2021

Fang Zhang, Southeast University
Jian Lu, Southeast University
Xiaojian Hu, Southeast University

In this paper, we study the tradable credit scheme design problem considering transaction cost and social equity issue. Heterogeneous users with different value of times (VOT) and elastic demand are assumed. The credit scheme is characterized by user anonymous initial endowment and link-specific credit charge, and incorporate transaction cost which is associated with trading volume and independent of credit price. The equilibrium problem is formulated as a VI problem and the existence and uniqueness of its solution are guaranteed. Based on the VI formulation, a credit scheme design problem with equity constraint is proposed, aiming at maximizing the total social welfare. Based on the results from the example network, the impacts of transaction cost under various equity constraints are investigated. It is found that the transaction cost can negatively affect travel disutility for low-VOT users, and the imposition of equity constraint can tackle with the inequity issue.

Kim Napoline, University of Minnesota
Erika Shepard, University of Minnesota
Lee Munnich, University of Minnesota, Twin Cities
Thomas Horan, University of Redlands

The medical device industry cluster in Minnesota is both essential to the state’s economic health and a global center of innovation and production. One crucial component that enables growth and success in the cluster is transportation. Without a fast and reliable transportation network, the distribution of medical devices would not be possible. The study assesses the transportation linkages and the medical device industry’s spatial development that benefits not just the seven-county Twin-Cities region but also Greater Minnesota. A geographic information systems (GIS) analysis was conducted to identify medical device “hot spots” to analyze surface transportation linkages to the airport. This analysis uses a case study of Plymouth, Minnesota, to demonstrate key policy implications for the medical device supply chain and freight planning.

Genís Majoral, Center For Innovation in Transport - CENIT
Francesc Gasparín, Center For Innovation in Transport - CENIT
Sergi Saurí, Center For Innovation in Transport - CENIT

The number of e-commerce transactions are increasing worldwide. Deliveries of goods purchased via the internet generate externalities throughout the whole supply chain. In particular, it is increasing the concern about the last-mile distribution of goods. The escalating presence of vans in cities contribute to poor air quality, climate change, noise and congestion. So far, the majority of solutions to address this issue are based on the supply side, such as electric vans, optimizing the routing, etc. Even in other transport sectors, pricing solutions are well-know, yet they have not been applied to the e-commerce delivery. This paper aims at proposing an environmental tax that would fall on the demand side and equal to the externalities form this activity. The analysis has been particularized for the case of Barcelona. A cost-benefit analysis to assess the impact such tax would have has been carried out. When revenue collection is reinvested in the logistic sector and to subsidize electric distribution vehicles, the results indicated that the implementation of the tax can provide positive results.

Md Mehedi Hasnat (mhasnat@ncsu.edu), North Carolina State University
Eleni Bardaka, North Carolina State University

This paper summarizes the impact of the COVID-19 pandemic on statewide travel in North Carolina and its subsequent adversities on the revenue stream of NCDOT. From March to June, 2020 NCDOT has recorded 11 billion less vehicle miles traveled (VMT) than the forecasted VMT, which led to significant loss of revenue. This study investigates several alternative funding mechanism that could have helped to reduce those adverse impacts by introducing additional transportation funds. The study analyzes whether higher tax rates for existing major revenue sources could have helped to eliminate or reduce the gap between expected and actually collected revenue. It also investigates the aspect of implementing new sources of revenue such as, use of state sales and use tax, introducing tax on VMT, and use of General Fund to mitigate the negative impacts of such emergency situations in the future. The results suggest that due to direct dependency on travel and travel-related activities, current state revenue sources are not reliable enough to tackle similar scenarios in the future. On the contrary, more general revenue sources, such as revenue from state’s General Fund and state’s sales and use tax are found to be less severely affected by the COVID-19 pandemic. This study finds that appropriation of General Fund by as low as 3% could have added $305 million during January 2020 to May 2020 and exceed the total revenue loss.

David Weinreich, Technion Israel Institute of Technology

Despite strong interest in toll finance, there is little in the transportation literature about how independent local tolling agencies make decisions to raise and spend revenue. This study hypothesizes that different toll road governance models provide varying incentives to raise tolls and spend them, particularly on equitable distribution. This study catalogues toll roads across the US, using state enabling legislation to classify toll roads by governance type (e.g. local government, private, public-private-partnership (P3), state DOT, state-owned entity, toll road authority and transportation authority).   This study selects a representative sample of 60 toll roads across 20 US states, chosen based on their governance type, centerline miles, and rate of toll increase since 2007. This study examines archival sources to identify whether/how much tolls were increased/decreased, and asks how/why governance methods affected spending outcomes through interviews with staff and elected officials from four toll road agencies.   The study finds strong incentives towards profit in private and P3 roads, but weak incentives towards transparency.   The study identifies barriers to using revenue towards equity-focused expenditures due to debt covenants, and incentives to distribute money toward new projects within an agency’s outer boundaries, thus failing to address the equity concerns that hamper public confidence in tolls as a revenue source.   Nesting a toll road within a larger transportation authority can mitigate this, providing incentives to subsidize public transit, and taxing powers that make debt less necessary—an institutional design which could mitigate equity concerns that have hampered expansion of tolls as a revenue source.

