Transit Agencies Research Articles

How effective are fixed-effects models in fixing the transit supply–demand bidirectional interaction?

ABSTRACT Transit agencies use direct demand models (DDM) to allocate services. Since the service supply – a crucial predictor in DDMs – is endogenous to demand, including it in the model might yield biased estimations. A widely used methodology that is believed to handle this issue is Fixed Effects (FE). However, the underlying assumptions of FE are valid only if service adjustments take a considerable amount of time. This study investigates the performance of FE for estimating transit ridership. We collected 2013–2019 data and constructed 16 DDMs, employing four methodologies with a shared set of variables. We found that FE has significant limitations in handling endogeneity and will result in parameter estimates that significantly differ from those produced by methodologies that are specifically designed to control for endogeneity (such as FE-IV). Moreover, the use of FE leads to the omission of certain predictors and inaccurate ridership predictions, misguiding agencies as to what changes to implement and potentially impacting revenue projections.

Real-Time Tracking System for City Bus Location And Passenger Count

This survey paper reviews the advancements in real-time tracking and passenger counting systems for city buses, emphasizing the growing need for efficient, data-driven public transit solutions. As urban populations rise, city transport systems face challenges in managing demand, reducing congestion, and improving service reliability. Real-time tracking systems using GPS, GIS, and IoT-enabled sensors enable passengers and transit authorities to monitor bus locations and optimize travel times. Additionally, passenger counting systems—utilizing infrared, AI-based vision models, and pressure sensors—provide data on bus occupancy levels, allowing commuters to make informed travel decisions and helping transit agencies manage resources efficiently. This paper examines existing technologies, compares various tracking and counting methods based on accuracy, cost, and scalability, and explores recent trends in artificial intelligence, big data analytics, and smart city integration. Furthermore, it identifies critical challenges, including data privacy, accuracy in urban environments, and energy consumption, proposing future research directions for enhancing the reliability, sustainability, and user-friendliness of these systems. Our findings underscore the transformative potential of real-time bus tracking and passenger counting in advancing public transportation infrastructure and enhancing urban mobility

Information Technology Systems as both Contributor to Risk Perception and Adaptive Behavior: Public Transit Agency’s Response to Extreme Weather Events

This paper aims to better understand how information strategies matter for the management of extreme weather events in public transit agencies. It examines how past extreme weather events and the availability of information on extreme weather impacts influence risk-related cognitions, which influence planning for future extreme events and eventually lead to investment in Information Technology (IT) systems as a protective measure The theoretical framework integrates prior work on perceived risk, protection motivation theory (PMT), and theory of planned behavior (TPB) to develop hypotheses, which are tested using structural equation modeling with data from national surveys of transit agencies conducted at two points in time, 2019 and 2023, merged with other institutional data. The paper demonstrates how access to critical information about the impacts of past extreme weather events on threat and coping appraisal, planning, and future investment in information technology systems. Findings show support that organization experience with extreme weather, risk perception and capacity are associated with more extensive planning for extreme weather in 2019, and that greater emphasis on planning leads to more investment in IT systems in 2023. The paper contributes to the broader discourse on the role of information and planning in strengthening organizational preparedness and adaptive capacity in the face of increasing climate challenges.

Decision support tools for effective bus fleet electrification: Replacement factors and fleet size prediction

The electrification of public transit systems represents a crucial strategy for advancing sustainable urban mobility. Thus, the development of efficient charging infrastructure and the optimization of fleet size emerge as major challenges for transit agencies. Switching from diesel buses to electric buses (Ebuses) will require increasing the fleet size to accommodate the limited range of Ebuses and the significant idle time required for charging. This study develops prediction models to estimate the required Ebus fleet size to maintain same transit route services for the case of overnight depot charging, using data from Ebuses operating in the City of Toronto. The analysis reveals that Ebuses equipped with diesel auxiliary heaters are less sensitive to temperature fluctuations compared to battery-heated buses. Thus, the required replacement factor, indicating the additional fleet needed to switch from diesel to Ebuses, varies depending on the heating system. Specifically, diesel-heated buses require a lower replacement factor (1.3) compared to battery-heated buses (1.4), with winter conditions exacerbating this disparity. Furthermore, the study employs vehicular, operational, route, and external variables to develop the prediction models. Additionally, SHAP analysis is utilized to interpret the machine learning models and evaluate the influence of the inputs on the required fleet size. The results show that the total distance traveled, and the average temperature are the primary factors affecting the fleet size for Ebuses using their batteries for heating, whereas the total distance traveled, and the average bus speed are the primary factors affecting the fleet size for Ebuses with diesel auxiliary heaters.

