scholarly journals Longitudinal Analysis of Transit-Integrated Ridesourcing Users and Their Trips

2021 ◽  
pp. 036119812199583
Author(s):  
Emma Swarney ◽  
Jacob Terry ◽  
Devin Feng ◽  
Chris Bachmann
Keyword(s):  
Performance Evaluation ◽  
Longitudinal Analysis ◽  
Transportation Network ◽  
Frequent Users ◽  
Frequency Changes ◽  
Transit Agencies ◽  
Changes Over Time ◽  
Evaluation Techniques ◽  
Over Time ◽  
Transportation Network Companies

Several municipal transit agencies have partnered with transportation network companies to provide a range of services, but data restrictions have limited research on trip-level observations of transit-integrated ridesourcing users. The goal of this study was to understand how users’ trip-making behaviors adapted to a transit-integrated ridesourcing pilot in Waterloo, Ontario. This research conducted a longitudinal analysis of 178 unique users and temporal analyses of their 4,536 ridesourcing trips (rides) taken throughout the pilot from November 2018 to December 2019. Trip type and frequency changes over time were measured for frequent, average, and infrequent users. Transit, walking, and cycling alternatives to the pilot rides were generated and characterized based on their complementarity with transit. The number of unique users and daily ridership increased over time, as new users made their first trips and existing users made trips more frequently. Frequent users shifted toward less transit-competitive trip types whereas average and infrequent users had a sporadic but larger share of more transit-competitive trip types. The pilot was mostly used during off-peak service periods, when transit was less frequent, which suggests these systems are valuable for nonwork trips. Transit trip alternatives were not temporally competitive with rides. Cycling was competitive with 5% to 10% of rides and was consistently faster than walking and transit alternatives. Walking was not a practical alternative to rides in most cases. This analysis may inform other agencies of performance evaluation techniques for their transit-integrated ridesourcing pilots and the unique characteristics of trips taken by users of this mode.

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).

Partnerships Between Transit Agencies and Transportation Network Companies

2019 ◽  
Author(s):  
Terra Curtis ◽  
Meg Merritt ◽  
Carmen Chen ◽  
David Perlmutter ◽  
Dan Berez ◽  
...  
Keyword(s):  
Transportation Network ◽  
Transit Agencies ◽  
Transportation Network Companies

scholarly journals Do transportation network companies increase or decrease transit ridership? Empirical evidence from San Francisco

2021 ◽  
Author(s):  
Gregory D. Erhardt ◽  
Richard Alexander Mucci ◽  
Drew Cooper ◽  
Bhargava Sana ◽  
Mei Chen ◽  
...  
Keyword(s):  
San Francisco ◽  
Transportation Network ◽  
Transportation Systems ◽  
Light Rail ◽  
Transit Ridership ◽  
Application Programming ◽  
Transit Agencies ◽  
Using Data ◽  
Transit Use ◽  
Transportation Network Companies

AbstractTransportation network companies (TNCs), such as Uber and Lyft, have been hypothesized to both complement and compete with public transit. Existing research on the topic is limited by a lack of detailed data on the timing and location of TNC trips. This study overcomes that limitation by using data scraped from the Application Programming Interfaces of two TNCs, combined with Automated Passenger Count data on transit use and other supporting data. Using a panel data model of the change in bus ridership in San Francisco between 2010 and 2015, and confirming the result with a separate time-series model, we find that TNCs are responsible for a net ridership decline of about 10%, offsetting net gains from other factors such as service increases and population growth. We do not find a statistically significant effect on light rail ridership. Cities and transit agencies should recognize the transit-competitive nature of TNCs as they plan, regulate and operate their transportation systems.

