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A study that aimed at designing a user interface for an autonomous agricultural sprayer was undertaken. It involved i) a survey of the farming community to gather their opinions about technological advancement of current agricultural machines and their expectations with respect to automated agricultural machines, ii) interviews with automated system designers and experts to understand how they intend/expect autonomous agricultural machines to be remotely supervised, iii) field and laboratory experiments to identify the necessary visual information for the remote supervisor to understand the operation of the automated machine, iv) ranking of machine and environment parameters based on their frequency of usage during machine monitoring, v) determining a suitable modality that will alert the supervisor of an issue requiring human attention and, vi) an evaluation of an automation interface. The survey of the farming community provided evidence that farmers and custom applicators are satisfied with the technological advancement of agricultural machines and are also willing to accept an automated sprayer when it becomes commercially available. The survey also provided an understanding of how farmers will prefer to interact with the automated machine. The field and laboratory experiments identified different regions of the machine and its environment that should be visually provided to the remote supervisor to enhance their understanding of the operation. A variety of remote supervision concepts were discovered during the interviews with designers of automated systems. These concepts were grouped into four categories based on the location of the human or remote station (within-the-field, close-to-the-field, farm office, and outside-the-farmland). Using the unranked paired analysis, the close-to-the-field remote supervision concept was considered the most viable concept. The study to identify the most suitable warning modalities revealed that the most suitable warning modal

The main obstacle in power scaling of the well-known Nd-doped lasers such as Nd:YVO4 is the thermal lensing effect. One of the proposed solutions to effectively alleviate this problem was based on the reduction of heating within the laser crystal. This was extensively investigated with the Nd:YVO4 crystal by pumping the laser at 914 nm instead of the standard pumping at 808 nm wavelength. In context of high power applications, the crystal of Nd:GdVO4 is an interesting alternative to the Nd:YVO4 as it offers the benefits of good spectral features (similar to Nd:YVO4) and much higher thermal conductivity. However, there is only one proof-of-principle work on continuous-wave (CW) Nd:GdVO4 laser using this pumping approach in which an output power of 3.35 W was reported. The full power scaling potential of the Nd:GdVO4 laser crystal to produce high output power has not been demonstrated to date. In this PhD thesis, I addressed this issue and investigated the high power operation of Nd:GdVO4 lasers under a new pumping wavelength of 912 nm. First, the thermal lensing behaviour of a 1063 nm Nd:GdVO4 was studied, both experimentally and by finite element analysis (FEA) method. The thermal lensing strength in Nd:GdVO4 laser under 912 nm pumping was significantly reduced when compared to the Nd:GdVO4 laser with 808 nm pumping or even Nd:YVO4 laser with 914 nm pumping. The next step of this research was focused on high power operation of Nd:GdVO4 lasers where we achieved 19.8 W of output power at 1063 nm. As a side work in the CW regime of operation, the possibility of discrete wavelength tuning and dual-wavelength operation of the Nd:GdVO4 laser were examined by using an intracavity birefringent filter. Discrete wavelength operation at four different wavelengths was demonstrated. Furthermore, for the first time we were able to demonstrate a dual-wavelength operation of the Nd:GdVO4 laser as a 1063 and 1071 nm wavelength pair. The last aspect of this PhD thesis was concentrate

Soybean (Glycine max L. Merr.) planting date and plant density are agronomic decisions made simultaneously at the beginning of the growing season that can be used to maximize yield and economic return. Research on these basic soybean agronomic decisions must be conducted to support the expansion of soybean production in northern growing regions of the Northern Great Plains (NGP). The objectives of this study were to evaluate the effects of planting dates based on soil temperature on soybean emergence, maturity, and yield for short and long season varieties in Manitoba, and to determine optimum soybean plant density for early to very late planting dates in northern growing regions of the NGP. In the first experiment, calendar date had a greater influence than soil temperature at planting on soybean yield. Soybean yield declined with later planting rather than increasing soil temperature at planting. The earliest planting dates resulted in the greatest soybean yields. In the second experiment, soybean yield-density relationships were responsive to planting date. Yield-density relationships formed early/mid (May 4 to 26) and late/very late (June 2 to 23) planting date groups for combined site years. Early/mid planting dates resulted in greater maximum yields. According to the yield-density model, true yield maximization did not occur for any planting dates and site years within the range of plant densities tested in this field study. Soybean economic optimum seed densities (EOSDs) were much lower than predicted plant densities that maximized yield. Soybean EOSDs were identified as 492,000 and 314,000 seeds ha-1 by marginal cost analysis for early/mid and late/very late planting, respectfully. These values were sensitive to changes in soybean grain price and seed cost. Thus, growers need to adjust EOSDs for changes in price and cost. A combined analysis of soybean yields from both experiments using similar target plant densities determined that a significant negative li

