Optimizing Public Transit Quality and System Access: The Multiple-Route, Maximal Covering/Shortest-Path Problem

2005 ◽  
Vol 32 (2) ◽  
pp. 163-178 ◽  
Author(s):  
Changshan Wu ◽  
Alan T Murray
Keyword(s):  
Service Quality ◽  
Shortest Path ◽  
Public Transit ◽  
The United States ◽  
Path Model ◽  
Transit System ◽  
Transit Service ◽  
Maximal Covering ◽  
Transit Ridership ◽  
Transit Agencies

Public transit service is a promising travel mode because of its potential to address urban sustainability. However, current ridership of public transit is very low in most urban regions—particularly those in the United States. Low transit ridership can be attributed to many factors, among which poor service quality is key. Transit service quality may potentially be improved by decreasing the number of service stops, but this would be likely to reduce access coverage. Improving transit service quality while maintaining adequate access coverage is a challenge facing public transit agencies. In this paper we propose a multiple-route, maximal covering/shortest-path model to address the trade-off between public transit service quality and access coverage in an established bus-based transit system. The model is applied to routes in Columbus, Ohio. Results show that it is possible to improve transit service quality by eliminating redundant or underutilized service stops.

Comparison of Two Common Approaches to Public Transit Service Equity Evaluation

2015 ◽  
Vol 2531 (1) ◽  
pp. 170-179 ◽  
Author(s):  
Alex Karner ◽  
Aaron Golub
Keyword(s):  
Census Data ◽  
Public Transit ◽  
Transit System ◽  
The Public ◽  
Transit Service ◽  
Transit Ridership ◽  
Data Source ◽  
Equity Evaluation ◽  
Equity Effects ◽  
Service Change

Understanding the equity effects of transit service changes requires good information about the demographics of transit ridership. Onboard survey data and census data can be used to estimate equity effects, although there is no clear reason to conclude that these two sources will lead to the same findings. Guidance from the FTA recommends the use of either of these data sources to estimate equity impacts. This study made a direct comparison of the two methods for the public transit system in the Phoenix, Arizona, metropolitan area. The results indicated that although both sources were acceptable for FTA compliance, the use of one or the other could affect whether a proposed service change was deemed equitable. In other words, the outcome of a service change equity analysis could differ as a result of the data source used. To ensure the integrity and meaning of such analyses, FTA should recommend the collection and use of ridership data for conducting service change analyses to supplement approaches that are based on census data.

GTFS-Ride: Unifying Standard for Fixed-Route Ridership Data

2019 ◽  
Vol 2673 (12) ◽  
pp. 173-181
Author(s):  
Phillip Carleton ◽  
Sylvan Hoover ◽  
Ben Fields ◽  
Matthew Barnes ◽  
J. David Porter
Keyword(s):  
Public Transit ◽  
The United States ◽  
Lessons Learned ◽  
Digital Data ◽  
Related Data ◽  
Standard Data ◽  
Transit Ridership ◽  
Technological Developments ◽  
Transit Agencies ◽  
Additional Support

The rapid growth in the availability and utility of vast amounts of digital data is arguably one of the most significant technological developments in recent years. In public transit, many agencies utilize modern technologies to collect large amounts of data, whereas smaller agencies with fewer resources and less expertise still use more traditional, manual data collection methods. Regardless of their technological capabilities, transit agencies recognize that some amount of transit data is useful and required. To the best of our knowledge, no standard data description of detailed fixed-route ridership exists today in the United States, forcing transit agencies to develop their own system of collecting, storing, and analyzing ridership and related data. In response to this need, this research aimed at developing one of the first public transit ridership data standards for fixed-route services and to support and promote its adoption and use. The resulting standard, an extension to the General Transit Feed Specification (GTFS) data standard, is referred to as GTFS-ride. GTFS-ride is easy to understand, able to accommodate the complexities of larger transit agencies, and capable of establishing a strong connection to the state of a transit network as it existed when the ridership data was collected. The first complete draft of GTFS-ride was released on September 6, 2017. This paper explains the structure of the five files that compose GTFS-ride, introduces additional support elements developed to facilitate its promotion and adoption, and documents the lessons learned from pilot implementations of GTFS-ride at three Oregon public transit agencies.

