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Item Pavement Performance Evaluation Using Connected Vehicles(North Dakota State University, 2015) Bridgelall, RajRoads deteriorate at different rates from weathering and use. Hence, transportation agencies must assess the ride quality of a facility regularly to determine its maintenance needs. Existing models to characterize ride quality produce the International Roughness Index (IRI), the prevailing summary of roughness. Nearly all state agencies use Inertial Profilers to produce the IRI. Such heavily instrumented vehicles require trained personnel for their operation and data interpretation. Resource constraints prevent the scaling of these existing methods beyond 4% of the network. This dissertation developed an alternative method to characterize ride quality that uses regular passenger vehicles. Smartphones or connected vehicles provide the onboard sensor data needed to enable the new technique. The new method provides a single index summary of ride quality for all paved and unpaved roads. The new index is directly proportional to the IRI. A new transform integrates sensor data streams from connected vehicles to produce a linear energy density representation of roughness. The ensemble average of indices from different speed ranges converges to a repeatable characterization of roughness. The currently used IRI is undefined at speeds other than 80 km/h. This constraint mischaracterizes roughness experienced at other speeds. The newly proposed transform integrates the average roughness indices from all speed ranges to produce a speed-independent characterization of ride quality. This property avoids spatial wavelength bias, which is a critical deficiency of the IRI. The new method leverages the emergence of connected vehicles to provide continuous characterizations of ride quality for the entire roadway network. This dissertation derived precision bounds of deterioration forecasting for models that could utilize the new index. The results demonstrated continuous performance improvements with additional vehicle participation. With practical traversal volumes, the achievable precision of forecast is within a few days. This work also quantified capabilities of the new transform to localize roadway anomalies that could pose travel hazards. The methods included derivations of the best sensor settings to achieve the desired performances. Several case studies validated the findings. These new techniques have the potential to save agencies millions of dollars annually by enabling predictive maintenance practices for all roadways, worldwide.Item Derived Demand for Grain Freight Transportation, Rail-Truck Competition, and Mode Choice and Allocative Efficiency(North Dakota State University, 2016) Ndembe, Elvis MokakeThe demand for grain freight transportation is a derived demand; consequently changes in the grain supply chain in production and handling, and those in the transportation domain will affect the demand for grain transportation. The U.S. transportation industry (e.g. railroad and trucking), and the grain supply chain in general have witnessed structural changes over the years that have potential long-run implications for demand, intermodal competition, and grain shippers mode choices both nationally and regionally. Deregulation of the railroad and trucking industries initiated innovations (e.g. shuttle trains) that have revolutionized the way grain is marketed. These and other related trends in agriculture including bioenergy suggest a dynamic environment surrounding grain transportation and the need to revisit agricultural transportation demand and evaluate changes over time. A majority of freight demand studies are based on aggregate data (e.g. regional) due to lack of disaggregate data. Aggregation of shippers over large geographic regions leads to loss of information with potential erroneous elasticity estimates. This study develops a method to estimate transportation rates at the grain elevator level to estimate a shipper link specific cost function for barley, corn, durum, hard red spring wheat, and soybeans shippers. The aim of this study is to assess and characterize the nature of rail-truck competition for the transportation of five commodities over distance and time as well as to assess whether North Dakota grain shippers’ mode choices reflect an allocatively efficient mix assuming the choice of mode is based on shipping rates. Our findings indicate that in general, rail dominates most of the grain traffic, however, the degree of dominance is variable by commodity. Additional findings suggest that grain shippers utilize more rail than they would if they chose modes based on rates. This may suggest unmeasured service quality advantages of rail in comparison to truck.Item Application of Data Mining Techniques in Transportation Safety Study(North Dakota State University, 2018) Zheng, ZijianMost of current studies are based on Generalized Linear Models (GLMs), which require several assumptions. Those assumptions limit GLMs with the nature of data, and jeopardize models’ performance when handling data with complex and nonlinear patterns, high missing values, and large number of input