The occurrence of D. weischeri Chizhov, Borisov & Subbotin, a newly described stem nematode species of creeping thistle (Cirsium arvense L.), and D. dipsaci (Kühn) Filipjev, a pest of garlic and quarantine parasitic species of many crops, has been reported in Canada. This research was conducted to determine if D. weischeri is a pest of agricultural crops, especially yellow pea (Pisum sativum L.) in the Canadian Prairies. Significant (P < 0.05) slight reproduction (1 < ratio of final to initial population < 2) of D. weischeri occurred on two (Agassiz and Golden) of five varieties of yellow pea examined. Other annual pulse and non-pulse crops, including common bean, chickpea, lentil, spring wheat, canola, and garlic were non-hosts for D. weischeri. Conversely, a range of reproduction responses to D. dipsaci was observed with all pulse crops being a host of the nematode. Ditylenchus weischeri was not a seed-borne parasite of yellow pea, unlike, D. dipsaci which was recovered from seed. Conversely, D. weischeri and not D. dipsaci was recovered from creeping thistle seeds. In callused carrot disks, with no addition of medium, an increase of 54 and 244 times the addition density of 80 nematodes was obtained for D. weischeri and D. dipsaci, respectively, after 90 days. Temperature had a significant influence on the development of D. weischeri and D. dipsaci in yellow pea. Development of D. weischeri did not proceed past adult stage at 17 and 22°C whereas a minimum generation time of 30 days was apparent at 27°C with the associated accumulated growing degree-days of 720 degree-days (above a base temperature of 3°C). The minimum generation time for D. dipsaci was 24, 18 and 22 days with 336, 342 and 528 degree-days at 17, 22 and 27°C, respectively. In field microplots, grain yield of yellow pea were not significantly affected by addition density of D. weischeri. At harvest, the total number of recovered nematodes per plant was not significantly different than the added at th

Cloud computing at a high level comprises of the availability of hardware, software and technical support via a network protocol to a remote client on a pay-per-use basis. Businesses using Cloud resources has been increasing steadily in the very recent past and the number of Cloud service providers (CSP) are increasing as well. The challenges that characterize a Cloud data center include: on-demand service, elasticity, resources pooling, broad network access, service meters. As the customer base is in creasing and their resource requirement and usage pattern has been becoming highly volatile, proper utilization of the resources and generating revenue by appropriately charging the clients for their uses has become an even more challenging research problem. In other words, Cloud resource pricing has emerged as an important and pressing problem to study for ever increasing utility of Cloud computing. Literature review reveals that there are economy-based models (cash flow, net present value etc.) used for charging mechanism suggested by many researchers. Most of these models are rigid that they are not build with the core of Cloud - elasticity in mind. Also, the economic models do not provide flexibility of the economy of scale to either increase or decrease the resource requirement and appropriately charge for such increase or decrease in resource use. For my thesis, I have designed and developed a Cloud resources pricing model that satisfies two important constraints: the dynamic ability of the model to provide a high satisfaction guarantee measured as Quality of Service (QoS) - from users perspectives, and profitability constraints - from the Cloud service providers perspectives. I have employed financial option theory and treated the Cloud resources as underlying assets to capture the realistic value of the Cloud Compute Commodities (C3). I have priced the Cloud resources using my model. Through this research, I show that the Cloud parameters can be mapped to financial e

Manitoba is the second largest potato-producing province in Canada, after Prince Edward Island. Although the Manitoba average yield is slightly higher than the Canadian average, there are commercial fields with lower yield as a result of the pressure of diseases like Verticillium wilt, caused by Verticillium dahliae. In Manitoba and elsewhere, there is increased interest in the use of soil fumigation and application of composted manures to reduce Verticillium wilt. However, accurate quantification of V. dahliae inoculum in soil is needed for disease control decisions as well as to determine success of practices to reduce pathogen levels in soil. The traditional wet plating method for determination of Verticillium levels in soil is often prone to errors, laborious and costly. Therefore, the objectives of this thesis research were to: (i) evaluate control measures including compost addition and soil fumigation on Verticillium wilt and yield of potato, cv. Norland and cv. Russet Burbank; (ii) investigate the presence and quantity of microsclerotia-forming Verticillium species and its relation to Verticillium wilt in potato; and (iii) evaluate pathogenicity of V. tricorpus on potato, cv. Russet Burbank. In a replicated field study, composted manure did not prove to consistently reduce Verticillium wilt. Fumigation with metam sodium resulted in a reduction of V. dahliae levels in soil; however, only the lowest rate at 374 L ha-1 reduced Verticillium inoculum at planting by up to 40%, and increased marketable yield in cv. Russet Burbank by up to 24%. This result could potentially help growers to reduce environmental impact on organisms not targeted and the costs associated to the use of soil fumigant for the control of Verticillium wilt. Examination of soils and plants from 17 commercial potato fields determined the presence of the microsclerotia-forming Verticillium species V. dahliae as well as Verticillium tricorpus and Verticillium klebahnii in Manitoba. Nevertheless

