Research Helps City Improve Crash-Prone Bike Lane

Dozens of cyclists have crashed on a slice of railroad tracks in Knoxville, Tennessee. Researchers at the Southeastern Transportation Center at the University of Tennessee, Knoxville (UTK), developed a cost-effective solution. According to a recent study published in the Journal of Transport & Health, Professor Chris Cherry, with Ziwen Ling and Nirbesh Dhakal, found that most of these accidents occur when cyclists cross railroad tracks at an angle that causes a bike tire to become stuck in the gap between the rails. These UTK researchers happened to have a clear view of the accidents occurring almost daily, and they decided to understand why it happens so frequently. From the vantage point of a window in UTK\u2019s John D. Tickle Engineering Building, Cherry, Ling, and Dhakal recorded a brutal compilation of bike crashes using a window-mounted camera that logged more than 50 accidents at the railroad crossing, involving paths on both sides of the street, in just two months in 2014

Quantifying the Impact of New Mobility on Transit Ridership

USDOT Grant 69A3552047141This Final Report presents the outcomes of Community Analysis Research Project C3 that analyzed the impacts of new mobility modes \u2013 particularly micromobility \u2013 on transit ridership. Micromobility includes modes such as bicycles, electric bicycles (e-bikes) and electric scooters (e-scooters). This research focused specifically on shared electric scooters (e-scooters) in Nashville, Tennessee because of the availability of detailed e-scooter trip and device location data that were obtained through a data request to Nashville\u2019s Metropolitan Planning Organization. T-SCORE Project C3 was divided into two primary parts. The first part of the research performed an empirical analysis to quantify the impacts of the shared e-scooters on bus ridership in Nashville, Tennessee. Fixed effects regression models were estimated to explore six hypotheses about the relationship between bus ridership and shared e-scooters using both infrastructure-based and trip-based measures. The findings suggest that utilitarian shared e-scooter trips are associated with a decrease of 0.94% in bus ridership in Nashville on a typical weekday, whereas shared e-scooter social trips are associated with an increase of 0.86% in bus ridership in Nashville on a typical weekday. These findings suggest that shared e-scooters were associated with a net decrease of about 0.08% of total bus ridership on a typical weekday in Nashville, which is a minimal impact. The second part of T-SCORE Project C3 proposed a mixed methods approach to select locations to place shared e-scooter corrals near transit stops to encourage the use of shared e-scooters connecting to transit using Nashville, Tennessee as a case study. The method first used machine learning techniques to identify shared e-scooters trips that complement transit. Then, a multi-criteria scoring system was applied to rank bus stops based on shared e-scooter activity and bus service characteristics. Based on this scoring system, bus stops with the 50 highest scores were selected as potential locations for shared e-scooter corrals. Then, the capacity for the potential parking locations was estimated based on the hourly shared e-scooter usage. The results suggest that the 50 proposed corral locations could capture about 44% of shared e-scooter demand. The findings of this part of the research project could guide the implementation of shared e-scooter corrals in Nashville and inform other cities about how to select locations for shared e-scooter corrals near transit

Quantify Freeway Safety Service Patrol and Protect the Queue Impact on Transportation Network Reliability

The objective of this project is to evaluate and quantify the impacts and benefits of Freeway Safety Service Patrol (FSSP) and Protect the Queue (PTQ) programs using data-driven analysis. TDOT\u2019s Locate/IM and PTQ daily working reports data are the primary source of this study, which will help better understand the characteristics of incidents. WAZE\u2019s crowd-sourced incident report logs will be also heavily used in this project for the purpose of affording TDOT the flexibility of analyzing incidents outside the coverage areas by Locate/IM. The study reviewed the state-of-the-practice of traffic incident management (TIM) programs\u2019 impact evaluation methodologies and end-of-queue crash risk probability estimation methods, evaluated the benefits of HELP program in three different aggregation levels and assessed the benefits of PTQ based on a risk probability model. The study also developed an automated workflow for generating benefit cost analysis for HELP and PTQ programs and provided an Excel-based automation tool for easy implementation. All reports and deliverables are ready to use with TDOT data. The procedures assess benefits resultant from savings in travel delay, emission, fuel consumption, and secondary crash for a wide range of programs. Results from this study will be readily implementable for the entire State, any region, or even individual counties. The deliverables of this project provide factual statistics backed by sound analysis to assist TDOT\u2019S decision making process. The B/C reports for HELP program, for PTQ program, and for a new rural HELP program helps TDOT make important investment decisions to best serve the motoring public. The automated B/C reports for HELP program fulfills the recurring comprehensive performance monitoring objective. Furthermore, the incorporation of crowdsourced WAZE data into TDOT\u2019s exiting traffic incident management data framework leads to better understanding of incident characteristics and more efficient incident management