Partnerships Between Transit Agencies and Transportation Network Companies (TNCs)

2019 ◽  
Author(s):  
Terra Curtis ◽  
Meg Merritt ◽  
Carmen Chen ◽  
David Perlmutter ◽  
Dan Berez ◽  
...  
Keyword(s):  
Transportation Network ◽  
Transit Agencies ◽  
Transportation Network Companies

Partnerships between Agencies and Transportation Network Companies for Transportation-Disadvantage Populations: Benefits, Problems, and Challenges

2021 ◽  
pp. 036119812110326
Author(s):  
Ruth L. Steiner ◽  
Xueyin Bai ◽  
Ilir Bejleri ◽  
Mengjie Han ◽  
Xiang “Jacob” Yan
Keyword(s):  
Low Income ◽  
Rural Areas ◽  
Transportation Network ◽  
Safety Issues ◽  
Service Demand ◽  
Human Service Agencies ◽  
Service Models ◽  
Transit Services ◽  
Transit Agencies ◽  
Transportation Network Companies

Transportation network companies (TNCs), such as Uber and Lyft, offer a new mobility option to consumers. An increasing number of transit agencies work with TNCs, and different types of partnerships have formed. While these service models may serve the general population well, their implications for transportation-disadvantage populations, including older adults, individuals with disabilities, and low-income people, have not received enough attention. These populations are highly dependent on public transit services. Additionally, we have limited firsthand knowledge of challenges that hinder transit agencies and related human service agencies from building partnerships with TNCs. Can these agency/TNC partnerships accommodate the needs of transportation-disadvantage populations? This study explores these issues through a literature review and interviews with 16 related organizations in the State of Florida, where transportation-disadvantage populations are served through a coordinated system but the partnerships with TNCs are still limited. The paper first categorizes the existing agency/TNC partnership service models into three types and examines their benefits and problems in serving transportation-disadvantage populations. It then identifies different organizations’ perceptions of TNCs and the challenges for some agencies to work with TNCs. The general challenges include difficulty in estimating service demand, data sharing problems, hidden costs and staff efforts, training and safety issues, and the need of complementary vendors. The challenges specifically in rural areas are a lack of motivation and commitment among TNCs, affordability issues, and TNCs’ adaptation to the rural geography. These challenges in agency/TNC partnerships need to be addressed to serve the public better, including transportation-disadvantage populations.

scholarly journals A Longitudinal Analysis Of Assessment Center Factors: Changes In Importance Of Managerial Potential Criteria

2011 ◽  
Vol 8 (1) ◽  
pp. 129
Author(s):  
Robert F. Scherer ◽  
James Brodzinski ◽  
Ted H. Shore
Keyword(s):  
Longitudinal Analysis ◽  
Assessment Center ◽  
Individual Factors ◽  
Assessment Centers ◽  
Changes Over Time ◽  
Over Time

Reviews of assessment centers have provided widespread support for their usage. However, an issue not previously considered is the degree to which the relationships among assessment factors and contributions of individual factors remain stable longitudinally. The present investigation provides evidence to show that while the factors are useful in differentiating among levels of management potential, the importance and contributions of any one factor changes over time.

Performance Analysis of Frequency Hopping Communication System Synchronization

2011 ◽  
Vol 403-408 ◽  
pp. 2927-2930 ◽  
Author(s):  
Jian Zheng ◽  
Xin Yu Wei ◽  
Xiao Gang Ni
Keyword(s):  
Performance Analysis ◽  
Low Frequency ◽  
Project Design ◽  
Improved Method ◽  
Frequency Method ◽  
System Synchronization ◽  
Frequency Changes ◽  
Changes Over Time ◽  
System Time ◽  
Over Time

This paper studies a method based on synchronized prefix improved method, use a synchronous frequency method related to the system time (TOD) to generate the synchronization frequency, each synchronous frequency changes over time in constantly changing, thus protecting synchronous frequency, and sent low frequency TOD Is calculated out of the high TOD, which increases the difficulty of deciphering. the results of Performance Analysis show that TOD self-synchronizing synchronizing time is quick, the synchronized probability is big, good randomness, has met the project design anticipated requirements.

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