Chapters authored
A Practical Approach to Evaluating the Economic and Technical Feasibility of LED Luminaires
LED roadway luminaires are currently under consideration for widespread implementation with departments of transportation, facilities managers, and city planners. This research focuses on a case study in Missouri and presents relevant research findings calculated by the authors as part of a project funded by the Missouri Department of Transportation. Although high-pressure sodium (HPS) luminaires have been the standard product for roadway illumination, advances in LED technologies have led many departments of transportation to consider them as viable options along state routes. For this case study, pilot sites were developed across the state of Missouri in sites assessed as moderately busy, medium pedestrian conflict zones. These zones were along roadways with an R3 pavement classification. This case study details the economic feasibility findings from the study; a life cycle cost approach was used. In addition, a technical feasibility analysis was conducted to determine fit with Illumination Engineering Society (IES) standards for the traffic pattern and pavement classification at study sites. Key findings reveal that LED roadway luminaires fail to outperform HPS in their current design, but may become technically and economically feasible in the future.
Part of the book: Advances in Statistical Methodologies and Their Application to Real Problems
Using Trend Extraction and Spatial Trends to Improve Flood Modeling and Control
Effective management of flood events depends on a thorough understanding of regional geospatial characteristics, yet data visualization is rarely effectively integrated into the planning tools used by decision makers. This chapter considers publicly available data sets and data visualization techniques that can be adapted for use by all community planners and decision makers. A long short-term memory (LSTM) network is created to develop a univariate time series value for river stage prediction that improves the temporal resolution and accuracy of forecasts. This prediction is then tied to a corresponding spatial flood inundation profile in a geographic information system (GIS) setting. The intersection of flood profile and affected road segments can be easily visualized and extracted. Traffic decision makers can use these findings to proactively deploy re-routing measures and warnings to motorists to decrease travel-miles and risks such as loss of property or life.
Part of the book: Data Science, Data Visualization, and Digital Twins