Antimicrobials are widely used in North America’s livestock industry. Field application of livestock manure disperses antimicrobials in to the environment. Antimicrobials can increase the level of antimicrobial resistance development in human and livestock pathogens. Three main studies were conducted to: i) quantify the simulated rain runoff losses of chlortetracycline, sulfamethazine and tylosin following surface application vs. soil incorporation of beef cattle feedlot manure; ii) quantify the dissipation kinetics of these antimicrobials in a seasonally-frozen soil following field application of manure; and iii) quantify and compare the dissipation of excreted vs. fortified (that is, added to antimicrobial-free manure) antimicrobials during indoor composting. Manure was sourced from cattle (Bos taurus) receiving no antimicrobial (control), 44 mg chlortetracycline, 44 mg each of chlortetracycline and sulfamethazine, or 11 mg tylosin per kg-1 feed. Antimicrobial concentration in simulated rain runoff following field application of manure generally reflected the corresponding concentrations in manure. Mass loss ranged from 1.7 to 6.5% for chlortetracycline and was 4.8% for sulfamethazine and 0.24% for tylosin. Incorporation of manure into the top 10 cm of soil significantly reduced the mass loss of chlortetracycline and the concentration in runoff of both chlortetracycline and sulfamethazine. Both chlortetracycline and sulfamethazine were persistent in the seasonally-frozen Canadian prairie soil tested. The first-order dissipation half-life (DT50) for chlortetracycline added along with sulfamethazine was 77 d during the growing season and 648 d during the non-growing season. The DT50 of chlortetracycline added alone did not differ significantly between the two seasons (mean DT50 = 121 d). Sulfamethazine was detected throughout the 10-mo monitoring period (mean ≤ 16 ± 10 µg kg-1). Composting dissipated 85–99% of initial concentrations of chlortetracycline, sulfamethaz

Brush encroachment is a serious problem on pastures in Western Canada. It results in a loss of productivity and habitat for wildlife. Sixty-seven pastures were visited in Manitoba, Saskatchewan and Alberta. Approximately half were privately owned lands and the remainder were public lands. Each field sampled was divided into grass, shrub and forest strata, within each stratum vegetation cover was noted and biomass and soil samples were taken. A historical reconstruction was created using aerial photos dating back to the 1940s up until most recent photos available. Six cover classes were delineated and patch statistics were calculated. Information on historical management practices were obtained also. It was determined that woody encroachment is occurring on pastures, but no significant trends found between environmental factors and encroachment. Therefore it was concluded that management probably has the greatest impact on the occurrence and extent of woody encroachment.

No Abstract.

From values of the heat capacity of microcrystalline Pr(OH)3 determined by precise adiabatic calorimetry from 15 to 350 K, the Schottky contribution associated with all but the lowest Stark level was resolved with the aid of a model of the lattice heat capacity based upon the molar volumes of the lanthanide trihydroxides. Visible and infrared absorption spectra were taken at approximately 95 K on microcrystalline mulls and the energy-level scheme and crystalline electric-field parameters evaluated. The Schottky contribution of all levels above the first excited state ([mu] = 3) was resolved by a new scheme for modeling the lattice contribution and compared with the same contribution deduced from the spectral results. Excellent accord was observed. These results together with magnetic results and the first excited Stark level were used to adjust the low-temperature heat capacities and thermodynamic functions so as to evaluate Cp/R, So/R, and - {Go - Ho(0)}/RT, at 298.15 K as 14.154, 15.84, and 7.766, respectively.

