Travel Behavior Reactions to Transit Service Disruptions

2017 ◽  
Vol 2649 (1) ◽  
pp. 79-88 ◽  
Author(s):  
Shanjiang Zhu ◽  
Hamza Masud ◽  
Chenfeng Xiong ◽  
Zhuo Yang ◽  
Yixuan Pan ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Behavioral Reactions ◽  
Transit System ◽  
System Failures ◽  
Transit Service ◽  
Effective Strategies ◽  
Aging Infrastructure ◽  
Infrastructure System ◽  
Network Disruptions ◽  
System Impact

Major transit infrastructure disruptions have become more frequent because of increasing maintenance needs for aging infrastructure, system failures, and disasters. Understanding travel behavior reactions to service disruptions on the basis of empirical observations is a fundamental step toward planning and operating an efficient and reliable transportation system. Few studies in the literature have investigated the behavioral and system impact of transit service disruptions. To bridge this gap in the literature, this research investigated travel behavioral reactions to transit service disruptions during the Metro SafeTrack projects in Washington, D.C., with the use of a unique panel survey. This study offers new insights on multimodal, multidimensional travel behavioral responses to major transit network disruptions, a critically theoretical prerequisite for developing and implementing effective strategies (e.g., how to deploy the reserve bus fleet optimally) that minimize system impact and improve transit system reliability and resilience.

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.

Opting Out of Transit: How Does Strong Local Autonomy Impact Allocation of Transit Service in a Multi-Jurisdictional Transit Agency? A Historical Case Study Analysis

2020 ◽  
pp. 1087724X2097304
Author(s):  
David Weinreich ◽  
Ahmad Bonakdar
Keyword(s):  
Resource Allocation ◽  
Historical Case Study ◽  
Study Analysis ◽  
Historical Case ◽  
Transit System ◽  
Case Study Analysis ◽  
Transit Service ◽  
Opt Out ◽  
The Impact

This study examines how the voluntary nature of local membership in transportation agencies can impact resource allocation, drawing on details from a major US transit agency in a state that lets cities opt in or out of transit agency membership. This study finds significant correlation between local opt-outs and transit service using national data. This study examines the impact opt-outs have on transit resource allocation and decision making over time, their effect on transit service over decades, and equity implications, using historical case study analysis from the Dallas Area Rapid Transit system (DART). This study concludes that authorizing legislation allowing local jurisdictions to opt out of transit districts weakens planning capacity, creates a structure making it difficult to allocate scarce transit dollars based on transit need and social equity goals, instead favoring allocation based on satisfying each municipality.

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.

Personal exposure to air pollutants in a Bus Rapid Transit System: Impact of fleet age and emission standard

2019 ◽  
Vol 202 ◽  
pp. 117-127 ◽  
Author(s):  
R. Morales Betancourt ◽  
B. Galvis ◽  
J.M. Rincón-Riveros ◽  
M.A. Rincón-Caro ◽  
A. Rodriguez-Valencia ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Personal Exposure ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Emission Standard ◽  
Transit System ◽  
System Impact

Productivity Frequency Index

1997 ◽  
Vol 1571 (1) ◽  
pp. 14-16 ◽  
Author(s):  
Kenneth J. Warren
Keyword(s):  
Time Of Day ◽  
Transit System ◽  
Transit Service ◽  
Milwaukee County ◽  
Frequency Index ◽  
Route Segment ◽  
Bus Service

The frequency of bus service on a specific route is directly related to the number of passengers using the route. Routes that exhibit high ridership should be provided frequent service, whereas routes with low ridership should be provided less frequent service. The productivity frequency index used by the Milwaukee County Transit System quantitatively measures the relationships between ridership demand and the frequency of service for each bus route both by route segment and by time of day. Use of this measure assists the transit system in equitably allocating the supply of transit service between individual routes, thereby resulting in more effective and efficient operations.

Reshaping the Region

2015 ◽  
Vol 2537 (1) ◽  
pp. 33-41
Author(s):  
Stephanie Pollack ◽  
Anna Gartsman ◽  
Timothy Reardon ◽  
Meghna Hari
Keyword(s):  
Land Use ◽  
Public Transportation ◽  
Travel Behavior ◽  
Massachusetts Bay ◽  
Data Set ◽  
Transit System ◽  
Transit Systems ◽  
Commuter Rail ◽  
In Transit ◽  
The Impact

The American Public Transportation Association's use of a “land use multiplier” as part of its methodology for calculating greenhouse gas reduction from transit has increased interest in methodologies that quantify the impact of transit systems on land use and vehicle miles traveled. Such transit leverage, however, is frequently evaluated for urbanized areas, although transit systems serve only a small proportion of those areas. If transit leverage is stronger in areas closer to transit stations, studies based on larger geographies may underestimate land use and travel behavior effects in transit-served areas. A geographic information system–based data set was developed to understand better the leverage effects associated with the mature and extensive Massachusetts Bay Transportation Authority transit system in areas proximate to its stations throughout Metropolitan Boston. The region was divided into the subregion that was transit-proximate (within a half mile of a rapid transit station or key bus route), the portion that was commuter rail–proximate, and the remaining 93.3% of the region that was not proximate to high-frequency transit. Households in the transit-proximate subregion were significantly more likely to commute by transit (and walking or biking), less likely to own a car, and drove fewer miles than households in the non-transit-served areas of the region. Commuter rail–proximate areas, although denser than the region as a whole, exhibited more driving and car ownership than regional averages. Given these spatial and modal variations, future efforts to understand transit leverage should separately evaluate land use and travel effects by mode and proximity to transit stations.

A Typological Approach to Individual Urban Travel Behavior Prediction

1975 ◽  
Vol 7 (2) ◽  
pp. 141-152 ◽  
Author(s):  
N Oppenheim
Keyword(s):  
San Francisco ◽  
Travel Behavior ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Urban Resident ◽  
Transit System ◽  
Urban Travel ◽  
Behavior Type ◽  
Bay Area ◽  
Typological Approach

With the use of cluster analysis a sample of 1018 residents of the San Francisco Bay Area was classified into eleven types of urban residents on the basis of overall similarity of personal and environmental characteristics, and independently into nine types of travel behavior. The relations between the two typologies, and the comparative travel behavior of the types of urban resident were investigated in an attempt to gain insight into the determinants of urban travel. The probability of the correct assignment of a travel behaviour type to an urban resident type was of the order of 0·30. Monte Carlo simulation methods were used to test empirically whether the value of a given travel behavior characteristic for a given urban resident type can be assumed to be higher (or lower) than the value in the general population, thus testing the predictability of the travel behavior of the various urban resident types. Conversely, the prediction of the urban traveler's personal characteristics given his travel behavior type was also evaluated. This typological approach made the prediction of the usage of the San Francisco Bay Area rapid transit system (for going to work, for going to shop, for going out for leisure, or for some other purpose) possible, in about 15% of the cases, from the knowledge of the urban resident type and, in about 25% of the cases, from the knowledge of the travel behavior type.

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