18,168 research outputs found
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What’s Behind Recent Transit Ridership Trends in the Bay Area? Volume I: Overview and Analysis of Underlying Factors
Public transit ridership has been falling nationally and in California since 2014. The San Francisco Bay Area, with the state’s highest rates of transit use, had until recently resisted those trends, especially compared to Greater Los Angeles. However, in 2017 and 2018 the region lost over five percent (>27 million) of its annual riders, despite a booming economy and service increases. This report examines Bay Area transit ridership to understand the dimensions of changing transit use, its possible causes, and potential solutions. We find that: 1) the steepest ridership losses have come on buses, at off-peak times, on weekends, in non-commute directions, on outlying lines, and on operators that do not serve the region’s core employment clusters; 2) transit trips in the region are increasingly commute-focused, particularly into and out of downtown San Francisco; 3) transit commuters are increasingly non-traditional transit users, such as those with higher incomes and automobile access; 4) the growing job-housing imbalance in the Bay Area is related to rising housing costs and likely depressing transit ridership as more residents live less transit-friendly parts of the region; and 5) ridehail is substituting for some transit trips, particularly in the off-peak. Arresting falling transit use will likely require action both by transit operators (to address peak capacity constraints; improve off-peak service; ease fare payments; adopt fare structures that attract off-peak riders; and better integrate transit with new mobility options) and public policymakers in other realms (to better meter and manage private vehicle use and to increase the supply and affordability of housing near job centers)
Utilizing Simulated Vehicle Trajectory Data from Connected Vehicles to Characterize Performance Measures on an Arterial After an Impactful Incident
Traffic incidents are unforeseen events known to affect traffic flow because they reduce the capacity of an arterial corridor segment and normally generate a temporary bottleneck. Identification of retiming requirements to enhance traffic signal operations when an incident occurs depends on operations-oriented traffic signal performance measurements. When effective and real-time traffic signal performance metrics are employed at traffic control centers, delays, fuel use, and air pollution may all be decreased. The majority of currently available traffic signal performance evaluations are based on high-resolution traffic signal controller event data, which gives data on an intersection-by-intersection basis but requires a substantial upfront expenditure. The necessary detecting and communication equipment also involves costly and periodic maintenance. Additionally, the full manifestation of connected vehicles (CVs) is fast approaching with efforts in place to accelerate the adaptation of CVs and their infrastructures. CV technologies have enormous potential to improve traffic mobility and safety. CVs can provide abundant traffic data that is not otherwise captured by roadway detectors or other methods of traffic data collection. Since the observation is independent of any space restrictions and not impacted by queue discharge and buildup, CV data offers more comprehensive and reliable data that can be used to estimate various traffic signal performance measures.
This thesis proposes a conceptual CV simulation framework intended to ascertain the effectiveness of CV trajectory-based measures in characterizing an arterial corridor incident, such as a vehicle crash. Using a four-intersection corridor with different signal timing plans, a microscopic simulation model was created in Simulation of Urban Mobility (SUMO), Vehicles in Network Simulation (Veins) and Objective Modular Network Testbed in C++ (OMNeT++) platforms. Furthermore, an algorithm for CVs that defines, detects and disseminates a vehicle crash incident to other vehicles and a roadside unit (RSU) was developed. In the thesis, it is demonstrated how visual performance metrics with CV data may be used to identify an incident. This thesis proposes that traffic signal performance metrics, such as progression quality, split failure, platoon ratios, and safety surrogate measures (SSMs), may be generated using CV trajectory data. The results show that the recommended approaches with access to CV trajectory data would help both performance assessment and operation of traffic control systems. Unlike the current state of the practice (fixed detection technology), the developed conceptual framework can detect incidents that are not captured by intersection-vicinity-limited detectors while requiring immediate attention
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Urban Air Mobility Market Study
The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of 2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized
Performance Measures to Assess Resiliency and Efficiency of Transit Systems
Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service.
This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster
Exploration Of New Methods In Long Distance Transportation Data Collection And Tourism Travel In Vermont
ABSTRACT
Human transportation patterns have continued to shift and increase in rate as technology has made travel between spatially disparate locations more feasible. These movements are responsible for approximately one third of global carbon emissions, and account for one half of Vermont’s greenhouse gas output. Modeling transportation behaviors is difficult due to changing travel patterns and issues of surveying human participants. Long distance travel patterns are especially difficult and have not received the attention that urban mobility has within the literature.