Glen Weisbrod, EBP US, Inc.
Jenna Goldberg, EBP US, Inc.
Parry Frank, Chicago Metropolitan Agency for Planning (CMAP)

Transportation planners are increasingly recognizing the importance of access in enabling employment growth and better paying job opportunities for residents. While regional economic impact analysis is often an important element of transportation investment evaluation by state DOTs, it can be particularly challenging for metropolitan area planners because existing economic modeling methods do not fully account for the multi-faceted market access roles of transportation links within large metropolitan areas that have multiple business activity clusters. This paper examines these issues and presents information from a study of the Chicago region, to demonstrate the interplay of population connectivity and business-to-business connectivity in explaining patterns of business clusters and their relative productivity. It presents elasticities of employment and wage impact from various access/connectivity measures for different sectors of the economy. It then provides guidance regarding aspects of access that metropolitan area planners can consider to better assess how proposed transportation system improvements can affect economic opportunities and benefits.

Narae Lee (nlee25@gmu.edu), George Mason University
Jonathan Gifford, George Mason University

The Transportation Infrastructure Finance and Innovation Act (TIFIA) program acts as the U.S. federal government’s primary financing program for the development of transportation infrastructure. This paper aims to evaluate whether and how the TIFIA program’s creditworthiness profile, measured via project credit ratings, may have changed between the recent MAP-21 and FAST Act policy periods.  After constructing a project-level data set, the authors employed a Linear Probability Model (LPM) and an Average Treatment Effect (LPM-ATE) estimation to evaluate FAST Act policy impacts on the credit ratings acquired by TIFIA-selected projects. The estimates controlled for differences in project type and reliance on toll revenues to secure repayment. A Binary Logit model was also employed as a sensitivity check, producing similar estimates.  The empirical estimates showed that credit ratings did not differ significantly between the MAP-21 and FAST Act policy periods when weighted by project counts.  However, the program allocated a larger proportion of its support to assist higher-rated projects during the FAST Act period, measured by TIFIA loan amount.

Giulio Giorgione (giulio.giorgione@uni.lu), Universite du Luxembourg
Dzmitry Kliazovich, Oply
Luca Bolzani, Universite du Luxembourg
Francesco Ciari, Ecole Polytechnique de Montreal
Francesco Viti, Universite du Luxembourg

The success of carsharing as a new and more sustainable way of travel is moving private car ownership towards a service use model. Competitivity is an essential aspect of this service and ways to increase profit while offering the most appealing service are still getting explored. Among others, dynamic pricing strategies can be designed to increase profit by attracting more users, selling more rental hours or maximizing fleet utilization. In this paper, we propose an experimental method aimed at developing a model for maximizing service profit. Using agent-based modeling to generate realistic scenarios, we analyze pricing as a function of the potential demand (i.e. number of members) and supply (hours of booking supplied). The process of reaching the maximum profit consists of testing various combinations of pricing - demand and pricing – supply ranges in order to find the price that maximize the profit for every demand and supply level. Once the optimal prices are known, a polynomial fitting and an optimization method are used to generate a function linking all the maximal profit obtaining the advised price to offer for any specific supply levels. Results show how the profit only slightly depends on the variability of the potential demand, while it strongly depends on the amount of supply. It is then shown how it is possible to obtain a linear relation that maximizes the profit in function of the price offered once the supply is known.

Praj Xuto (p.xuto17@imperial.ac.uk), Imperial College London
Richard Anderson, Imperial College London
Daniel Graham, Imperial College London
Daniel Hörcher, Imperial College London

The infrastructure condition in many developed cities around the world is often a pressing issue, with higher costs the longer repairs are deferred. In particular, the urban rail network is crucial since infrastructure failures can have severe economic consequences for both the operator and users. In the US alone, it is estimated that $90 billion is needed to bring transit infrastructure up to a ‘state-of-good-repair’. Although the benefits of non-expansion capital spending are well-known within the industry, empirical studies from an organisational perspective are relatively rare. This research seeks to redress that by combining 70 years’ worth of London Underground data with a time series econometrics analysis, alongside contextual discussions of industry practices and funding issues. The exploratory results suggest that an accelerating increase in annual growth of cumulative capex is positively associated with annual growth in passenger demand (both in percentage terms). This implies that new, major reinvestment spending can be related to a positive annual increase in demand, since the rate of change in annual growth is typically highest at the start of programme launches. Additionally, the capex impact on demand appears to take some time to be felt. The link between capex and operating cost was also tested, yielding no significant result for capex, potentially due to the aggregated data. Instead, an unanticipated result related to financing was found, where the period immediately prior to the launch of infrastructure PPPs in 2003 is associated with positive annual growth in operating cost.

