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Ride-hailing is a climate problem for two primary reasons. First, a typical ride-hailing trip is more polluting than a trip in a personal car, mainly as a result of “deadheading”the miles a ride-hailing vehicle travels without a passenger between hired rides. The second reason is that ride-hailing is not just replacing personal car trips; instead, it is increasing the total number of car trips. In the absence of ride-hailing, many would-be ride-hailing passengers would take mass transit, walk, bike, or forgo the trip. This report focuses on ride-hailing, but many of its findings and recommendations apply to taxis as well. For example, electrification, increased pooling, and improved coordination with mass transit would lessen the negative impacts of taxi service on transportation systems and the environment.
Ridesharing holds promise as a more efficient and sustainable version of emergent ride-hailing services. However, the adoption of pooled services in which individuals pay a reduced fare to share a portion of their ridehailing trip with other passengers has substantially lagged in popularity to the standard single-party services offered by Uber and Lyft in many American cities. To help guide policies and programs targeted at increasing pooling shares, this study analyzes data collected during fall 2017 from an in-vehicle intercept survey of 944 ride-hailing passengers in the Greater Boston region. These data, which describe the socioeconomic background, mobility options, and trip context of single-party and pooled ride-hailing survey respondents, were used to identify differences in the trip patterns and individual characteristics of passengers adopting the two service types and then estimate the individual-level social and trip-related predictors of ridesharing for different purposes.
The impacts of ride-hailing services on the transportation system have been immediate and major. Yet, public agencies are only beginning to understand their magnitude because the private ride-hailing industry has provided limited amounts of meaningful data. Consequently, public agencies responsible for managing congestion and providing transit services are unable to clearly determine who uses ride-hailing services and how their adoption influences established travel modes, or forecast the potential growth of this emergent mode in the future. To address these pressing questions, an intercept survey of ride-hailing passengers was conducted in the Greater Boston region in fall 2017. The responses, which enabled a robust description of ride-hailing passengers for the region, were used to analyze how new on-demand mobility services such as Uber and Lyft may be substituting travel by other modes.
This report builds on an on-going research effort that investigates emerging mobility patterns and the adoption of new mobility services. In this report, the authors focus on the environmental impacts of various modality styles and the frequency of ridehailing use among a sample of millennials (i.e., born from 1981 to 1997) and members of the preceding Generation X (i.e., born from 1965 to 1980). The total sample for the analysis included in this report includes 1,785 individuals who participated in a survey administered in Fall 2015 in California. In this study, the researchers focus on the vehicle miles traveled, the energy consumption, and greenhouse gas (GHG) emissions for transportation purposes of various groups of travelers.
Transportation 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.
Ride-hailing such as Uber and Lyft are changing the ways people travel. Despite widespread claims that these services help reduce driving, there is little research on this topic. This research paper uses a quasi-natural experiment in the Denver, Colorado, region to analyze basic impacts of ride-hailing on transportation efficiency in terms of deadheading, vehicle occupancy, mode replacement, and vehicle miles traveled (VMT).
In 2020, the microtransit company. “Via” partnered with Jersey City to provide on-demand car rides to underserved communities whose mass public transit routes had been canceled due to low ridership during the 2020 Covid-19 pandemic. The company aims to complement existing transit which operates comprehensively and frequently in the central areas of Jersey City. Via offers rides outside of this well-served district but not within to minimize competition with public transit. The same company launched in Arlington, Texas in 2017. Arlington, which was the largest city in America without a public transit system, opted to contract Via to provide an alternative transportation mode to driving in a personal vehicle. The on-demand service offers point-to-point rides within Arlington and connections to intercity train stations to Dallas-Fort Worth.
Microtransit—shared transportation that offers dynamic routing and scheduling to efficiently match demand—is emerging as an ally to fixed-route services. However, its positive impacts are too often constrained by the politics and economics imposed by existing transit infrastructure. This paper proposes a solution that ‘‘flips transit on its head.’’ By rapidly prototyping microtransit services across cities and analyzing supply-demand mismatches, it is possible to launch truly data-driven transit services. To illustrate the framework, a unique dataset generated from a year of Dallas Area Rapid Transit’s GoLink service, one of the largest ondemand microtransit services in North America, is used. Mapping and machine learning are combined to empower planners to ‘‘join the dots’’ when (re)designing fixed-route transit lines. It is shown that microtransit should not simply fill in the gaps left by inefficiently scheduled bus routes: by incorporating it fully into their planning processes, cities and transit agencies could dramatically reverse the fortunes of public transit.
