The purpose of this applied research study was to test the sensitivity of the Evacuation Simulation Prediction (ESP) tool in predicting travel time during high volume traffic periods. The discrete event-based simulation tool was designed to aid local evacuation planning contingencies. Research of the Florida Department of Transportation traffic count data demonstrated parallel trends in rush hour volume versus hurricane evacuation volume. A model validation was designed to test if the model closely predicted high volume travel on a major interstate. For this macroscopic sensitivity test, volume, travel time and speed were collected to examine the baseline predictability under crash and non-crash, high volume travel periods. The comparative field data included collection during the 2006 Volusia County wildfire evacuations. The tool demonstrated a highly predictive fit; the variance accounted for (r2) was 0.993. The results of this study will be useful in the continued calibration and ESP tool validation.
","abstract_html":"<p>The purpose of this applied research study was to test the sensitivity of the Evacuation Simulation Prediction (ESP) tool in predicting travel time during high volume traffic periods. The discrete event-based simulation tool was designed to aid local evacuation planning contingencies. Research of the Florida Department of Transportation traffic count data demonstrated parallel trends in rush hour volume versus hurricane evacuation volume. A model validation was designed to test if the model closely predicted high volume travel on a major interstate. For this macroscopic sensitivity test, volume, travel time and speed were collected to examine the baseline predictability under crash and non-crash, high volume travel periods. The comparative field data included collection during the 2006 Volusia County wildfire evacuations. The tool demonstrated a highly predictive fit; the variance accounted for (r2) was 0.993. The results of this study will be useful in the continued calibration and ESP tool validation.</p>","abstract_has_math":false,"creators":["Borglum, Kay Fortinberry"],"institution":null,"degree_name":"Master of Science in Human Factors & Systems","degree_level":"Thesis - Open Access","degree_discipline":"Human Factors and Systems","degree_department":null,"school":null,"contributors":["Jon French","Albert J. Boquet","Ram Nayer"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007-04-01T07:00:00Z","date_published":"2007-04-01T07:00:00Z","updated_at":"2026-07-27T19:25:37Z","subjects":["evacuation","simulation","highway travel times","Infrastructure","Transportation"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/11","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jon French","Albert J. Boquet","Ram Nayer"]},{"key":"dc:creator","label":"Author","values":["Borglum, Kay Fortinberry"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Human Factors and Systems"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Human Factors & Systems"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["evacuation","simulation","highway travel times","Infrastructure","Transportation"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/db-theses/11"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The purpose of this applied research study was to test the sensitivity of the Evacuation Simulation Prediction (ESP) tool in predicting travel time during high volume traffic periods. The discrete event-based simulation tool was designed to aid local evacuation planning contingencies. Research of the Florida Department of Transportation traffic count data demonstrated parallel trends in rush hour volume versus hurricane evacuation volume. A model validation was designed to test if the model closely predicted high volume travel on a major interstate. For this macroscopic sensitivity test, volume, travel time and speed were collected to examine the baseline predictability under crash and non-crash, high volume travel periods. The comparative field data included collection during the 2006 Volusia County wildfire evacuations. The tool demonstrated a highly predictive fit; the variance accounted for (r2) was 0.993. The results of this study will be useful in the continued calibration and ESP tool validation.
"]},{"key":"dc:title","label":"Title","values":["A Macroscopic Validation of the Evacuation Simulation Prediction Tool on Highway Travel Times"]}]}],"canonical_facts":{"dc:contributor":["Jon French","Albert J. Boquet","Ram Nayer"],"dc:creator":["Borglum, Kay Fortinberry"],"dc:description.abstract":["The purpose of this applied research study was to test the sensitivity of the Evacuation Simulation Prediction (ESP) tool in predicting travel time during high volume traffic periods. The discrete event-based simulation tool was designed to aid local evacuation planning contingencies. Research of the Florida Department of Transportation traffic count data demonstrated parallel trends in rush hour volume versus hurricane evacuation volume. A model validation was designed to test if the model closely predicted high volume travel on a major interstate. For this macroscopic sensitivity test, volume, travel time and speed were collected to examine the baseline predictability under crash and non-crash, high volume travel periods. The comparative field data included collection during the 2006 Volusia County wildfire evacuations. The tool demonstrated a highly predictive fit; the variance accounted for (r2) was 0.993. The results of this study will be useful in the continued calibration and ESP tool validation.
"],"dc:identifier":["https://commons.erau.edu/db-theses/11"],"dc:subject":["evacuation","simulation","highway travel times","Infrastructure","Transportation"],"dc:title":["A Macroscopic Validation of the Evacuation Simulation Prediction Tool on Highway Travel Times"],"thesis:degree_discipline":["Human Factors and Systems"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Human Factors & Systems"]},"updated_at":"2026-07-27T19:25:37Z"}