UBER IN EXURBIA: Peripheral Platformization, Post‐Suburbanization and the Public–Private Ridehail Partnership in the Toronto City Region

AbstractAfter their widespread legalization, ridehailing companies Uber and Lyft soon embarked on a new stage of their respective business models: the initiation of a wave of strategic partnerships with local and regional transit agencies across the North American continent. This article accounts for this trend by putting forward the concept of the public–private ridehail partnership (PPRP). It aims to render visible the PPRP as a variously contradictory attempt to splice Uber and Lyft's platform‐based business models with the existing social and physical realities of North American post‐suburban space. While conceived as a strategic response to pressing sub‐ and exurban problems such as low physical densities, widespread car centrism and extensive transit undersupply, the PPRP, as I argue, is neither able to adequately address these dilemmas nor to ultimately resolve them. Rather, the PPRP latches onto old—and sets in motion new—powerful dynamics of heightened uneven development and continued urban entrepreneurialism. Each of these two dynamics is explored through empirical analyses of two recent PPRPs in the Toronto city region: the Lyft–Metrolinx pilot carried out between July and December 2019; and Uber's ongoing partnership with the town of Innisfil, located about 80 km north of downtown Toronto.

Plan Your System and Price for Free: Fast Algorithms for Multimodal Transit Operations

We study the problem of jointly pricing and designing a smart transit system, where a transit agency (the platform) controls a fleet of demand-responsive vehicles (cars) and a fixed line service (buses). The platform offers commuters a menu of options (modes) to travel between origin and destination (e.g., direct car trip, a bus ride, or a combination of the two), and commuters make a utility-maximizing choice within this menu, given the price of each mode. The goal of the platform is to determine an optimal set of modes to display to commuters, prices for these modes, and the design of the transit network in order to maximize the social welfare of the system. In this work, we tackle the commuter choice aspect of this problem, traditionally approached via computationally intensive bilevel programming techniques. In particular, we develop a framework that efficiently decouples the pricing and network design problem: Given an efficient (approximation) algorithm for centralized network design without prices, there exists an efficient (approximation) algorithm for decentralized network design with prices and commuter choice. We demonstrate the practicality of our framework via extensive numerical experiments on a real-world data set. We moreover explore the dependence of metrics such as welfare, revenue, and mode usage on (i) transfer costs and (ii) cost of contracting with on-demand service providers and exhibit the welfare gains of a fully integrated mobility system. Funding: This work was supported by the National Science Foundation [Awards CMMI-2308750, CNS-1952011, and CMMI-2144127]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0452 .

Predicting costs of local public bus transport services through machine learning methods

The present study developed several machine learning-based cost models to predict an efficient total economic cost per vehicle revenue-mile of urban public bus transport. The models were trained on a built-in dataset from 269 transit agencies providing urban services in the United States from 2015 to 2019. A feature selection strategy was implemented, finding that, for each proposed model, a subset of features determined a large impact on unit cost. These “core” features included commercial speed, average salary expenses per employee, vehicle productivity, and fleet ownership cost per vehicle. Machine learning techniques outperformed the linear regression method in terms of predictive power and robustness (understood as the dispersion of predictive power measures over the training sets). Based on SHAP values, the sensitivity analyses showed that the proposed models could be used to predict the impact of changes in some critical features on corresponding unit costs. The results may be useful for: (i) introducing regulatory constraints to the allocation of national public resources to local public bus transport services, aimed at minimizing the resources needed to provide a given level of service; (ii) defining the maximum economic compensation required by firms involved in competitive tendering for the allotment of service concessions, or firms with monopoly rights (by political choice and/or local public ownership); and (iii) improving service contract management and design by identifying key cost drivers of transit services.