scholarly journals Planning for the First and Last Mile: A Review of Practices at Selected Transit Agencies in the United States

2021 ◽  
Vol 13 (4) ◽  
pp. 2222
Author(s):  
Hossain Mohiuddin
Keyword(s):  
Los Angeles ◽  
Gap Analysis ◽  
The United States ◽  
Design Guidelines ◽  
Plan Implementation ◽  
Marginalized Communities ◽  
Transit Ridership ◽  
Last Mile ◽  
Transit Agencies

A transit trip involves travel to and from transit stops or stations. The quality of what are commonly known as first and last mile connections (regardless of their length) can have an important impact on transit ridership. Transit agencies throughout the world are developing innovative approaches to improving first and last mile connections, for example, by partnering with ride-hailing and other emerging mobility services. A small but growing number of transit agencies in the U.S. have adopted first and last mile (FLM) plans with the goal of increasing ridership. As this is a relatively new practice by transit agencies, a review of these plans can inform other transit agencies and assist them in preparing their own. Four FLM plans were selected from diverse geographic contexts for review: Los Angeles County Metropolitan Transportation Authority (LA Metro), Riverside (CA) Transit Agency (RTA), and Denver Regional Transit District (RTD), and City of Richmond, CA. Based on the literature, we developed a framework with an emphasis on transportation equity to examine these plans. We identified five common approaches to addressing the FLM issue: spatial gap analysis with a focus on socio-demographics and locational characteristics, incorporation of emerging mobility services, innovative funding approaches for plan implementation, equity and transportation remedies for marginalized communities, and development of pedestrian and bicycle infrastructures surrounding transit stations. Strategies in three of the plans are aligned with regional goals for emissions reductions. LA Metro and Riverside Transit incorporate detailed design guidelines for the improvement of transit stations. As these plans are still relatively new, it will take time to evaluate their impact on ridership and their communities’ overall transit experience.

scholarly journals Understanding Users’ Satisfaction Towards Public Transit System in India: A Case-Study of Mumbai

2021 ◽  
Vol 10 (3) ◽  
pp. 155
Author(s):  
Rahul Das
Keyword(s):  
Service Quality ◽  
Public Transport ◽  
Travel Demand ◽  
Resource Constraints ◽  
Public Transit ◽  
Sampling Bias ◽  
Relevant Information ◽  
Transit System ◽  
Transport Services ◽  
Developing Cities

In this work, we present a novel approach to understand the quality of public transit system in resource constrained regions using user-generated contents. With growing urban population, it is getting difficult to manage travel demand in an effective way. This problem is more prevalent in developing cities due to lack of budget and proper surveillance system. Due to resource constraints, developing cities have limited infrastructure to monitor transport services. To improve the quality and patronage of public transit system, authorities often use manual travel surveys. But manual surveys often suffer from quality issues. For example, respondents may not provide all the detailed travel information in a manual travel survey. The survey may have sampling bias. Due to close-ended design (specific questions in the questionnaire), lots of relevant information may not be captured in a manual survey process. To address these issues, we investigated if user-generated contents, for example, Twitter data, can be used to understand service quality in Greater Mumbai in India, which can complement existing manual survey process. To do this, we assumed that, if a tweet is relevant to public transport system and contains negative sentiment, then that tweet expresses user’s dissatisfaction towards the public transport service. Since most of the tweets do not have any explicit geolocation, we also presented a model that does not only extract users’ dissatisfaction towards public transit system but also retrieves the spatial context of dissatisfaction and the potential causes that affect the service quality. It is observed that a Random Forest-based model outperforms other machine learning models, while yielding 0.97 precision and 0.88 F1-score.