The heat capacities of the anhydrous lanthanide trichlorides from 5 to 350 K of Sommers and Westrum provide an excellent opportunity further to test the volumetric lattice heat-capacity approximation method. Schottky contributions in PrCl3, SmCl3, and EuCl3 were calorimetrically derived using the volume-weighted interpolation between the lattice heat capacities of the La and Gd homologs. Previously qualitative agreement had been observed upon comparison of these calorimetrically derived Schottky contributions with those calculated from spectroscopic data obtained for Ln(III)-doped LaCl3 crystals. Excellent accord between "spectroscopic" and "calorimetric" Schottky contributions is achieved by adjusting the Stark-level energies to represent those of the concentrated salts through extrapolation of the Ln(III)-doped LaCl3 energies to stronger crystal fields either empirically or by means of estimated crystal-field parameters. These methods are described and the resulting energy levels are compared with the extant spectroscopic results for the concentrated trichlorides. In addition, new electronic-Raman-scattering determinations were made on PrCl3 and SmCl3 at 15 K and vibrational Raman lines are reported for SmCl3 at 300 K. Deduced electronic energy levels for the ground and first excited [SL]J-manifolds are listed for both compounds.

View looking south of Broadway from just north of the N.P. Avenue intersection in Fargo, N.D. showing the White Building, the First National Bank building, J. C. Penney's and the Fargo National Bank building in the distance. View shows the Red River Mall with canopies and trees decorated with lights., 21 x 26 cm., "Downtown Fargo Mall" - handwritten on back of photograph., Title supplied by staff. Photographer unknown.

View, looking east, of wood bridge over the railroad tracks on Twelfth Avenue North. Two automobiles parked on edge of bridge and a young man standing by bridge. In distance railroad cars under bridge. Center portion of bridge is of metal trestle construction., Gelatin silver prints, 19 x 26 cm., "Last fall the 12th Avenue overpass was torn down to make way for a new, safer and more reliable replacement. No one was sorry to see the old overpass go, although it did have a certain ramshackle charm. The new overpass will be a long time in coming however, and by the time it's completed some may be wishing they had the old bridge back." - citation with photo in The Bison 1977 yearbook, p. 168., Title supplied by staff. Photographer either Don Pearson or Jerry Anderson, 1977 Bison yearbook staff.

Taco John's fast food restaurant located on corner of 10th Street and 4th Avenue N. Small building has Coca-Cola signs on it. In front of the building are two picnic tables. Two garbage cans also visible. Business sign on pole located at right., Gelatin silver prints, 17 x 25 cm., "Misc. Fargo Scene - Taco John's c. mid 1980s" - Handwritten on back of print., Title supplied by staff. Photographer unknown., This was the first Taco John's located in Fargo, N.D. opened about 1974., Published in the 1978 Bison yearbook, p. 113.

Achieving and maintaining public transportation rolling stocks in a state of good repair is very crucial to providing safe and reliable services to riders. Transit agencies that seek federal grants must also keep their transit assets in a state of good repair. Therefore, transit agencies in small urban and rural transit systems need an intelligent predictive model for analyzing their transportation rolling stocks, determining the current conditions, predicting when they need to be replaced or rehabilitated, and determining the funding needed to replace in a future year to maintain the state of good repair. Since many transit agencies in small urban and rural transit systems do not have adequate analytical tools for predicting the service life of vehicles, this simple predictive model would be a valuable resource for their state of good repair needs and their prioritization of capital needs for replacement and rehabilitation. The ability to accurately predict the service life of revenue vehicles is crucial in achieving the state of good repair. In this research, three unique tree-based ensemble learning methods have been applied to build three predictive models. The machine learning methods used in this research are random forest regression, gradient boosting regression, and decision tree regression. After evaluation and comparison of the performance results among all models, the gradient boosting regression model with the top 35 most important features was found to be the best fit for predicting the service life of transit vehicles. This model can be used to predict the projected retirement year for all small urban and rural vehicles in operation.

The local road safety program strategy has been proven effective in reducing crashes on rural roads. In this study, local road managers were surveyed about road safety activities with special emphasis on the western counties in the oil impact region. The survey provides insight for improved local road safety program delivery and monitoring.

Food insecurity is a persistent problem in the U.S. that is disproportionately distributed across racial groups. Native American tribes, many located in rural areas, have high rates of food insecurity. Transportation plays a role in the limited access to food. This study focused on transportation used by Native Americans in North Dakota to access healthy foods. A survey was administered in September and October 2022. Responses from 246 Native Americans revealed that nearly 50% of the respondents have very low food security, 27% have low food security, and 25% have high or marginal food security. An ordered logit model revealed that income, food assistance programs, education, and the ability to drive to the grocery store significantly influence food security. The study found that 20% of respondents do not drive or have access to a vehicle for transportation. Native Americans in North Dakota are significantly less likely to own or have access to a vehicle. Most respondents (71%) drive to get groceries, while 27% get a ride from someone, and 21% walk. Age, income, living within walking distance of a grocery store, availability of fresh food, and living on the reservation were found to be positively associated with the likelihood of an individual eating healthy food every day.

