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Multi-Level Safety Performance Functions for High Speed Facilities

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Multi-Level Safety Performance Functions for High Speed Facilities University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2012 Multi-level Safety Performance Functions For High Speed Facilities Mohamed Ahmed University of Central Florida Part of the Civil Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Ahmed, Mohamed, "Multi-level Safety Performance Functions For High Speed Facilities" (2012). Electronic Theses and Dissertations, 2004-2019. 2488. https://stars.library.ucf.edu/etd/2488 MULTI-LEVEL SAFETY PERFORMANCE FUNCTIONS FOR HIGH SPEED FACILITIES by MOHAMED MOSTAFA ABDUL-RAHMAN AHMED B.Sc. Al-Azhar University, Cairo, Egypt, 2001 M.Sc. University of Central Florida, USA, 2009 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Civil, Environmental and Construction Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Spring Term 2012 Major Professor: Mohamed A. Abdel-Aty © 2012 Mohamed M. Ahmed i ABSTRACT High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the crash risk on long and short term basis. Therefore, the main focus of the research in this dissertation is to provide a framework of risk assessment to promote safety and enhance mobility on freeways and expressways. Multi-level Safety Performance Functions (SPFs) were developed at the aggregate level using historical crash data and the corresponding exposure and risk factors to identify and rank sites with promise (hot-spots). Additionally, SPFs were developed at the disaggregate level utilizing real-time weather data collected from meteorological stations located at the freeway section as well as traffic flow parameters collected from different detection systems such as Automatic Vehicle Identification (AVI) and Remote Traffic Microwave Sensors (RTMS). These disaggregate SPFs can identify real-time risks due to turbulent traffic conditions and their interactions with other risk factors. In this study, two main datasets were obtained from two different regions. Those datasets comprise historical crash data, roadway geometrical characteristics, aggregate weather and traffic parameters as well as real-time weather and traffic data. ii At the aggregate level, Bayesian hierarchical models with spatial and random effects were compared to Poisson models to examine the safety effects of roadway geometrics on crash occurrence along freeway sections that feature mountainous terrain and adverse weather. At the disaggregate level; a main framework of a proactive safety management system using traffic data collected from AVI and RTMS, real-time weather and geometrical characteristics was provided. Different statistical techniques were implemented. These techniques ranged from classical frequentist classification approaches to explain the relationship between an event (crash) occurring at a given time and a set of risk factors in real time to other more advanced models. Bayesian statistics with updating approach to update beliefs about the behavior of the parameter with prior knowledge in order to achieve more reliable estimation was implemented. Also a relatively recent and promising Machine Learning technique (Stochastic Gradient Boosting) was utilized to calibrate several models utilizing different datasets collected from mixed detection systems as well as real-time meteorological stations. The results from this study suggest that both levels of analyses are important, the aggregate level helps in providing good understanding of different safety problems, and developing policies and countermeasures to reduce the number of crashes in total. At the disaggregate level, real-time safety functions help toward more proactive traffic management system that will not only enhance the performance of the high speed facilities and the whole traffic network but also provide safer mobility for people and goods. In general, the proposed multi-level analyses are useful in providing roadway authorities with detailed information on where countermeasures must be implemented and when resources should be devoted. The study also proves that traffic data collected from different detection systems could be a useful asset that should be utilized iii appropriately not only to alleviate traffic congestion but also to mitigate increased safety risks. The overall proposed framework can maximize the benefit of the existing archived data for freeway authorities as well as for road users. iv To My Beloved Family v ACKNOWLEDGMENTS All praise is due to Allah who guided me to complete this work, without His help this research would not have been possible. This dissertation is dedicated to my parents who taught me the value of success and gave me the moral support to accomplish it in all aspects of my life. Particularly, I am deeply indebted to my mother for her untiring prayer and persistent faith in me. I would like to express my sincere gratitude to my advisor, Dr. Mohamed Abdel-Aty, for his continuous support and valuable guidance throughout my research. I am grateful to work with such a sincere and hard working advisor. I also want to acknowledge the support of the other committee members, Dr’s. Ahmed Radwan, Haitham Al-Deek, Nizam Uddin, Kevin Mackie, and Anurag Pande. Additionally, I want to express my appreciation to my colleagues for their friendship. In addition, I am thankful for my mother in law for her unyielding love and care; without her help, my family and I would not have been able to enjoy our life while studying here at UCF. Words fail me to express my appreciation to my wife Mona Zahra whose help, love and continuous believe in me, has lightened the load off my shoulders. I owe her for her patience, passions and sacrifice of her priceless time to make more time for me to succeed. Last but not the least I would also like to acknowledge the precious gift that was given to me by almighty Allah; my two adorable daughters, Jumana and Malak who brought the joy and happiness to our small family during this work. vi TABLE OF CONTENTS LIST OF FIGURES ..................................................................................................................... xi LIST OF TABLES ..................................................................................................................... xiii LIST OF ACRONYMS/ABBREVIATIONS ........................................................................... xiv CHAPTER 1. INTRODUCTION ................................................................................................ 1 1.1 Overview ............................................................................................................................... 1 1.2 Research Objectives .............................................................................................................. 3 1.3 Dissertation Organization ..................................................................................................... 6 CHAPTER 2. LITERATURE REVIEW .................................................................................... 7 2.1 General .................................................................................................................................. 7 2.2 Aggregate Analysis of Crashes ............................................................................................. 7 2.2.1 Overview ........................................................................................................................ 7 2.2.2 Factors Affecting Crash Frequency ............................................................................... 8 2.2.3 Statistical Techniques of Analyzing Crash Frequency ................................................ 11 2.3 Disaggregate Crash Analysis .............................................................................................. 14 2.3.1 Applications of ITS-archived Data in Traffic Safety ................................................... 14 2.3.2 Real-Time Analysis Based on Traffic Regimes ........................................................... 18 2.3.3 Identification of Type of Crash Using Real-Time Data ............................................... 20 2.3.4 Crash Prediction Using Archived Weather and ITS Traffic Data ............................... 23 2.3.5 Transferability of Real-Time Crash Potential Models ................................................. 24 2.3.6 Real-Time Crash Risk Prevention ............................................................................... 25 vii CHAPTER 3. AGGREGATE ANALYSIS: SAFETY PERFORMANCE
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