Synergizing shared micromobility and public transit towards an equitable multimodal transportation network

This paper assesses the equity impacts of shared micromobility and investigates regulatory policies that improve transport equity and promote synergy between public transit and shared micromobility. We consider a multimodal transportation network, where a micromobility platform deploys docking stations and operates a fleet of micromobility vehicles to provide shared micromobility services and a public transit agency offers transit services over a transportation network. A market equilibrium model is developed to capture the intimate interactions among access and egress times of shared micromobility services, waiting times of transit services, the spatial distribution of docking stations, passenger demand, platform pricing and fleet sizing, vehicle repositioning and the micromobility platform profit. The platform decision problem is cast as a high-dimensional non-convex program. A solution method is proposed to efficiently compute the solution through problem reformulation and dimensionality reduction. Based on the proposed framework, we evaluate spatial equity in transport accessibility using the Gini index, and find that although shared micromobility improves overall transport accessibility, the benefits are not fairly distributed across different geographic zones, which leads to enlarged spatial inequity gaps after introducing shared micromobility. To promote transport equity, we investigate three policy directions: (a) to impose a vehicle density floor on shared micromobility; (b) to offer a subsidy on shared micromobility rides for first/last-mile connections; and (c) to promote collaboration between public transit and shared micromobility. We show that different regulatory policies have advantages and limitations. The minimum vehicle density requirement can simultaneously improve spatial equity and passengers’ surplus, but has limited equity improvements. In contrast, the subsidy on bundled services could significantly mitigate spatial inequity, but it hurts passengers and the platform profit. Compared to the other two policies, the transit-micromobility collaboration can lead to higher equity improvement, higher passenger surplus, while offering a guarantee on the platform profit, which turns out to be the most cost-effective approach. These insights are validated through realistic numerical studies for San Francisco.

Transit-oriented development (TOD) or development-oriented transit (DOT): how does it matter for sustainable urban growth?

ABSTRACT Urban growth patterns occur in various ways with tangible practical consequences. A key dilemma with regard to development and transportation revolves around whether the former follows the latter or vice versa. This study assessed this nexus with transit-oriented development (TOD) and development-oriented development (DOT) cases by using the land use/land cover (LU/LC) classification technique in a developing country example of a city in Turkey. Spatial data included high-resolution Sentinel 2A, Rapid Eye, and two SPOT satellite images and CORONA air photos acquired in 2021, 2013, 2000, 1989, and 1979, respectively, within three buffer zones (500, 750, and 1000 m) for both development forms. While the study acknowledges unorthodox TOD selection criteria and generalizability concerns, the results demonstrate that the TOD drastically reduced green areas (as opposed to ideal TOD requirements), while the DOT excessively grew commercial land uses and street networks. Both developments commonly impaired agricultural, vacant, and water land use. Such transformations direct local governments, transit agencies, and city planners to resolve ideal sustainable urban growth patterns by using remote sensing data and quantitative analysis.

Feeder bus service design under spatially heterogeneous demand

In rapidly sprawling urban areas and booming intercity express rail networks, efficiently designed feeder bus systems are more essential than ever to transport passengers to and from trunk-line rail terminals. When the feeder service region is sufficiently large, the spatial heterogeneity in demand distribution must be considered. This paper develops continuum approximation models for optimizing a heterogeneous fixed-route feeder network in a rectangular service region next to a rail terminal. Our work enhances previous studies by: (i) optimizing heterogeneous stop spacings along with line spacings and headways; (ii) accounting for passenger boarding and alighting numbers on bus dwell times and patron transfer delays at the rail terminal; and (iii) examining the advantages of asymmetric coordination between trunk and feeder schedules in both service directions. To tackle the increased modeling complexity, we introduce a semi-analytical method that combines analytically derived properties of the optimal solution with an iterative search algorithm. Local transit agencies can readily utilize this approach to design a real fixed-route feeder system.This paper reveals many findings and insights not previously reported. For instance, integrating the heterogeneous stop spacing optimization further reduces the system cost (by 4% under specific operating conditions). The cost savings increase with demand heterogeneity but decrease with the demand rate and service region size. Choosing the layout of feeder lines where buses pick up and drop off passengers along the service region’s shorter side also significantly lowers the system cost (by 6% when the service region’s aspect ratio is 1 to 2). Furthermore, coordinating trunk and feeder schedules in both service directions yields an additional cost saving of up to 20%.