variables with various data types. Data mining models are famous for strong capability of extracting valuable information and detecting complex patterns from large noisy data. However, they are not popular in transportation safety research, because they are criticized to be unable to provide interpretable and practical outputs. In this study, data mining models are tested in transportation safety research to prove their feasibility to be served as alternative models in safety study. Influential variable importance, contributor variable marginal effect analysis, and model predicting accuracy are further conducted to identify complex and nonlinear patterns in study dataset, and to respond to the criticism that data mining models do not provide practical outputs. Due to the high fatality rate, two types of crashes are selected as research areas: 1) predicting crashes at Highway Rail Grade Crossings (HRGCs); and 2) commercial truck involved crash injury severity. In the HRGC crash likelihood study, three data mining models, Decision Tree (DT), Gradient Boosting (GB), and Neural Network (NN), are tested, and demonstrated to be solid in Highway Rail Grade Crossing (HRGC) crash likelihood study. In the commercial truck involved crash injury severity study, the GB model identifies 11 out of 25 studied variables to be responsible for more than 80% of injury severity level forecasting, and their nonlinear impact on the severity level. Several factors such as trucking company attributes (e.g., company size), safety inspection values, trucking company commerce status (e.g., interstate or intrastate), and registration condition are found to be significantly associated with crash injury severity. Even though most of the identified contributing factors are significant for all four levels of crash severity, their relative importance and marginal effect are all different. Findings in this study can be helpful for transportation agencies to reduce injury severity level, and develop efficient strategies to improve safety.Item Limiting Financial Risk from Catastrophic Events in Project Management(North Dakota State University, 2020) Simonson, Peter DouglasThis dissertation develops a mixed integer linear program to establish the upper and lower bounds of the Alphorn of Uncertainty. For a project manager, planning for uncertainty is a staple of their jobs and education. But the uncertainty associated with a catastrophic event presents difficulties not easily controlled with traditional methods of risk management. This dissertation brings and modifies the concept of a project schedule as a bounded “Alphorn of Uncertainty” to the problem of how to reduce the risk of a catastrophic event wreaking havoc on a project and, by extension, the company participating in that project. The dissertation presents new mathematical models underpinning the methods proposed to reduce risk as well as simulations to demonstrate the accuracy of those models. The dissertation further assesses the complexity of the models and thus their practical application. Finally, the dissertation presents strategies to reduce the risk to a project of a catastrophic event using the upper bound of the Alphorn as the measure of risk.Item Modeling Pavement Performance and Preservation(North Dakota State University, 2011) Lu, PanThe number of highway lane-miles in the United States increased by 7% from 1980 to 2007, while vehicle-miles of travel almost doubled. During the same period, the Federal Highway Trust Fund (the major source of funding for highways) grew by only 40% in constant 1980 dollars. With growth in trade and commerce, truck traffic levels are expected to increase significantly in the future. Highway agencies throughout the United States are facing complex decisions about maintaining, repairing, and renewing existing pavements in the most cost-effective ways. Decision makers need to learn: to what degrees different pavement preservation treatments will improve a pavement condition; how pavement conditions will change over time; when to apply which treatment to what section; and what budget level will be needed to maintain and improve pavement conditions. The objectives of this dissertation are to 1) estimate the effectiveness of appropriate different levels of pavement preservation treatments, 2) evaluate pre-treatment and posttreatment pavement performances, and 3) use the uniformed results (of the first two objectives) to develop a decision making tool for integrated pavement management systems. The dissertation will utilize data from the Long Term Pavement Performance (LTPP) program. LTPP data will be used to estimate statistical models of the benefit effectiveness of preservation-related treatments and pavement performance, including models of performance jump--i.e., the instantaneous improvement in the performance or condition of a pavement due to a maintenance treatment. The forecast values from the statistical models will be used as inputs to optimization models that will allow for the simultaneous solution of several objectives or constraints. The results will benefit pavement management systems and improve pavement preservation planning in the United States.Item Analyzing Supply