Choungryeol Lee (lee1210@purdue.edu), Purdue University
Srinivas Peeta, Georgia Institute of Technology (Georgia Tech)

A value increment created by real options (i.e., managerial flexibility in decision-making) can be critical for augmenting the total value of the road infrastructure projects under uncertainty. In the public-private partnership (PPP) setting where credit risk concerning the private firm’s bankruptcy can depreciate the real options for the public entity, the neglect of its impact on value can cause the overestimation of the project value, thus leading to inefficient decisions in terms of project priority and private partner selection on bid-and-ask. To solve the aforementioned issue related to unpriced credit risk, this study proposes a risk expanded net present value (NPV) approach that integrates the existing NPV approaches and the risk expanded real options valuation framework to determine a fair value of the PPP projects embedded with real options subject to credit risk. For real options for PPP, credit risk is measured as the expected loss of the public entity in terms of the potential unavailability of exercising its real options due to bankruptcy. The expected loss is estimated as the product of the estimate of default probability and the nominal value (i.e., the option value under no credit risk), and it is deducted from the nominal value to compensate for the potential loss under uncertainty. Results from numerical experiments show that credit risk concerning bankruptcy can significantly depreciate the real options of the public entity, causing the potential loss of the PPP project’s value. Impacts of pricing credit risk are further analyzed using empirical data on real-life firm mortality.

Daniel Vignon (dvignon@umich.edu), University of Michigan, Ann Arbor
Yafeng Yin, University of Michigan, Ann Arbor
Sina Bahrami, University of Michigan, Ann Arbor
Ken Laberteaux, Toyota Motor Corporation

The current approach to automated driving has thus far been vehicle-centric. However, it is likely that an infrastructure-vehicle cooperative approach, in which infrastructure and vehicles interact to perform the different driving tasks, will prevail in enabling automated driving. To this effect, we present a model that captures investment decisions in automation and digitalization and their effect on travellers' purchase and travel decisions. Our analysis of the social optimum shows that both digitalization and automation are needed to enable automated driving. Subsequently, we also show that strategic interactions between a monopolistic automaker and a monopolistic road operator result in under-investment in both automation and digitalization when users' travel patterns remain fixed. This is due, in part, to the lack of coordination which prevents automakers from enjoying the non-pricing benefits that driving generates for road operators. However, when users are allowed to adjust their travel patterns in response to automation and digitalization, automakers have an incentive to over-invest in automation for certain user segments. For road operators, users' ability to change travel patterns may be a mixed blessing. On the one hand, investment in digitalization attracts more users on a given road segment. On the other hand, increased traffic volume increases the negative externality of driving which reduces users' willingness to pay for road usage, thus making infrastructure investment less attractive. As such, our analysis produces two takeaways. First, cooperation between automakers and road operators should be increased, since it provides an opportunity for automakers to take the non-pricing benefits from driving into account in their decision-making, thus making the resulting investment decisions closer to the social optimum. Second, road operators will likely need additional monetary incentives to catalyze infrastructure spending when negative congestion externalities reduce their ability to recover the cost of their investment.

Asha Agrawal, San Jose State University
Hilary Nixon, Mineta Transportation Institute

This paper presents the results of an online public opinion survey asking U.S. adults questions related to their views on mileage fees. A nationally representative sample of 2,515 respondents completed the online survey. The survey tested public opinions about five different mileage fee options: two variants on the idea of replacing the gas tax with a mileage fee, and three variants on the idea of imposing a new fee on commercial travel. The survey also collected data on respondents’ views about privacy and equity matters related to mileage fees, opinion on whether electric vehicles should pay the same or lower rate than internal-combustion-engine vehicles, preferred frequency of paying a mileage fee, and basic questions about travel behavior and sociodemographic characteristics. This large set of variables is used to identify personal characteristics and opinions correlated with support for the tax options.   Key findings include that close to half of respondents supported a mileage fee on all travel to replace the gas tax, slightly over half supported a fee assessed just on commercial vehicles, half supported some form of mileage fee, a majority (57%) thought that electric vehicles should pay a lower rate per mile than gas and diesel vehicles, and more than three-quarters would prefer to pay a mileage fee either at the time of buying gas or charging an electric vehicle instead of receiving an annual bill.

