Transportation agencies are facing what are widely accepted as the most serious fiscal challenges in nearly a century. Most critically, fuel tax revenue is declining in relation to road use and transportation costs are continuing to increase with inflation. In light of this situation, many innovative funding and financing methods have been proposed or implemented. This session highlights both the current state of practice in funding and financing and innovative methods that show promise for the future.
Incorporation of Attitudinal Aspect in Value of Time and Value of Reliability Estimation: Thinking Beyond Travel Time, Travel Cost, and Travel Time Reliability
Md Sakoat Hossan, CDM Smith
Using Value of Reliability in Traffic and Revenue Estimates: Case Study of I-10 Express Lanes
Nikhil Sikka, RSG
Mark Fowler, RSG
Cissy Kulakowski, CDM Smith
Empirical Analysis of State Legislative Initiatives for Funding Transportation Improvements: January 1, 2000, to August 1, 2016
Nicolas Norboge, NCSU-ITRE
Who Pays for Local Streets? Who Should Pay? Survey of New Jersey Municipalities
Carl Peters, Carl E. Peters LLCShow Abstract
Jonathan Peters, City University of New York (CUNY)
Cameron Gordon, Australian National University
Deconstruction of the Goethals PPP deal
Applying Lean-Engineering Principles to Agency Business Processes to Improve Collections Associated with Infrastructure Damaged by Motor Vehicle Crashes
Darcy Bullock, Purdue UniversityShow Abstract
Deborah Horton, Purdue University
Dan Brassard, Indiana Department of Transportation
State and local agencies have an enormous investment in roadway infrastructure that is routinely damaged by motor vehicle crashes and must be repaired in a timely manner. Recovering the costs associated with repairing damage to state property (DSP) from responsible parties can be difficult if careful business processes are not followed by state and local agencies. In 2009, the Indiana Department of Transportation (INDOT) initiated a review of their DSP business processes, their peer state DSP business processes. Subsequently, they implemented a series of improvements that have increased the amount invoiced for repair of damaged roadway infrastructure from $1.4M in FY 2010 to $8.3M in FY 2016. During this same time period, the number of DSP invoices increased from 1,352 to 4,405 and the collection rate improved from 63% to 88%. This paper provides a summary of the evaluation process, implementation effort, and outcome assessment metrics to guide agencies that are looking for opportunities to identify improvement opportunities in repair and invoicing activities related to damage from motor vehicle crashes.
Implementing Distance-Based Fees Through Shared Mobility Model
Kenneth Buckeye, Minnesota Department of TransportationShow Abstract
This paper introduces a unique approach to implementing distance based fees on the nation’s roadways via the rapidly developing model called shared mobility. This model recognizes that consumer travel and vehicle ownership expectations are evolving and the ability to share vehicles is enabled by modern technologies embedded in those vehicles. That same technology gathers miles driven by each vehicle on public roads.
The collection of miles traveled for the purpose of levying distance based fees is a well suited function of shared mobility as providers already collect that information as a component of their business model. Objections to distance based fees are minimized since customers of those services have already yielded to many concerns expressed. The motor fuel tax, which continues to be a solid revenue generator today and into the foreseeable future, remains in place for personal vehicles that use fossil fuels. Individually owned alternative fueled and electric vehicles will continue to pay the ad-valorem tax, or the equivalent, to account for their road use as they do today.
The ultimate evolution of shared mobility and the application of distance based fees is enabled by the introduction of automated vehicles. Automated vehicles, which are forecast to grow significantly in coming decades, are a disruptive technology likely to change the way we travel, enhance the safety of our roads and altering the way we pay for mobility. The shared mobility model will help the nation chart an efficient, rational and evolutionary path to widespread introduction of distance based fees.
Measuring Drivers´ Attitudes Toward Use of Electronic Toll Collection Systems in Spain
Javier Heras-Molina, Universidad Politécnica de MadridShow Abstract
Juan Gomez, Universidad Politécnica de Madrid
Jose Manuel Vassallo, Universidad Politecnica de Madrid
Electronic Toll Collection (ETC) systems are relentlessly penetrating as a means for paying the use of roads worldwide. However, governments and infrastructure operators still have a long way ahead to increase the effectiveness and expediency of these mechanisms. Previous literature in this field has focused on analyzing users´ perceptions and willingness to pay to use toll roads. However, there is little research addressing drivers´ attitudes towards the use of ETC systems. The aim of this paper is to identify the explanatory factors influencing the use of ETC technologies by toll road drivers. To that end, based on a nationwide survey conducted to road users in interurban toll roads in Spain, we develop three binomial logit models to explore users’ attitudes towards the use of electronic tolling. The research concludes that drivers´ willingness to own a TAG is mainly related to trip frequency, the professional character of the trip and the region of residence. Other variables, such as income or age, evidence to play a minor role to determine drivers’ willingness to use electronic payment.
