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How Uber affects public transit ridership is a relevant policy question facing cities worldwide. Theoretically, Uber’s effect on transit is ambiguous: while Uber is an alternative mode of travel, it can also increase the reach and flexibility of public transit’s fixed-route, fixed-schedule service. We estimate the effect of Uber on public transit ridership using a difference-in-differences design that exploits variation across U.S. metropolitan areas in both the intensity of Uber penetration and the timing of Uber entry. We find that Uber is a complement for the average transit agency, increasing ridership by five percent after two years. This average effect masks considerable heterogeneity, with Uber increasing ridership more in larger cities and for smaller transit agencies.
On May 7, 2016, residents of Austin, Texas, voted against Proposition 1, which would have allowed ridesourcing/transportation networking companies (TNCs) to continue using their own background check systems. The defeat of the proposition prompted Uber and Lyft to suspend services in Austin indefinitely. The disruption provided for a natural experiment to evaluate the impact of Uber and Lyft on users’ travel demand and the supply side implications of the entry of new players. Our paper focuses solely on the demand side user response to the disruption. In examining the impact, we conducted an online survey that combines stated and revealed preference questions (N=1,840) of former Uber and/or Lyft users in Austin to explore the effect of the disruption on travel behavior. In order to test our hypothesis of the impact of the service suspension on changes in travel mode choice and trip frequency we used regression analyses to model both the before and after travel behavioral pattern.
Using data derived from 597 face-to-face interviews with ride-hailing users in Chengdu (China), we examined the influence of ride-hailing on travel frequency and mode choice and further analyzed what the main determinants for these are.
The growth of app-based ridesharing, microtransit, and TNCs presents a unique opportunity to reduce congestion, energy use, and emissions through reduced personal vehicle ownership and increased vehicle occupancy, the latter of which is largely dependent on the decisions of individual travelers to pool or not to pool. This research provides key insights into the policy levers that could be employed to reduce vehicle miles traveled and emissions by incentivizing the use of pooled on-demand ride services and public transit. We employ a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San FranciscoBay Area) to examine the opportunities and challenges for drastically expanding the market for pooling, taking into account the nuances in emergent travel behavior and demand sensitivity across on-demand mobility options.
Even as ride-hailing has become ubiquitous in most urban areas, its impacts on individual travel are still unclear. This includes limited knowledge of demand characteristics (especially for pooled rides), travel modes being substituted, types of activities being accessed, as well as possible trip induction effects. The current study contributes to this knowledge gap by investigating ridehailing experience, frequency, and trip characteristics through two multi-dimensional models estimated using data from the Dallas-Fort Worth Metropolitan Area. Ride-hailing adoption and usage are modeled as functions of unobserved lifestyle stochastic latent constructs, observed transportation-related choices, and sociodemographic variables. The results point to low residential location density and people’s privacy concerns as the main deterrents to pooled ridehailing adoption, with non-Hispanic Whites being more privacy sensitive than individuals of other ethnicities.
This report analyzes EV use in TNC fleets from 2016 through 2018. Data sets from TNCs and charging service providers are used to analyze charging and use patterns of EVs within TNC fleets. The emissions benefits of EV use withing TNC fleets is quanitfied, assessments of EVs to perform TNC services are made, and the effects of EV use within TNC fleets on charging behavior of non-TNC EVs is understood.
In this study, newly available Chicago transportation network provider data were explored to identify the extent to which different socioeconomic, spatiotemporal, and trip characteristics affect willingness to pool (WTP) in ridehailing trips. Multivariate linear regression and machine-learning models were employed to understand and predict WTP based on location, time, and trip factors. The results show intuitive trends, with income level at drop-off and pickup locations and airport trips as the most important predictors of WTP. Results from this study can help TNCs and cities devise strategies that increase pooled ride-hailing, thereby reducing adverse transportation and energy impacts from ride-hailing modes.
