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Using experience from working on the Knight AV Initiative, Urbanism Next created this white paper to provide a foundation for public sector agencies to approach autonomous vehicle deployment and policy with a focus on equity. This report outlines ways that public agencies can identify community needs and shape deployment to ensure that AVs will be accessible for all.
This article questions the effects of parking minimums and policies on residential renters in the U.S. by analyzing a sample of rental housing units from the 2011 American Housing Survey.
Parking drives up the cost of development and puts the burden on tenants who purchase or rent housing in these developments. Most zoning codes and practices require generous parking supply, and tenants are forced to pay for parking regardless of if they are using it. This reduces housing affordability which has a disproportionate effect on lower-income households.
“The introduction of driverless cars could affect how much money cities collect in parking, traffic citations, traffic cameras, towing fees, gasoline taxes, licensing, registration and other revenues.”
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 report explores peer-to-peer carsharing, its impacts on travel behavior, and how it can be incorporated with other shared mobility services.
TNCs provide on-demand mobility service that either complements or competes with transit services. This article studies how TNCs influence changes in urban travel patterns as well as energy and environmental implications.
The growth of ride-hailing services has led to more traffic and less transit use in the United States, contrary to predictions that suggested the opposite would happen when transportation network companies first started becoming popular. Some data shows that household vehicle ownership increased in cities where Uber and Lyft are most heavily used, while there is also a growing number of urban households that own zero or few cars. The article analyzes this data to determine whether Americans own fewer cars, and discusses how vehicle ownership relates to population growth in several cities.
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.
The report is intended to provide guidance to Australia and New Zealand in planning road changes for the introduction of automated vehicles. Key issues that are discussed in this report include physical infrastructure, digital infrastructure, and road operations. The analysis of each issue includes different possible use cases of automated vehicles and includes discussion of optimal conditions required to support the introduction of automated vehicles.
“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.”
This document includes the interests of most, if not all, major issues surrounding the impact AVs will have on our communities, government, and environment once they land.
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.
Seattle City Council passes in a 7 to 1 vote a plan for large parking reforms including separating parking costs from rent and increasing bike parking requirements.
This report recommends potential research and policies that will help shape progress towards that vision. It also clarifies some opportunities and preparatory work for TransLink to consider as an operator. These are explained in the body.
We quantify the importance of early action to tackle urban sprawl. We focus on the long-term nature of infrastructure decisions, specifically local roadways, which can lock in greenhouse gas emissions for decades to come. The location and interconnectedness of local roadways form a near permanent backbone for the future layout of land parcels, buildings, and transportation options. We provide new estimates of the environmental impact of low-connectivity roads, characterized by cul-de-sacs and T-intersections, which we dub street-network sprawl. We find an elasticity of vehicle ownership with respect to street connectivity of –0.15—larger than suggested by previous research. We then apply this estimate to quantify the long-term emissions implications of alternative scenarios for street-network sprawl. On current trends alone, we project vehicle travel and emissions to fall by ∼3.2% over the 2015–2050 period, compared to a scenario where sprawl plateaus at its 1994 peak. Concerted policy efforts to increase street connectivity could more than triple these reductions to ∼8.8% by 2050. Longer-term reductions over the 2050–2100 period are more speculative, but could be more than 50% greater than those achieved by 2050. The longer the timescale over which mitigation efforts are considered, the more important it becomes to address the physical form of the built environment.
Local governments, municipal planning organizations, and transit agencies are understandably circumspect in their actions to regulate autonomous vehicles. Policymakers must strike a delicate balance between crafting forward-thinking regulations and being so quick-to-act that decisions are rendered obsolete by the changing marketplace. In this case, however, it is crucial that metropolitan actors do not fall behind the wave of technological progress—now is the moment to envision their ideal land use and transportation scenarios.
"In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs.
This Electric Vehicle Strategy focuses on electrification of the public transit system, shared vehicles and the private automobiles that remain in use, which is one of many strategies the City is taking to reduce carbon emissions from the transportation sector. This strategy also seeks to maximize the benefits of air quality and affordability for low-income residents and parts of Portland that are the most dependent on private vehicles.
"Ridehail services nearly eliminate the racial-ethnic differences in service quality. Policy and platform-level strategies can erase the remaining mobility gap and ensure equitable access to ridehailing and future technology-enabled mobility services."
"Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half – or nearly double them – depending on which effects come to dominate."
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.
New data from the US EPA on power plant greenhouse gas emissions are in, and electric vehicles (EV) in the US are even cleaner than they were before. The climate change emissions created by driving on electricity depend on where you live, but on average, an EV driving on electricity in the U.S. today is equivalent to a conventional gasoline car that gets 80 MPG, up from 73 MPG in our 2017 update.