The public transport disadvantaged in a highly transit-oriented city: An analytical framework, key challenges and opportunities

This paper proposes a holistic framework to identify public transport disadvantaged areas in terms of the level of services (LOS), area-based accessibility, and facility-based accessibility by employing the General Transit Feed Specification (GTFS) dataset. The framework considers the spatial and temporal levels of transit services, the spatial separation by urban functional areas, the availability of facilities based on the cumulative opportunity method, and the minimum time cost based on dual accessibility. A case study is performed in Hong Kong. The results show that the main problem for rural residents using public transport services lies in walking to transit stops/piers instead of long waits at public transport stops or infrequent services. The map of area-based accessibility shows great variations by urban functional areas. Despite being a highly transit-dependent city, we find huge disparities of accessibility to public facilities within Hong Kong and people living in some rural areas have difficulties in accessing basic services such as education, health care and shopping through public transport. Theoretically, this study reinforces the significance of place-based transport disadvantage and its intricate relationship with urban form. Empirically, it provides practical recommendations for public transport planning. The findings can direct transit agencies to re-plan and deploy services such as introducing demand-responsive transit services to better address the needs of people living in transport disadvantaged areas.

Electric buses as an air pollution and meteorological observation network: Methodology and preliminary results

Many local agencies in the United States and other countries are tasked to install air pollution monitoring systems of highly accurate sensors that have high acquisition, operating, and maintenance costs. The need for expanded coverage of air quality measurements across Salt Lake County (SLCO), Utah is being met by mounting air quality and temperature sensors on an expanding fleet of battery electric buses (BEBs). Monitoring air quality from a mobile sensor network provides real-time insights into air pollution patterns at high temporal and spatial resolution. Mobile measurements contribute to assessing residents' exposure to air pollution, facilitating the implementation of cost-effective public health policies and highlighting disparities. The Electric Bus Air Quality Observation Project was launched in SLCO during July 2021 and has collected millions of observations to date. A BEB traveling at typical traffic speeds (~10 m s−1) can provide multiple measurements along city block lengths of up to ~200 m. With careful analysis that factors in the time response of the differing sensors, variability from block-to-block may be attributed to fine-scale factors (e.g., pollution and heat sources, tree shading and urban vegetation, etc.). Preliminary findings showcase the value of increased coverage and resolution. During an extreme heat event in July 2023, both the morning and afternoon temperature readings showed differences of over 6.5 °C (12 °F), primarily as an east-west gradient with similar gradients in ozone. We conclude that temperature and pollutant concentration readings, at fine spatial and temporal resolutions, will facilitate future health studies and equitable policy and mitigation strategies. Our study demonstrates that our partnerships established with governmental, non-profit, and transit agencies facilitate the successful transfer of research and development to operational real-time mobile air quality monitoring.

Human Trafficking Awareness Training and Response Procedure Template for Transit Agencies

As the frontline eyes on communities, transit operators are uniquely positioned to recognize suspicious activities and report them to authorities. Training is necessary to inform and empower transit agencies in the fight against human trafficking. Human trafficking is modern day slavery, which the U.S. Department of Justice defines as a crime that involves the exploitation of a person for labor, services, or commercial sex. Human trafficking is a worldwide criminal industry that the denies freedom of 25 million people around the world. This heinous crime often targets the most vulnerable populations and preys on their needs, weaknesses, and insecurities as a strategy to control their victims through force, fraud, and coercion. This paper reviews the resources available for transit agencies to train their employees on the signs of human trafficking that they should be on the lookout for. Truckers Against Trafficking’s Busing on the Lookout program has shared success stories related to transit employees recognizing situations and saving human trafficking victims. However, the existence of transit agency policies and associated procedures is a recognized resource gap in the transit industry. The available training materials direct trainees to refer to their agency policy on how to report suspicious activity. However, as noted, many transit agencies do not have a formalized policy or procedures in place to dictate how to report suspected human trafficking activity. This paper provides agencies with valuable human trafficking awareness training resources and a response procedure template as tools to improve the awareness and reporting procedures in their agency.

