introduces energy storage systems (ESSs) into the BEB fast-charging scheduling problem. A stochastic programming model considering uncertain discharge efficiencies of ESSs is established, aiming to minimize total operation costs of fast charging stations. It is then transformed into a deterministic one with a manageable scenario sample size, using an integrated sample average approximation (SAA) and K-means approach, as well as an integrated SAA and K-means++ approach. We also present a heuristic algorithm and an improved genetic algorithm to solve the transformed model. Numerical studies based on a real-life urban transit network in Shanghai, China, are conducted to demonstrate the effectiveness of the proposed methods. Sensitivity analysis further reveals the impact of charging power on total operation cost.

Transforming Urban Environments: Understanding the Social Implications of Metrobus (MBS) Service Development in Lahore, Pakistan

This research investigates how the Lahore Metrobus system (MBS) influences perceptions of urban space quality through the lens of urban design and transport infrastructure. Lahore is undergoing significant urban changes with the introduction of a newly constructed mass transit system, which thus necessitates a joint development strategy to preserve its cultural heritage. Recent evolutions in transport planning has heightened the interest in analyzing the way mobility factors affect the perceptions of a place’s quality. The gap in previous work lies in the limited focus on qualitative, human-centered perspectives regarding the impacts of public projects like the MBS on urban space quality. This study uniquely fills this void by examining the influence of the MBS on people’s lives and the quality of urban spaces. Comparing pre- and post-Metrobus scenarios, along with questionnaire surveys of riders and shopkeepers, exposes the neglect of the social image during design and construction. The system was implemented with a focus solely on hard, core infrastructure, thereby neglecting soft components such as area development, social and cultural value, and human-centered design. The government should unite transport agencies, stakeholders, and the public to craft a joint policy for enhancing revenue, ridership, and fostering transit-oriented development (TOD). Research findings will help in achieving social and cultural sustainability for upcoming transport lines in Pakistan, as well as directions for other developing nations looking to implement mass transit networks.

A multi-stage optimization of battery electric bus transit with battery degradation

Battery electric buses (BEBs) are appealing to transit operators for their elevated comfort, low noise, and zero tailpipe emissions. However, the degradation of BEB batteries over time challenges their performance and necessitates infrastructure adjustments. This study develops a generic multi-stage optimization model for BEB systems. The model addresses the dynamic influence of BEB battery degradation rates on the optimal BEB system configuration and operation, including component sizing, charging infrastructure allocation, BEB charging schedule, and battery replacement throughout the BEB usage lifecycle. A surrogate model-based space mapping (SMSM) algorithm is employed to address the inherent nonlinearity of incorporating battery degradation rates within the developed model. The model is tested on a real-world, multi-hub transit network, and the results highlight significant implications of battery degradation on the optimal spatiotemporal allocation of charging infrastructure, charging schedules, and battery replacement decisions throughout the 12-year BEB usage lifecycle. Sensitivity analysis highlights the influence of operational conditions on total system cost, indicating a 16.3 % increase in cost with a 50 % rise in both energy consumption rates and time-of-use (ToU) tariffs. Overall, the proposed model is a valuable decision-making tool for transit operators navigating BEB transit system planning.

Rail Transit Networks and Network Motifs: A Review and Research Agenda

The railway plays an essential role in urban and intercity transport of goods and people. Intercity and urban rail transit infrastructures contribute to the economic and environmental sustainability of global economies. Those infrastructures can be modeled as complex networks, so that we can evaluate system properties of the network structure. This stream of research has focused on the topological analysis of global network structure, but little research exists that examines how local network structures affect system properties. The local structure of complex networks can be examined with network motif analysis, as those network motifs are the building blocks of networked systems. Nevertheless, there has been scarce attention given to local network properties in rail transit networks. We contribute to covering this gap in the literature with a literature review of motif analysis research and its application to weighted and unweighted rail transit networks, also covering the current state-of-the-art of network motif decomposition and analysis. We demonstrate that network motif analysis is not only applicable, but also beneficial for the design and planning of rail transit networks, enhancing their sustainability by improving efficiency, reducing environmental impact, and optimizing resource allocation. Based on our findings, we propose future research directions that involve applying motif analysis to enhance the sustainability features of both unweighted and weighted rail transit networks.

Integration of Shared Micromobility into Public Transit: A Systematic Literature Review with Grey Literature

Shared micromobility services have become increasingly prevalent and indispensable as a means of transportation across diverse geographical regions. Integrating shared micromobility with public transit offers opportunities to complement fixed-route transit networks and address first- and last-mile issues. To explore this topic, a systematic literature review was conducted to consolidate knowledge, analyze research achievements and best practices, and provide future research recommendations. This study examined 108 journal papers from the Web of Science (WoS) core collection from 2016 to 2022, along with grey literature. Citation and co-citation analyses were performed to build and illustrate the literature’s bibliometric networks. This analysis categorized the literature into four major study themes: policy, sustainability, the interaction between shared micromobility and public transportation, and infrastructure. The implementation approaches of integrating shared micromobility and public transportation in different cities were classified into four categories: physical integration, payment and fee integration, informational integration, and institutional integration. The findings indicate that the relationship between shared micromobility and public transportation varies with spatial–temporal conditions and the population density of the city. Overall, integrating micromobility into public transit can offer faster and more cost-effective mobility options for most trips, contributing to urban resilience, a better air quality, lower greenhouse gas emissions, and livable communities. Based on these insights, further research is recommended to explore dynamic and context-specific strategies for successful shared micromobility and public transit integration, considering diverse urban settings and demographic factors.

TRAFFIC PULSE-ROADWAY CONTROL SYSTEM

Rapid transit and transportation networks are essential to any country's economic progress. Long wait times, lost fuel, and financial losses are the outcomes of poor management and traffic congestion. For the sake of national development, a quick, affordable, and effective traffic control system is thus absolutely essential. In many nations, keeping an eye on and managing urban traffic is turning into a significant issue. The Traffic Monitoring Authority needs to come up with innovative ways to solve this issue because there are more and more cars on the road. Using automation and intelligent control techniques is one option to enhance the current transportation system's traffic flow and safety. Efficient and quick congestion relief is the aim. The project includes sound sensors that can recognize emergency cars as they approach in order to improve emergency vehicle detection. By prioritizing and streamlining emergency vehicle traffic at signalized junctions, this cutting-edge feature seeks to enhance overall traffic management and response times. Additionally, the concept has a novel element for pedestrian safety: when a signal changes from red to orange or orange to green, a dynamically triggered block is deployed. By erecting a barrier that guarantees pedestrians are securely clear of traffic before crossing, this creative solution seeks to improve pedestrian safety. Keywords: Traffic jams, traffic surveillance, automation, and clever control techniques, Changes in signals, sound sensors, emergency vehicle detection, quicker reaction times, barriers, and pedestrian safety.