New Jersey Institute of Technology Digital Commons @ NJIT Dissertations Electronic Theses and Dissertations Fall 1-31-2004 Intercity travel demand : a utility-consistent simultaneous trip generation and mode choice model Guilin Li New Jersey Institute of Technology Follow this and additional works at: https://digitalcommons.njit.edu/dissertations Part of the Transportation Engineering Commons Recommended Citation Li, Guilin, "Intercity travel demand : a utility-consistent simultaneous trip generation and mode choice model" (2004). Dissertations. 606. https://digitalcommons.njit.edu/dissertations/606 This Dissertation is brought to you for free and open access by the Electronic Theses and Dissertations at Digital Commons @ NJIT. It has been accepted for inclusion in Dissertations by an authorized administrator of Digital Commons @ NJIT. For more information, please contact [email protected]. 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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. ABSTRACT INTERCITY TRAVEL DEMAND: A UTILITY-CONSISTENT SIMULTANEOUS TRIP GENERATION AND MODE CHOICE MODEL by Guilin Li An intercity travel decision includes a complex set of subdecisions, such as when to travel, where to travel, which mode to choose, and others. The main focus of this dissertation is to examine trip frequency and mode choice of intercity non-business travel. The objective of this study is to understand intercity travel behavior using disaggregate models. The proposed conceptual framework for intercity travel behavior leads to a nested logit/continuous choice model that is rigorously linked to the utility maximization theory. Compared to a traditional intercity travel demand model, the proposed model is utility consistent in that trip generation and mode choice models flow from one utility function. Thus, the resultant model embodies the interrelationship of trip generation and mode choice. Applying the model to the NorthEast Corridor, the calibrated results show that trip generation of non-business travelers is interdependent with mode choice. The factors influencing mode choice may exert an impact on trip generation directly or indirectly. INTERCITY TRAVEL DEMAND: A UTILITY-CONSISTENT SIMULTANEOUS TRIP GENERATION AND MODE CHOICE MODEL by Guilin Li 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 Transportation Interdisciplinary Program in Transportation January 2004 Copyright © 2004 by Guilin Li ALL RIGHTS RESERVED APPROVAL PAGE INTERCITY TRAVEL DEMAND: A UTILITY-CONSISTENT SIMULTANEOUS TRIP GENERATION AND MODE CHOICE MODEL Guilin Li ogag 7(ace iu isseaio Aiso ae Assisa oesso o Cii a Eiomea Egieeig I Aaassios K aikas Commiee Meme ae Associae oesso a Cai o Iusia a Mauacuig Egieeig a ieco o Ieisciiay ogam i asoaio I aa Sasoic Commiee Meme ae oesso o Maageme a ieco o Ieaioa Iemoa asoaio Cee I aice aie Commiee Meme ae Assisa oesso o Cii a Eiomea Egieeig I ueao Cu Commiee Meme ae Ecoomis Seio eseac Associae Cee o Ua asoaio Cee US BIOGRAPHICAL SKETCH Author: Guilin Li Degree: Doctor of Philosophy in Transportation Date: January 2004 Undergraduate and Graduate Education: • Doctor of Philosophy in Transportation, New Jersey Institute of Technology, Newark, NJ, 2004 • Master of Science in Transportation, New Jersey Institute of Technology, Newark, NJ, 2001 • Master of Science in Traffic Engineering, Tongji University, Shanghai, P. R. China, 1999 • Bachelor of Science in Traffic Engineering, Tongji University, Shanghai, P. R. China, 1996 Major: Transportation Engineering Presentations and Publications: iu a i G "e Suecie aues o Saey a Secuiy i e Coe o Ieciy ae" oceeigs o e 3 Aua Meeig o e asoaio eseac oa Wasigo C iu a i G "yamic ae eaio Aaysis ase o Socasic ecisio-Makig Syes" esee a e 1 Ieaioa Coeece o ae eaio eseac ucee Swiea Augus 1-15 3 iu a i G "Ieciy ae Coices Aece y Saey a Secuiy Measues" esee o Commiee A1 C Socia a Ecoomic acos i asoaio a e Aua Meeig o e asoaio eseac oa Wasigo C auay 3 i i G Wu a ou S "O Esimaio Suy o Eeae oas" esee a e 7 Coss Sai Coeece o Ua asoaio i-A Cia Augus 3- 1999 i G i a ou S "Oeaio Aaysis o e Sou-o Eeae eway i Sagai" aic a asoaio 1999 o 1 To