A Case Study of Ridership and Equity Implications of All-Day Massachusetts Bay Transportation Authority Commuter Rail Service

As the COVID-19 pandemic emerged from the acute phase and vaccines became widely available in 2021, transit agencies like the Massachusetts Bay Transportation Authority (MBTA) faced a daunting challenge of drawing riders back into their systems. Despite systemwide staffing shortages, service disruptions, and ridership patterns that have yet to return to 2019 levels, ridership on MBTA’s Commuter Rail has consistently outperformed the agency’s other services in the current COVID recovery era. In April 2021, as part of a multiyear vision to overhaul the system, MBTA switched from a schedule focused on serving traditional peak-period commuters to providing steady, all-day service modeled on more legible “clockface” departures. This study used regression analysis to show this change was consistent with the Commuter Rail outperforming other modes in ridership recovery, generating over 7,000 average daily weekday boardings and over 9,000 average weekend boardings. Latent class analysis demonstrated that this schedule shift primarily benefited riders traveling for a variety of purposes, rather than just traditional office work. This group, which we referred to as general riders, was more likely to be low-income (household income below $75,000), young (25 or younger), and Hispanic. This research demonstrated the ability of all-day service on Commuter Rail to serve MBTA’s key aims of increasing ridership and providing more equitable, accessible service.

Transit Board Diversity and Pandemic Service Cuts in Vulnerable Communities

Despite its primary role in shaping policy and service characteristics, board governance is an understudied topic in the field of urban transit. Existing research on board management and representative bureaucracy theory suggests that the race and gender diversity of boards has a significant impact on organizational activity but that these relationships are highly dependent on the cultural context and industry analyzed. In this paper, we evaluate how the diversity of transit boards (with respect to race, gender, and disability) in the U.S.A. correlates with service changes authorized by these boards during the COVID-19 pandemic. Utilizing a database on board governance and general transit feed specification data for 36 agencies, we find a positive relationship between the presence of women on transit boards and vertically equitable service cuts, defined as increasing or maintaining transit service in more vulnerable neighborhoods. Overall, transit agencies with more female board members had more equitable service cuts, on average, during the COVID-19 pandemic.

Neoliberalism and the splintering of city-regionalism: the case of Denver’s regional transit agency in times of COVID-19 urban austerity

ABSTRACT Public transit service provision is fraught with contradictions and tensions, which today tend to converge around the city-regional scale of planning and governance. The promise of public transit is to promote economic development and improve regional accessibility, mobility, equity, and sustainability. However, these priorities can often conflict with each other, resulting in the splintering of the corresponding city-regional planning and governance structures set up to finance and deliver major transit infrastructure projects. Drawing upon a case study of transit-led city-regionalism in Denver, Colorado, USA, this article explores how the tensions and contradictions embedded within regional public transit service planning are exposed and exacerbated during times of financial austerity, such as during the COVID-19 pandemic. It examines how the neoliberal goals of promoting transit-oriented redevelopment in Denver alongside expanding service to Denver’s wealthier suburbs clash with the pandemic-induced expediency of targeting transit service for front-line workers and transit-dependent populations in core urban neighborhoods. The article demonstrates that in times of COVID-19-induced urban austerity the entrepreneurial city-regional approach to infrastructure provision originally developed for the FasTracks expansion program is increasingly at odds with regional objectives to use mass transit to foster equity and transport justice.

