Public bikesharing—the shared use of a bicycle fleet—has recently emerged in major North American cities. Bikesharing has been found to decrease driving and increase bicycling. But shifts in public transit have been mixed. The authors evaluate survey data from two U.S. cities to explore who is shifting toward and away from public transit as a result of bikesharing. The authors explore this question by mapping geocoded home and work locations of respondents within Washington DC and Minneapolis. Respondents were mapped by their modal shift toward or away from bus and rail transit. The results show that in Washington DC, those shifting toward bus and rail transit live on the urban periphery, whereas those living in the urban core tend to use public transit less. In Minneapolis, the shift toward rail extends to the urban core, while the modal shift for bus transit is more dispersed. The authors analyze socio-demographics associated with modal shift through cross-tabulations and four ordinal regression models. Common attributes associated with shifting toward public transit include increased age, being male, living in lower density areas, and longer commute distances. The authors conclude with a discussion of the final results in the context of bikesharing’s impacts on other cities throughout North America. 

GIG Car Share is a free-floating carsharing system that began operations in the East Bay in April 2017. Similar to other free-floating carsharing systems, such as car2go and ReachNow (which later combined as ShareNow), members of GIG have access to a fleet of vehicles which they can book and unlock via an app. Once booking the vehicle, members can drive anywhere, but must park back in the home zone in order to terminate their session. The price of driving a GIG vehicle is charged per hour, per mile, or per day, and is calculated based on the lowest cost to the user. This report uses the results from a pre- and post-survey of GIG members in Oakland to measure the changes in travel behavior, with special attention paid to changes in personal vehicle use that occurred as a result of joining GIG. The pre-survey (N = 362) was conducted in December 2017 and the postsurvey (N = 221) was conducted in January 2019. The demographics of GIG survey respondents in Oakland are similar to previous findings from evaluations of shared mobility in other cities. The sample of post-survey respondents was younger than the general Oakland population, with 50% of the sample under the age of 34 compared to 36% for the general population. The survey sample was also highly educated; 88% of respondents have at least a 4- year college degree, compared to only 40% in the general population. Income distribution was relatively similar, though GIG survey respondents had a slightly higher income than the rest of Oakland. However, the race/ethnicity distribution was more imbalanced, where 60% of survey respondents were White, while only 27% of the Oakland population is White. African Americans and Hispanic/Latinos were relatively underrepresented; 12% of survey respondents were African American compared to 23% of the Oakland population and 7% of survey respondents were Hispanic/Latino compared to 30% of the population. Table 1 presents a distribution of demographics for key attributes.

This project is a two-year evaluation of pricing/incentives applied to the one-way, all electric carsharing system operated by car2go in San Diego, CA. This system is the only electric vehicle-based, one-way carsharing system with instant access (i.e., accessible without reservation) operating in the U.S. The goal of this project is to work with car2go and the San Diego region to develop and evaluate pricing/incentive structures for their members, which improve system operational efficiency (vehicle redistribution, state-of-charge management, use of vehicles placed at public transit stations) and encourage shared-vehicle use.

The study found that roundtrip carsharing in NYC mostly serves as a substitute for car rental, other personal vehicle modes, and personal vehicle ownership. The analysis showed that the broader pilot program had a modest impact on user behavior through carsharing (i.e., reduced vehicle ownership, reduced VMT, and mode shift). It also found that the pilot program likely expanded the membership base of carsharing to demographic cohorts that are traditionally underrepresented in carsharing populations (i.e., increased participation by lower education levels, lower household incomes, minority demographics). The study also examined vehicle ownership impacts and changes in vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. Analysis of survey and activity data indicated that 7% of NYC carsharing members avoided a car purchase, and 0.61% of members got rid of a car they already owned due to carsharing. Across the membership base, VMT was reduced by 7% and GHG emissions were reduced by 6%. These findings showed that carsharing reduced VMT and delivered associated environmental benefits within NYC, and more broadly had a substantive impact on travel behavior among members in form of mode shift away from personal automotive modes.

Transportation Network Companies (TNCs, also known as ridehailing and ridesourcing) have expanded across California over the past decade and changed the way people travel. Using a smartphone, travelers can quickly summon a vehicle from almost anywhere and know what the estimated wait time, travel time, and cost will be before stepping into the vehicle. While TNCs are clearly addressing an unmet need for travelers, their growing popularity has raised a number of policy questions, including if TNCs are shifting people away from public transit and other travel modes (e.g., carshare, walking, biking).