Property and Sales Taxes for Transportation Funding: Evaluating the Economic Stress Borne by Taxpayers in the Washington, D.C.,-Baltimore Area
Eirini Kastrouni, University of Maryland, College ParkShow Abstract
Carlos Carrion, University of Maryland, College Park
Lei Zhang, University of Maryland, College Park
This paper explores the use of transportation-dedicated property and sales taxes to fund the surface transportation system, and evaluates each policy’s distributional effects for the Washington D.C. - Baltimore area. A synthetic dataset is created via statistical matching, using the Gower distance hot deck matching technique, and is used to assess each policy’s economic stress on the HHs. Shifting from state fuel taxes to property taxes will decrease the taxpaying population for most income groups, while the tax-to-income ratios for all income groups will increase. Approximately 8.6% of the generated revenue would come from HHs that do not drive any vehicle. On the other hand, shifting to sales taxes will increase the taxpaying population across all income groups, with 7.1% of the generated revenue coming from HHs that do not drive any vehicle. As a result of the increase in the taxpaying population, all income groups will experience a decrease in their tax-to-income ratios. For both policies, Montgomery, Prince George’s, and Baltimore counties will be the top 3 jurisdictions in terms of revenue generation. However, D.C., and Baltimore City will experience the highest tax-to-income ratios, compared to their bottom 3 ranking under the state fuel taxes policy.
Making Self-Help Finance: Overcoming the Legislative Obstacles to Using Local Option Taxes for Regional Transportation
David Weinreich, University of Texas, ArlingtonShow Abstract
Due to stagnation of federal money for new transportation infrastructure, local jurisdictions have, increasingly, found the need to fund capital projects themselves, through transportation voter initiatives, known as local option taxes. Localized funding decisions make coordination across jurisdictions more difficult, despite growing needs to solve regional problems like air quality, economic growth, and transport of the economically disadvantaged. In an effort to self-finance new projects, while building an integrated regional system, some regions have taken the ambitious step to develop multi-jurisdictional self-help taxes, asking voters across multiple counties to support their proposals. However few states authorize such taxes, and in some cases, advocates have had to lobby for legislative permission to hold a referendum. While local obstacles are significant, legislative ones may stop such proposals before they even get started. This study looks at seven cases in four regions that have occurred since 1990. Using interviews and archival evidence, this study examines how state authorizing legislation and other factors shaped each process. It finds that very restrictive legislation can be problematic, while the need for new legislation makes the process cumbersome, and difficult to repeat. Conversely, pre-authorization, using permissive language for particular factors like the tax rate, the timing/election cycle, the jurisdictions to be included, and the rules for selecting projects, is particularly important to ensuring that the process can adapt to local politics and changing circumstances. This can lift a significant obstacle to using multi-jurisdictional option tax processes as a way to fund regional transportation on a more regular basis.
Optimal Portfolio Strategy for Risk Management in Toll Road Forecasts and Investments
Rohan Shah, CDM SmithShow Abstract
Phani Jammalamadaka, CDM Smith
The study leverages modern portfolio theory and stochastic time series models to develop a new risk management strategy for future traffic projections along brownfield toll facilities. Uncertainty in future traffic forecasts may give rise to concerns about performance reliability and revenue potential. Historical time series of traffic data offered by brownfield corridors are utilized for developing econometric forecast estimates, and Monte-Carlo simulation is used to quantify à priori risks or variance in them. Optimal forecast portfolios are developed using mean-variance optimization strategies. Numerical analysis is presented using historical toll transactions along the Massachusetts Turnpike system. Diversification strategies are found to achieve better forecast efficiencies in the long-term, with better trade-offs between expected returns and risks. Forecast performance expectations and risk-propensity of planners and agencies are thus jointly captured.
The Build America Bureau: Harmonizing Federal Transportation Funding and Finance Resources
Jodie Misiak, Build America Bureau
Economic Effects of Autonomous Vehicles
Lewis Clements, University of Texas, AustinShow Abstract
Kara Kockelman, University of Texas, Austin
Connected and fully automated or autonomous vehicles (CAVs) are becoming increasingly viable as a technology and may soon dominate the automotive industry. Once CAVs are sufficiently reliable and affordable, they will gain greater market penetration, generating significant economic ripple effects throughout many industries. This paper synthesizes and expands upon analysis from multiple reports on the economic effects of CAVs across 13 different industries and the overall economy.
CAVs will soon be central to the automotive industry, with software making up a greater percent of vehicle value than it had previously and hardware’s percentage value falling. The number of vehicles purchased each year may fall, due vehicle-sharing within families/across household members or through shared fleets, but rising travel distances and a shift away from air travel may lead to greater vehicle-miles traveled (VMT) and ultimately higher vehicle sales (due to faster fleet turnover from heavy daily use). Heavy commercial trucks may be the first industry to implement AV technology in order to increase efficiency. The opportunity for drivers to do other work or rest during long drives may allow heavy trucks to travel for longer periods of time, at lower cost, reducing the demand for rail transport. Personal transport may shift toward shared autonomous vehicle (SAV) fleet use, threatening the business of taxis, buses, and other forms of public transport. Fewer collisions and more law-abiding vehicles, due to smarter, automated vehicle operations, will lower demand for auto repairs, traffic police, medical, insurance, and legal services. CAVs will also impact infrastructure investment and land use, leading to new methods for managing travel demands and a repurposing of some land, such as curbside and off-street parking.
A reduction in crashes and tighter headways between vehicles, thanks to inter-vehicle communications and automation may diminish traffic congestion, but be overcome by VMT increases. CAVs will also generate savings from productivity gains during hands-free travel, as well as a decrease in fuel use and crash costs. Assuming that CAVs eventually capture a large share of the automotive market, they will have major economic impacts, on the order of $4,900 per American per year. All estimates provided here are largely speculative, since the future of CAVs and the forces that will influence their adoption and use are still highly uncertain, but this paper presents important considerations for the overall effects of AVs on the U.S. economy and quantifies the impacts.