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Optimal Train Control on Various Track Alignments Considering Speed and Schedule Adherence Constraints

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Optimal Train Control on Various Track Alignments Considering Speed and Schedule Adherence Constraints Copyright Warning & Restrictions The copyright law of the United States (Title 17, United States Code) governs the making of photocopies or other reproductions of copyrighted material. Under certain conditions specified in the law, libraries and archives are authorized to furnish a photocopy or other reproduction. One of these specified conditions is that the photocopy or reproduction is not to be “used for any purpose other than private study, scholarship, or research.” If a, user makes a request for, or later uses, a photocopy or reproduction for purposes in excess of “fair use” that user may be liable for copyright infringement, This institution reserves the right to refuse to accept a copying order if, in its judgment, fulfillment of the order would involve violation of copyright law. Please Note: The author retains the copyright while the New Jersey Institute of Technology reserves the right to distribute this thesis or dissertation Printing note: If you do not wish to print this page, then select “Pages from: first page # to: last page #” on the print dialog screen The Van Houten library has removed some of the personal information and all signatures from the approval page and biographical sketches of theses and dissertations in order to protect the identity of NJIT graduates and faculty. ASAC OIMA AI COO O AIOUS ACK AIGMES COSIEIG SEE A SCEUE AEECE COSAIS b Kt K The methodology discussed in this dissertation contributes to the field of transit operational control to reduce energy consumption. Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called "golden run". To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route. OPTIMAL TRAIN CONTROL ON VARIOUS TRACK ALIGNMENTS CONSIDERING SPEED AND SCHEDULE ADHERENCE CONSTRAINTS by Kitae Kim A Dissertation Submitted to the Faculty of New Jersey Institute of Technology In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Civil Engineering Department of Civil and Environmental Engineering January 2010 Copyright © 2010 by Kitae Kim ALL RIGHTS RESERVED IOGAICA SKEC Athr Kitae Kim r Doctor of Philosophy t January 2010 Undrrdt nd Grdt Edtn • Doctor of Philosophy in Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ, 2010 • Master of Science in Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ, 2005 • Master of Science in Transportation Planning and Engineering, Polytechnic University, Brooklyn, NY, 2002 • Bachelor of Science in Civil Engineering, Chung-Ang University, Seoul, Korea, 1999 Mjr Transportation Engineering rnttn nd bltn Kt K and Steven Chien, "Optimal Train Operation for Minimum Energy Consumption Considering Schedule Adherence", Transportation Research Board 89th Annual Meeting, January 2010 (Forthcoming) Kt K and Steven Chien, "Simulation Analysis of Energy Consumption for Various Train Controls and Alignment", Transportation Research Board 88 th Annual Meeting, January 2009 Steven Chien, Sunil Kumar Daripally, and Kt K "Development of a Probabilistic Model to Disseminate Bus Arrival Time", Journal of Advanced Transportation, Vol. 41, No. 2, 2007 Steven Chien, Kt K and Janice Daniel, "Cost and Benefit Analysis for Optimized Signal Timing Case Study: New Jersey Route 23", ITE Journal, Vol. 76, No. 10, 2006 v AOA AGE OIMA AI COO O AIOUS ACK AIGMES COSIEIG SEE A SCEUE AEECE COSAIS Kt K Dr, Steven I-Jy Chien, Dissertation Advisor Date Professor of Civil and Environmental Engineering, NJIT Dr. Lazar Spasovic, Committee Member Date Professor of Civil and Environmental Engineering, NJIT Dr. Athanassios Bladikas, Committee Member Date Associate Professor of Mechanical and Industrial Engineering, NJIT Dr. Janice