In this Masters thesis, I describe current methods of transportation data collection and propose new methods, as well as attempt to quantify the impact on Vermont’s roadways of the transportation-based tourism sector. In the first chapter of this thesis, I describe a GPS-based travel survey conducted over the course of one year, coupled with interview data of long distance trips undertaken by 10 participants. Long distance travel has historically been underrepresented in travel surveying due to its infrequency, resulting in decreased likelihood of capturing a long distance trip in a short travel study. By extracting points at intervals from the GPS dataset, it becomes possible to determine accuracy of trip matching between the two datasets with adjusted data collection methods. The second chapter examines transportation related to tourism in Vermont. As one of Vermont’s largest industry sectors, economic impact has been of particular interest to state planners. However, limited analyses of the transportation impacts of this sector are currently available. My research models route choice of drive through tourists, whom constitute 40% of visitors, attempting to begin quantifying tourist mileage and CO2 emissions within the state.
Together, these studies expand knowledge on long distance transport data collection and the role of tourism in Vermont’s transportation mileage
Center for Economic Studies and Research Data Centers Research Report: 2013
Many individuals within and outside the Census Bureau contributed
to this report. Randy Becker coordinated the production of this
report and wrote, compiled, or edited its various parts. Matthew
Graham and Robert Pitts authored Chapter 2, C.J. Krizan authored
Chapter 3, and Lucia Foster, Todd Gardner, Christopher Goetz,
Cheryl Grim, Henry Hyatt, Mark Kutzbach, Giordano Palloni,
Kristin Sandusky, James Spletzer, and Alice Zawacki all contributed
to Chapter 4. Brian Holly provided the material found in
Appendix 3. Our RDC administrators and executive directors helped
compile information found in Appendixes 2 and 6. Other CES staff
contributed updates to the other appendixes.
Linda Chen of the Census Bureau’s Center for New Media and
Promotions and Donna Gillis of the Public Information Office
provided publication management, graphics design and composition,
and editorial review for print and electronic media.
Benjamin Dunlap of the Census Bureau’s Administrative and
Customer Services Division provided printing management.The Center for Economic Studies partners with stakeholders within
and outside the U.S. Census Bureau to improve measures of the
economy and people of the United States through research and
innovative data products.Research summaries in this report have not undergone the review
accorded Census Bureau publications and no endorsement should be
inferred. Any opinions and conclusions expressed herein are those
of the author(s) and do not necessarily represent the views of the
Census Bureau or other organizations. All results have been reviewed
to ensure that no confidential information is disclosed
Examining macro-level correlates of farm equipment theft : a test of routine activity theory and social disorganization theory.
This dissertation explores the potential for routine activity theory and social disorganization theory to explain incidence of farm equipment theft at the county level. Relatively few attempts have been made to discern the factors that contribute to such theft. Most are relatively dated, and all focus upon the relationship between victimization risk and the characteristics of individual farms. Accordingly, the current study represents the first attempt to examine the influence of macro-level processes and characteristics upon the problem. Data are gathered for 306 counties housed within four Southeastern States. Counts of farm equipment theft are collected from the 2011-2012 iterations of the National Incident Based Reporting System, and attributed to the county in which they occurred. The routine activity measures employed are based upon the findings of micro-level studies, and drawn primarily from the 2007 version of the Census of Agriculture. Social disorganization measures are created in line with past attempts to explore the applicability of the theory to crime problems outside of metropolitan areas. These measures are derived from the 2010 version of the United States Census. Negative binomial regression analysis suggests that both theories have applicability to our understanding of farm equipment theft incidence. Agricultural characteristics aggregated to the county level appear to condition the number of opportunities available to motivated offenders. Moreover, counties featuring structural characteristics conducive to disorganization appear to experience higher incidence of theft than those that would be considered “more organized.” Based upon these findings, implications for each theoretical framework are addressed. In addition, policy implications are covered, with a specific focus upon strategies designed to reduce opportunities for theft and improve levels of informal social control in rural areas. The dissertation concludes with a brief discussion of limitations associated with the study, directions for future research, and concluding remarks
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