Chain Networks for Blood Products(North Dakota State University, 2019) Xu, YuanThe blood supply chain, starting from the donor until the blood is used to meet transfusion demands of patients, is a multi-echelon and complex system. The perishable and lifesaving characteristics of blood products, such as red blood cells and platelets, as well as uncertainties in both supply and demand make it difficult to maintain a balance between shortage and wastage due to expiry. An effective blood supply chain should be able to meet the demand while at the same time reducing wastage and total operational cost. In order to be cost effective, the related organizations have to decide how much blood should be collected from donors, how much blood products should be produced at the blood center, and how much blood products should be distributed to hospitals or transshipped between hospitals. The objective of this dissertation is to provide these tactical and operational decisions to guide those who work in healthcare supply chain management and explore new opportunities on performance improvement for an integrated blood supply chain by optimization with aim of minimizing total cost, consideration of transshipment between hospitals, and application of a coordinated multi-product model. This dissertation presents three multi-stage stochastic models for an integrated blood supply chain to minimize total cost incurred in the collection, production, inventory, and distribution echelons under centralized control. The scope of this study focuses on modeling a supply chain of blood products in one regional blood center, several hospitals and blood collection facilities. First, we develop an integrated model for the platelet supply chain that accounts for demand uncertainty and blood age information, then we develop this model further by investigating the impact of transshipment between hospitals on cost savings, and then we propose a multi-product model that accounts for red blood cells and platelets at the same time and compare it with an uncoordinated model where the red blood cell and platelet supply chains are considered separately.Item Identification, investigation, and spatial analysis of various contributing factors to crash and injury severity in different crash types(North Dakota State University, 2024) Khan, IhsanThis dissertation had three main objectives related to improving road safety by investigating factors that contribute to injury severity in different types of single-vehicle crashes. The first objective was to develop a generalized ordered logit model to examine factors affecting injury severity of occupants in single-vehicle rollover crashes using 5 years of U.S. crash data from 2012-2016. Results showed likelihood of serious/fatal injuries increased in rollovers with occupant ejection, speeding, higher speed limits, roadside/median rollovers, undulating terrain, blacktop surfaces, rural roads, evenings, weekdays, older drivers, lack of occupant protection, previous driver crashes, distracted/aggressive driving, and passenger cars. Airbag deployment reduced serious/fatal injury risk. Regional variations also impacted injury severity. The second objective identified high-risk areas for lane departure crashes on rural North Dakota roads using techniques like Global/Local Moran's I, network kernel density estimation (NetKDE), and emerging hotspot analysis. While Global Moran's I indicated clustering, Local Moran's I revealed specific hot/cold spots. NetKDE quantified and prioritized crash clusters by density along roadways. Emerging hotspot analysis evaluated temporal patterns of hot/cold spots. This approach can guide deployments of education, enforcement, and infrastructure countermeasures. The third objective used a mixed logit model to analyze factors contributing to injury severity in single-vehicle run-off-road (ROR) crashes for passenger cars, SUVs, and pickups. Common factors increasing injury risk were older driver age, impaired driving, no seatbelt, no airbag, high speeds, and older vehicles. However, driver age impacts were most pronounced for pickups. Seatbelts substantially mitigated injury severity across all vehicle classes. Passenger cars had a higher injury risk than SUVs/pickups, especially over 75 mph. Future research should examine additional factors stratified by vehicle class using larger datasets.Item Optimizing Transportation Infrastructure and Global Supply Chain Integration for Nicaragua’s Autonomous Caribbean Regions through Network Modernization(North Dakota State University, 2019) Leiman, JamesThe autonomous regions of the Nicaraguan Caribbean Coast are resource rich, yet they are among the poorest regions of Latin America. To realize economic growth and potential, this research examined Nicaragua’s primary-sector economic activities and developed a transportation network that would enable the creation of a functional logistics network, therefore enabling integration into the global supply chain for timber, beef, seafood, and light manufactured goods. The main goal of this research is to determine the minimum cost of developing a multimodal transportation network in the region by using roads, rail, intracoastal waterways, and