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A NEW APPROACH TO IDENTIFY THE EXPECTED CRASH PATTERNS BASED ON SIGNALIZED INTERSECTION SIZE AND ANALYSIS OF VEHICLE MOVEMENTS
Title
A NEW APPROACH TO IDENTIFY THE EXPECTED CRASH PATTERNS BASED ON SIGNALIZED INTERSECTION SIZE AND ANALYSIS OF VEHICLE MOVEMENTS.
Creator
Salkapuram, Hari, Mohamed, Abdel-Aty, University of Central Florida
Abstract / Description
Analysis of intersection crashes is a significant area in traffic safety research. This study contributes to the area by identifying traffic-geometric characteristics and driver demographics that affect different types of crashes at signalized intersections. A simple methodology to estimate crash frequency at intersections based on the size of the intersection is also developed herein. First phase of this thesis used the crash frequency data from 1,335 signalized intersections obtained from...
Show moreAnalysis of intersection crashes is a significant area in traffic safety research. This study contributes to the area by identifying traffic-geometric characteristics and driver demographics that affect different types of crashes at signalized intersections. A simple methodology to estimate crash frequency at intersections based on the size of the intersection is also developed herein. First phase of this thesis used the crash frequency data from 1,335 signalized intersections obtained from six jurisdictions in Florida, namely, Brevard, Seminole, Dade, Orange, and Hillsborough Counties and the City of Orlando. Using these data a simple methodology has been developed to identify the expected number of crashes by type and severity at signalized intersections. Intersection size, based on the total number of lanes, was used as a factor that was simple to identify and a representative of many geometric and traffic characteristics of an intersection. The results from the analysis showed that crash frequency generally increased with the increased size of intersections but the rates of increase differed for different intersection types (i.e., Four-legged intersection with both streets two-way, Four-legged intersection with at least one street one-way, and T-intersections). The results also showed that the dominant type of crashes differed at these intersection types and severity of crashes was higher at the intersections with more conflict points and larger differential in speed limits between major and minor roads. The analysis may potentially be useful for traffic engineers for evaluating safety at signalized intersections in a simple and efficient manner. The findings in this analysis provide strong evidence that the patterns of crashes by type and severity vary with the size and type of intersections. Thus, in future analysis of crashes at intersections, the size and type of intersections should be considered to account for the effects of intersection characteristics on crash frequency. In the second phase, data (crash and intersection characteristics) obtained from individual jurisdictions are linked to the Department of Highway Safety and Motor Vehicles (DHSMV) database to include characteristics of the at-fault drivers involved in crashes. These crashes are analyzed using contingency tables and binary logistic regression models. This study categorizes crashes into three major types based on relative initial movement direction of the involved vehicles. These crash types are, 1) Initial movement in same direction (IMSD) crashes. This crash type includes rear end and sideswipe crashes because the involved vehicles for these crashes would be traveling in the same direction prior to the crash. 2) Initial movement in opposite direction (IMOD) crashes comprising left-turn and head on crashes. 3) Initial movement in perpendicular direction (IMPD) crashes, which include angle and right-turn crashes. Vehicles involved in these crashes would be traveling on different roadways that constitute the intersection. Using the crash, intersection, and at-fault driver characteristics for all crashes as inputs, three logistic regression models are developed. In the logistic regression analyses total number of through lanes at an intersection is used as a surrogate measure to AADT per lane and also intersection type is introduced as a 'predictor' of crash type. The binary logistic regression analyses indicated, among other results, that at intersections with one-way roads, adverse weather conditions, older drivers and/or female drivers increase the likelihood of being at-fault at IMOD crashes. Similar factors associated with other groups of crashes (i.e., IMSD and IMPD) are also identified. These findings from the study may be used to develop specialized training programs by zooming in onto problematic intersections/maneuvers.
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Date Issued
2006
Identifier
CFE0001208, ucf:46954
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001208
AN ANALYSIS OF THE RELATIONSHIP BETWEEN ECONOMIC DEVELOPMENT AND DEMOGRAPHIC CHARACTERISTICS IN THE UNITED STATES
Title
AN ANALYSIS OF THE RELATIONSHIP BETWEEN ECONOMIC DEVELOPMENT AND DEMOGRAPHIC CHARACTERISTICS IN THE UNITED STATES.
Creator
Heyne, Chad, Ni, Liqiang, University of Central Florida
Abstract / Description
Over the past several decades there has been extensive research done in an attempt to determine what demographic characteristics affect economic growth, measured in GDP per capita. Understanding what influences the growth of a country will vastly help policy makers enact policies to lead the country in a positive direction. This research focuses on isolating a new variable, women in the work force. As well as isolating a new variable, this research will modify a preexisting variable that was...
Show moreOver the past several decades there has been extensive research done in an attempt to determine what demographic characteristics affect economic growth, measured in GDP per capita. Understanding what influences the growth of a country will vastly help policy makers enact policies to lead the country in a positive direction. This research focuses on isolating a new variable, women in the work force. As well as isolating a new variable, this research will modify a preexisting variable that was shown to be significant in order to make the variable more robust and sensitive to recessions. The intent of this thesis is to explore the relationship between several demographic characteristics and their effect on the growth rate of GDP per capita. The first step is to reproduce the work done by Barlow (1994) to ensure that the United States follows similar rules as the countries in his research. Afterwards, we will introduce new variables into the model, comparing the goodness of fit through the methods of R-squared, AIC and BIC. There have been several models developed to answer each of the research questions independently.
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Date Issued
2011
Identifier
CFH0003837, ucf:44712
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH0003837
FLORIDA SCHOOL INDICATOR REPORT DATA AS PREDICTORS OF HIGH SCHOOL ADEQUATE YEARLY PROGRESS (AYP)
Title
FLORIDA SCHOOL INDICATOR REPORT DATA AS PREDICTORS OF HIGH SCHOOL ADEQUATE YEARLY PROGRESS (AYP).
Creator
Carr, John, Bozeman, William, University of Central Florida
Abstract / Description
The focus of this research was to identify variables reported in the 2008-2009 Florida School Indicator Report (FSIR) that had a statistical impact, positive or negative, on the likelihood that a school would achieve Adequate Yearly Progress (AYP) in reading or mathematics using the logistic regression technique. This study analyzed four broad categories reported by the FSIR to include academic, school, student, and teacher characteristics. FSIR and AYP data was collected for 468 Florida high...
Show moreThe focus of this research was to identify variables reported in the 2008-2009 Florida School Indicator Report (FSIR) that had a statistical impact, positive or negative, on the likelihood that a school would achieve Adequate Yearly Progress (AYP) in reading or mathematics using the logistic regression technique. This study analyzed four broad categories reported by the FSIR to include academic, school, student, and teacher characteristics. FSIR and AYP data was collected for 468 Florida high schools that were categorized by the Florida Department of Education as presenting a comprehensive curriculum to grades 9-12 or grades 10-12. It was determined in this study that academic data associated with ACT results and the grade 11 FCAT Science were effective predictors of a school's academic health in reading and mathematics. Student absenteeism showed the greatest impact on a school obtaining AYP in reading while the percentage of students qualifying for free and disabled populations within a school showed the greatest impact on a school obtaining AYP in mathematics. Teachers teaching out of field were identified as having a negative influence on AYP in reading and mathematics while a teacher's experience was considered a positive influence on AYP in mathematics only. Further research is necessary to fully explore the use of logistic regression as a predictive tool at the state, school district, and school level.
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Date Issued
2011
Identifier
CFE0003638, ucf:48848
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003638