Public Transport Planning with Smart Card Data: 1st Edition (Hardback) book cover

Public Transport Planning with Smart Card Data

1st Edition

Edited by Fumitaka Kurauchi, Jan-Dirk Schmöcker

CRC Press

274 pages | 20 Color Illus. | 59 B/W Illus.

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Hardback: 9781498726580
pub: 2016-11-10
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Description

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

An Overview on Opportunities and Challenges of Smart Card Data Analysis

Introduction

Smart Card Systems and Data Features

Analysis Challenges

Categorization of Potential Analysis using Smart Card Data

Book Overview, What is Missing and Conclusion

References

Author Biography

PART 1: ESTIMATING PASSENGER BEHAVIOR

Transit Origin-Destination Estimation

Introduction

General Principles

Inference of Destinations

Tour ("Trip Chain") Assumptions

Inference Methods

Transfer vs. Activity Inference

O-D Matrix Methods

Journey and Tour Pattern Analysis

Identification of Routes from Smart Card Data

Journey Pattern Analysis

Activity Inference and Analysis

Areas for Future Research

References

Author Biography

Destination and Activity Estimation

Smart Card Use in Trip Destination and Activity Estimation

Smart Card Data Structure in Seoul 39viii 2. Methodology for Trip Destination Estimation

Data Cleaning

Trips and Trip Legs

Trip Purpose Imputation using Household Travel Survey

Activity Start Time and Duration

Trip Purpose Prediction

Results and Discussion

Illustration of Results with MATSim

References

Author Biography

Modelling Travel Choices on Public Transport Systems with Smart Card Data

Introduction

Theoretical Background

Choice-Set Generation Methods

Discrete Choice Models

Modelling Behaviour with Smart Card Data

Modelling Origins and Destinations

Modelling the Choice-Set

Modelling Travel Times and Fares

Modelling Transfers

Modelling Comfort

Modelling Individual Preferences

Modelling Travel Strategies

Case Study: Santiago, Chile

Choice-Set Generation

Model Specification

Estimation Results

References

Author Biography

PART 2: COMBINING SMART CARD DATA WITH OTHER DATABASES

Combination of Smart Card Data with Person Trip Survey Data

Introduction

Exploration of Smart Card Data Set Using Visualization

Interpretation of Features of Smart Card Data Set

Interpretation of Features Using Data Fusion

Model

Schema of Smart Card Data and Person Trip Survey Data

An Overview of Data Fusion Method

Formulation of Naïve Bayes Probabilistic Model

Estimation of Probability Functions

Empirical Analysis

Data Sets

Validation with Person Trip Survey Data

Application to Data Mining of Smart Card Data

References

Author Biography

A Method for Conducting Before-After Analyses of Transit Use by Linking Smart Card Data and Survey Responses

Introduction

Literature Review

Background

Data Collection

Survey Content

Methodo

The Intervention: Availability of Real-Time Information

Condition 1: Panel Eligibility

Condition 2: Completeness and Uniqueness (One Smart Card = One Person)

Condition 3: Congruence (That Smart card = That Person)

Evaluation of the Intervention

Difference of Mean Differences

Regression Analysis

Areas for Improvement and Future Research

Conclusion

References

Author Biography

Multipurpose Smart Card Data: Case Study of Shizuoka, Japan

Introduction

Multipurpose Smart Cards

Case Study Area and Smart Card Data Overview

Shizuoka and Shizutetsu

Multipurpose Smart Card "LuLuCA"

Overview of Collected Data Stated Preference Survey on Sensitivity to Point System

Survey Structure and Hypotheses

Descriptive Survey Results

OLM and MNL Analysis

References

Author Biography

Using Smart Card Data for Agent–Based Transport Simulation

Introduction

User Equilibrium and Public Transport in MATSim

CEPAS

Suitability of Using CEPAS Data to Describe Public Transport Demand

Combining Agent-based Transport Simulation and CEPAS Data

Method

Reconstruction of Bus Trajectories

Generation of a Public Transit Schedule

Generation of Public Transport Trips

Simplification of the Network and Mobility Simulation

Speed Regression Model

Dwell Time Model

Validation and Performance

Speed

Headways, Dwell Times and Bus Bunching

Passenger Travel Time Measures

Application

Impact on Bus Bunching

Excess Waiting Times

References

Author Biography

PART 3: SMART CARD SATA FOR EVALUATION

Smart Card Data for Wider Transport System Evaluation

Introduction

Level of Service Indicators

Application to Santiago

Global Indicators

Indicators at the Municipality Levels

Indicators at Zone Level

Indicators at the Avenue Level

Bus-stop-level Indicators

Indicators at a Specific OD Pair (i.e., Trip) Level

References

Authors Biography

Evaluation of Bus Service Key Performance Indicators using Smart Card Data

Introduction

Background

Performance Indicators

Destination Estimation Algorithm

Information System

KPI Assessment

Error Detection

KPI Calculation Framework

Some Examples

Commercial Speed and Average Trip Distance and Duration

Passenger-kilometres, Passenger-hours

Load Profile

Service Variability

Service Fit

Schedule Adherence

Fare Evasion

Conclusion

Limitations and Challenges

Perspectives

References

Author Biography

Ridership Evaluation and Prediction in Public Transport by Processing Smart Card Data: A Dutch Approach and Example

Introduction

Smart Cards and Data

Smart Card Data Applications

The Dutch Smart Card System: OV-Chipkaart

Dutch Smart Card Data

Predicting Ridership by Smart Card Data

Introduction

Deriving OD Demand from Smart Card Data

Elasticity Model

Incorporating Comfort Impacts

Case Study: The Tram Network of The Hague

Introduction

Evaluation

Predicting

Reflection

References

Author Biography

Evaluation of Bus Stop Conditions Using a Combination of Probe Data and Smart Card Data

Introduction

Previous Tracking Data Research in Japan and the Positioning of this Study

Development of Evaluation Measures

Procedure for Obtaining Evaluation Measures

Saitama City Case Study

Saitama City

Overview of Tracking Data Use

Results and Discussion

References

Author Biography

Conclusions: Opportunities Provided to Transit Organizations by Automated Data Collection Systems, Challenges and Thoughts for the Future

Automated Data Collection Systems (ADCS)

Automatic Vehicle Location Systems (AVL)

Automatic Passenger Counting Systems (APC)

Automatic Fare Collection Systems (AFC)

Other Pertinent Data Systems

A Conceptual Framework for ADCS in a Transit Organization

ADCS and Key Transit Organization Functions

Analytic Framework

Challenges

Challenges Specific to AFC Data

Other Challenges Related to ADCS (including AFC data)

An Unexplored Area for Research Using Smart Card Data: Elasticities and Pricing Strategy

Conclusions: Looking to the Future

Subject Categories

BISAC Subject Codes/Headings:
POL002000
POLITICAL SCIENCE / Public Policy / City Planning & Urban Development
TEC008000
TECHNOLOGY & ENGINEERING / Electronics / General
TEC009160
TECHNOLOGY & ENGINEERING / Civil / Transport