Many cities are rolling out bike share programs. However, few studies have evaluated how bike share systems (BSS) are used to quantify their sustainability impacts. This study proposes a Bike Share Emission Reduction Estimation Model (BS-EREM) to quantify the environmental benefits from bike share trips and compare the greenhouse gas (GHG) emission reductions from BSS in eight cities in the United States, including New York, Chicago, Boston, Philadelphia, Washington D.C., Los Angeles, San Francisco, and Seattle. The BS-EREM model stochastically estimates the transportation modes substituted by bike share trips, considering factors such as trip distance, trip purpose, trip start time, the accessibility of public transits, and historical distributions of transportation mode choices.
Jarrett Walker, author of "Human Transit: How Clearer Thinking about Public Transit Can Enrich our Communities and Lives," writes about the costs and benefits of microtransit on his blog, "Human Transit". Walker is skeptical of Microtransit. He argues that it is spacially, economically, and fiscally inefficient and should only be used in very rare and specific cases.
Bike enthusiasts argue that bikesharing programs can be an important element of sustainable mobility planning in the urban cores of large metropolitan areas. However, the objective longterm impact of bikesharing on reducing auto-dependence is not well-examined, as prior studies have tended to rely on self-reported subjective mode substitution effects. We use a unique longitudinal dataset containing millions of geo-referenced vehicle registrations and odometer readings in Massachusetts over a six-year period - the Massachusetts Vehicle Census - to examine the causal impact of bikesharing on various metrics of auto-dependence in the inner core of Metro Boston.
This report builds on an on-going research effort that investigates emerging mobility patterns and the adoption of new mobility services. In this report, the authors focus on the environmental impacts of various modality styles and the frequency of ridehailing use among a sample of millennials (i.e., born from 1981 to 1997) and members of the preceding Generation X (i.e., born from 1965 to 1980). The total sample for the analysis included in this report includes 1,785 individuals who participated in a survey administered in Fall 2015 in California. In this study, the researchers focus on the vehicle miles traveled, the energy consumption and greenhouse gas (GHG) emissions for transportation purposes of various groups of travelers.
Vehicle sharing services (bikeshare, carshare, and e-scooters) offer the potential to improve mobility and accessibility for disadvantaged populations. This article reviews research related to equity and vehicle sharing, focusing on race/ethnicity, income, gender, age, and disability. We find evidence of disparities in use of shared vehicles, which is only partly explained by lack of physical proximity. Some studies reveal additional barriers to use, particularly for bikesharing.
This study analyzes the relation between shared mobility services and greenhouse gases (GHGs) emissions by using a nationally representative sample of US young adults. We conduct a comprehensive analysis based on the data collected in the 2017 National Household Travel Survey (NHTS).
Shared micro-mobility services are rapidly expanding yet little is known about travel behaviour. Understanding mode choice, in particular, is quintessential for incorporating micro-mobility into transport simulations in order to enable effective transport planning. We contribute by collecting a large dataset with matching GPS tracks, booking data and survey data for more than 500 travellers, and by estimating a first choice model between eight transport modes, including shared e-scooters, shared e-bikes, personal e-scooters and personal e-bikes.
This study aims to quantitatively estimate the environmental benefits of bike sharing. Using big data techniques, we estimate the impacts of bike sharing on energy use and carbon dioxide (CO2) and nitrogen oxide (NOX) emissions in Shanghai from a spatiotemporal perspective.
Technology-enhanced bikeshare features a dockless system with GPS-tracked electric bikes and a mobile app. As an additional transportation mode, it offers users greater accessibility and more flexibility compared to traditional bikeshare. This paper examines the causal impact of a tech-enhanced bikeshare program on public transit ridership, using evidence from a mid-sized metropolitan area in the Midwest of the United States.
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.
This paper synthesizes and reviews all literature regarding autonomous vehicles and their impact on GHG emissions. The paper aims to eliminate bias and provide insight by incorporating statistical analysis.