Transportation network companies (TNCs) such as Uber and Lyft have grown tremendously over the last decade, particularly in the San Francisco Bay Area. Nonetheless, relatively little publicly available data exist about the users of these services, their travel behaviors, volume of use, the times and locations of TNC trips, and how TNC services are affecting transportation system performance overall. This paper describes the methods and descriptive results of the first large-scale smartphone-based TNC user survey conducted in the California Bay Area in the fall 2018 and spring of 2019.
On-demand ridesourcing services from transportation network companies (TNCs), such as Uber and Lyft, have reshaped urban travel and changed externality costs from vehicle emissions, congestion, crashes, and noise. To quantify these changes, this study simulated replacing private vehicle travel with TNCs in six U.S. cities.
This dissertation work addresses three fundamental bikeshare equity problems. Chapter 2 examines whether bikeshare systems have targeted specific populations. Chapter 3, extends knowledge about how to estimate bikeshare ridership in underserved communities. This research fills a gap by analyzing the current utilization rates of bikeshare systems among disadvantaged populations. Chapter 4, develops a destination competing model to estimate destination choices and analyze spatial patterns.
The 2020 report quantifies the impact of the COVID-19 pandemic on shared micromobility and demonstrates the industry’s response and resilience during this time to provide essential mobility services. The report also compares trends from 2019 and presents new research that shows the impact of the industry in North America.
"Sacramento Regional Transit District (SacRT) has adopted a groundbreaking micromobility strategy to address the “first mile/last mile problem.” The agency has partnered with JUMP, an electric micromobility provider, to offer on-demand access to and from light rail stations."
"Developed for cities, by cities, this guidance outlines best practices for cities and public entities regulating and managing shared micromobility services on their streets."
"The City of Santa Monica designed a pilot program to test shared electric scooters and bikes operated by private companies, using a flexible approach that could be responsive to community needs, technological advancements, and a nascent and evolving industry."
The introduction of shared autonomous vehicles (SAVs) in cities could potentially increase the number of vehicle miles traveled (VMT). The implementation of dynamic ride-sharing (DRS) systems could limit this increase and potentially result in a net reduction in VMT.
This resource studies whether mobility as a service (MaaS) can be used to promote shared modes. Initial results from surveys showed that MaaS bundles can be used as a tool to introduce more travelers to shared modes.
Large San Diego parking company Ace Parking has reported lower parking rates due to the increasing popularity of Uber and Lyft.
Self-driving cars will be first available to robotaxi-fleet operators, not private owners. This availability restriction comes from the expensive nature of LIDAR sensors that make the sensors themselves more expensive than the rest of the vehicle. The safety and reliability of automated vehicles also impacts their ability to be privately owned, at least at first. Safe and reliable vehicle operation is easier to achieve when the vehicles operate within a geographic range that has been mapped in detail, meaning automated vehicles will mainly operate in city centers in their early stages of adoption. These considerations driving automated vehicles toward fleet ownership will have impacts on many areas of the automotive industry.
Sustainable, inclusive, prosperous, and resilient cities depend on transportation that facilitates the safe, efficient, and pollution-free flow of people and goods, while also providing affordable, healthy, and integrated mobility for all people. The pace of technology-driven innovation from the private sector in shared transportation services, vehicles, and networks is rapid, accelerating, and filled with opportunity. At the same time, city streets are a finite and scarce resource.These principles, produced by a working group of international NGOs, are designed to guide urban decision-makers and stakeholders toward the best outcomes for all.
The Future of Work in Cities contrasts the realities cities face today with the ways they are planning for tomorrow, exploring the means by which cities can exploit innovative opportunities while realigning local governance priorities.
This report was developed to inform a Federal Highway Administration (FHWA) workshop, held in September 2015, exploring emerging technological trends in transportation. This paper provides an overview of select developing transportation technologies and includes a discussion of the policy implications of these new technological trends.
