Public Transport Planning with Smart Card Data

Fumitaka Kurauchi, Jan-Dirk Schmöcker, Fumitaka Kurauchi, Jan-Dirk Schmöcker

• Publisher: CRC Press
• Year: 2017
• ISBN:
  9781315353333
• Edition: 1
• Topic: Politics & International Relations
• Subtopic: City Planning & Urban Development
• Index: Politics & International Relations

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.

Chapter

1

An Overview on Opportunities and Challenges of Smart Card Data Analysis

J.-D. Schmöcker^1,*, F. Kurauchi² and H. Shimamoto³

ABSTRACT

In this chapter, an overview on opportunities and challenges for the use of smart card data for public transport planning is provided. As an introduction to the topic examples of customer services that have become feasible due to smart cards are discussed. These include smart card as a general payment method for a wide range of services, pricing caps as well as “loyalty points”. For operators, smart cards provide opportunities such as revised fare structure. The focus of this chapter and this book in general is on the benefits that emerge through better understanding of customer behavioural patterns for short and longer term service planning. This chapter also points out that in practice smart card data are though not yet as much used as one might expect given these opportunities. As explanation for this challenges connected to big data issues, privacy and missing information are discussed. The chapter concludes by providing an overview on the contributions in this book.

1. INTRODUCTION

Automatic Fare Collection through “smart cards” is becoming a standard in most advanced public transport networks of major cities around the world. Using such cards has an advantage for users as well as operators. Whereas smart cards are mainly increasing convenience for travellers, operators value in particular the reduced money handling fees. Smart cards further make it easier to integrate the fare systems of several operators within a city and to split the revenues.

These are the primary reasons that led in many cities to invest in the introduction of smart card systems. The focus of this book is though the secondary benefits that are obtained through smart card data. Smart card data are increasingly recognised as a rich data source to better understand demand patterns of passengers. As this book will discuss, origin-destination matrices, routes and activities all can be inferred from this data. Furthermore, smart card data can be used partly as replacement of other data sources to collect evaluation measures of the service quality. That is, the time and the location stamps of the records allow the operator to measure, for example, actual versus the scheduled arrivals of the buses.

Before discussing the analysis options in detail the following section will give an overview on the spread of smart card systems across the world, including the differences in the collected data. Recognizing these differences is not only important to understand the analysis potential but also to understand the challenges an analyst faces. These challenges together with a discussion on actual usage of smart card data in practice is the topic of Section 4.

Section 5 then provides an overview on the contents of the following chapters in the book. The primary purpose of the book is to provide an overview on smart card data analysis opportunities and how challenges are overcome. Evidently, considering that the literature on smart card data is rapidly growing, the book does not claim completeness. The section will hence briefly discuss further data analysis options and examples which could be perceived as important but missing in this book before concluding.

2. SMART CARD SYSTEMS AND DATA FEATURES

The numbers of smart cards are increasing year by year, for example Wikipedia lists more than 350 smart card systems all over the world covering all continents. As this book focuses on smart card systems that have their primary application payment for public transport, one needs to recognise that smart cards are in use for a wider range of applications. An important development is therefore the integration of different applications into smart card systems.

Through the worldwide spread of smart cards, international standardization, which define the signal frequency and the data transmission speed, has progressed. For the contactless cards there are several standards that cover the lower levels of interface between cards and terminals and mainly three types of standard, referred to as Type A, Type B and FeliCa, are widely prevalent. For transit smart cards, either Type-A or FeliCa systems are adopted. Type-A systems are common all over the world since they could be introduced with low cost. The biggest advantage of the FeliCa system is the faster transmission speed. Due to this feature, FeliCa system cards prevail in many transit companies in Japan where it is essential to handle large amount of passengers in short time during the rush hours. For further detailed criteria of these standards, readers can refer to Pelletier et al. (2011). Table 1 shows information on the selection of noteworthy major smart cards that are issued mainly for the purpose of transportation fare collection. For users (and data analysts) the increasing standardization further means that not only the arrangement of same card usage for different operators becomes easier but also the usage of the same card in different cities. For example, in Japan since 2013 most of the smart cards from major public operators can be used across the country. The Netherlands is one of the first countries where a single smart card can be used throughout the country for local as well as long distance travel.

