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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 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 Transportation Sustainability on Economic and Environmental Aspects in the United States: Statistical and Quantitative Approaches(North Dakota State University, 2015) Choi, JaesungThe dissertation consists of three essays: 1) Productivity growth in the transportation industries in the United States: An application of the DEA Malmquist productivity index; 2) how does a carbon dioxide emissions change affect transportation productivity? A case study of the U.S. transportation sector from 2002 to 2011; and 3) forecast of CO2 emissions from the U.S. transportation sector: Estimation from a double exponential smoothing model. The first essay reviews productivity growth in the five major transportation industries in the United States (airline, truck, rail, pipeline, and water) and the pooled transportation industry from 2004 to 2011. The major findings are that the U.S. transportation industry shows strong and positive productivity growth except in the years of the global financial crisis in 2007, 2008, and 2010, and among the five transportation industries, the rail and water sectors show the highest productivity growth in 2011. The second essay examines the effects of a carbon dioxide (CO2) emissions change on actual productivity in the U.S. transportation sector. This study finds that a CO2 emissions increase from 2002 to 2007 had a negative effect on actual productivity in the U.S. transportation sector, but the CO2 emissions reduction for 2008–2011 increases actual productivity. States mainly showing sustainable growth patterns (decrease in CO2 emissions concurrent with increasing actual productivity) experience higher technological innovation increase than an efficiency decrease. This finding suggests that fuel-efficient and carbon reduction technologies as well as alternative transportation energy sources may be essential factors to both grow transportation and slow global warming. The third essay reviews whether the decreasing trend in U.S. CO2 emissions from the transportation sector since the end of the 2000s is consistent across all states in the nation for 2012‒2021. A double exponential smoothing model is used to forecast CO2 emissions for the transportation sector in the 50 states and the U.S., and its findings are supported by pseudo out-of-sample forecasts validity testing. This study concludes that the decreasing trend in transportation CO2 emissions in the U.S. will continue in most states in the future.Item Organizing Transit in Small Urban and Rural Communities(North Dakota State University, 2012) Ripplinger, DavidThe justification of government support of rural transit on the basis of the presence of increasing returns to scale and the most efficient regional organization of transit is investigated. Returns to density, size, and scope at most levels of output were found. Cost subadditivity, where a monopoly firm can provide service at a lower cost than two firms, was found for many, but not all observations. The presence of natural monopoly in rural transit in a strict sense is rejected. The findings and implications are directly applicable to rural transit in North Dakota and should be helpful in informing future federal policy as well as rural transit policy, service design, and operation in other states.Item Municipal Solid Waste Collection Route Optimization Using Geospatial Techniques: A Case Study of Two Metropolitan Cities of Pakistan(North Dakota State University, 2016) Hina, SyedaThe population growth in many urban cities and its activities in developing countries have resulted in an increased solid waste generation rate and waste management has become a global environmental issue. Routing of solid waste collection vehicles in developing countries like Pakistan poses a challenging task. In the process of solid waste management, collection and transportation play a leading role in waste collection and disposal, in which collection activities contributed the most to total cost for solid waste collection activities. Therefore, this study describes an attempt to design and develop an appropriate collection, transportation and disposal plan for the twin cities of Pakistan by using Geographic Information System (GIS) and Remote Sensing (RS) techniques to determine the minimum cost/distance/time efficient collection paths for the transportation of the solid wastes to the landfill sites. In addition to this, identification of solid waste disposal sites and appropriately managing them is a challenging task to many developing countries and Pakistan is no exception to that. The existing landfill sites for the twin cities are not technically viable and environmentally acceptable and are thus damaging to the environment due to their location and the type of waste dumped. Therefore, the second aim of our study was to find out the suitable landfill sites for the twin cities and the study employed Multi-Criteria Evaluation (MCE) methods to combine necessary factors considered for landfill site selection for the twin cities. Hence, our present study has proved that GIS is a tool that can be used in integration with other techniques such as MCE for a identifying new landfill sites and it can help decision makers deal with real-world developmental and management issues. Finally, the study has developed a Wed-Based Decision Support System (DSS) via Application Programming Interface (API) which will help decision-makers to search for cost-effective alternatives and it can be operated by people who don’t have knowledge of GIS. The proposed study can be used as a decision support tool by the municipalities of the twin cities for efficient management and transportation of solid wastes to landfill sites, managing work schedules for workers, etc.Item Estimation of Increased Traffic on Highways in Montana and North Dakota due to Oil Development and Production(North Dakota State University, 2012) Dybing, Alan GabrielAdvances in oil extraction technology such as hydraulic fracturing have improved capabilities to extract and produce oil in the Bakken and Three Forks shale formations located in North Dakota, Montana, Manitoba, and Saskatchewan. From 2004 to the present, there has been a significant increase in oil rigs and new oil wells in these areas, resulting in increased impacts to the local, county, state, and federal roadway network. Traditional methods of rural traffic forecasting using an established growth rate are not sufficient under the changing traffic levels. The goal of this research is to develop a traffic model that will improve segment specific traffic forecasts for use in highway design and planning. The traffic model will consist of five main components: 1) a Geographic Information Systems (GIS) network model of local, county, state and federal roads, 2) a truck costing model for use in estimating segment specific user costs, 3) a spatial oil location model to estimate future oil development areas, 4) a series of mathematical programming models to optimize a multi-region oil development area for nine individual input/output movements, and 5) an aggregation of multiple routings to segment specific traffic levels in a GIS network model.