Annually, many injuries and fatal crashes happen on local rural roads in North Dakota. The local road safety program (LRSP) strategy has been proven effective in reducing crashes on these roads. It relies on state engagement with local stakeholders to collectively reduce crash injuries in their communities. The LRSP presents a framework for stakeholders to identify, analyze, and prioritize traffic safety improvements for their roadways. In this study, local road managers were surveyed about road safety activities with special emphasis on the western counties in the oil impact region. The results reflect current practices in local government road management. It will be a resource for growing program participation and activities by providing best practices and peer knowledge sharing. One in five counties reported applying for LRSP projects over the past five years. Comparison to a previous survey shows a notable expansion in counties adopting low-cost safety strategies. The benefits of federal and state support in instituting local road safety practices were evident in funding sources and planning activities reported by counties. Several opportunities to carry this forward in proactive safety opportunities for individual counties with specific crash-type prevention strategies and for systemwide site-based safety countermeasures were evident. The survey investigation can inform other states by providing insight regarding LRSP practices and perceptions, with regard to improvements in local road safety and the potential to grow local agencies as champions in the effort.

The Office of Highway Policy Information of Federal Highway Administration (FHWA) publishes statistical data about motor vehicle registrations reported by the 50 states and District of Columbia. According to its 2020 publication, the 97.94% of vehicles in the State of North Dakota are registered as either private or commercial. The remaining 2.06% are publicly owned. The national averages are 98.51% private or commercial and 1.49% publicly owned.

MPC 23-506 (project 666), The emerging field of Advanced Air Mobility (AAM) presents myriad opportunities for disrupting traditional modes of transport, including passenger travel to cargo logistics. However, its path to full-scale adoption is fraught with regulatory, market, and logistical challenges. This report presents a nuanced understanding of AAM's complexities and its potential for transformative impact, particularly to reduce the impacts on surface transportation degradation. The research employs data-driven methodologies, machine learning algorithms, and Geographic Information System (GIS) techniques to explore the landscape of AAM.

As part of this study, 15 intersections with approximately 60 cameras were to be configured to collect traffic volumes and speeds. All of these cameras are the newer VISION models. In addition, the objectives of the study include building enhancements to the existing North Dakota State University (NDSU) Traffic Analysis Tool and to obtain cost estimates for upgrading East Grand Forks signalized intersections to enable similar data collection efforts within the metropolitan planning organization (MPO) region. This study was divided into six major tasks: Data Polling & Transfer, VISION Data Reporting, Data Quality Audits, East Grand Forks Estimation, Level of Service Estimation Feasibility Check, and Traffic Analysis Tool Enhancements.

The CMMM will collect a wide range of data from testing facilities at its associated universities. This includes but is not limited to behavioral data collected from surveys and field observations, data collected from driving simulators, emissions data collected from the field and simulators, crash statistics, demographic information, video footage, traffic operations data, and geolocation data. This data will be either collected directly by the principal investigators carrying out the projects in question (primary data collection) or aggregated and analyzed to produce new insights (secondary data).

Bicycle and scooter use entails significant safety and health risks. News stories have described the reckless behavior of users across the United States with the emergence of micromobility options. This paper investigates risky behaviors associated with U.S. bicycle and scooter riding adults. Two separate surveys were administered through the Qualtrics platform. Participants were asked to rate the severity and frequency of 20 risky behaviors of riders on five Likert scales. The risk matrix is built based on the magnitude and frequency of each risk, and ordered logistic regression is applied to identify significant factors. Regression analysis revealed that age and income are significant factors shared between both survey groups. Education level and living in urban areas are two statistically significant factors explaining the different risky behaviors with bicycles or scooters. In general, the survey results show that participants perceive there is a low risk associated with reckless behaviors.

Tree failures due to strong winds in urban areas cause extensive direct and indirect economic and environmental loss, including disrupting adjacent infrastructures, such as buildings, underground pipelines, roads, and overhead powerlines. To effectively improve the resilience of a community subjected to extreme wind events through prevention, response, and recovery, it becomes critical to rationally assess the risks of wind-induced tree failures and the disruptions to different types of infrastructures due to fallen trees. An integrated probabilistic methodology to model the performance of disrupted infrastructures is developed for fallen urban trees subjected to extreme winds in a typical community. First, the finite-element modeling of the trees subjected to wind loads is conducted and, based on which, the windthrow fragility curves of several typical urban tree species are developed. Second, a probabilistic framework is developed based on the fragility results to characterize the disrupted scenarios and further predict the disruption probability of some critical infrastructures due to fallen trees. The matrix-based system reliability (MSR) method is introduced to assess the transportation network performance. The proposed framework and MSR method are demonstrated in detail while studying the overhead powerline and transportation network of a small urban community in the city of Fort Collins, Colorado. In the demonstrative example, the probabilities of powerline disruption, road closure, and origin-destination (OD) disconnection and travel time reliability under different wind conditions are predicted. Finally, mitigation efforts such as crown thinning of trees are discussed to reduce possible risks of disrupting the infrastructures.