Transit Planning Optimization Under Ride-Hailing Competition and Traffic Congestion

2021 ◽  
Author(s):  
Keji Wei ◽  
Vikrant Vaze ◽  
Alexandre Jacquillat
Keyword(s):  
New York ◽  
Traffic Congestion ◽  
Service Providers ◽  
Public Transit ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Transit Planning ◽  
Planning Optimization ◽  
Transit Ridership ◽  
Transit Agencies

With the soaring popularity of ride-hailing, the interdependence between transit ridership, ride-hailing ridership, and urban congestion motivates the following question: can public transit and ride-hailing coexist and thrive in a way that enhances the urban transportation ecosystem as a whole? To answer this question, we develop a mathematical and computational framework that optimizes transit schedules while explicitly accounting for their impacts on road congestion and passengers’ mode choice between transit and ride-hailing. The problem is formulated as a mixed integer nonlinear program and solved using a bilevel decomposition algorithm. Based on computational case study experiments in New York City, our optimized transit schedules consistently lead to 0.4%–3% system-wide cost reduction. This amounts to rush-hour savings of millions of dollars per day while simultaneously reducing the costs to passengers and transportation service providers. These benefits are driven by a better alignment of available transportation options with passengers’ preferences—by redistributing public transit resources to where they provide the strongest societal benefits. These results are robust to underlying assumptions about passenger demand, transit level of service, the dynamics of ride-hailing operations, and transit fare structures. Ultimately, by explicitly accounting for ride-hailing competition, passenger preferences, and traffic congestion, transit agencies can develop schedules that lower costs for passengers, operators, and the system as a whole: a rare win–win–win outcome.

Understanding Transit Agency Perceptions about Transportation Network Companies, Shared Mobility, and Autonomous Transit: Lessons from the United States

2019 ◽  
Vol 2673 (5) ◽  
pp. 95-108
Author(s):  
Mengjie Han ◽  
Matthew D. Dean ◽  
Pedro Adorno Maldonado ◽  
Parfait Masungi ◽  
Sivaramakrishnan Srinivasan ◽  
...  
Keyword(s):  
United States ◽  
New Technologies ◽  
Transportation Network ◽  
Critical Role ◽  
The United States ◽  
Transit System ◽  
Emergent Technologies ◽  
Shared Mobility ◽  
Transit Agencies ◽  
Transportation Network Companies

Emergent technologies like autonomous/connected vehicles and shared mobility platforms are anticipated to significantly affect various aspects of the transportation network such as safety, mobility, accessibility, environmental effects, and economics. Transit agencies play a critical role in this network by providing mobility to populations unable to drive or afford personal vehicles, and in some localities carry passengers more efficiently than other modes. As transit agencies plan for the future, uncertainty remains with how to best leverage new technologies. A survey completed by 50 transit agencies across the United States revealed similar yet different perceptions and preparations regarding transportation network companies (TNCs) and autonomous transit (AT) systems. Transit agencies believe TNC market share will grow, either minimally or rapidly (72%), within the next 5 years and have either a negative (43%) or positive (35%) impact on their transit system. Only 30% of agency boards instructed the agency to work with TNCs, despite no perceived transit union support. For AT systems, 22% of agencies are studying them, 64% believe the impacts of AT over the next 10–20 years will be positive, but fewer agencies are influenced to consider new technologies because of AT systems (38%) compared with TNCs (72%). Surprisingly, transit administration is mostly unsure about driver and transit unions’ perceptions of these technologies. In addition, a significant number of transit agencies do not believe they should play a role in ensuring TNCs are safe and equitable and that TNCs should not have to adhere to the same regulations (50%, 28% respectively).