Caribbean Sea transport. In addition to the initial construction costs, a 50-year horizon was evaluated, including operation and maintenance expenses for all possible modes as well as the cost to move all goods from point to point within the network using various options per Ton-kilometer. Several sensitivities were also run using Excel Solver in order to determine what triggers would alter the network’s construction and operation plan for each transportation arc. In the aggregate, the least-expensive option, to include deployment of rail, road, and intracoastal waterway use, costs $861,419,624.87 over a 50-year period. This cost captured the initial construction expenses, operation and maintenance estimates, and the rate to move goods across the network; the best-case scenario enabled construction over a 5-year period. More expensive options for the network’s construction and operation/movement of goods are more likely given the region’s inefficiencies. This research will be given to the Nicaraguan Department of Transportation with the hope that the findings may be used to orchestrate economic and community development in the region.Item The Impact of Automated Requisitioning Systems on the Effectiveness of Emergency Supply Chains(North Dakota State University, 2014) Shatzkin, Matthew PattersonThis research examines the relevance of an automated requisitioning system on an emergency supply chain's performance. In this context, "automated requisitioning" refers to the ability to transmit requisitions through an automated method that can be viewed and acted upon by multiple members of the supply chain. Automated requisitioning suggests some sophistication compared to manual methods which include phone calls, email and text messaging. These manual methods carry an implied higher probability of error and also have a limited capacity to process higher volumes of requisitions. Emergency supply chains are characterized by some demand that can be anticipated and other demand that must be addressed through a requisitioning procedure. Two subcategories of emergency supply chains are military expeditions and nongovernmental organizations. While military and disaster relief supply chains each provide supplies to different customers, they are similar in their need to both push and pull required commodities. Although military supply chains support soldiers while disaster relief supply chains provide relief to people in need, both supply chains involve pushing supplies while requesting specific needs based on the particular situation, overall addressing a demand that is largely unknown. This research examines the role automated requisitioning plays in the midst of these push and pull systems by simulating automation in a military expedition, then generalizing the results to suggest conclusions regarding a disaster relief supply chain.Item Game Theory Approach to the Vertical Relationships for U.S. Containerized Imports(North Dakota State University, 2013) Liu, QingMulti-player interactions and vertical relationships in the U.S. containerized-import shipment market are investigated using game theory approaches. Bi-level programming problems (BLPP) are built to capture the hierarchy structure of the container shipping industry, whereas the ocean carriers (OC) are considered as the market leader. For a case study with five players from several levels of the shipment chain, 16 BLPPs are built to analyze the 32 coalition possibilities. Two routes are compared: The West Coast route (WCR) includes one terminal (P1) and one railroad (R); the East Coast route (ECR) includes a second terminal (P2) and the Panama Canal (PC). The impact of Panama Canal expansion is investigated by comparing scenarios with different assumptions of vessel size. Capacity constraints at port terminals are also analyzed by assuming different capacity levels. The grand coalition of the five players is found to be very unstable because of the unavoidable competition within the coalition; hence, following games are further created, supposing the grand coalition could not form. Model results indicate the OC prefers to form an East Coast Coalition (ECC) with East Coast players if the grand coalition could not form. Sensitivity analyses on some parameter values for the grand coalition and for the ECC bring some interesting findings. With higher cargo values, the WCR becomes more appealing because of its quicker delivery time and lower inventory costs compared with the ECR. The Panama Canal expansion will improve market power and profit shares for the East Coast players if the canal operator could increase its competitive price more than the increase of costs. Generally, a player will gain more market power if its cost could be reduced. A player's upper bound rate is a reflection of its relative market power. But in a complicated market characterized with various cooperation-competition strategies and an ambiguous definition of partners and competitors, the impact of a player's upper bound rate on the market power structure could not be easily explained. For future research, the challenge mainly lies on the large number of BLPPs that need to be constructed and solved in order to study more players.