A transportation system, consisting of roads and bridges, experiences various types of disruptions subjected to different hazards, including long-term, short-term and temporary ones. Due to the complex nature and different causes, disruptions can be very hard to predict with high uncertainty.

The geogrid-reinforced pavement system on the section of State Route 10 between Muddy Creek and Emery, Utah, experienced premature deterioration. Research was needed to understand the reasons for this deterioration and to develop an improved understanding of the significant influence that native subgrade and fill materials have on the performance of pavement systems constructed on soft subgrades and how geogrid can limit damage stemming from these materials.

The emerging field of Advanced Air Mobility (AAM) presents myriad opportunities for disrupting traditional modes of transport, including passenger travel to cargo logistics. However, its path to full-scale adoption is fraught with regulatory, market, and logistical challenges. This report presents a nuanced understanding of AAM's complexities and its potential for transformative impact, particularly to reduce the impacts on surface transportation degradation. The research employs data-driven methodologies, machine learning algorithms, and Geographic Information System (GIS) techniques to explore the landscape of AAM. These studies reveal the crucial role of regulatory frameworks and gross domestic product in AAM adoption, the importance of accurate market forecasting, and the value of identifying key commodity and geographical targets for cargo drones. Additionally, this study highlights the potential of AAM in safely transporting dangerous cargo and improving pharmaceutical supply chains. The successful integration of AAM into global transportation systems requires a multi-disciplinary and multi-stakeholder approach. This study highlights the need for future research to build on this work to scale and optimize AAM technologies to meet the varying needs of nations and industries worldwide.

69A3552348329, This document describes the Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH) policy on data handling, storage, and sharing. CARTEEH is a Tier 1 University Transportation Center (UTC) that aims to promote interdisciplinary research in the area of transportation and health, including facilitating collaboration between health and transportation researchers by integrating data sources from the two research fields. The CARTEEH center was originally set up under the Fixing America’s Surface Transportation (FAST Act) in 2016 and has been renewed for funding under the Bipartisan Infrastructure Legislation (BIL) UTC Competition in 2023. The integration of transportation and health data presents novel challenges for effective and safe data handling and sharing. For this reason, CARTEEH’s Data Management Plan (DMP) will be a “living document” that will be updated as necessary over the life of the Center.

The statewide driver traffic safety survey provides baseline metrics for the Highway Safety Division and others to use in understanding perceptions and self-reported behaviors related to focus issues. A core set of questions addressed nationally agreed upon priorities, including seat belts, impaired driving, and speeding. In addition to the core issues, questions were included to better understand views on specific programs and attitudes pertinent to North Dakota drivers. Results show that more North Dakota drivers have adopted safe-driving practices, but additional efforts are needed to improve safety on the state’s roads.

As part of this study, a total of 16 intersections comprising of approx. 61 cameras were to be set to collect traffic volumes and speeds. Note that one of the intersections originally part of this project had not been brought online (resulting in delayed completion). In order to avoid further delays, in lieu of the offline intersections, other area intersections which had been affected by current or past construction and required data collection to be reset were included in this project.

MPC-657, The U.S. Department of Transportation (USDOT) needs to respond quickly and adapt to the coronavirus (COVID- 19) to ensure continuation of critical infrastructure support and relief for the American people. Since early March 2020, the COVID-19 pandemic has had significant impact on traffic across the United States. It is clear to see that traffic patterns, traffic demands, and duration alter with COVID status. Therefore, there is a critical research need to study the impact of COVID on traffic patterns and to analyze the relationships among traffic demand patterns, daily confirmed cases/deaths, state policies, public perceptions, etc. In this research, we investigate the impact of COVID-19 on traffic safety in different stages, focusing on Salt Lake County, Utah. Statistical methods are employed to determine if there are any differences in the effects of the pandemic. Further, the effect of COVID-19 on traffic patterns in Salt Lake County and Utah County from January 2019 to July 2021 was analyzed. Different vehicle miles traveled (VMT) patterns in the pre-pandemic stage, early stage of the pandemic, and late stage of the pandemic are identified. Finally, a knowledge-based traffic prediction model utilizing an innovative approach that integrates machine learning with graph theory is proposed to forecast traffic patterns in the near future.