R. Daniel, Committee Member Date Associate Professor of Civil and Environmental Engineering, NJIT Dr. Jerome Lutin, Committee Member Date Di nguished Research Professor, Office of the Dean, NCE, NJIT I would like to dedicate this dissertation to My beloved wife, Dongwook Oh, who showed me her love, sacrifice, and encouragement throughout; My parents, II-Rang Kim and Heeja Ha, who motivated me to study abroad and made all the sacrifices and my brother Su-young Kim, who gave me encouragement ; and My mentor, Sun-gak, who always gave me help and advice during my study. ACKNOWLEDGEMENT I do greatly appreciate my dissertation advisor, Dr. Steven I-Jy Chien, who constantly supported, inspired and encouraged me with his insight, dedication and understanding during my Ph.D. study. Special thanks are given to Dr. Jerome Lutin, Dr. Lazar Spasovic, Dr. Athanassios Bladikas, and Dr. Janice Daniel for serving as committee members and providing me with precious suggestions on research and industrial practice, I also express my appreciation to Mr. Anthony Pincherri at NJ TRANSIT, who provided me with valuable data for my dissertation. My fellow graduate students, Dr. Feng-Ming Tsai, Dr, Sungmin Maeng, Dr, Mingzheng Cao, Mr. Yavuz Ulusoy, Ms. Patricia DiJoseph, and Mr. Jinuk Ha, are deserving recognition for their support. I also appreciate all projects sponsored by the New Jersey Department of Transportation, New Jersey Transit, the National Center for Transportation and Industrial Productivity, New Jersey Institute of Technology, and the International Road Federation (IRF) Fellowship Program, which supported my tuition and other financial needs. vi TABLE OF CONTENTS Chapter Page 1 INTRODUCTION 1 1.1 Background 1 1.2 Problem Statement 2 1.3 Objective and Work Scope 4 1,4 Dissertation Organization 6 2 LITERATURE REVIEW 7 2.1 Sustainable Train Operation 7 2.2 Train Performance Simulation (TPS) 12 2.3 Kinematic Models for Train Movement 19 2.3.1 Tractive Effort and Adhesion 19 2.3.2 Train Resistances 22 2,4 Train Control Regimes 26 2.5 Minimization of Energy Consumption for Train Operation 31 2.6 Optimization Algorithms and Heuristics 35 2,7 Summary 38 3 DEVELOPMENT OF TRAIN PERFORMANCE SIMULATION (TPS) 41 3,1 Train Traction Module (TTM) 41 3.2 Track Alignment Module (TAM) 49 3.3 Train Control Module (TCM) 51 4 METHODOLOGY FOR MINIMIZING ENERGY CONSUMPTION 59 vii TABLE OF CONTENTS (Continued) Chapter Page 4,1 Model I — SVA and Constant MOS (Case I) 59 4,1.1 System Assumptions 60 4.1.2 Model Formulation 61 4.1.3 Constraints 62 4.1.4 Optimization Model 64 4.2 Model II - SVA and Variable MOS (Case II) 64 4,2.1 System Assumptions 64 4.2,2 Optimization Model 66 4,3 Model III — MVA and Constant MOS (Case III) 66 4.3.1 System Assumptions 67 4.3.2 Optimization Model 69 4.4 Model IV — MVA and Variable MOS (Case IV) 69 4.4.1 System Assumptions 69 4,4.2 Optimization Model 71 4.5 Summary 71 5 SOLUTION METHODS 72 5.1 SVA with Constant MOS (Case I) 72 5,1.1 Train Control for Case I 72 5.1.2 SA for Case II 74 5,1.3 Fitness Function for Case I 81 viii TABLE OF CONTENTS (Continued) Chapter Page 5.1.4 Cooling Schedule for Case I 82 5,2 SVA with Variable MOS (Case II) 83 5.2.1 Train Control for Case II 83 5.3 MVA with Constant MOS (Case III) 85 5.4 MVA with Variable MOS (Case IV) 85 5.5 Summary 86 6 CASE STUDY 87 6.1 Optimal Results for Cases I and II 87 6.1.1 SVA with Constant MOS (Case I) 89 6.1,2 SVA with Variable MOS (Case II) 94 6.2 Optimal Results for Cases III and IV 98 6.2.1 The Metro-North Railroad (New Haven Line) 100 6.2.2 MVA with Constant MOS (Case III) 101 6,2.3 MVA with Variable MOS (Case IV) 103 6.3 Results Comparison 105 6.4 Sensitivity Analysis 110 7 CONCLUSIONS AND FUTURE RESEARCH 133 7.1 Conclusions 133 7,2 Future Research 136 REFERENCES 138 ix LIST OF TABLES Table Page 1.1 Proposed Work Scope 5 2.1 Indicators of Sustainable Transportation
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