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Automatic Data for Applied Railway Management

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Automatic Data for Applied Railway Management: Passenger Demand, Service Quality Measurement, and Tactical Planning on the London Overground Network by Michael S Frumin B.S., Computer Science, Stanford University (2000) Submitted to the Department of Civil and Environmental Engineering and the Operations Research Center in partial fulfillment of the requirements for the degrees of Master of Science in Transportation and Master of Science in Operations Research at the Massachusetts Institute of Technology June 2010 c 2010 Massachusetts Institute of Technology. All rights reserved. Author................................................................................... Department of Civil and Environmental Engineering Operations Research Center May 18, 2010 Certified by............................................................................... Nigel H.M. Wilson Professor of Civil and Environmental Engineering Thesis Supervisor Certified by............................................................................... Jinhua Zhao Research Scientist of Civil and Environmental Engineering Thesis Supervisor Accepted by.............................................................................. Dimitris J. Bertsimas Boeing Professor of Operations Research Codirector, Operations Research Center Accepted by.............................................................................. Daniele Veneziano Chairman, Departmental Committee for Graduate Students Automatic Data for Applied Railway Management: Passenger Demand, Service Quality Measurement, and Tactical Planning on the London Overground Network by Michael S Frumin Submitted to the Department of Civil and Environmental Engineering and the Operations Research Center on May 18, 2010, in partial fulfillment of the requirements for the degrees of Master of Science in Transportation and Master of Science in Operations Research Abstract The broad goal of this thesis is to demonstrate the potential positive impacts of applying automatic data to the management and tactical planning of a modern urban railway. Tactical planning is taken here to mean the set of transport-specific analyses and decisions required to manage and improve a railway with time horizons measured in weeks, months, or up to a year and little or no capital investment requirements. This thesis develops and tests methods to (i) estimate on-train loads from automatic measurements of train payload weight, (ii) estimate origin-destination matrices by combin- ing multiple types of automatic data, (iii) study passenger incidence (station arrival) behavior relative to the published timetable, (iv) characterize service quality in terms of the differ- ence between automatically measured passenger journey times and journey times implied by the published timetable. It does so using (i) disaggregate journey records from an entry- and exit-controlled automatic fare collection system, (ii) payload weight measurements from \loadweigh" sensors in train suspension systems, and (iii) aggregate passenger volumes from electronic station gatelines. The methods developed to analyze passenger incidence behavior and service quality using these data sources include new methodologies that facilitate such analysis under a wide variety of service conditions and passenger behaviors. The above methods and data are used to characterize passenger demand and service qual- ity on the rapidly growing, largely circumferential London Overground network in London, England. A case study documents how a tactical planning intervention on the Overground network was influenced by the application of these methods, and evaluates the outcomes of this intervention. The proposed analytical methods are judged to be successful in that they estimate the desired quantities with sufficient accuracy and are found to make a positive contribution to the Overground's tactical planning process. It is concluded that relative measures of service quality such as the one developed here can be used in cross-sectional analysis to inform tactical planning activity. However, such measures are of less utility for longitudinal evaluation of tactical planning interventions when the basis against which service quality is judged (in this case the timetable) is changed. Under such circumstances, absolute measures, such as total observed passenger journey times, should be used as well. Thesis Supervisor: Nigel H.M. Wilson Title: Professor of Civil and Environmental Engineering Thesis Supervisor: Jinhua Zhao Title: Research Scientist of Civil and Environmental Engineering Acknowledgments The research presented in this thesis, indeed the entire course of graduate study which culminates in this thesis, was made possible by a number of parties whom the author wishes to thank and acknowledge. • The Massachusetts Institute of Technology, its Department of Civil and Environmental Engineering, and the faculty and staff of the Master of Science in Transportation program for making a home for students interested in the science and practice of transportation. • Professor