Nicolas Norboge, North Carolina Office of State Budget and Management
Weston Head, North Carolina State University
Daniel Findley, North Carolina State University
Paul Broussard, North Carolina State University
Ravi Chittilla, North Carolina State University
Humberto Tasaico, North Carolina Department of Transportation

Changing trends in the automobile market are challenging the long-term sustainability of revenue streams—and possibly how the public perceives them. . In response, NCDOT commissioned a survey to better understand how the public perceives transportation taxes and fees. Using the knowledge gained from the literature review, the research team designed and administered a 21-question survey to 37,000 randomly selected households in North Carolina. The results suggest several instances where providing background information does have an impact. Preferences for general-based transportation taxes and fees are 14 percent greater when given the information-based survey than when compared to the baseline survey response. Second, there appears to be statistical differences by demographic group regarding support for increasing transportation funding. Those living in urban areas, males, those 50 years or older, those with a Bachelor’s degree or higher, and self-identified Democrats tend to be more supportive of transportation funding increases while those living in rural areas; females, those less than 50 years old, those with less than a Bachelor’s degree, and self-identified Republicans tend to be less supportive. In addition, 26.8 percent of respondents correctly identified the combined federal and state gas tax rate in North Carolina of 53.9 cents (selected by ranges.) Finally, the findings suggest a relatively little difference in responses between those that live in urban and rural areas. Finally, the results suggest statistical differences (but not many practical differences) in education, political affiliation, and age.

Asha Agrawal, San Jose State University
Hilary Nixon, Mineta Transportation Institute

This report summarizes the results from the eleventh year of a national public opinion survey asking U.S. adults questions related to their views on the federal gas tax. A nationally-representative sample of 2,515 respondents completed the online survey between February 14 and 28, 2020. The core of the survey tested public opinion about different variations on raising the federal gas tax rate by ten cents per gallon. In addition, respondents were asked about their views on the quality of their local transportation system, their priorities for federal transportation spending, their knowledge about gas taxes, travel behavior, and standard sociodemographic variables. This large set of variables is used to identify personal characteristics and opinions correlated with support for the tax options. Key findings include that large majorities support transportation improvements across modes, only 3% of respondents knew that the federal gas tax rate had not been raised in more than 20 years, and three-quarters of respondents supported increasing the federal gas tax by 10 cents-per-gallon if the revenue would be dedicated to maintenance. The trend analysis also found that support for all variants of the gas increase has increased since 2011.

Isabel Victoria-Jaramillo, Cambridge Systematics
Oscar Galvis Arce, University of Texas

This paper develops a tool that quantifies the additional direct costs accruing to highway users due to poor pavement conditions and estimates the necessary inputs to assess the total (direct, indirect and induced) economic losses. The paper presents the methodological approach for estimating the economic impacts arising from poor pavement condition based on the findings from the literature review; the metrics and open data sources to quantify the direct cost accrued by highway users; the formulas to monetize the direct costs; and the process to translate the monetized direct costs into the necessary model inputs for an economic model. The paper provides a practical example using data from three states and conducts a side-by-side comparison of the tool outcomes. Transportation agencies without sophisticated models and pavement condition data can benefit in many ways from the Economic Costs of Pavement Deterioration (ECPD) Excel-based tool. This tool estimates metrics on the economic cost of deteriorating pavement that are easily understood and broadly accepted by interested stakeholders and therefore, can be used to articulate the importance of highway preservation investments for economic growth.

Michael Lawrence, Jack Faucett Associates, Inc.
Jeffrey Cohen, JPC Milo Consulting
Sharada Vadali, Economic Insights and Research
Shikha Dave, Jack Faucett Associates, Inc.
Clayton Clark, Federal Highway Administration (FHWA)

This report describes the findings of an independent peer review of the modeling tools used by the Volpe 3 National Transportation Center to forecast national vehicle miles traveled (VMT) over the next thirty 4 years. Overall, the VMT forecasting models, which use auto-regressive distributed lag (ARDL) models 5 for light duty vehicle (LDV), single unit truck (SUT), and combination truck (CT) VMT, work well to 6 estimate travel demand. All model estimations were reviwed, and all models perfrom well against several 7 validation and testing techniques. The study team was supported by an expert panel selected from 8 academia, government, and industry with experience in econometric methods, transportation and 9 economic data, and modeling methods. The panel reviewed model documentation as well as the report 10 assessing the VMT forecasting models and provided insight on alternative model research. The paper is 11 an effort to synthesize the approaches and the validation methods used. A complementary literature 12 search is also conducted to test the validity and comparability of several estimated variable coefficients. 13 The paper concludes with summarizing the key findings and making recommendations on future model 14 improvements.