Shared Mobility: Current Adoption, Use, and Potential Impacts on Travel Behavior
Regina Clewlow, Populus Gouri Shankar Mishra, University of California, Davis
Show Abstract
Shared mobility services have experienced significant
growth in adoption since the introduction of Uber, a ride-hailing service, in
2010. Although business models to support the sharing of vehicles (e.g.,
carsharing) have been present in the United States for more than 15 years, their
adoption has been somewhat limited to niche markets in dense, urban cities or
college campuses. To date, carsharing has attracted over 1.5 million members in
North America and close to 5 million globally. Conversely, new models of ‘shared
mobility,’ are estimated to have grown to more than 250 million users within
five years.
The rapid adoption of these new mobility services poses
significant challenges for transportation researchers, policymakers, and
planners, as there is limited information and data about how these services may
affect travel decisions and usage patterns. Given the long-range business,
policy, and planning decisions that are required to support transportation
infrastructure (including transit, roads, and vehicles), there is an urgent need
to collect data on the adoption of these new services, and in particular, their
potential impacts on travel choices.
This paper presents findings from a comprehensive travel
and residential survey deployed in seven major U.S. cities that included
questions on the adoption and use of carsharing and ride-hailing services. The
findings suggest that early adopters of ride-hailing services tend to be
younger, more highly educated, have higher incomes, and are more likely to
reside in dense urban areas.
Although we find that ride-hailing adopters have lower
levels of vehicle ownership than non-adopters, they are more likely to own a
vehicle than core transit users. Given that ride-hailing services are relatively
new, the majority of individuals report few changes in travel behavior. However,
we do find preliminary evidence that these services support the disposal of a
personal vehicle (9% of ride-hailing adopters reported having doing so) and a
reduction in personal driving (26% of ride-hailing adopters). Reported changes
in transit use by adopters are minimal; however, here we find early evidence
that ride-hailing serves as a substitute for bus services, and may serve as a
complement for commuter rail. While further research is needed, this study
presents early findings on the potential impacts that emerging shared mobility
services may have on travel behavior.
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17-05729
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Impacts of a Multimodal Mobility Offer on Travel Behavior and Preferences: Insights from a Survey Among Users of the First Mobility Station in Munich, Germany
Montserrat Miramontes, Technische Universitaet Muenchen Maximilian Pfertner, Technical University of Munich Hema Rayaprolu, University of Sydney Martin Schreiner, Landeshauptstadt München Gebhard Wulfhorst, Technical University of Munich
Show Abstract
The City of Munich, in cooperation with the local public
transport provider MVG, is testing a pilot project of a Mobility Station
(multimodal mobility hub connecting public transport and new sharing mobility
offers). The project’s goal is to provide sustainable mobility options that
allow citizens to be mobile without owning a car.
To evaluate the acceptance of the offer, as well as
short and long term effects on mobility behavior, we developed an online user
survey in close cooperation with the stakeholders and experts in the field of
sharing mobility.
The results provide insights on the awareness and
perception of the Mobility Station among users, their mobility patterns, current
degree of multimodality, as well as actual and potential changes on mobility
behavior and travel preferences due to the multimodal mobility offer.
Most users are young, male, and highly educated individuals with access to multiple
mobility options. Public transport plays a central role for daily mobility together
with the services they were identified to be customers of.
The high share of users that use different mobility services at
least once a month indicates some degree of multimodality.
Actual and potential changes in mobility behavior
towards multimodality were revealed. Some users declared to use other mobility
services more often. They appreciate the availability of different mobility
options and show interest in other
services and intermodal connections indicating that there is still potential to increase multimodal
behavior. Based on previous findings multimodality can contribute to reduce car use and
car ownership.
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17-00137
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Assessing Public Opinions on Uber as a Ridesharing Transportation System: Explanatory Analysis and Results of a Survey in the Chicago, Illinois, Area
Seyed Mahmoudifard, University of Illinois, Chicago Amirhassan Kermanshah, University of Illinois, Chicago Ramin Shabanpour, University of North Florida Abolfazl Mohammadian, University of Illinois, Chicago
Show Abstract
Transportation Network Companies (TNCs) have been facing
significant growth in the past few years. Due to remarkable effect of these
ridesharing alternatives on people`s travel behavior, travel demand modelers
need to modify the key assumptions of the current practical models that are
likely to be changed as the new travel modes emerge. In order to better
understand the TNCs as a new mode of transportation and to comprehend the
characteristics, preferences, and behavior of the people who use ridesharing
options, we have conducted an internet-based survey of Uber riders in Chicago
area. To analyze the effect of this alternative on utilization of other modes of
travel, a nested logit model is developed on the second choice of riders in the
absence of ridesharing mode. The results of estimated model highlight the
influencing factors in shifting mode of travel from passenger car or transit to
Uber.
