Impacts of Bike Sharing Program on Subway Ridership in New York City

2021 ◽  
pp. 036119812110049
Author(s):  
Md Tanvir Ashraf ◽  
Md Amdad Hossen ◽  
Kakan Dey ◽  
Sarah El-Dabaja ◽  
Moathe Aljeri ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Subway Station ◽  
Transit System ◽  
Last Mile ◽  
Bike Sharing ◽  
Transit Services ◽  
Transportation Agencies ◽  
Citi Bike

Bike sharing programs have become increasingly popular in many cities. These services allow users to rent bikes for utilitarian and recreational trips in the urban area. Bike sharing has been considered a suitable mode to support the first- and last-mile connectivity problems of fixed-route transit services. Bike sharing has also emerged as a convenient mode for short-distance trips that previously would not have been possible without using public transit or personal bikes. This study investigated the impacts of Citi Bike—a bike sharing program—on the subway ridership in New York City (NYC), using Poisson-Gamma models. Bike sharing trips with destinations within a quarter-mile radius of a subway station were associated with subway ridership increase. A 10% increase in the number of bike trips increased the average daily subway ridership by 2.3%. However, a higher number of bike stations around a subway station decreased the subway ridership in instances where more bike trips originated (as opposed to ended) in the subway station’s service area. The presence of dedicated bike lanes and bike racks attracted more bike users and increased subway ridership. Findings from this study indicate that the development of bike-friendly infrastructure such as activities outlined in the recent NYC Department of Transport (DOT) “Green Wave” program can increase both bike sharing and subway ridership. In addition, policies and initiatives by transportation agencies to better integrate bike sharing programs with the transit system have the potential to increase the attractiveness of bike sharing programs and maximize the subway ridership.

Public Bike Sharing in New York City: Helmet Use Behavior Patterns at 25 Citi Bike™ Stations

2014 ◽  
Vol 40 (3) ◽  
pp. 530-533 ◽  
Author(s):  
Corey H. Basch ◽  
Danna Ethan ◽  
Patricia Zybert ◽  
Sarah Afzaal ◽  
Michael Spillane ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Behavior Patterns ◽  
Helmet Use ◽  
Bike Sharing ◽  
Use Behavior ◽  
Citi Bike

An environmental benefit analysis of bike sharing in New York City

Cities ◽  
2021 ◽  
pp. 103475
Author(s):  
Yan Chen ◽  
Yongping Zhang ◽  
D'Maris Coffman ◽  
Zhifu Mi
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Benefit Analysis ◽  
Environmental Benefit ◽  
Bike Sharing

The Billionaire’s Ambitions

Last Subway ◽  
2020 ◽  
pp. 49-72
Author(s):  
Philip Mark Plotch
Keyword(s):  
New York ◽  
New York City ◽  
Public Transportation ◽  
York City ◽  
Transportation Network ◽  
East Side ◽  
Legislative Session ◽  
Transportation Agencies ◽  
The City ◽  
Grand Vision

This chapter assesses the roles played by New York governor Nelson Rockefeller and New York City mayor John Lindsay, as well as William Ronan, in transforming the transportation system. Ronan, Rockefeller, and Lindsay all realized that improving public transportation was critical to strengthening the economy of the city and the region. They were also well aware of the benefits of a Second Avenue subway, since all three of them lived on the Upper East Side. After Lindsay failed to reorganize the transportation agencies, Rockefeller and Ronan developed their own grand vision for the region's transportation network, and in December of 1966, Ronan stepped down from his post as secretary to begin implementing their plan. At the beginning of the state's 1967 legislative session, Rockefeller and Ronan announced their two-pronged approach. First, they proposed integrating the New York City Transit Authority and the Triborough Bridge and Tunnel Authority (TBTA) into the Metropolitan Commuter Transportation Authority (MCTA). In addition, Rockefeller and Ronan would seek voter approval to borrow $2.5 billion that would be dedicated for roadway and public transportation improvements across the state. In 1967, the governor and Ronan obtained the support they needed to transform the transportation network, a feat that Lindsay had not been able to accomplish.