WAZE Data Reporting

This study evaluated the quality of crowdsourced Waze data (including reports and speed) and explored promising use scenarios of Waze data to facilitate the development of intelligent transportation in Tennessee. To this end, the thoroughly assessed Waze reports quality in terms of spatiotemporal accuracy and coverage. The study found Waze users reported crash events about 2.2 minutes sooner, on average, than reports of the same events recorded in the state\u2019s Locate/IM incident log. The reported crash locations per Waze are on average 6 feet from the Locate/IM log reported by the officials. It is found that 26% of crashes reported in Waze was matched with 67% Locate/IM crash reports, with the rest 74% reports pointing to unreported incidents. Waze speed is affected by the Wazers behaviors and tends to be slightly higher than detector speed in free-flow status. This study evaluated several novel use scenarios such as secondary crash detection, end of queue detection and tracking, level of service evaluation, work zone monitoring, wildlife hazards and crashes, and pothole detection and maintenance. Results show that Waze is a suitable data source for incident management, level of service evaluation, work zone management, roadway maintenance management, etc. when properly used and in cooperation with the agency\u2019s other information sources

The Economic Impact of a Renewable Biofuels/Energy Industry Supply Chain Using the Renewable Energy Economic Analysis Layers Modeling System

13-C-AJFF-UTenn-13This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: English BC, Menard RJ and Wilson B (2022) The Economic Impact of a Renewable Biofuels/Energy Industry Supply Chain Using the Renewable Energy Economic Analysis Layers Modeling System. Front. Energy Res. 10:780795. doi: 10.3389/fenrg.2022.78079The University of Tennessee\u2019s (UT) Department of Agricultural and Resource Economics models supply chains for both liquid and electricity generating technologies currently in use and/or forthcoming for the bio/renewable energy industry using the input\u2013output model IMPLAN\uae. The approach for ethanol, biodiesel, and other liquid fuels includes the establishment and production of the feedstock, transportation of the feedstock to the plant gate, and the one-time investment as well as annual operating of the facility that converts the feedstock to a biofuel. This modeling approach may also include the preprocessing and storage of feedstocks at depots. Labor/salary requirements and renewable identification number (RIN) values and credits attributable to the conversion facility, along with land-use changes for growing the feedstock are also included in the supply chain analyses. The investment and annual operating of renewable energy technologies for electricity generation for wind, solar, and digesters are modeled as well. Recent modeling emphasis has centered on the supply chain for liquid fuels using the Bureau of Economic Analysis\u2019s 179 economic trading areas as modeling regions. These various data layers necessary to estimate the economic impact are contained in UT\u2019s renewable energy economic analysis layers (REEAL) modeling system. This analysis provides an example scenario to demonstrate REEAL\u2019s modeling capabilities. The conversion technology modeled is a gasification Fischer\u2013Tropsch biorefinery with feedstock input of 495,000 metric tons per year of forest residue transported to a logging road that is less than one mile in distance. The biorefinery is expected to produce sustainable aviation fuel (SAF), diesel, and naphtha. An estimated one million tons of forest residue are required at fifty percent moisture content. Based on a technical economic assessment (TEA) developed by the Aviation Sustainability Center (ASCENT) and the quantity of hardwood residues available in the Central Appalachian region, three biorefineries could be sited each utilizing 495,000 dry metric tons per year. Each biorefinery could produce 47.5 million liters of SAF, 40.3 million liters of diesel, and 23.6 million liters of naphtha. Annual gross revenues for fuel required for the biorefineries to break even are estimated at $193.7 million per biorefinery. Break-even plant gate fuel prices when assuming RINs and 12.2 percent return on investment are$1.12 per liter for SAF, $1.15 per liter for diesel, and$0.97 per liter for naphtha. Based on IMPLAN, an input\u2013output model, and an investment of $1.7 billion, the estimated economic annual impact to the Central Appalachian region if the three biorefineries are sited is over a half a billion dollars. Leakages occur as investment dollars leaving the region based on the regions local purchase coefficients (i.e., LPPs), which totals$500 million. This results in an estimated $2.67 billion in economic activity with a multiplier of 1.7, or for every million dollars spent, an additional$0.7 million in economic activity is generated in the regional economy. Gross regional product is estimated at $1.28 billion and employment of nearly 1,200 jobs are created during the construction period of the biorefineries, which results in$700 million in labor income with multiplier effects. Economic activity for the feedstock operations (harvesting and chipping) is estimated at slightly more than $16.8 million resulting in an additional$30 million in the economic impact. The stumpage and additional profit occurring from the harvest of the forest residues result in $40 million directly into the pockets of the resource and logging operation owners. Their subsequent expenditures resulted in a total economic activity increase of$71.4 million. These operations result in creating an estimated 103 direct jobs for a total of 195 with multiplier effects. Direct feedstock transportation expenditures of more than $36.7 million provide an estimated increase in economic activity of almost$68 million accounting for the multiplier effects

New Safety UTC Envisions Safe Systems Approach for U.S. Roadways

The Collaborative Sciences Center for Road Safety (CSCRS), the new University Transportation Center (UTC) at The University of North Carolina, Chapel Hill (UNC) is taking a fresh approach to road safety. This national safety UTC is focused on implementing a collaborative, multidisciplinary, safe systems approach to reducing transportation-related injuries and fatalities and to helping traffic safety become recognized as a public health priority in the United States

