Transportation asset management: methodology and applications

761 Pages·2019·157.635 MB·English

by  Li, Zongzhi

Transportation Asset
Management
Methodology and Applications

Transportation Asset
Management
Methodology and Applications
Zongzhi Li
CRC Press
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Library of Congress Cataloging-in-Publication Data
Names: Li, Zongzhi, (Professor of transportation engineering), author.
Title: Transportation asset management : methodologies and applications / by Zongzhi Li.
Description: Boca Raton ; London : CRC Press, [2018] | Includes bibliographical references
and index.
Identifiers: LCCN 2017030456| ISBN 9781482210521 (hardback : alk. paper) |
ISBN 9781315117966 (ebook)
Subjects: LCSH: Transportation--Planning. | Transportation--Forecasting. |
Transportation--United States--Management. | Infrastructure
(Economics)--United States--Management. |
Transportation--Management--Economic aspects--United States.
Classification: LCC HE147.5 .L5 2018 | DDC 388.068--dc23
LC record available at https://lccn.loc.gov/2017030456
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To my parents, uncles, and family who stimulated and
encouraged my early work in transportation systems

Contents
List of symbols xxv
List of abbreviations xxix
Preface xxxvii
Author xli
1 Introduction 1
1.1 Overview of a multimodal transportation system 1
1.1.1 Multimodal transportation facilities 1
1.1.2 Transportation vehicles 1
1.1.3 Passenger and freight movements 1
1.2 Transportation system characteristics 2
1.2.1 Interdependent system components 2
1.2.2 System component life cycle considerations 2
1.2.3 Multidimensional impacts and multiple performance goals 2
1.3 Transportation asset management process 3
1.3.1 Transportation goals, objectives, and performance measures 4
1.3.2 Data needs, collection, processing, and database management 4
1.3.3 Multimodal physical facility and system usage performance
modeling 5
1.3.4 Travel demand and traffic flow predictions 5
1.3.5 Transportation system performance trend analysis 5
1.3.6 Needs assessment and investment alternatives 5
1.3.7 Project evaluation 6
1.3.8 Project selection and programming 6
1.3.9 Project implementation and feedback 7
2 Transportation goals, objectives, and performance measures 9
2.1 General 9
2.2 Transportation policy goals, system management goals, and objectives 9
2.3 Transportation performance measures 10
2.3.1 Desirable properties 10
2.3.2 Performance measures under policy goals 11
2.3.3 Performance measures under system management goals 12
2.3.4 Network- and project-level performance measures 12
vii
viii Contents
3 Data collection, processing, and database management 19
3.1 Dimensions of data needs for transportation asset
management 19
3.1.1 Data needs for pavement management 19
3.1.2 Data needs for bridge and tunnel management 22
3.1.3 Data needs for maintenance management 22
3.1.4 Data needs for traffic control and safety hardware
management 23
3.1.5 Data needs for congestion management 24
3.1.6 Data needs for safety management 25
3.1.7 Data needs for transit performance management 25
3.1.8 Network-wide forecasted traffic data 25
3.2 Data sampling methods 27
3.2.1 Simple random sampling method 28
3.2.1.1 Sample size 28
3.2.1.2 Data sampling analysis 29
3.2.2 Systematic random sampling method 31
3.2.3 Stratified random sampling method 32
3.2.3.1 Sample size 32
3.2.3.2 Data sampling analysis 33
3.2.4 Cluster sampling method 36
3.2.4.1 Sample size 36
3.2.4.2 Data sampling analysis 37
3.2.5 Combined sampling 39
3.3 Data collection techniques 40
3.3.1 Passenger demand data collection 40
3.3.2 Truck demand data collection 41
3.3.3 Pavement data collection 42
3.3.3.1 Pavement segment delineation 42
3.3.3.2 Surface condition data collection 43
3.3.3.3 Pavement structural capacity data collection 45
3.3.4 Bridge condition data collection 46
3.3.5 Traffic control and safety hardware data collection 48
3.3.5.1 Traffic sign and pavement marking data collection 48
3.3.5.2 Traffic lighting illumination level data collection 50
3.3.6 Travel time data collection 50
3.3.6.1 Conventional travel time data collection 50
3.3.6.2 Real-time traffic data collection 52
3.3.7 Transit performance data collection 53
3.3.7.1 Speed-and-delay survey 53
3.3.7.2 Passenger volume and load count 53
3.3.7.3 Passenger boarding and alighting counts 54
3.4 Data collection frequency 54
3.5 Data quality assurance 54
3.5.1 Quality standards 56
3.5.2 Quality assurance 56
Contents ix
3.6 Data integration 57
3.6.1 Data integration process 57
3.6.2 Data transformations 60
3.6.3 Transformation between linear reference systems 62
3.6.4 Transformation between GPS and LRS 63
3.6.5 Data integration techniques 63
3.7 Database development and management 66
3.7.1 Database planning, design, and construction 66
3.7.1.1 Data standards 66
3.7.1.2 Metadata and data dictionary 66
3.7.1.3 Requirements 67
3.7.1.4 Testing and implementation 68
3.7.1.5 Database evaluation 68
3.7.2 Data modeling 68
3.7.3 New requirements for database management 70
3.7.3.1 Storage capacity 70
3.7.3.2 Heterogeneous data 71
3.7.3.3 Bad data and missing data 71
Problems 71
4 Transportation facility performance modeling 75
4.1 General 75
4.1.1 Characteristics of facility performance measures and models 75
4.1.2 Facility condition deterioration and service life expectancy 75
4.2 Performance model types 76
4.2.1 Condition deterioration model types 76
4.2.1.1 Regression models 76
4.2.1.2 Econometric models 77
4.2.1.3 Markov models 79
4.2.1.4 Reliability-based models 79
4.2.1.5 Ordered probability models 79
4.2.1.6 Bayesian models 80
4.2.1.7 Nonparametric binary recursive partitioning method 80
4.2.1.8 Artificial intelligence models 80
4.2.2 Service life expectancy model types 81
4.2.2.1 Regression models 81
4.2.2.2 Parametric survival models 81
4.2.2.3 Semi-parametric survival models 82
4.2.2.4 Neural network models 82
4.3 Model estimation techniques 82
4.3.1 Preliminary data analysis 82
4.3.2 Classical regression model assumptions 84
4.3.3 OLS estimation 84
4.3.4 ML estimation 86
4.3.5 Model validation 87
4.3.6 Model predictability evaluation 87