In this report, the Portland Bureau of Transportation (PBOT) evaluates the second e-scooter pilot project conducted in Portland, Oregon. PBOT used data and feedback from the community to evaluate the e-scooter pilot project, specifically evaluating "the potential for e-scooters to advance equity, ease traffic congestion and reduce climate-harming emissions."
Modal race between different freight transport modes, which must include at least one cargo bike or trike. An origin, destination, time of the day and cargo weight are set. Each participant loads the cargo and starts travelling at the same time. Each one must carry a chronometer and there will be independent supervisors timing the participants as well. When arriving at the set destination, travel time is recorded for each participant and compared. Modelling costs, pollutant and GHG emissions, as well as predicted travel time, is useful to show additional benefits of using micromobility for freight transport. Using mobile apps to show positions in real time and streaming can also help the activity be more engaging and attractive.
What are transportation options for people with disabilities in San Francisco and how have these options been impacted by TNCs?
This study examines the impacts of transportation network companies (TNCs) such as Uber and Lyft on trends in travel, parking, car-rental and the economy by analyzing the effects of ride-hailing at four major airports in the U.S.
This paper seeks to understand the potential causes of a decline in transit ridership by examining data from seven major U.S. cities – Boston, New York City, Washington D.C., Chicago, Denver, San Francisco and Los Angles.
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.
Despite a growing economy, there has been a decrease in the average miles driven due in part to alternate modes of transportation and more opportunities to work and shop remotely.
In an effort to reduce personal vehicle usage and its carbon footprint Minneapolis has launched new “mobility hubs” where multiple modes of low- or no-carbon transportation are available in one convenient place.
This article discusses an experiment conducted to investigate the factors contributing to travel mode choice. The experiment found that subjects were more inclined to chose cars over other forms of transportation, even when another form of transportation might have been more ideal based on cost or travel time. This demonstrates the concept of car stickiness, where travelers are heavily biased towards traveling in cars over other forms of transportation.
Despite national averages of shrinking transit ridership, seven United States cities have seen increased ridership. These cities have seen growth because of their efforts to improve or expand their bus services.
This paper surveys emerging mobility services in order to highlight the key points of the concept of “mobility as a service” and to develop an index that evaluates the level of mobility integration of each service.
Ride-hailing services like Uber and Lyft are changing how travelers get to the airport. This trend is negatively affecting airports, which depend on parking, rental car, and taxi fees as a primary source of revenue.
“Taking Uber or Lyft to and from work and to run errands might seem more expensive than driving yourself–but in many cases, relying on a ride-hailing service is cheaper than buying and using a car of your own. A new calculator compares both scenarios, and might help you decide to ditch car ownership entirely.”
In New York City, conflict has erupted between private ride-hailing services and neutral third-party mobility platforms battling for bikeshare access. Companies like Lyft and Mobility as a Service (MaaS) providers such as Transit both want to remove the friction of switching in between modes for commuters, however the ride-sharing companies want to build brand loyalty while third-party MaaS platforms want to offer access to all mobility options available.
The NUMO New Mobility Atlas is an extensive, data-driven platform mapping the rapid proliferation of new mobility, including micromobility, in cities around the world. Developed in partnership with partner organizations from the public and private sectors, the Atlas uses open data to track which shared transportation options — currently dockless scooters, bicycles and mopeds — are available in cities.
This is a fact sheet suitable for use as a printed handout on Urbanism Next's topline research findings regarding TNCs.
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 purpose of this report is to analyze potential impacts and offer recommendations for the cities of Gresham and Eugene, OR, to understand the potential impacts of new mobility technologies – with an emphasis on autonomous vehicles (AVs) – and prepare a policy and programmatic response. While Gresham and Eugene are case studies, it provides mid-sized communities information on how new mobility services could impact their communities and what they can do about it, from broad strategies to specific policy responses. While this work focuses on the various new mobility and goods delivery services that currently exist, the framework that is discussed here is also applicable to emerging technologies that haven’t yet been introduced, such as autonomous vehicles (AVs).
This purpose of this report is to help the cities of Gresham, Oregon and Eugene, Oregon understand the potential impacts of new mobility technologies – with an emphasis on autonomous vehicles (AVs) – and prepare a policy response. While Gresham and Eugene are case studies, it provides communities of all sizes information on how new mobility services could impact their communities and what they can do about it, from broad strategies to specific policy responses. While this work focuses on the various new mobility and goods delivery services that currently exist, the framework that is discussed here is also applicable to emerging technologies that haven’t yet been introduced, such as AVs.
