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Cover image for Public Transport Planning with Smart Card Data
Title:
Public Transport Planning with Smart Card Data
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Publication Information:
CRC Press, 2017
ISBN:
9781498726580

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Status
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PSZ JB1On Order

Summary

Summary

Collecting fares through "smart cards" is becoming standard in most advanced public transport networks of major cities around the world. Travellers value their convenience and operators the reduced money handling fees. Electronic tickets also make it easier to integrate fare systems, to create complex time and space differentiated fare systems, and to provide incentives to specific target groups. A less-utilised benefit is the data collected through smart cards. Records, even if anonymous, provide for a much better understanding of passengers' travel behaviour as current literature shows. This information can also be used for better service planning.

Public Transport Planning with Smart Card Data handles three major topics: how passenger behaviour can be estimated using smart card data, how smart card data can be combined with other trip databases, and how the public transport service level can be better evaluated if smart card data is available. The book discusses theory as well as applications from cities around the world and will be of interest to researchers and practitioners alike who are interested in the state-of-the-art as well as future perspectives that smart card data will bring.


Table of Contents

Prefacep. v
1 An Overview on Opportunities and Challenges of Smart Card Data Analysisp. 1
1 Introductionp. 1
2 Smart Card Systems and Data Featuresp. 2
3 Analysis Challengesp. 5
4 Categorization of Potential Analysis using Smart Card Datap. 7
5 Book Overview, What is Missing and Conclusionp. 9
Referencesp. 11
Author Biographyp. 11
Part 1 Estimating Passenger Behavior
2 Transit Origin-Destination Estimationp. 15
1 Introductionp. 15
2 General Principlesp. 17
3 Inference of Destinationsp. 18
4 O-D Matrix Methodsp. 24
5 Journey and Tour Pattern Analysisp. 25
6 Areas for Future Researchp. 29
Referencesp. 30
Author Biographyp. 35
3 Destination and Activity Estimationp. 37
1 Smart Card Use in Trip Destination and Activity Estimationp. 38
2 Smart Card Data Structure in Seoulp. 39
3 Methodology for Trip Destination Estimationp. 41
4 Trip Purpose Imputation using Household Travel Surveyp. 43
5 Results and Discussionp. 48
6 Illustration of Results with MATSimp. 50
7 Conclusionp. 51
Referencesp. 52
Author Biographyp. 53
4 Modelling Travel Choices on Public Transport Systems with Smart Card Datap. 55
1 Introductionp. 55
2 Theoretical Backgroundp. 56
3 Modelling Behaviour with Smart Card Datap. 59
4 Case Study: Santiago, Chilep. 63
5 Conclusionp. 68
Acknowledgementsp. 68
Referencesp. 68
Author Biographyp. 70
Part 2 Combining Smart Card Data with other Databases
5 Combination of Smart Card Data with Person Trip Survey Datap. 73
1 Introductionp. 73
2 Modelp. 77
3 Empirical Analysisp. 82
4 Conclusionp. 90
Referencesp. 91
Author Biographyp. 92
6 A Method for Conducting Before-After Analyses of Transit Use by Linking Smart Card Data and Survey Responsesp. 93
1 Introductionp. 94
2 Literature Reviewp. 94
3 Backgroundp. 96
4 Data Collectionp. 96
5 Methodologyp. 99
6 Evaluation of the Interventionp. 103
7 Areas for Improvement and Future Researchp. 108
8 Conclusionp. 109
Acknowledgementsp. 109
Referencesp. 110
Author Biographyp. 110
7 Multipurpose Smart Card Data: Case Study of Shizuoka, Japanp. 113
1 Introductionp. 113
2 Multipurpose Smart Cardsp. 115
3 Case Study Area and Smart Card Data Overviewp. 115
4 Overview of Collected Datap. 118
5 Stated Preference Survey on Sensitivity to Point Systemp. 119
6 Conclusionp. 129
Referencesp. 130
Author Biographyp. 130
8 Using Smart Card Data for Agent-Based Transport Simulationp. 133
1 Introductionp. 133
2 User Equilibrium and Public Transport in MATSimp. 135
3 CEPASp. 136
4 Methodp. 138
5 Validation and Performancep. 147
6 Applicationp. 154
7 Conclusionp. 157
Acknowledgementsp. 158
Referencesp. 158
Author Biographyp. 159
Part 3 Smart Card Sata for Evaluation
9 Smart Card Data for Wider Transport System Evaluationp. 163
1 Introductionp. 163
2 Level of Service Indicatorsp. 164
3 Application to Santiagop. 166
4 Conclusionp. 176
Acknowledgementsp. 177
Referencesp. 177
Authors Biographyp. 178
10 Evaluation of Bus Service Key Performance Indicators using Smart Card Datap. 181
1 Introductionp. 181
2 Backgroundp. 182
3 Information Systemp. 183
4 KPI Assessmentp. 184
5 Some Examplesp. 186
6 Conclusionp. 193
Acknowledgementsp. 194
Referencesp. 194
Author Biographyp. 196
11 Ridership Evaluation and Prediction in Public Transport by Processing Smart Card Data: A Dutch Approach and Examplep. 197
1 Introductionp. 197
2 Smart Cards and Datap. 199
3 Predicting Ridership by Smart Card Datap. 203
4 Case Study: The Tram Network of The Haguep. 213
5 Conclusionp. 219
Acknowledgementsp. 221
Referencesp. 221
Author Biographyp. 223
12 Assessment of Traffic Bottlenecks at Bus Stopsp. 225
1 Introductionp. 225
2 Background of this Studyp. 226
3 Development of Evaluation Measuresp. 227
4 Saitama City Case Studyp. 234
5 Conclusionp. 242
Acknowledgementsp. 242
Referencesp. 242
Author Biographyp. 243
13 Conclusions: Opportunities Provided to Transit Organizations by Automated Data Collection Systems, Challenges and Thoughts for the Futurep. 245
1 Backgroundp. 246
2 Automated Data Collection Systems (ADCS)p. 247
3 A Conceptual Framework for ADCS in a Transit Organizationp. 249
4 Challengesp. 254
5 An Unexplored Area for Research Using Smart Card Data: Elasticities and Pricing Strategyp. 256
6 Conclusions: Looking to the Futurep. 259
Author Biographyp. 260
Indexp. 263
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