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Using AVL Data to Measure the Impact of Traffic Congestion on Bus

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Using AVL Data to Measure the Impact of Traffic Congestion on Bus Using AVL Data to Measure the Impact of Traffic Congestion on Bus Passenger and Operating Cost A Thesis Presented By Ahmed Talat M. Halawani to The Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering in the field of Transportation Engineering Northeastern University Boston, Massachusetts December, 2014 ii ABSTRACT Letting buses operate in mixed traffic is the least costly way to accommodate transit, but that exposes transit to traffic congestion which causes delay and service unreliability. Understanding the real cost that traffic congestion imposes on both passengers and operating agencies is critical for the efficient and equitable management of road space. This study aims to develop a systematic methodology to estimate those costs using Automated Vehicle Location data. Traffic congestion increases cost to both transit operators and passengers. For transit operators, congestion results in longer running times and increased recovery time. To passengers, traffic congestion increases riding time and, because of how congestion increases unreliability, waiting time. Using data from a low-traffic period as a baseline, incremental running time in each period can be calculated. However, some of this incremental running time is due to the greater passenger volumes that typically accompany higher traffic periods. Passenger counts and a regression model for dwell time, estimated from detailed ride check data, are used to estimate the passenger volume effect on running time so that incremental delay due to congestion can be identified. Cost impacts for operators and passengers follow directly. Observed running time variability is a combination of variability due to greater demand, variability in the schedule, inherent variability in running time, variability due to imperfect operating control, and variability due to traffic congestion. Methods are developed to estimate the first four components so that incremental variability due to traffic congestion can be identified for each period, again using a low traffic period as a baseline. From this incremental variability, we can estimate the additional recovery time needed as well as increases in passenger waiting time and potential travel time, which the difference between budgeted travel time and actual travel time. iii The methodology was tested on nine different bus routes including both high and low frequency routes. Overall, the average impact on operating cost is $20.4 per vehicle- hour, and the average impact to passengers is $1.30 per passenger; naturally, these impacts are far greater during peak periods. iv ACKNOWLEDGMENTS First and foremost I would like to express my special appreciation and thanks to my advisor, Prof. Peter G. Furth, who offered his continuous advice and encouragement through the past two years. I have been extremely lucky to have a supervisor who has a great personality, wisdom and knowledge. I would also like to thank my committee member, Prof. Haris N. Koutsopoulos, for his advice. I am grateful to Dr. Daniel Dulaski for his instruction during my study at Northeastern University. This paper would not have been completed without the willingness and support of Melissa Dullea, Samuel Hickey, and David Schmeer at MBTA who provided us with all the needed data for this thesis. I also thank the MIT transit research group for providing us with a sample of the AVL data that we used as a first step in exploring the data. I would also like to thank my parents and brothers who were always supporting me and encouraging me with their best wishes. Last but not least, I would like to thank my wife and best friend, Alyaa Alharbi, for her love, patience, and understanding. Finally, I would like to thank my daughter, Basema, who has been such a great inspiration to me. v TABLE OF CONTENTS ABSTRACT ........................................................................................................................ ii TABLE OF CONTENTS .................................................................................................... v LIST OF TABLES ............................................................................................................ vii LIST OF FIGURES ........................................................................................................... ix Chapter 1. Introduction ................................................................................................. 1 1.1. Overview ............................................................................................................. 1 1.2. Research Objective ............................................................................................. 2 1.3. Thesis Organization ............................................................................................ 3 Chapter 2. Literature review ......................................................................................... 5 2.1. Measuring Congestion ........................................................................................ 5 2.2. AVL systems ....................................................................................................... 6 2.3. Reliability ............................................................................................................ 7 2.4. Conclusion .......................................................................................................... 8 Chapter 3. Data Sources ............................................................................................... 9 3.1. Automated Vehicle Location system (AVL) ...................................................... 9 3.1.1. Heartbeat Data ............................................................................................ 9 3.1.2. Time-point Data ........................................................................................ 10 3.1.3. Announcement Record Data ..................................................................... 12 3.2. Automated Passenger Counting Data (APC) .................................................... 14 Chapter 4. AVL Data Analysis Methodology ............................................................ 15 4.1. Announcement record data processing ............................................................. 15 4.2. Time-point data processing ............................................................................... 16 4.3. Evaluation & Suggestion for the Reviewed AVL Archived Data .................... 17 Chapter 5. Methodology ............................................................................................. 19 5.1. Stop Time Model .............................................................................................. 19 5.1.1. Dwell Time Model .................................................................................... 19 5.1.2. Lost time ................................................................................................... 21 5.2. Grouping trips ................................................................................................... 23 5.3. Average lower speed impact ............................................................................. 24 5.4. Variability in Running Time impact ................................................................. 26 vi 5.4.1. Variability at the trip level ........................................................................ 26 5.4.1.1. Variations from the scheduled running time VFSch(RT)........................ 27 5.4.1.2. Adjust running time variation for greater demand ................................ 29 5.4.1.3. Impact on Operating Cost ..................................................................... 30 5.4.2. Variability at stop level ............................................................................. 32 5.4.2.1. Impact on waiting time “with high frequency service” ........................ 32 5.4.2.2. Impact on waiting time “with low frequency Service” ......................... 34 5.4.2.3. Impact on potential (Budgeted) Travel Time........................................ 35 5.5. Value of time..................................................................................................... 36 5.6. Summary ........................................................................................................... 37 5.7. AVL-Free Methodology ................................................................................... 38 5.7.1. The Number of Stops Made Model. ......................................................... 38 5.7.2. Summary ................................................................................................... 39 5.8. Application to MBTA Route 1 ......................................................................... 40 5.8.1. Annual Impact ........................................................................................... 44 5.8.2. Analyzing route 1 using scheduled RT. .................................................... 46 Chapter 6. Results ....................................................................................................... 48 Chapter 7. Summary and Conclusions ....................................................................... 52 7.1. Conclusion ........................................................................................................ 52 7.2. Future Research ................................................................................................ 52 REFERENCES
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