Metro data enables deep analysis of cyclist and pedestrian activity including popular or avoided routes, peak commute times, intersection wait times, and origin/destination zones. Metro processes this data for compatibility with geographic information system (GIS) environments.
The Portland Bureau of Transportation (PBOT) report provides a preliminary analysis of an E-Scooter Pilot Program conducted in Portland, Oregon, from July 2018 through November of the same year. The report includes ridership data, public perception and concerns, areas for improvement, and proposed next steps for implementing e-scooters in Portland.
The Go Centennial pilot was the first pilot project in the country where a government or transit agency fully subsidized first and last-mile rides provided by a transportation network company (in this case Lyft). The Go Centennial pilot was launched in Centennial, Colorado on August 2016 and ran for six months until February 2017. This final report is one of the most comprehensive evaluations of a TNC partnership pilot, and details the goals, preexisting conditions, and procurement and design of the pilot. The report concludes with a qualitative and quantitative analysis of the pilot and a set of lessons learned and key takeaways.
This paper, for the first time, presents comparable projections of travel behavior impacts of the introduction of autonomous vehicles (AVs) into the private car fleet for two countries, namely the USA and Germany. The focus is on fully autonomous vehicles (AVs) which allow drivers to engage in other activities en route. Two 2035 scenarios – a trend scenario and an extreme scenario – are presented for both study countries. For these projections, we combine a vehicle technology diffusion model and an aspatial travel demand model. Factors that influence AV impact in the behavioral model are mainly new automobile user groups, e.g. travelers with mobility impairments, and altered generalized costs of travel, e.g. due to a lower value of travel time savings for car travel. The results indicate that AV penetrations rates might be higher in Germany (10% or 38% respectively) than in the USA (8% or 29% respectively) due to a higher share of luxury cars and quicker fleet turnover. On the contrary, the increase of vehicle mileage induced by AVs is not higher in Germany (+2.4% or +8.6% respectively) than in the USA (+3.4% or +8.6% respectively). This is mainly due to the lack of mode alternatives and lower fuel costs resulting in a higher share of travel times among the total generalized costs of travel in the USA. These results clearly indicate that context factors shaped by national policy will influence AV adoption and impact on travel demand changes. Based on these results the paper draws policy recommendations which will help to harness the advantages of AVs while avoiding their negative consequences.
This report summarizes the major assumptions, predictions and forecasts that have been made for autonomous vehicles. It emphasizes their impact and takes focus on the effects it will have on previously immobile people and what it will take to integrate them legislatively.
"Transit ridership fell in 31 of 35 major metropolitan areas in the United States last year, including the seven cities that serve the majority of riders, with losses largely stemming from buses but punctuated by reliability issues on systems such as Metro, according to an annual overview of public transit usage."
Inclusive of manufacturing, transportation to the US, and the use phase, this study looks at the environmental impact of e-scooters compared to the use of alternative modes of transportation.
This report combines recently published research and newly available data from a national travel survey and other sources to create the first detailed profile of TNC ridership, users and usage. The report then discusses how TNC and microtransit services can benefit urban transportation, how policy makers can respond to traffic and transit impacts, and the implications of current experience for planning and implementation of shared autonomous vehicles in major American cities.
"Our City of the Future: Technology and Mobility report is meant to help city leaders understand, imagine and plan for the coming changes in the urban environment that will affect how we all move from one place to another."
The survey results described here provide a new window into ride-hailing utilization in the Boston Region. Our findings confirm many widespread assumptions about ride-hailing, but also provide new insights into previously unexplored and unmeasured topics. Ride-hailing is used by a wide variety of Metro Boston residents, and riders are relatively representative of the region in terms of race and income.
