Browsing by Author "Lee, EunSu"

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Context Sensitive Solution: A Case Study of Northwest Highway White Rock Lake, Dallas in Texas
(2015) Bridgelall, Raj; Lee, EunSu; Upper Great Plains Transportation Institute
Loop 12 is the first ring around the city of Dallas. The project is a three-quarter mile section of Loop 12 on Northwest Highway. The project section of Northwest Highway is a set of six bridges that cross a 100-year floodplain. The environmental challenges, the diversity of stakeholders and their needs, and heightened sensitivities from special interest groups posed significant challenges for this project. Texas Department of Transportation (TxDOT) initially identified the traditional stakeholder groups to be representatives of area residences, school, small businesses, highway users, and transportation providers. However, the unique setting for this project also created a number non-traditional stakeholder groups. A major construction that would last a few years would substantially disrupt their normal activities. These groups were particularly sensitive to changes in the environment as TxDOT leaned after contracting HNTB Corporation to research the community and its history. From the project, we learned that forming multidisciplinary and hierarchical teams is one of the key factors for a successful project. Early and regular engagement of the public helps the environmental assessment and project progress. Visual simulation is one of the effective tools to communicate with the public. Inter-agency coordination is critical. Traffic management strategies must adapt with context sensitive solutions of transportation projects.
Rapid Hyperspectral Image Classification to Enable Autonomous Search Systems
(2016) Bridgelall, Raj; Rafert, J. Bruce; Tolliver, Denver D.; Lee, EunSu; Upper Great Plains Transportation Institute
The emergence of lightweight full-frame hyperspectral cameras is destined to enable autonomous search vehicles in the air, on the ground, and in water. Self-contained and long-endurance systems will yield important new applications, for example, in emergency response and the timely identification of environmental hazards. One missing capability is rapid classification of hyperspectral scenes so that search vehicles can immediately take actions to verify potential targets. Onsite verifications minimize false positives and preclude the expense of repeat missions. Verifications will require enhanced image quality, which is achievable by either moving closer to the potential target or by adjusting the optical system. Such a solution, however, is currently impractical for small mobile platforms with finite energy sources. Rapid classifications with current methods demand large computing capacity that will quickly deplete the on-board battery or fuel. To develop the missing capability, the authors propose a low-complexity hyperspectral image classifier that approaches the performance of prevalent classifiers. This research determines that the new method will require at least 19-fold less computing capacity than the prevalent classifier. To assess relative performances, the authors developed a benchmark that compares a statistic of library endmember separability in their respective feature spaces.
Resolution Agile Remote Sensing for Detection of Hazardous Material Spills
(2016) Bridgelall, Raj; Rafert, James B.; Tolliver, Denver D.; Lee, EunSu; Upper Great Plains Transportation Institute
Traffic carrying flammable, corrosive, poisonous, and radioactive materials continues to increase in proportion with the growth in their production and consumption. The sustained risk of accidental releases of such hazardous materials poses serious threats to public safety. The early detection of spills will potentially save lives, protect the environment, and thwart the need for expensive clean up campaigns. Ground patrols and terrestrial sensing equipment cannot scale cost-effectively to cover the entire transportation network. Remote sensing with existing airborne and spaceborne platforms has the capacity to monitor vast areas regularly but often lack the spatial resolution necessary for high accuracy detections. The emergence of unmanned aircraft systems with lightweight hyperspectral image sensors enables a resolution agile approach that can adapt both spatial and spectral resolutions in real-time. Equipment operators can exploit such a capability to enhance the resolution of potential target materials detected within a larger fieldof- view to verify their identification or to perform further inspections. However, the complexity of algorithms available to classify hyperspectral scenes limits the potential for real-time target detection to support rapid decision-making. This research introduces and benchmarks the performance of a low-complexity method of hyperspectral image classification. The hybrid supervised-unsupervised technique approaches the performance of prevailing methods that are at least 30-fold more computationally complex.
Sourcing Strategy for Asphalt Production Feedstock Considering Multimodal Transport Options
(2016) Bridgelall, Raj; Lee, EunSu; Talegani, Ali Rahim; Upper Great Plains Transportation Institute
This paper examines the logistics and distribution channels for importing heavy crude oil, which is a source of bitumen. The study conducts a sensitivity analysis to assess the suitability of existing or new distillery locations based on the available transportation modes and carrier options. The model accommodates rate changes based on multimodal shipping rates, import taxes, and other factors to assess the effects on total cost, schedule, and risks. Although a strategic location near direct pipeline options using existing facilities could yield the least transportation cost, the lack of pipeline capacity with increasing demand and delays in building additional capacity weighs heavily against pipeline options. The analysis points to multimodal shipments via ocean vessels and pipelines as the least-cost solution for a proposed strategic location for the distillery, but other factors such as strained international relationships make them less attractive. Depending on the selected refinery location, the analysis found that railroad options present a viable alternative and could potentially lead to the best overall logistical solution for obtaining asphalt production feedstock.
Strategic Global Logistics Management for Sourcing Road Oil in the U.S.
(2017) Bridgelall, Raj; Lee, EunSu; Bell, Michael; Upper Great Plains Transportation Institute
The demand for asphalt and road oil heavily leverages local supply because the product is a hot binder of aggregates that form the final mix needed to pave roads. This paper discusses the supply chain characteristics of crude oil feedstock by considering the overall logistics of sourcing heavy crude oil domestically, or importing it from international trading partners. Heavy crude oil is a source of asphalt and road oil production. The study examines critical global and domestic logistics factors such as customs, regulations, security, environmental compliance, and natural events that will affect costs, schedules, and risks. The study provides a framework for decision-making in sourcing the feedstock. The study helps global logisticians and transportation managers improve strategic design and planning towards efficient sourcing.