MPC-524, Liquefaction-induced lateral spread is a type of permanent ground deformation from the horizontal movement of surface soil resulting from soil liquefaction and resulting loss of shear strength during earthquakes. It is generally the most pervasive and damaging type of liquefaction-induced ground failure occurring during major earthquakes, and it has caused hundreds of millions of dollars of damage to transportation infrastructure such as bridges, embankments, culverts, and pavements. There is a need to improve the analytical and numerical methods to estimate the amount of permanent ground displacement associated with liquefaction-induced lateral spread. These methods will be used to make transportation more resilient to such damages and to proactively identify, quantify, visualize, prioritize, and mitigate risk from earthquakes.

MPC-657, Researchers examined the impacts of COVID-19 on traffic safety in three different stages to better understand the relationship between traffic demand patterns, daily confirmed cases/deaths, state policies, and public perceptions and other factors.

The primary objective of this research was to identify veterans affected by COVID-19 who have mobility needs and who live in rural areas and to quantify the cost of transportation options for meeting those needs. Secondary objectives included analyzing the role of telehealth and how the pandemic has affected mobility and isolation among veterans in rural America. Analysis showed that a coordination effort between VA medical centers and rural public transit agencies would be feasible if projected ridership levels could be met. Policies to encourage possible coordination should be considered to improve veteran medical transportation services.

MPC-454, Tribal communities recognize the need to improve roadway safety. A five-step methodology has been developed by the Wyoming Technology Transfer Center to improve roadway safety on reservations. This methodology was initially implemented on the Wind River Indian Reservation, which led to the Wyoming Department of Transportation’s funding of three system-wide, low-cost safety improvement projects. Due to the success of the program on the Wind River Indian Reservation, tribes across the country have become interested in implementing the program. WYT2/LTAP and the Northern Plains Tribal Technical Assistance Program (NPTTAP) are helping tribes implement this program on their reservations in the Great Plains region, and have developed criteria to identify tribes for participation. This study aimed to improve roadway safety of the Standing Rock Sioux Reservation.

The current pandemic has affected the lives of all Americans. Rural communities are particularly vulnerable because of a lack of mobility services and the great distances individuals must travel for healthcare and other needs. Nearly five million veterans live in rural communities, representing 57% of Veterans Administration (VA) health care enrollees (MOAA 2020). COVID-19 cases and deaths among rural veterans have increased at a faster rate compared to veterans in urban areas according to Johns Hopkins University (2020). They also found that delayed COVID-19 testing contributed to a higher rate of cases in rural areas compared to urban areas. The primary objective of this research was to identify veterans affected by COVID-19 who live in rural areas and have mobility needs and to quantify the cost of transportation options for meeting these needs. Secondary objectives included analyzing the role of telehealth and how the pandemic has affected mobility and isolation among veterans in rural America. Survey results of 150 military veterans showed that many veterans have experienced considerable change due to the COVID-19 pandemic.

The research focused on providing tools and knowledge on the following four issues: 1) integrated grade-crossing crash frequency and severity prediction models, 2) marginal effectiveness of countermeasures, 3) geometric factors’ contribution to crash frequency and severity, and 4) integrated hazard rankings of North Dakota grade crossings. The research proposed an innovative statistical method, competing risk modeling (CRM), to identify the contributors, quantify marginal effects of geometric factors and control devices, and predict crash occurrence and severity simultaneously. Traffic exposure variables such as annual average daily traffic, day through-train, night through-train, train speed, and percentage of trucks are all significant contributors. Type of train services, commercial power availability, and train detection technologies are also identified as significant contributors. Moreover, the research also further quantified the four geometric contributors’ effects and conducted detailed marginal effectiveness analysis for traffic control devices considering the pre-control conditions. The four geometric factors are: distance between a crossing and its nearest intersection, crossing angle as a continuous variable, number of lanes, and number of tracks. These geometric factors are spatially calculated with GIS software if they are not readily available. The research also investigated use of the effectiveness and prediction results to rank and prioritize crossings based on safety hazard.

Researchers have determined needs and available resources through a literature review and interview process. They developed a benefits estimation methodology focused on benefits related to traffic operations, traffic safety, environmental impacts, and project costs, and subsequently developed spreadsheet software tools that implement the benefits estimation and calculation of traffic safety benefits, using Synchro/SimTraffic for estimating traffic operations and environmental impacts.