As a strategic roadmap, this document does not commit to specific budgets or metrics but serves as a vision and communications document to capture a wide variety of viewpoints into Austin’s mobility future. This roadmap will be incorporated into the larger Austin Strategic Mobility Plan to be finalized and approved at a future date. Critical to the development of the broader Mobility Plan will be an extensive analysis of the resource requirements for implementation of this shared, electric and autonomous vehicle (e-av) Roadmap.
This white paper discusses the forces affecting U.S. passenger travel, the permanence of which is often unclear. We explore travel demand’s relationship with explanatory factors such as economic activity, gas prices, urban form, socio-demographic traits and generational effects, the expanding availability of travel options (including electronic alternatives to travel) and technological innovations in the transportation sector (including the advent of emerging transportation and shared mobility services). We discuss how these factors modify the alternatives available to travelers, the characteristics of each alternative, and the way travelers perceive and evaluate these characteristics.
This document provides background on micromobility and what it is, answers the question "Who uses shared micromobility?" and identifies current policies and practices.
The researcher examined six jurisdictions: three in Canada and in from the United States. In helping frame the issue for B.C. and—more specifically— the Vancouver metropolitan area context, the researcher conducted primary research to understand the accessibility challenges in the regional context and to help frame the topic of accessibility within the for-hire sector.
Texas is one of the fastest growing states in the nation, and its growth is expected to continue, supported by diversity in its economy, geography, and population. The challenge of prioritizing limited resources in this environment requires a proactive approach to travel demand management. This project provides guidance for TxDOT in its planning and mobility efforts and in understanding the viability of various alternative mobility programs.This report describes research of best practices and lessons learned from mobility programs. The research describes executive interviews, focus groups, and surveys to obtain details and document perspectives of the varying stakeholder groups. The research produced a guidebook that will aid TxDOT in determining how to best identify and implement alternative mobility programs in a given region as part of its planning and mobility efforts.
This article talks about the Electric Moped as a new mobility launch in Brooklyn. This e-motorcycles can serves as affordable people and provide longer trip distance. How it can integrate with transit, bikeshare and other modes need to be considered.
This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
"This paper identifies three promising applications of new mobility services by public transit agencies, and presents economic, social, and environmental modeling that illustrate the value of such partnerships to mass transit systems."
TCRP Report 108 presents the research team’s findings on the: Current and potential roles of car-sharing in enhancing mobility as part of the transportation system; Characteristics of car-sharing members and neighborhoods where car-sharing has been established; Environmental, economic, and social impacts of car-sharing; Ways in which partner organizations have tried to promote car-sharing; Barriers to car-sharing and ways to mitigate these barriers; and Procurement methods and evaluation techniques for achieving car-sharing goals.
This paper discusses the history of shared mobility within the context of the urban transportation landscape, first in Europe and Asia, and more recently in the Americas, with a specific focus on first- and last-mile connections to public transit. The authors discuss the known impacts of shared mobility modes—carsharing, bikesharing, and ridesharing—on reducing vehicle miles/kilometers traveled (VMT/VKT), greenhouse gas (GHG) emissions, and modal splits with public transit. The future of shared mobility in the urban transportation landscape is discussed, as mobile technology and public policy continue to evolve to integrate shared mobility with public transit and future automated vehicles.
"With this white paper, we hope to explore the rapidly changing and disruptive nature of micromobility, and provide city officials useful information to deploy micromobility options in a safe, profitable and equitable way. We begin by defining micromobility and exploring the recent history of docked and dockless bikes and e-scooters. We then explore the challenges and opportunities facing cities, and illustrate a few examples of cities that are addressing these issues head-on. We conclude with a set of recommendations cities can consider as they work to regulate these new mobility technologies."
"This white paper provides a framework and examples to assist transportation agencies in anticipating and planning for shared mobility as part of a higher-performing regional multimodal transportation system. It synthesizes noteworthy practices in 13 metropolitan areas as of spring/summer 2017 collected from online research and conversations with planning practitioners, identifies challenges and opportunities, and provides recommendations for future research needed to improve planning practices related to shared mobility."