Tier 1 University Transportation Center Match Funds for the Strategic Implications of Changing Public Transportation Travel Trends

69A3552047141Even before the onset of the COVID-19 pandemic, public transit ridership was declining in many metropolitan areas in the United States. To regain riders, transit agencies and their partners must make decisions about which strategies and policies to pursue within the constraints of their operating environments. To help address this, the Transit-Serving Communities Optimally, Responsively, and Efficiently (T-SCORE) Tier 1 University Transportation Center was set up as a research consortium from 2020 to 2023 led by Georgia Tech with research partners at the University of Kentucky, Brigham Young University and University of Tennessee, Knoxville (UTK). The T-SCORE Center had two primary research tracks: (1) Community Analysis (led by the University of Tennessee; included in this report) and (2) Multi-Modal Optimization and Simulation (led by the University of Kentucky; not included). The Community Analysis research track employed a combination of quantitative and qualitative research methods to assess three main drivers of change that have affected transit ridership: price and socioeconomic factors, the competitive landscape, and system disruptions, including COVID-19. The research approach for the Community Analysis track was divided into separate projects, and the UTK team led three projects that aimed to: (1) quantify the impact of different factors affecting transit ridership - including the COVID-19 pandemic - at a nationwide scale; (2) assess the impacts of shared micromobility, particularly electric scooters, on transit ridership; and (3) evaluate new fare payment technologies and emerging pricing strategies, with the vision of taking a step toward Mobility-as-a-Service (MaaS). The findings of these three Community Analysis projects can help inform transit agencies and city officials making decisions about how to increase transit ridership and plan for a sustainable future

Economic Analysis of Developing a Sustainable Aviation Fuel Supply Chain Incorporating With Carbon Credits: A Case Study of the Memphis International Airport

13-C-AJFF-UTENN-005This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Sharma BP, Yu TE, English BC and Boyer CN (2021) Economic Analysis of Developing a Sustainable Aviation Fuel Supply Chain Incorporating With Carbon Credits: A Case Study of the Memphis International Airport. Front. Energy Res. 9:775389. doi: 10.3389/fenrg.2021.775389Sustainable aviation fuel (SAF) has been considered as a potential means to mitigate greenhouse gas (GHG) emissions from the aviation sector, which is projected to continuously expand. This study examines the impact of developing a SAF sector along with carbon credits on carbon equivalent emissions from aviation using a Stackelberg leader-follower model that accounts for economic interaction between SAF processor and feedstock producers. The modeling framework is applied to an exante optimization of commercial scale SAF production for the Memphis International Airport from the switchgrass-based alcohol-to-jet pathway. Results suggest that supplying 136 million gallons of SAF to the Memphis International Airport annually could reduce 62.5% of GHG emissions compared to conventional jet fuel (CJF). Incorporating with carbon credits, SAF could lower GHG emissions by about 65% in total from displacing CJF and generate additional welfare gains ranging between $12 and$51 million annually compared to the case without carbon credits. In addition, sensitivity analysis suggests advancing SAF conversion rate from biomass could lower the SAF break-even considerably and enhance the competitiveness of SAF over CJF

Optimal N Application Rates on Switchgrass for Producers and a Biorefinery

13-C-AJFF-UTenn-005This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Robertson, K.A.; English, B.C.; Clark, C.D.; Thompson, J.M.; Jensen, K.L.; Menard, R.J.; Labb\ue9, N. Optimal N Application Rates on Switchgrass for Producers and a Biorefinery. Energies 2021, 14, 7912. https://doi.org/10.3390/en14237912This study analyzes the effects of N fertilizer application rates on profitability of growing switchgrass and using the feedstock in a pyrolysis biorefinery facility to create a source of sustainable aviation fuel (SAF) supply in Tennessee. Switchgrass (Panicum virgatum L.) is a perennial bunchgrass native to North America with traits suitable for biofuel and co-product production. Previous chemical analysis has shown that ash content in switchgrass is related to the amount of nitrogen applied to the field, while at the biorefinery level, the percentage ash content reduces the biorefinery fuel output. To obtain optimal nitrogen (N) application rates for the switchgrass producers and the biorefinery, a two-part analysis is employed. First, a partial budgeting profitability analysis is conducted for this cropping enterprise at the farm-gate level without considering downstream implications of biomass quality, i.e., ash content. Second, the effects of higher ash content as a percentage of the feedstock on biorefinery output are analyzed. Results show farm-gate profit is maximized when N fertilizer is applied at 111 kg/ha, while as a result of increased production levels and decreased percentage ash content, biorefinery profit is maximized when N is applied at 157 kg/ha. Lower ash could lead to premium prices paid to switchgrass producers if higher quality feedstock were to be demanded as part of an integrated biofuel industry