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17-01198
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Can Autonomous Vehicles Reduce Car Mobility? Evidence from a Stated Adaptation Experiment in Belgium
Mario Cools, University of Liege Caroline Rongy, University of Liege Sabine Limbourg, University of Liege
Show Abstract
From literature, it is clear that the discussion about the potential benefits and drawbacks of autonomous vehicles is not finished. In order to provide insight into this discussion, this paper investigates different attitudes with respect to different key factors for the deployment of system of autonomous taxis. To this end, a stated adaptation experiment was carried out in Belgium in March 2016. To investigate which factors influence the variables of interest, i.e. (i) the number of minutes one is prepared to wait before an autonomous taxi picks up the person, (ii) the ownership of a private car when autonomous taxis are available, (iii) the willingness to share an autonomous taxi, (iv) the permittance for the autonomous vehicle to take a detour when it is beneficial for the society, and (v) the willingness to share your private agenda to ensure a timely autonomous taxi, different regression models are constructed. The results show that the considered explanatory factors only capture a small part of the variability of the five variables of interest. This is as signal that market segmentation might be very challenging. Besides, this is an indication that a broader range of factors should be included such as life-style factors and psychological constructs. Finally, this acknowledges the need for some skepticism with regard to the potential benefits of autonomous vehicles. The results are interesting for providing realistic boundaries and cross-classification in further simulation studies that look at the benefits of autonomous vehicles.
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17-06847
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Modeling Preferences for Smart Modes and Services: Case Study in Lisbon, Portugal
Charisma Choudhury, University of Leeds Lang Yang João de Abreu e Silva,
Instituto Superior Técnico Universidade de Lisboa
Moshe Ben-Akiva, Massachusetts Institute of Technology (MIT)
Show Abstract
In this research, we explore the acceptability of
several new and emerging travel options by presenting them alongside more
established measures like congestion pricing and improved public transport
systems. These include shared taxi (where passengers have the option to share
their ride with other travellers with similar routes, benefiting from lower
fares), one-way car rental (where
stackable light
electric vehicles can be picked up and dropped off at different points), and
school bus services for park and ride (where children younger than 10 can be
dropped off to be picked up by professional tutors). The acceptability and
willingness-to-pay for these modes have been tested in the context of Lisbon
using stated preferences (SP) techniques. The survey was extremely challenging
to design and analyse given the multi-dimensionality, heterogeneity in the type
of the influencing variables and the large choice set (9 modes, 5 departure
times, 2 occupancies leading to 135alternatives).A sequential choice set
presentation approach was used. The survey administered over the internet and
computer aided personal interviews included 2372 valid SP observations from 1248
respondents. Mixed logit models were used to capture the complex correlations
introduced due to the non-traditional survey design. Results indicated a
significant preference of one-way car rental and shared taxi for non-commute
trips. For commute trips, improved versions of traditional public transport
modes were favoured. These findings are expected to provide important
information to transportation planners and policy makers working to achieve
sustainable transportation systems in Lisbon as well as in other
cities.
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17-05568
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Behavioral Choice Model of the Use of Carsharing and Ride-Sourcing Services
Felipe Dias, University of Texas, Austin Patricia Lavieri, University of Melbourne Venu Garikapati, National Renewable Energy Laboratory (NREL) Sebastian Astroza, Universidad de Concepcion Ram Pendyala, Arizona State University Chandra Bhat, University of Texas, Austin
Show Abstract
There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.