Based on the 2001 and 2009 National Household Travel Surveys, this paper analyzes trends and determinants of multimodal car use in the U.S. during a typical week by distinguishing between (1) monomodal car users who drive or ride in a car for all trips, (2) multimodal car users who drive or ride in a car and also use non-automobile modes, and (3) individuals who exclusively walk, cycle, and/or ride public transportation. We find that during a typical week a majority—almost two thirds—of Americans use a car and make at least one trip by foot, bicycle, or public transportation. One in four Americans uses a car and makes at least seven weekly trips by other modes of transportation. Results from multinomial and logistic regression analyses suggest there may be a continuum of mobility types ranging from monomodal car users to walk, bicycle, and/or public transportation only users—with multimodal car users positioned in-between the two extremes. Policy changes aimed at curtailing car use may result in movements along this spectrum with increasing multimodality for car users.
This paper introduces Metrolinx’s recently released Mobility Hub Guidelines and highlights two key aspects of the document: the importance of classifying the current and planned urban context and transportation function at a mobility hub, and methods to overcome challenges in achieving both transport and placemaking roles.
A study was done to see how location to transit impacts the amount you spend on transportation in a year - this article explains the findings.
This article is a review of Adonia Lugo's book: "Bicycle / Race: Transportation, Culture, & Resistance". The book talks about issues of race and class in bicycle culture. It is a call to refocus bicycle-planning beyond physical infrastructure to include human-infrastructure that centers on the stories and identities that shape how, where, when, and why we travel.
This article briefly outline the success of upgrades made to a bus line in the Twin Cities. So far ridership has increased 30%.
"Carsharing exemplifies a growing trend towards service provision displacing ownership of capital goods. We developed a model to quantify the impact of carsharing on greenhouse gas (GHG) emissions. The study took into account different types of households and their trip characteristics. The analysis considers five factors by which carsharing can impact GHG emissions: transportation mode change, fleet vintage, vehicle optimization, more efficient drive trains within each vehicle type, and trip aggregation. Access to carsharing has already been shown to lead some users to relinquish ownership of their personal vehicle. We find that even without a reduction in vehicle-kilometers traveled the change in characteristics of the vehicles used in carsharing fleets can reduce GHGs by more than 30%. Shifting some trips to public transit provides a further 10%–20% reduction in GHGs"
Transit bus automation could deliver many potential benefits, but transit agencies need additional research and policy guidance to make informed deployment decisions. Although funding and policy constraints may play a role, there is also a reasonable unwillingness to risk public funding or to undertake new operational models without a full understanding of the approach or without federal leadership and guidance. The purpose of this report is to define a five-year Strategic Transit Automation Research Plan that will establish a research and demonstration framework to move the transit industry forward. Key components of the Plan include conducting enabling research, identifying and resolving barriers to deployment, leveraging technologies from other sectors, demonstrating market-ready technologies, and transferring knowledge to the transit stakeholder community.
This year’s report builds on that same contextual foundation with updated travel trend charts and speed maps. Since 2015, the number of residents, jobs, and annual tourists have continued to grow. Even as the City encourages and facilitates the use of high performance modes, we recognize that the demands on our ?nite street network are only growing and our roadways are frequently functioning at capacity.
CityLab is launching Bus to the Future that puts public coaches at the center of the transportation future. It also plan to look at how technology can improve bus fundamentals. Automation (combined TNCs) could also transform surface transit.
Technology is transforming transportation. The ability to conveniently request, track, and pay for trips via mobile devices is changing the way people get around and interact with cities. This report examines the relationship of public transportation to shared modes, including bikesharing, carsharing, and ridesourcing services provided by companies such as Uber and Lyft. The research included participation by seven cities: Austin, Boston, Chicago, Los Angeles, San Francisco, Seattle and Washington, DC. The objective of this research analysis is to examine these issues and explore opportunities and challenges for public transportation as they relate to technology-enabled mobility services, including suggesting ways that public transit can learn from, build upon, and interface with these new modes.
Warren Logan, a Bay Area transportation planner, has new ideas about how to truly engage diverse communities in city planning. Hint: It starts with listening.
As public transit stagnates in most U.S. cities, central Seattle continued its rapid growth by adding roughly 10,000 morning transit commuters last year, new local data show.
This paper models the market potential of a fleet of shared, autonomous, electric vehicles (SAEVs) 20 by employing a multinomial logic mode choice model in an agent-based framework and different 21 fare settings.
"AVs are already being road tested in several states and will be available for sale within five to ten years. They promise to make automobile travel safer and more efficient, and to dramatically change transportation planning and engineering. This paper assesses the most likely effect of AVs on traffic generation and highway capacity and congestion over time as AVs come to represent a greater percentage of the vehicles on the road."
