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Determining the Factors That Influence the Odds and Time to Streetcar Bunching Incidents

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Determining the Factors That Influence the Odds and Time to Streetcar Bunching Incidents Determining the Factors that Influence the Odds and Time to Streetcar Bunching Incidents by Paula Diem Quynh Nguyen A thesis submitted in conformity with the requirements for the degree of Master of Applied Science Graduate Department of Civil Engineering University of Toronto © Copyright by Paula Nguyen 2017 Determining the Factors that Influence the Odds and Time to Streetcar Bunching Incidents Paula Diem Quynh Nguyen Master of Applied Science Department of Civil Engineering University of Toronto 2017 Abstract Bunching is a common operational problem in surface transit systems with negative impacts on service quality and users’ perception. While many studies have focused on understanding the causes of bus bunching and developing strategies to mitigate its negative effects, there has been little research on streetcar bunching. This research aims at understanding the factors that impact the likelihood of streetcar bunching and to investigate the factors that impact the time to the initial bunching incident from the terminal. Focusing on Toronto’s streetcar lines, this study developed a binary logistic regression model and an accelerated failure time (AFT) model to address the first and second goals, respectively. Data from multiple sources, including the automatic vehicle location (AVL) system, were used to estimate the models. Headway deviations at the terminal and the usage of different vehicles types were two interesting factors found to increase odds of bunching and accelerate time to bunching. ii Acknowledgments Firstly, I’d like to thank my thesis supervisor, Dr. Amer Shalaby, for his expertise, advice, and vision throughout this foreign experience of academia for me. He has provided so much guidance and helped me stay on track while I got lost in the process and the mounds of data. As cliché as it sounds, I would not be here without him. I want to express my deep appreciation and gratitude to Ehab Diab, who has shared, taught, and spared so much of his time during this process. I would have been hopeless without you on this journey. Despite all of my dim questions, he has remained smiling, patient, understanding, and encouraging. From the Toronto Transit Commission, I’d like to thank Kenny Ling and Francis Li for providing the data that has enabled me to conduct this study. I can’t forget to thank my family. My cousin, Katherine, was my biggest supporter in the pursuit of graduate studies. I wouldn’t have even submitted my application to the program without her encouragement. Of course, I wouldn’t have been successful without my parents, aunt, and sister and their unconditional love. Thank you, Christopher for the endless support you have given me. These words cannot express how grateful I am for all of you. Thanks to the Auto Parts group for all of your help and support over these past two years. Whenever I had trouble with software or with concepts, you were always there for me. You guys provided comedic relief and support during those tough times. Without you, I wouldn’t be sitting here writing this. Finally, I want to recognize and thank two of my undergraduate supervisors from the University of Windsor. Dr. Faouzi Ghrib always believed that I had the potential and was destined for higher education. Thank you for your faith in me. It was because of my undergraduate research experience with Dr. Chris Lee that inspired me to pursue graduate studies in transportation engineering. Thank you for your continuous support of my growth and development. iii Contents Acknowledgments.......................................................................................................................... iii List of Tables ................................................................................................................................. vi List of Figures ............................................................................................................................... vii 1 Introduction .................................................................................................................................1 1.1 Background ..........................................................................................................................1 1.2 Motivation ............................................................................................................................2 1.3 Research Objective ..............................................................................................................4 1.4 Methodology ........................................................................................................................5 1.5 Thesis Structure ...................................................................................................................6 2 Literature Review ........................................................................................................................7 2.1 Bunching in Public Transit ..................................................................................................8 2.2 Streetcar Performance ..........................................................................................................9 2.3 Transportation Applications on Time to an Event .............................................................10 3 Study Context and Data ............................................................................................................12 3.1 Study Context.....................................................................................................................12 3.2 Data Description ................................................................................................................14 3.3 Data Processing ..................................................................................................................16 3.4 Variable Definition ............................................................................................................19 4 Modelling Framework ...............................................................................................................25 4.1 Binary Logistic Regression Model ....................................................................................27 4.2 Survival Analysis ...............................................................................................................29 5 Model Results and Discussion ..................................................................................................32 5.1 Descriptive Statistics/Data Trends .....................................................................................32 5.2 Binary Logistic Regression Model Results........................................................................38 iv 5.3 Accelerated Failure Time Model Results ..........................................................................42 6 Summary and Conclusions ........................................................................................................46 6.1 Summary of Thesis ............................................................................................................46 6.2 Key Results ........................................................................................................................46 6.3 Policy Implications ............................................................................................................47 6.4 Future Work .......................................................................................................................48 7 References .................................................................................................................................50 8 Appendix ...................................................................................................................................54 8.1 TTC Service Summary (January 3 – February 13, 2016) ..................................................54 8.2 Stata Code ..........................................................................................................................55 v List of Tables Table 1 Average Daily Streetcar Ridership .................................................................................. 12 Table 2 TTC Fleet Details............................................................................................................. 13 Table 3 Streetcar Route Characteristics ........................................................................................ 14 Table 4 Service Hours Defined by the TTC ................................................................................. 14 Table 5 Sample of Raw Data Provided by the TTC ..................................................................... 15 Table 6 Independent Variables Considered in Study .................................................................... 20 Table 7 Variable Definitions ......................................................................................................... 23 Table 8 Descriptive Statistics of All Variables Used in Models .................................................. 32 Table 9 Summary Statistics of All Headways .............................................................................. 33 Table 10 Statistics on Time to First Bunch ................................................................................... 36 Table 11 Summary Statistics of Bunched Incidents ..................................................................... 38 Table 12 Logistic Regression Model Fit ......................................................................................
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