Advisor
John Lipor
Document Type
Report
Publication Date
6-28-2019
Abstract
As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses the lack of studies on this subject in Portland, OR. An application of the A*Prune algorithm is proposed for the purpose of reducing personal exposure for children attending Harriet Tubman Middle School in NE Portland, one area of Portland where residents are disproportionately affected by pollution. This method can sometimes identify alternative routes which reduce pollution exposure without significantly increasing travel distance over the shortest route.
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Persistent Identifier
https://archives.pdx.edu/ds/psu/29450
Citation Details
Payne, Elling, "A Resource Constrained Shortest Paths Approach to Reducing Personal Pollution Exposure" (2019). REU Final Reports. 15.
https://archives.pdx.edu/ds/psu/29450
The python code that implements and agent-based model of customers entering a coffeeshop
REU-Presentation-Exercise.pdf (847 kB)
Presentation slides for two presentations
Elling_Payne_annotated_bib.odt (277 kB)
Annotated Bibliography
Final Presentation.pdf (7151 kB)
Slides for the final symposium presentation
Included in
Computer Engineering Commons, Electrical and Computer Engineering Commons, Theory and Algorithms Commons