"This report consists of nine chapters. Chapter 2 describes the effects of technology on transportation in general, the innovative services relevant to this report, what is known about the use of these services, and their potential impacts. Chapter 3 explains the existing regulatory structure of the taxi, sedan, and limousine industries and the challenges to that existing structure presented by the rise of TNCs. Chapter 4 presents an economic framework for address- ing those challenges. Chapters 5 through 8 then review specific issues facing shared mobility services: Chapter 5 examines labor and employment issues; Chapter 6 addresses personal security for drivers and passengers and safety for the public; Chapter 7 reviews insurance issues; and Chapter 8 looks at issues of access and equity. Chapter 9 presents the overall conclusions resulting from this study and the committee’s recommendations for policy makers and regulators who must consider whether and how to regulate these new services to serve public policy goals, and outlines research needs."
"WRI’s research provides initial findings regarding the feasibility and impact of carsharing in emerging markets, though many uncertainties remain. Limitations of the study include a light methodology that only scratched the surface of these important issues, and uncertain transferability from Hangzhou and Bangalore. In addition, the relative absence of carsharing (and research on carsharing) in emerging markets limits the extent to which observations can be interpreted and extrapolated. That said, this study provides important early findings on the current industry, barriers, and service features; and suggests significant potential for carsharing in emerging markets. The results could help inform more in-depth research, operational approaches, and public policy."
This study aims at capturing the users’ preference, while considering investors’ limitations and societal cost and benefits of each mode. The problem is defined as a mixed-integer non-liner problem, with non- linear objective function and constraints. Because of the computationally challenging nature of the problem, a metaheuristic algorithm based on simulated annealing algorithm is proposed for its solution. The performance of the algorithm is tested in this study and convergence patterns are observed.
"This paper presents findings from a comprehensive travel and residential survey deployed in seven major U.S. cities, in two phases from 2014 to 2016, with a targeted, representative sample of their urban and suburban populations. The purpose of this report is to provide early insight on the adoption of, use, and travel behavior impacts of ride-hailing. The report is structured around three primary topics, key findings of which are highlighted below."
"This paper advances understanding of modal shifts caused by bikesharing through a geographic evaluation of survey data collected through recently completed research. Working with surveys in two of the cities surveyed in the United States, the authors analyze the attributes of individuals who increased and decreased their rail and bus usage in a geospatial context along with the population density of respondent home and work locations. The results inform the nuances of bikesharing impacts on the modal shift of urban residents with respect to public transportation."
The sharing economy and on-demand services are weaving their way into the lives of (some) Americans, raising difficult issues around jobs, regulation and the potential emergence of a new digital divide. This report offers a detailed examination of three different services that exemplify the shared, collaborative and on-demand economy: ride-hailing apps, home-sharing platforms and crowdfunding services.
This blog post summarizes a larger article written by University of Michigan faculty member Saif Benjaafar's research on smart technology. It specifically focuses on his analysis of ride-sharing companies.
In recent years, economic, environmental, and social forces have quickly given rise to the “sharing economy,” a collective of entrepreneurs and consumers leveraging technology to share resources, save money, and generate capital. Homesharing services, such as Airbnb, and peer-to-peer carsharing services, such as Getaround, have become part of a sociodemographic trend that has pushed the sharing economy from the fringe and more to the mainstream. The role of shared mobility in the broader landscape of urban mobility has become a frequent topic of discussion. Major shared transportation modes—such as bikesharing, carsharing, ridesourcing, and alternative transit services—are changing how people travel and are having a transformative effect on mobility and local planning.
We review the history, current developments, projected future trends and environmental impacts of automated vehicles (AVs) and on-demand mobility, and explore potential synergies. Many automobile manufacturers and Google plan to release AVs between 2017 and 2020, with potential benefits including increased safety, more efficient road use, increased driver productivity and energy savings. Combining on-demand mobility and AVs may amplify adoption of both, and further lower energy use and GHG emissions through the use of small, efficient shared AVs.
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