Analysis of paratransit crimes in Akure, Nigeria

BackgroundParatransit is a system that operates along a more or less defined route and then stops to take passengers on demand. They offer on-demand door-to-door service from any origin to any destination in a service area, and are operated by public transit agencies, community groups or not-for-profit organizations, and for-profit private companies or operators. In transit, criminal acts including rape, kidnapping and/or abduction, robbery, carjacking, vehicle theft, and even acts of terrorism are committed. These crimes are occasionally committed by other passengers since not every individual who boards a vehicle is a real traveller. This study examined the incidence of paratransit crimes in Akure, Nigeria using a Secured System Approach.ResultsThis study employed a household-based form of sampling to select the study locations in Akure. Convenient sampling was used to select two streets in each of the residential areas from which one hundred and twenty (120) houses were sampled purposively. The questionnaire was used to gather the primary data, with descriptive analysis. The study found that most of the transit crimes were perpetuated with taxi and motorcycles. Also, kidnapping was the major transit crimes in Akure. The Oba-Adesida road and Arakale road (situated along the study areas) were the hotspots for transit crimes in Akure. Finally, the respondents did not have a good perception of the proactiveness, integrity, reliability, respectability, and trustworthiness of security agencies regarding paratransit crimes in Akure.ConclusionsIncidence of paratransit crimes in Akure, Nigeria was explored among residents in Akure households. Kidnapping was dominant in Akure along Oba-Adesida and Arakale road, and mostly perpetuated with taxi and motorcycles. Since the participant did not have a good perception concerning the proactiveness, integrity, reliability, respectability, and trustworthiness of security agencies in Akure. Recommendations were suggested.

Increasing the precision of public transit user activity location detection from smart card data analysis via spatial–temporal DBSCAN

Smart Card (SC) systems have been increasingly adopted by public transit (PT) agencies all over the world, which facilitates not only fare collection but also PT service analyses and evaluations. Spatial clustering is one of the most important methods to investigate this big data in terms of activity locations, travel patterns, user behaviours, etc. Besides spatio-temporal analysis of the clusters provide further precision for detection of PT traveller activity locations and durations. This study focuses on investigation and comparison of the effectiveness of two density-based clustering algorithms, DBSCAN, and ST-DBSCAN. The numeric results are obtained using SC data (public bus system) from the metropolitan city of Konya, Turkey, and clustering algorithms are applied to a sample of this smart card data, and activity clusters are detected for the users. The results of the study suggested that ST-DBSCAN constitutes more compact clusters in both time and space for transportation researchers who want to accurately detect passengers’ individual activity regions using SC data.

Public transit and the needs of people experiencing homelessness: a directed content analysis guided by Maslow’s hierarchy of needs

ABSTRACT Transportation has rarely been a variable of interest in studying homelessness, yet its role in the lives of people experiencing homelessness (PEH), especially those in U.S. urban areas, is critical. The National Academies of Sciences, Engineering, and Medicine found transit agencies often frame riders experiencing homelessness as a problem to solve. Examining the experiences of PEH riders and appreciating the centrality of transit vehicles, properties, and personnel in the lives of PEH are critical to craft ethical solutions. Research question: How does the Dallas Area Rapid Transit system meet the daily needs of individuals experiencing homelessness? We utilized a descriptive phenomenological research design to frame the interview questions and then used Maslow’s hierarchy of needs in service of directed content analysis. We interviewed 42 PEH in Dallas, Texas, who also used the local transit system. Themes included “Transit Meets Basic Needs of Rest and Homeostasis,” “Ambivalent Safety on Transit,” “Transit and Recognition Needs,” and “Transit as a Metaphor for Being Needs.” Findings are discussed in light of previous literature and the potential for critical intervention.

Transit to parks initiatives in the U.S. and Canada: Practitioners’ perspectives

As large open spaces, such as national and regional parks, have become popular as recreational destinations, car dependency to access those open spaces has created capacity challenges. Due to these issues, transit-to-parks (T2P) initiatives—public transportation services connecting populated areas to large parks—have gained global traction. Limited research has examined these sustainability initiatives, and more knowledge is needed about how these initiatives are created and function. To address these gaps, this study explores motivations, facilitators, and challenges related to T2P initiatives in the U.S. and Canada. We conducted semi-structured interviews with 28 practitioners involved in the planning or operation of T2P initiatives in the two countries. Motivations for T2P included parking and congestion issues, environmental concerns, equity, and economic development. Facilitators of T2P initiatives included robust partnerships, community engagement, and advocacy efforts, emphasizing the importance of tailored narratives and coalition-building. The primary challenges mentioned were limited funding and labor, inadequate infrastructure, and siloed agencies and politics. This study reveals the complex dynamics of T2P initiatives and provides practical implications for transit agencies, public lands agencies, and community advocates seeking to enhance more sustainable and equitable access to nature.