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17-06359
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Estimating the Trip Generation Impacts of Autonomous Vehicles on Car Travel in Victoria, Australia
Long T. Truong, La Trobe University Chris De Gruyter, RMIT University Graham Currie, Monash University Alexa Delbosc, Monash University
Show Abstract
Autonomous vehicles (AVs) potentially increase vehicle
travel by reducing travel and parking costs and by providing improved mobility
to those who are too young to drive or older people. The increase in vehicle
travel could be generated by both trip diversion from other modes and entirely
new trips. Existing studies however tend to overlook AVs’ impacts on entirely
new trips. There is a need to develop a methodology for estimating possible
impacts of AVs on entirely new trips across all age groups. This paper explores
the impacts of AVs on car trips using a case study of Victoria, Australia. A new
methodology for estimating entirely new trips associated with AVs is proposed by
measuring gaps in travel need at different life stages. Results show that AVs
would increase daily trips by 4.14% on average. The 76+ age group would have the
largest increase of 18.5%, followed by the 18-24 age group and the 12-17 age
group with 14.6% and 11.1% respectively. If car occupancy remains constant in AV
scenarios, entirely new trips and trip diversions from public transport and
active modes would lead to a 7.31% increase in car trips. However increases in
car travel are substantially magnified by reduced car occupancy rates, a trend
evidenced throughout the world. Car occupancy would need to increase by at least
5.3% to 7.3% to keep car trips unchanged in AV scenarios.
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17-00317
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Tracking a System of Shared Autonomous Vehicles Across the Austin, Texas, Network Using Agent-Based Simulation
Jun Liu, University of Alabama Kara M. Kockelman, University of Texas, Austin Patrick Boesch, ETHZ - Swiss Federal Institute of Technology Francesco Ciari, Ecole Polytechnique de Montreal
Show Abstract
This study provides a large-scale micro-simulation of
transportation patterns in a metropolitan area reliant on a system of shared
autonomous vehicles (SAVs). The six-county Austin, Texas region is used for its
land use patterns, demographics, networks and general travel behaviors. The
MATSim toolkit is applied here since it runs quickly on large networks while
allowing modelers to track individual travelers and individual vehicles, with
great temporal and spatial detail. The main purpose of using MATSim in this
study is to get the executable travel plans for individuals competing resources
of time and space of road networks in Austin area. Having such travel plans
(with trip start time, locations, distances, and routes), SAVs were introduced
to serve travelers who request SAVs. The SAV requests were simulated through a
stochastic process of mode choices based on four possible fare rates of using a
SAV ($0.2, $0.5, $0.75, and $1.0 per mile). The mode choice was discussed for
travelers who have access to privately owned vehicles (including AVs), and for
those who do not have the access. Mode choice results showed that lower fare
rates gain preferences from the long-distance travelers because of the reduced
burden of in-vehicle activities in SAVs, relative to human-driving vehicles
(HVs). For travelers who do not own a vehicle, SAVs (with four possible fare
rates) seem to be preferable for trips shorter than 10 miles which account for
80% of travels in Austin area. Therefore, public transit services may be easily
replaced by SAVs once SAVs are on road in this area. Under four possible fare
rates ($0.2, $0.5, $0.75, or $1.0 per mile), four levels of demand for SAVs were
obtained: 36.6%, 12.1 %, 8.0%, and 6.4% of trips respectively requested SAVs.
Then SAVs were simulated to serve these requests. Simulation results showed that
with the increase in SAV fleet size, more SAV requests can be served within 10
minutes; and the fare rate $0.5 per mile is associated with the greatest vehicle
replacement. Reasons are discussed in the paper. Further this study discussed
the mobility and sustainability benefits of SAVs. If SAV fare rate is low enough
(not necessarily lower than the cost of using a HV), SAV users can travel a few
extra miles compared to HV travelers. Also, the extra VMTs by SAVs are not
sizeable enough to trade off the benefits gained from AV’s advancements. This
study offers insights for industrial innovators who seek to implement SAVs in a
metropolitan area, as well as transportation planners and policy (or decision-)
makers who must be ready for the arrivals of SAVs in near
future.
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17-00469
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Are We Ready to Embrace Connected and Self-Driving Vehicles? A Case Study of Texans
Kara M. Kockelman, University of Texas, Austin Prateek Bansal, Cornell University
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P17-21423
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Review of Changing Prices and Tax Levels for Neighborhood Car Sharing in the United States: 2011-2016
Joseph Schwieterman, DePaul University
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P17-21582
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What Drives Millennials: Comparison of Vehicle Miles Traveled Between Millennials and Generation X in California
Kate Tiedeman, University of California, Davis Giovanni Circella, University of California, Davis Farzad Alemi, University of California, Davis Rosaria Berliner, University of California, Davis
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P17-21584
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