Shangwu Zhou, a professor in Tongji University, Shanghai, P.R. China Ying Xiao and Jason Li And my beloved family i ACKNOWLEDGMENT While many people deserve my thanks for their contribution to this dissertation, I would like to single out a few for special attention. My dissertation advisor, Dr. Rongfang (Rachel) Liu, has my sincere gratitude for her great mentorship. Indeed her inspirational ideas and insightful comments were the reasons that this work could be completed. Her experience and advices have proven to be an invaluable guidance for my study and life. Special thanks are given to Dr. Athanassios K. Bladikas, Dr. Lazar N. Spasovic, Dr. Janice Daniel, and Dr. Xuehao Chu for actively participating in my committee. Dr. Athanassios K. Bladikas deserves credit for the wisdom and kindness he has shown me these four and half years. I would like to thank Dr. Lazar N. Spasovic for his mentorship in the first two years and encouragement in the following years. He also has provided his sage advice in our discussions for this dissertation. Thanks to Dr. Janice Daniel for being helpful in the writing of this dissertation. Thanks to Dr. Xuehao Chu at the University of South Florida for kindly helping me solve various econometric problems through the end of this task. I have communicated with many people while working on my dissertation. Among which the following individuals are worth mentioning: Professor William H. Greene from New York University, Professor Sheila Olmstead from Yale University, Professor Jeongwen Chiang from National University from Singapore, Professor Pradeep Chintagunta from University of Chicago, Professor Tat Chan from Washington vii University in St. Louis, Statistician Kevin Meyer from SAS and Professor Janet M. Bodner from NJIT. My appreciation also goes to the Interdisciplinary Program in Transportation, National Center for Transportation and Industrial Productivity (NCTIP), and International Intermodal Transportation Center (IITC) at New Jersey Institute of Technology for awarding me the Research Scholarship which made it possible for me to finish my graduate study. I would like to thank my friends. With apologies to those inadvertently omitted, the following list is as close to exhaustive as my memory will allow: Dr. Ye Li, Fuyun Cao, Fayun Luo, Shouxiang Cheng, Dr. Cheryl Allen-Munley, Dr. Jiangtao Luo, Xiaobo Liu, Qiang Hu, Yonghui Zhang, Yiming Tang, Jing Qu, Changqian Guan, Fei Yang, Yi Deng, Jiahua Song, David Antonio, Dr. Mark A Ladolcetta, and Hao Liu. v TABLE OF CONTENTS Chapter Page 1 INTRODUCTION 1 1.1 Problem Statement 1 1.2 Research Objective and Methods 3 1.3 Research Scope 4 1.4 Dissertation Organization 5 2 LITERATURE REVIEW 6 2.1 Intercity Travel Demand Model Structure 6 2.1.1 Conventional Travel Demand Models 7 2.1.2 Trip Generation/Frequency Models 7 2.1.3 Mode Choice Models.. 11 2.2 Early Intercity Travel Demand Models.. 13 2.2.1 Origin of Intercity Travel Demand Model 13 2.2.2 Direct Demand Models 13 2.3 Simultaneous Travel Demand Models 17 2.3.1 CRA Model for Urban Travel Demand 18 2.3.2 Damodaran Model for Intercity Travel 19 2.3.3 Multidimensional Model System for Intercity Travel Choice 21 Behavior 2.3.4 Use of Roy's Identity for Comprehensive Travel Demand Modeling 22 2.4 Discrete/Continuous Model 23 i TABLE OF CONTENTS (Continued) Chapter Page 3 INTERCITY TRAVEL ANALYSIS 28 3.1 Intercity Travel Decision-Making 28 3.2 Intercity Trip Frequency 32 3.3 Transferability of Current Framework 34 3.4 Conceptualization of Individuals' Travel Choice Decisions 37 4 NESTED LOGIT/CONTINUOUS MODEL 42 4.1 Introduction 42 4.2 Random Utility Maximization Model 43 4.3 Mode Choice Model 50 4.4 Trip Generation Model 55 4.5 Model Estimation 60 4.5.1 Full Information Likelihood Maximization Estimation 60 4.5.2 Two-Step Estimation Approach 61 5 DATA PREPARATION 62 5.1 Data Needs 62 5.2 Data Sources 64 5.2.1 Different Data Sources 65 5.2.2 1995 ATS 68 5.3 Data Preparation 70 5.3.1 Corridor Background 70 5.3.2 Data Filtering 76 TABLE OF CONTENTS (Continued) Chapter Page 5.3.3 Data Preparation 77 6 CALIBRATION
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