The Hangover: Assessing Impact of Major Service Interruptions on Urban Rail Transit Ridership

2017 ◽  
Vol 2648 (1) ◽  
pp. 79-85
Author(s):  
Julene Paul ◽  
Michael J. Smart
Keyword(s):  
New York ◽  
Urban Areas ◽  
Hurricane Sandy ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Transit Systems ◽  
Service Interruptions ◽  
Transit Ridership ◽  
Transit Agencies

Driven by several factors, transit ridership has increased dramatically in some major U.S. urban areas over the past several years. Developing accurate econometric models of system ridership growth will help transit agencies plan for future capacity. As major weather events and maintenance issues can affect transit systems and have large impacts on the trajectory of ridership growth, this study examined the effect of major and minor service interruptions on the PATH heavy rail transit system in northern New Jersey and New York City. The study, which used PATH ridership data as well as data on weather, economic conditions, and fares for both PATH and competing services, concluded that Hurricane Sandy likely dampened ridership gains. Other major service interruptions, which lasted only hours or days, had little effect on long-term ridership growth. Suggestions for further study of service interruptions, especially in the face of climate change and resiliency issues in coastal regions, are presented.

Understanding Differences in Public Transit: Comparison of Boston and Toronto

1997 ◽  
Vol 1604 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Paul Schimek
Keyword(s):  
Population Density ◽  
Public Transit ◽  
Operating Costs ◽  
Level Of Service ◽  
Massachusetts Bay ◽  
Transit System ◽  
Transit Systems ◽  
Transit Service ◽  
American Cities ◽  
The City

Public transit systems in Toronto and Boston, two North American cities of similar size and income, are compared. Although Boston has a reputation as a transit-oriented city, there are about twice as many public transit trips in Toronto. Transit service in Toronto runs, on average, twice as frequently as service in Boston on a network of similar size. This level of service can be supported in part because population density does not decrease as much with increasing distance from the center of the city and because employment is more centralized. The transit system in Boston is constrained from emulating the Toronto transit system not only by a less transit-favorable distribution of population and employment but also by operating costs that are twice as high. The Massachusetts Bay Transit Authority’s higher costs are the result of more fringe benefits for employees and disproportionately more managers and fixed facilities.

Empirical Analysis of Long-Run Elasticities and Asymmetric Effects of Transit Demand Determinants

2020 ◽  
Vol 2674 (8) ◽  
pp. 274-284
Author(s):  
Lisa Li ◽  
Dena Kasraian ◽  
Amer Shalaby
Keyword(s):  
Policy Making ◽  
Demand Elasticity ◽  
Transit Planning ◽  
Dynamic Panel Model ◽  
Transit Service ◽  
Demand Elasticities ◽  
Transit Ridership ◽  
Long Run ◽  
Short Run ◽  
Transit Agencies

The effects of transit ridership determinants can be quantified as demand elasticities which are often used to inform transit planning and policy making. This study seeks to determine the impacts of transit service supply, fare, and gas prices on ridership by quantifying the short-run and long-run demand elasticities, as well as test whether transit ridership exhibits an asymmetric response to the rise and fall of these factors using a panel data of 99 Canadian transit agencies over the period of 2002–2016. The results of the dynamic panel model show the effects of transit service and fare to be greater in the long run. The short-run fare elasticity was found to be –0.24 while the long-run elasticity was –1.1. Furthermore, the demand elasticity with respect to service levels was also found to be inelastic (0.28) in the short run but elastic (1.3) in the long run. The cross-elasticity of gas prices was estimated to be 0.17. The existence of asymmetry was analyzed using decomposition techniques to separately estimate the coefficients for the rise and fall in each of the determinants. The equality of these coefficients was tested against each other and it was found that ridership responded more to an increase in transit supply than a decrease. The importance of these results to policy making are then discussed.

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

2021 ◽  
Author(s):  
Auyon Siddiq ◽  
Christopher S. Tang ◽  
Jingwei Zhang
Keyword(s):  
Public Transit ◽  
Cost Effective ◽  
The United States ◽  
The Public ◽  
Direct Mechanism ◽  
Indirect Mechanism ◽  
Transit Ridership ◽  
Last Mile ◽  
Transit Station ◽  
The Government

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.

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