This paper advances the understanding of peer-to-peer (P2P) carsharing within the broader context of shared mobility and its connection to the built environment in the US through a survey conducted in 2014 (n = 1,151). Eleven per cent of respondents used carpooling/ridesharing more, and 19% avoided a vehicle purchase due to P2P vehicle access in urban areas. Nevertheless, P2P carsharing has the potential to operate in a range of land-use environments and could be an important strategy to further deemphasize car ownership. Additionally, as the deployment of automated vehicles (AVs) is examined, sharing of privately owned AVs could mirror current P2P carsharing dynamics in important ways.

This brief explores how shared micromobility (bikesharing and scooter sharing) has evolved since the pandemic. Primary data for this report were collected through four surveys: An Operator Survey (n=25) and an Agency Survey (n=52) distributed between January 2022 and May 2022 to all known shared micromobility operators and agencies and included questions about the attributes of shared micromobility systems1 operating within those agency jurisdictions and operator markets; and a similar Operator Survey (n=29) and an Agency Survey (n=52) distributed between January 2023 and June 2023 to all known shared micromobility operators and agencies.

Transportation Network Companies (TNCs) like Lyft, Uber, and their global counterparts have expanded around the world over the past decade and have changed the way that people travel around cities and regions. The individual mobility benefits provided by TNCs have been clear. Passengers can summon a vehicle quickly via smartphone from almost anywhere to take them almost anywhere, with advance communication on estimated wait time, travel time, and cost. TNCs may also provide users with added mobility benefits, especially for those living in areas where public transit service is infrequent or non-existent. However, the growing popularity of TNCs has forced important questions about their impacts on the overall transportation network. While past research has focused on many different aspects of TNC impacts, including their effects on travel behavior, modal shift, congestion, and other topics, there are still many important questions. This report advances the understanding of TNC effects on vehicle miles traveled (VMT), greenhouse gas (GHG) emissions, and personal vehicle ownership. The research also explores key questions regarding the impact of pooled TNC services, Lyft Shared rides and uberPOOL, and further investigates how TNCs alter the use of other transportation modes, including public transit.

Travelers are increasingly turning to smartphone applications for an array of transportation functions. Four types of transportation apps have emerged: 1) mobility apps; 2) connected vehicle apps; 3) smart parking apps; and 4) courier network service (CNS) apps. This chapter discusses the history and trends leading to the growth and development of transportation apps and summarizes key characteristics of 83 transportation apps identified through an Internet search cataloging transportation apps with more than 10,000 downloads each. Seventy-one percent of the 83 apps identified incorporated a real-time data function (e.g., traffic conditions, roadway incidents, parking availability, and public transit wait times). Additionally, the chapter reports on findings from a survey, conducted in spring 2016, of 130 app users who downloaded the RideScout mobility aggregator app (which ceased operations in August 2016). The survey, was asked questions about their use of mobility aggregators more generally, sought to understand how multimodal information apps shift travel behavior. The findings showed that most users of such apps would walk, drive alone, and carpool during a typical month. Fifty percent of respondents drove alone once or more per day. Twenty-five percent owned one vehicle, and 75% owned two or more vehicles. Thirty-nine percent of respondents reported that they drove less or much less due to the apps. Findings from the survey suggest that multi-modal app users do change their travel behavior in response to information provided, and they may contribute to a reduction in vehicle use.

Public bikesharing—the shared use of a bicycle fleet by the public—is an innovative mobility strategy that has recently emerged in major North American cities. Bikesharing systems typically position bicycles throughout an urban environment, among a network of docking stations, for immediate access. This paper discusses the modal shift that results from individuals participating in four public bikesharing systems in North America. The authors conducted an online survey (n =10,661 total sample), between November 2011 and January 2012, with members of four major bikesharing organizations (located in Montreal, Toronto, the Twin Cities, and Washington D.C.) and collected information regarding travel-behavior changes, focusing on modal shift, as well as public bikesharing perceptions. The survey probed member perceptions about bikesharing and found that a majority in the surveyed cities felt that bikesharing was an enhancement to public transportation and improved transit connectivity. With respect to modal shift, the results suggest that bikesharing generally draws from all travel modes. Three of the four largest cities in the study exhibited declines in bus and rail usage as a result of bikesharing. For example, 50% of respondents in Montreal reported reducing rail use, while 44% and 48% reported similar shifts in Toronto and Washington D.C., respectively. However, within those same cities, 27% to 40% of respondents reported using public transit in conjunction with bikesharing to make trips previously completed by automobile. In the Twin Cities, the dynamic was different, as 15% of respondents reported increasing rail usage versus only 3% who noted a decrease in rail use. In all cities, bikesharing resulted in a considerable decline in personal driving and taxi use, suggesting that public bikesharing is reducing urban transportation emissions, while at the same time freeing capacity of bus and rail networks within large cities.