Nigel Wilson and the other leaders of the Transit Research Group for the opportunity to conduct research into practical problems facing the public transport providers who make our cities possible. • Transport for London, and its many staff members in the departments of London Rail, London Underground, and Fares & Ticketing, for financial support, feedback, knowledge, and two summers of internship employment. • Certain railway managers in and around London and New York City, including Oliver Bratton and Herbert Lambert, for helping ground this thesis in the contemporary needs and practices of the managers of modern urban railways. • Dr. Jinhua Zhao, along with Professor Wilson, for supervising the writing of this thesis. • The MIT Operations Research Center for allowing the author to dig deeper into many of the technical and analytical methods applied in the field of transportation and in this thesis. • The family, friends, colleagues, and classmates without whom it is difficult to imagine how the author would be anywhere near where he is today. 5 6 Contents 1 Introduction 15 1.1 Railway Management, Tactical Planning, and Automatic Data . 16 1.2 Motivation . 17 1.3 Objectives . 18 1.4 Research Approach . 19 1.5 Thesis Organization . 20 2 Public Transport in London 21 2.1 London and the Greater London Authority . 21 2.2 The Public Transport Network . 21 2.3 Public Transport Fares and Ticketing . 23 2.4 The London Overground Network . 25 2.5 Institutional Structures . 27 2.6 Investment and Expansion . 28 3 Data Needs and Sources 31 3.1 Data Needs . 31 3.2 A Synthetic Approach for the London Overground . 32 3.3 Data Sources . 34 3.3.1 The Oyster Smartcard Ticketing System . 34 3.3.2 \Loadweigh" Train Payload Weighing Systems . 35 3.3.3 Station Gatelines . 36 3.3.4 Manual Passenger Counts . 36 3.3.5 Network Representations . 36 3.3.6 Additional Data Sources . 37 4 Calibration of Loadweigh Systems 39 4.1 Literature Review and Industry Experience . 39 4.2 Model Development . 41 4.3 Exploratory Analysis . 43 4.4 Calibration Results for the London Overground . 45 4.5 Variability of On-board Loads . 48 4.6 Conclusions and Recommendations . 50 7 5 Origin-Destination Matrix Estimation 53 5.1 Public Transport Network Assignment Literature Review . 54 5.1.1 Supply Models . 54 5.1.2 Paths and Path Choice Models . 56 5.1.3 Assignment Models . 58 5.2 OD Matrix Estimation Literature Review . 59 5.2.1 OD Estimation Example . 60 5.2.2 OD Estimation Methods . 61 5.2.3 Simulation of OD Estimation Methodologies . 66 5.3 OD Estimation Strategy for the London Overground . 66 5.3.1 Assignment Model for the London Overground . 67 5.3.2 Information Minimization Matrix Estimation . 76 5.4 Exploratory Analysis of OD Estimation Inputs . 78 5.4.1 Oyster Seed Matrix . 78 5.4.2 Link Flows . 78 5.4.3 Gateline Data . 80 5.5 OD Estimation Results . 81 5.5.1 Validation . 84 5.5.2 Loadweigh Sensitivity Analysis . 87 5.6 Conclusions and Recommendations . 89 5.6.1 Conclusions . 90 5.6.2 Recommendations . 91 6 Passenger Incidence Behavior 93 6.1 Literature Review . 93 6.1.1 Passenger Incidence Behavior . 94 6.1.2 Schedule-Based Assignment . 99 6.2 Methodology . 101 6.2.1 Behavioral Assumptions . 103 6.2.2 Algorithm . 103 6.2.3 Implementation . 105 6.3 Passenger Incidence Behavior on the London Overground Network . 106 6.3.1 Data . 106 6.3.2 Validation . 107 6.3.3 Results . 108 6.4 Conclusions and Recommendations . 110 6.4.1 Conclusions . 110 6.4.2 Recommendations . 111 7 Service Quality Measurement from AFC Data 113 7.1 Service Delivery and Service Quality Measurement Literature Review . 114 7.1.1 Service Delivery Measurement and The Operator's Perspective . 115 7.1.2 Service Quality Measurement and The Passenger's Perspective . 117 7.1.3 Relative Service Quality . 119 7.1.4 Discussion . 121 8 7.2 Analytical Framework and Assumptions . 124 7.2.1 Journey Time Components and Standards . 124 7.2.2 Passenger Incidence and Behavioral Assumptions . 126 7.2.3 Framework Intuitions . 129 7.3 A Unified Unbiased Estimator for Aggregate Excess Journey Time . 130 7.3.1 Framework for Aggregate EJT . 130 7.3.2 Equivalence of Random and Scheduled Incidence Assumptions for Ag- gregate EJT of Random Incidence Passengers . 131 7.3.3 Blended Passenger Incidence Behavior . 133 7.3.4 Extension to a Heterogeneous Rail Network with Interchanges . 135 7.4 Discussion . 136 7.4.1 Application Considerations . 136 7.4.2 Negative EJT . 137 7.4.3 EJT and Longitudinal Analysis . 138 7.5 Conclusions . 139 8 Oyster-Based Excess Journey Time on the London Overground 141 8.1 Excess Journey Time Methodology for the London Overground . 141 8.2 Graphical Validation . 143 8.3 Results . 146 8.3.1 Excess Journey Time on the London Overground . 146 8.3.2 Comparison with Existing Performance Metrics . 152 8.4 Conclusions . 154 9 Tactical Planning Case Study on the London Overground 157 9.1 The North London Line: Spring 2008 . 157 9.1.1 The Service Plan . 158 9.1.2 Passenger Demand . 160 9.1.3 Operating Performance: Service Delivery and Quality . 162 9.2 Tactical Planning Intervention: The Case for Even Intervals . 165 9.2.1 \3 + 3" Service on the North London Line . 167 9.3 Evaluation . ..
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