MPC-458, In this study, researchers used the agent-based simulation (ABS) for modeling agricultural transportation demand. With the simulation model, geographic information systems (GIS) was utilized to collect and analyze remote sensing of agricultural crops. The researchers reviewed agent-based modeling in freight and public transportation planning to fill the gap between traditional modeling efforts and emerging needs of adopting behavioral modeling for an agricultural transportation model. The study then investigated adoption of an agent-based model for a large-scale travel demand model. The objective of the proposed model was to provide a platform to analyze grain transportation movement at the micro-level, since most industry reports lack such micro-level freight analysis while supporting regional and statewide planning.

The Grand Forks – East Grand Forks MPO contacted ATAC with regards to expanding the use of existing traffic detection cameras for traffic data collection. Prior to this project, the City of Grand Forks had 31 intersections comprising of 122 cameras set for traffic data collection purposes. As part of the current project, 7 intersections comprising of 24 cameras are to be setup for traffic data collection. Additionally, the MPO had requested a feasibility study to include rail preemption event data in the archival databases similar to those created during Phase II of the study. It is envisioned that if feasible, all intersections with rail preemption will be setup (under a separate study) such that Traffic Analysis web interface may be used to run rail preemption event reports.

The Grand Forks – East Grand Forks MPO contacted ATAC with regards to extending the use of existing traffic detection cameras for traffic data collection and archival. The City of Grand Forks currently has approx. 43 intersections where Autoscope cameras are being used for traffic signal actuation purposes. More intersections within the network are being updated to have the same camera-based detection capabilities. Additional functions of these Autoscope cameras include traffic data collection.

19-TMTSD-ND-005, A survey of farm operators in the Central Plains Region, including Illinois, Indiana, Iowa, Kansas, and Nebraska, was conducted to gather information about transportation of crops, the inventory and characteristics of farmer-owned truck fleets, and on-farm storage capacity. The objective of the study is to provide information about the farm truck inventory and marketing patterns in the Central Plains. There is no other source for this information, and it should be unique and complementary to other farm-to-market information and national commodity flow publications. Farmers may use the results for their own investment and productivity assessments. Local and regional planners and policy makers can use the information to calibrate travel demand and freight flow models for investment and asset management choices and to estimate pavement impacts. Survey results indicate that the 5-axle semi is the most common truck configuration within the study area and that single-axle and tandem-axle truck ownership will decline in the future in favor of 5-axle and 7-axle configurations. On-farm storage is concentrated on larger farms in terms of average capacity, but the storage per bushel harvested is inversely related to farm size. The average distance to the first-choice delivery point was 14.92 miles.

As a result of the considerable differences in mass between vehicles and trains, crashes at highway-rail grade crossings (HRGCs) often result in severe injuries and fatalities. Therefore, HRGC safety is considered a crucial transportation safety issue. Transportation decision makers and agencies need an efficient safety decision-making framework that is able to predict crash occurrence and severity likelihoods in the same prediction model, identify and quantify contributors and their marginal effects, quantify geometric and countermeasures’ safety improvement effectiveness, and rank the priorities for the crossings in terms of their safety improvement needs. This study proposed a statistical approach for HRGC crash analysis. The proposed method is competing risk model and the approach is Cox proportional hazard regression. This predictive method was well established in the bioscience area but never utilized in the transportation area. Competing risk model (CRM) is a special type of survival analysis to accommodate the competing nature of multiple outcomes from the same event of interest; in transportation safety analysis, the competing multiple outcomes are accident severity levels while the event of interest is accident occurrence. Transportation decision makers need a prioritization system to categorize crossings’ risk level based on their expected crash frequency and crash severity simultaneously. Therefore, with a hazard-ranking approach, which considers a crossing’s crash severity and frequency output, transportation decision makers are able to ensure that federal and state funds for grade crossing improvement projects are spent at crossings that are considered the most in need of improvement. Moreover, significant contributors, including geometric contributors and countermeasures, are identified, and their marginal effectiveness is also summarized. In this study, the hazard ranking model based on crash likelihoods resulted by the proposed CRM method is used to

This study developed a level of traffic stress (LTS) map for Fargo-Moorhead (ND-MN) and used crowdsourced bicycle use data from Strava to show relationships between the built environment and bicycle use. The LTS map is useful for showing how friendly and encouraging areas are toward bicycle use, as well as for showing the connectivity of low-stress pathways. The bicycle ridership model shows how the development of bicycle facilities and other changes to the built environment are associated with bicycle use, as measured using Strava count data. The results of the bicycle use model show that the existence of bicycle facilities is positively associated with bicycle use.