The important aspect for data analysis and transport demand management possibilities is whether the transactions are pre-paid (debit) or post-paid (credit). Although most of the smart card systems adopt the pre-paid system, an increasing number also offer post-payment systems, mostly not in replacement but in addition to pre-paid ones. This means, that, similar to credit cards, the total transportation fares accumulated over a month will debit from the bank account next month. The drawback of the post-payment system for the user is that it requires personal details and an application for qualification to get the cards. This means that it often takes a considerable amount of time until the cards are issued. However, the post-paid system cards also have some merits for the users. First of all, since the bank debits the fare later from the account, users do not have to worry about the remaining money on the card. Secondly, with personalized post-payment cards, loyalty schemes are more widely spread. One example is the “PiTaPa” card, which could be used for fare payment on most of the private trains and bus companies in the Kansai region of Japan. Operators utilizing PiTaPA offer different amount of discounts per journey and some set an upper limit for the fare-to-be paid for pre-registered origins and destinations by the users. For other (not pre-registered) journeys PiTaPa also offers discount based on how much fare the users have paid or how often the users have used PiTaPA for public transport during the previous month. Furthermore, some of the transit companies in Japan give points for the users based on the boarding history as well as the shopping history at the designated shops. In Chapter 7 this is further discussed with the help of an example of Shizutetsu Railway Co., Ltd., a private rail operator in Shizuoka, Japan. The cardholders can use these points for fare or shopping discounts in stores associated with the transport operator. Therefore, for demand management, in general post-paid systems are preferable. For the data analyst post-paid systems further mean that travel data and socio-demographic data required for registration can be obtained, though obviously privacy issues are a major concern for this.

Table 1 includes some additional observations on selected smart cards that appear noteworthy to us: The Octopus card was one of the early card schemes not only for transport but also in general promoting the usage of the card for different purposes, which is also included in the etymology of the card’s name. Nowadays, the card could be used for a variety of shopping including online purchases.

Table 1. Information on selected smart card systems

Name of Card	City and Country	Year of Introduction	Noteworthy Points (but not necessarily unique features of these cards)
Octopus Card	Hong Kong, China	1997	Various added functions, including payment at international chains such as Starbucks or McDonald’s. Currently replacement of 1st generation cards: 2nd generation cards allow, among others, online payment.
Suica	Various metropolitan areas in Japan	2001	The fare calculation is by one yen unit with the smart card whereas the fare calculation for paper-based tickets is by ten yen units. Mutual use of other smart cards such as ICOCA or PASMO.
Oyster Card	London, UK	2003	Paying by smart card is much cheaper than paper ticket; “daily cap” and “weekly caps” are implemented on smart cards.
T-money	Various metropolitan areas in Korea	2004	Over 100 million cards (accumulated) are allotting by now (Korea smart card, 2016). The system is also supplied to operators outside Korea. Chapter 3 shows an application of analysis with T-Money data from Seoul.
OV-Chip Card	Nationwide in the Netherlands	2005 (Rotterdam only)	Can be used for almost all public transport in the Netherlands, including local and long distance travel (see Chapter 12).
LuLuCa	Shizuoka, Japan	2006	Extensive loyalty point scheme to encourage usage of card for transit as well as for shopping (see Chapter 7).
Bip! Card	Santiago, Chile	2007	Bip! Card is the only allowed payment method on buses. (see Chapters 2 and 9)

Several operators have also been promoting the uptake of smart cards by providing cheaper fares compared to paper tickets. Noteworthy are the discounts provided in London, where paper tickets can be priced double compared to the payment by Oyster card. In Japan, generally no discounts are given for the usage of smart cards. Recently though, due to an increase in the VAT, there are small price differences between paper tickets and payments by smart cards. The increase in fares due to VAT raise is reflected accurate to 1 Yen for smart cards where paper tickets are rounded to the nearest 10 Yen. Such minor price differences are though unlikely to have an impact on travel decisions. More important might be the effect of “daily caps” or, recently, “weekly caps” that have been applied in London. These caps mean that the user does not have to decide in...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Preface
• 1. An Overview on Opportunities and Challenges of Smart Card Data Analysis
• Part 1: Estimating Passenger Behavior
• Part 2: Combining Smart Card Data with other Databases
• Part 3: Smart Card Sata for Evaluation
• Index