This doctoral dissertation analyzes the impacts of ridesourcing on several areas of transportation including: efficiency in terms of distance Vehicles Miles Traveled (VMT) versus Passenger Miles Traveled (PMT) – and travel times, mode replacement, VMT increase, parking, transportation equity, and travel behavior.
The author presents his view of limitations of prediction and how it apply to transportation prediction such as ridership prediction. He describes the concepts for planning the future (with time and space) that always emphasize the freedom as the goal.
"This Mobility Hub Features Catalog is a resource for regional agencies, local jurisdictions, transit operators, and private service providers as they collaborate to design and implement mobility hubs around the region. It describes the kinds of services, amenities, and technologies that can work together to make it easier for people to connect to transit, while also providing them with more transportation options overall. These mobility hub features may include various transit station improvements such as enhanced waiting areas with landscaping and lighting, complimentary WiFi and real-time travel information; wider sidewalks, pedestrian lighting and trees for shade; bike paths, designated bike lanes, and bike parking options; dedicated bus lanes and supporting signal improvements; service facilities for shared cars, scooters, and electric vehicles; smart parking technology; and more. Each feature can be tailored to the unique needs of an individual community."
Chicago’s pilot electronic-scooter program is proving to be a hit with low-income residents who have few transit choices in their far-flung neighborhoods.
The Chicago metropolitan area has one of the most extensive public transit systems in the United States, yet there are many places in the region where people do not have convenient access to transit service. To address that deficiency, this paper identifies practical ways to give more travel options to people in areas that are underserved by transit, including people who are unable to own or rent a car or have physical limitations that prevent them from driving.
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."
In this study, we present exploratory evidence of how “ridesourcing” services (app-based, on-demand ride services like Uber and Lyft) are used in San Francisco. We explore who uses ridesourcing and for what reasons, how the ridesourcing market compares to that of traditional taxis, and how ridesourcing impacts the use of public transit and overall vehicle travel. In spring 2014, 380 completed intercept surveys were collected from three ridesourcing “hot spots” in San Francisco. We compare survey results with matched-pair taxi trip data and results of a previous taxi user survey. We also compare travel times for ridesourcing and taxis with those for public transit.
"This research shows that public transportation (in its current form) will only remain economically competitive where demand can be bundled to larger units. In particular, this applies to dense urban areas, where public transportation can be offered at lower prices than autonomous taxis (even if pooled) and private cars. Wherever substantial bundling is not possible, shared and pooled vehicles serve travel demand more efficiently."
"This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs."
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 study examines the potential for public e-scooter sharing systems to fill mobility needs within and between Chicago neighborhoods. It explores how availability of this micro-mode of transportation could influence travel time, cost, and the convenience of trips relative to other active and shared-use modes including walking, bicycling, bikeshare, and public transit."
According to the latest statistics from the American Public Transit Association, the region has experienced a 5.7 per cent increase in the number of boardings year-over-year. Only three other urban areas with a population of more than one million saw transit ridership growth last year.
The goals of this study were to explore e-hail (e.g., Uber/Lyft) knowledge, use, reliance, and future expectations among older adults. Specifically, we aimed to identify factors that were related to e-hail, and how older adults view this mode as a potential future transportation option. Data were collected from a sample of older adults using a pencil-and-paper mailed survey. Univariate, bivariate, and regression techniques were used to assess the relationships among e-hail and several demographic and other factors. E-hail may be a viable future option for older adults who have limited or stopped driving. More exposure to e-hail and continued evolution of these services is required to overcome older adults’ lower internet/smartphone use. Policies could be implemented at departments of motor vehicles to pair information or training on transportation alternatives (like e-hail) with elimination of driving privileges, or at doctors’ offices, senior centers, or hospitals. Potential underlying reasons for the findings are also discussed.
"Completing urban freight deliveries is increasingly a challenge in congested urban areas, particularly when delivery trucks are required to meet time windows. Depending on the route characteristics, Electric Assist (EA) cargo bicycles may serve as an economically viable alternative to delivery trucks. The purpose of this paper is to compare the delivery route cost trade-offs between box delivery trucks and EA cargo bicycles that have the same route and delivery characteristics, and to explore the question, under what conditions do EA cargo bikes perform at a lower cost than typical delivery trucks?"
