Is this project an undergraduate, graduate, or faculty project?
Graduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Charles Hruda, Senior Tate Grant, Graduate Student
Lead Presenter's Name
Charles Hruda
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Hongyun Chen
Abstract
Florida has the highest number of motorcycle fatalities in the United States. Florida also contains the second largest population of registered motorcycles of any state. In recent years the Federal Highway Administration (FHWA) has developed safety performance functions (SPFs), or mathematical models for identifying locations and predicting the number of crashes over a highway segment. Existing SPFs are not currently used solely for motorcycle crash prediction; this study aims to develop SPFs for different degrees of severity in motorcycle crashes in Florida. Historical crash data will be used to develop the SPFs before the pandemic (2018-2019) as a baseline; the two-year crash data (2020-2021) will be used for the SPFs during the pandemic. The objective is to compare pre and post pandemic crash predictions using the SPFs. The results from the models formulated throughout this study can be used to mitigate motorcycle crashes and fatalities in the state of Florida.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Development of Safety Performance Functions (SPFs) for Motorcycle Crashes in Florida for Pre and Post Pandemic Conditions
Florida has the highest number of motorcycle fatalities in the United States. Florida also contains the second largest population of registered motorcycles of any state. In recent years the Federal Highway Administration (FHWA) has developed safety performance functions (SPFs), or mathematical models for identifying locations and predicting the number of crashes over a highway segment. Existing SPFs are not currently used solely for motorcycle crash prediction; this study aims to develop SPFs for different degrees of severity in motorcycle crashes in Florida. Historical crash data will be used to develop the SPFs before the pandemic (2018-2019) as a baseline; the two-year crash data (2020-2021) will be used for the SPFs during the pandemic. The objective is to compare pre and post pandemic crash predictions using the SPFs. The results from the models formulated throughout this study can be used to mitigate motorcycle crashes and fatalities in the state of Florida.