Is There a Limit to Adoption of Dynamic Ridesharing Systems? Evidence from Analysis of Uber Demand Data from New York City

2018 ◽  
Vol 2672 (42) ◽  
pp. 127-136 ◽  
Author(s):  
Raymond Gerte ◽  
Karthik C. Konduri ◽  
Naveen Eluru
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Transportation Networks ◽  
Autonomous Vehicle ◽  
Temporal Trends ◽  
Technological Advances ◽  
Vehicle Operation ◽  
Bike Sharing ◽  
And Shifts

Recent technological advances have paved the way for new mobility alternatives within established transportation networks, including on-demand ride hailing/sharing (e.g., Uber, Lyft) and citywide bike sharing. Common across these innovative modes is a lack of direct ownership by the user; in each of these mobility offerings, a resource not owned by the end users’ is shared for fulfilling travel needs. This concept has flourished and is being hailed as a potential option for autonomous vehicle operation moving forward. However, substantial investigation into how new shared modes affect travel behaviors and integrate into existing transportation networks is lacking. This paper explores whether the growth in the adoption and usage of these modes is unbounded, or if there is a limit to their uptake. Recent trends and shifts in Uber demand usage from New York City were investigated to explore the hypothesis. Using publicly available data about Uber trips, temporal trends in the weekly demand for Uber were explored in the borough of Manhattan. A panel-based random effects model accounting for both heteroscedasticity and autocorrelation effects was estimated wherein weekly demand was expressed as a function of a variety of demographic, land use, and environmental factors. It was observed that demand appeared to initially increase after the introduction of Uber, but seemed to have stagnated and waned over time in heavily residential portions of the island, contradicting the observed macroscopic unbounded growth. The implications extend beyond already existing fully shared systems and also affect the planning of future mobility offerings.

Helmet Use Among Users of the Citi Bike Bicycle-Sharing Program: A Pilot Study in New York City

2013 ◽  
Vol 39 (3) ◽  
pp. 503-507 ◽  
Author(s):  
Corey H. Basch ◽  
Danna Ethan ◽  
Sonali Rajan ◽  
Sandra Samayoa-Kozlowsky ◽  
Charles E. Basch
Keyword(s):  
New York ◽  
New York City ◽  
Pilot Study ◽  
York City ◽  
Helmet Use ◽  
Citi Bike

Understanding the Relationships between Demand for Shared Ride Modes: Case Study using Open Data from New York City

2019 ◽  
Vol 2673 (12) ◽  
pp. 30-39 ◽  
Author(s):  
Raymond Gerte ◽  
Karthik C. Konduri ◽  
Nalini Ravishanker ◽  
Amit Mondal ◽  
Naveen Eluru
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Transportation Network ◽  
Temporal Trends ◽  
Primary Objective ◽  
Linear Modeling ◽  
Modeling Framework ◽  
Exogenous Factors ◽  
Citi Bike

The concept of shared travel, making trips with other users via a common vehicle, is far from novel. However, a changing technological climate has laid the tracks for new dynamically shared modes in the form of transportation network companies (TNCs), to substantially impact travel behavior. The current body of research on how these modal offerings impact the demand for existing shared modes (e.g., bikeshare, transit) is growing. However, a comprehensive investigation of the temporal evolution of the demand for TNCs and their relationship to other shared modes, is lacking. This research tackles this important limitation by analyzing ridership data for TNCs, taxi, subway, and Citi Bike in New York City using daily ridership data from January 2015 through June 2017. The primary objective was to understand the relationship between TNCs and other shared modal offerings while accounting for the influence of temporal trends and other exogenous factors. A dynamic linear modeling framework was formulated to accommodate time-dependent trends, periodicity, and time-varying exogenous factors on the demand for TNCs. As a preliminary work, the findings of this study reinforce the observed substitution relationship between taxis and TNCs. The results may also indicate a substitutional relationship between TNCs and Citi Bike, and a complementary relationship with subway, however these results still need to be explored further. With potentially impactful findings for planning and policymakers, the predictive model developed in the study can be used to carry out forecasting in support of short- and long-term operations and planning applications.

Optimization of Multiple-Route Feeder Bus Service: Application of Geographic Information Systems

2003 ◽  
Vol 1857 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Steven I-Jy Chien ◽  
Feng-Ming Tsai ◽  
Edwin Hou
Keyword(s):  
New York ◽  
New York City ◽  
Information Systems ◽  
Geographic Information Systems ◽  
York City ◽  
Geographic Information ◽  
Service Area ◽  
Street Network ◽  
Transit System ◽  
Demand Distribution

A genetic algorithm (GA) was developed to optimize a bus transit system serving an irregularly shaped area with a grid street network. The developed objective total cost function was minimized subject to realistic demand distribution and street pattern. The service area in New York City was selected as an example to demonstrate the application of the developed model. With the application of geographic information systems, the street network within the service area was obtained and applied, while the passenger demand information was approximated based on the New York City census report of 1990. The optimal number of bus routes and their locations were found by applying the proposed GA, while the optimal headways of the routes were analytically derived. The method developed here can be applied to dynamic routing buses under various incident situations.

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