"The aim of this paper is to show how TNCs could replace public transportation in the United States if subsidized at the same level of transit agencies."
"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."
Smartphone data from riders and drivers schlepping meals for restaurant-to-home courier service Deliveroo shows that bicycles are faster than cars. In towns and cities, bicyclists are also often faster than motorized two-wheelers.
In 2013, advocates, planners, and policymakers were abuzz with the 10.7 billion rides taken on transit, an all-time U.S. record. Yet the discussion focused too much on the sheer number of rides, without a deep look at the riders themselves, and particularly the changing attitudes that are propelling recent ridership increases. TransitCenter commissioned a survey to take that deeper look. We now have a snapshot into perceptions of transit and neighborhoods in 2014. As Millennials take center stage in American life and the Baby Boom generation confronts retirement, both the transit and real estate industries will have to adjust.
This report draws on results from six focus groups in New York, Raleigh and Denver as well as a survey of 3,000 people in 17 U.S. metropolitan areas with varying levels of transit development and ridership. It builds on the findings from TransitCenter’s first Who’s On Board report released in 2014.
With so much transportation funding going toward highways, it’s tempting to support any transit investment as a step in the right direction. But not all transit investments will produce service that helps people get where they need to go. To make transit a useful travel option that people want to ride, says TransitCenter, there are three basic goals that officials and advocates should strive for: speed, frequency and reliability, walkability and accessibility.
Public transit accounts for only 1% of U.S. passenger miles traveled but nevertheless attracts strong public support. Using a simple choice model, we predict that transit riders are likely to be individuals who commute along routes with the most severe roadway delays. These individuals’ choices thus have very high marginal impacts on congestion. We test this prediction with data from a sudden strike in 2003 by Los Angeles transit workers. Estimating a regression discontinuity design, we find that average highway delay increases 47% when transit service ceases. This effect is consistent with our model’s predictions and many times larger than earlier estimates, which have generally concluded that public transit provides minimal congestion relief. We find that the net benefits of transit systems appear to be much larger than previously believed.
Shared micromobility devices could thrive in a city like New York where individuals are encouraged to get out of their cars due to impending congestion pricing tolls and an expansion of protected bike lanes, according to the report. But biker and pedestrian safety remain a major issue in U.S. cities. Therefore, the most effective way to get people to use micromobility devices is to make them easy and safe to use, INRIX Transportation Analyst Trevor Reed told Smart Cities Dive in an email.
On Thursday, five years after launching and two and half years after being acquired by Ford for a reported $65 million, the app-based shuttle service announced it is rolling to a permanent stop. Transportation technology companies have never been sexier than in the past decade, but this stumble is a potent reminder that creating a profitable transportation business can be far harder than it seems.
First came e-bikes, then scooters. Now the District is adding mopeds to the mix of micromobility services available in the nation’s capital. Looking forward, they are focused on luring electric tricycles (trikes) and e-cargo bikes to the city. D.C. transportation officials say they’re open to testing whatever happens to be the next big thing in transportation technology.
This report summarizes findings from a three-year collaboration between the World Economic Forum and The Boston Consulting Group (BCG) to explore how autonomous vehicles could reshape the future of urban mobility. The project built on the collective insights generated from the Autonomous and Urban Mobility Working Group (Working Group) of the System Initiative on Shaping the Future of Mobility, composed of roughly 35 business executives from diverse industries (including automotive, technology, logistics, insurance, utilities and infrastructure) that convened for 10 full-day workshops and numerous conference calls.
In the last ten years transit use in Southern California has fallen significantly. This report investigates that falling transit use. We define Southern California as the six counties that participate in the Southern California Association of Governments (SCAG) – Los Angeles, Orange, Riverside, San Bernardino, Ventura and Imperial. We examine patterns of transit service and patronage over time and across the region, and consider an array of explanations for falling transit use: declining transit service levels, eroding transit service quality, rising fares, falling fuel prices, the growth of Lyft and Uber, the migration of frequent transit users to outlying neighborhoods with less transit service, and rising vehicle ownership. While all of these factors probably play some role, we conclude that the most significant factor is increased motor vehicle access, particularly among low-income households that have traditionally supplied the region with its most frequent and reliable transit users.
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