"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"
Different business models of AVs, including Shared AVs (SAVs) and Private AVs (PAVs), will lead to significantly different changes in regional vehicle inventory and Vehicle Miles Traveled (VMT). Most prior studies have already explored the impact of SAVs on vehicle ownership and VMT generation. Limited understanding has been gained regarding vehicle ownership reduction and unoccupied VMT generation potentials in the era of PAVs. Motivated by such research gap, this study develops models to examine how much vehicle ownership reduction can be achieved once private conventional vehicles are replaced by AVs and the spatial distribution of unoccupied VMT accompanied with the vehicle reduction. The models are implemented using travel survey and synthesized trip profile from Atlanta Metropolitan Area. The results show that more than 18% of the households can reduce vehicles, while maintaining the current travel patterns. This can be translated into a 9.5% reduction in private vehicles in the study region. Meanwhile, 29.8 unoccupied VMT will be induced per day per reduced vehicles. A majority of the unoccupied VMT will be loaded on interstate highways and expressways and the largest percentage inflation in VMT will occur on minor local roads. The results can provide implications for evolving trends in household vehicles uses and the location of dedicated AV lanes in the PAV dominated future.
This study examines the potential changes in residential location choice in a scenario where shared autonomous vehicles (SAVs) are a popular mode of travel in the Atlanta metropolitan area. This hypothetical study is based on an agent-based simulation approach, which integrates residential location choice models with a SAV simulation model. The coupled model simulates future home location choices given current home location preferences and real estate development patterns. The results indicate that commuters may relocate to neighborhoods with better public schools and more amenities due to reductions in commute costs.
This paper evaluates the greenhouse gas (GHG) emission impacts that result from individuals participating in carsharing organizations within North America. The authors conducted an online survey with members of major carsharing organizations and evaluated the change in annual household emissions (e.g., impact) of respondents that joined carsharing. The results show that a majority of households joining carsharing are increasing their emissions by gaining access to automobiles.
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.
This report estimates that by 2030, a substantial share of the 175 million Americans who live in the nation's largest cities will turn to SAEVs, cutting transportation costs by nearly 50%, reclaiming time instead of losing hours a day to traffic and putting up with all the expense and hassle of urban automobile ownership. SAEV fleets will account for nearly 25% of all auto passenger miles traveled in the US by 2030. Such a change will have an enormous impact on health, safety, and quality of life in cities: Traffic accidents and fatalities will be reduced by nearly two-thirds. Pollution will be drastically curtailed. Cities can repurpose millions of square feet once used for parking to new green spaces or commercial uses while securing more affordable mobility and accessibility for elderly, disabled, and low-income people.
The article discusses how new technology in transportation can achieve equity by leveraging technology. Strategies include defining boundaries, eligibility, and subsidies.
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.
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."
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.
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.
"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."
Upon the roll-out of AVs into our streets, the importance of public and private sector partnerships are emphasized. With increased mobility, the demand for private rides could be increased and therefore increase congestion in our streets.
Driverless vehicles will likely have a huge impact on our future; however, it is the government’s actions (now and in the future) that will determine how they are integrated into society and if the impacts are largely positive or negative. The intent of this guide is to outline the role of government in the integration of driverless vehicles in society and present the information that local and regional governments need to inform planning and decision-making – now and in the future.
"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 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.
We are on the cusp of one of the fastest, deepest, most consequential disruptions of transportation in history. By 2030, within 10 years of regulatory approval of autonomous vehicles (AVs), 95% of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by fleets, not individuals, in a new business model we call “transportas-a-service” (TaaS). The TaaS disruption will have enormous implications across the transportation and oil industries, decimating entire portions of their value chains, causing oil demand and prices to plummet, and destroying trillions of dollars in investor value — but also creating trillions of dollars in new business opportunities, consumer surplus and GDP growth.
Autonomous vehicles use sensing and communication technologies to navigate safely and efficiently with little or no input from the driver. These driverless technologies will create an unprecedented revolution in how people move, and policymakers will need appropriate tools to plan for and analyze the large impacts of novel navigation systems. In this paper we derive semi-parametric estimates of the willingness to pay for automation. We use data from a nationwide online panel of 1,260 individuals who answered a vehicle-purchase discrete choice experiment focused on energy efficiency and autonomous features. Several models were estimated with the choice micro-data, including a conditional logit with deterministic consumer heterogeneity, a parametric random parameter logit, and a semi-parametric random parameter logit.
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.
This report by KPMG discusses how the new market will look like for autonomous future. It talks about transportation market, new customer demand, change of economic models, trip mission, and other market changes.
One of the more confusing words frequently associated with robocars (and all discussion of the future of transportation) is "shared." Unfortunately, this means two very different things, with quite different consequences.
This report is the culmination of the Connected Mobility Initiative launched by the New Cities Foundation in June 2015. "The primary aim of the initiative is to explore the triple convergence of “mobility” — physical, digital, and socio economic — and to propose strategies and steps of this transformation while ameliorating its potentially corrosive effects on public institutions. To this end, the report is split between brief policies of four cities Washington, D.C., London, Sao Paulo, and Manila — facing challenges representative of their respective peers, along with a list of near-, mid-, and long-term recommendations for transport authorities to aid them in their transformations.
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