Measuring Airport Similarity to Create a Towering Decision Aid

Austin Anderson, Toby Hansford, Mason Jordan, Sragdhara Khakurel, Chris Marshall, Michael Quinn, Katherine Taylor, Amy Xie,Cody Fleming

2020 Systems and Information Engineering Design Symposium (SIEDS)(2020)

引用 0|浏览2
暂无评分
摘要
The focus of this project was on formulating a model and decision support tool to aid in the decision to build and maintain an Air Traffic Control Tower (ATCT). An important aspect of air travel are ATCTs, towers that help facilitate communication between the airport system and airplanes ascending and descending. ATCTs bring economic, safety, and efficiency benefits to airports and nearby communities. Currently, the Federal Aviation Administration (FAA) uses a document outlining a benefit-cost ratio for building a new tower, with tower funding provided if the ratio is greater than 1. However, the current policy lacks a comprehensive and systematic assessment of factors that influence both costs and benefits to operators and the region.To address these issues, we started by speaking with air traffic stakeholders and then began to collect data from a variety of aviation datasets. Based on the collected data, we identified economy, safety, and efficiency as our three areas of focus. With this data, we were able to compute the similarity, using hierarchical clustering, of a given airport to currently towered airports based on data from the economy, safety, and efficiency sources. We then built an interactive interface to display these similarities and provide information for airports to contact the similar airports.
更多
查看译文
关键词
Air Traffic Control,Systems Analysis,Clustering
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要