Although the spatial accuracy of bus boardings is
currently limited to the route level in the London
smartcard data, the identification of complete passenger
journeys using elapsed time threshold assumptions
certainly provides new, relevant information about
passenger demand and transfers that supports a more
integrated evaluation of the public transport network.
However, there are some challenges related to
implementing a new information system based on
smartcard data.
An important aspect of implementation is the
availability of data across days.Any given route, station or
transfer combination in the system is likely to vary with
time so the implementation of a smartcard database
system for bus network planning would need to allow
for queries across multiple days, and, ideally, across time
periods. Due to relatively low passenger volumes on
some routes, in a large network the best compromise
might be for all smartcard journey stages to be used for
any given day, but that complete journeys datasets be
created for two weeks out of each quarter or some
other sampling method that will ultimately limit the
amount of data processing and storage required.
Another important consideration relates to
institutional structure and information flow. There are
already numerous data systems in use at most transport
agencies.These generally require substantial resources to
maintain, and have been created for specific purposes.
Rationalisation of information systems and procedures is
essential to the process of developing a new smartcard
data system.
Validation against survey data is also important, both
to evaluate survey data and to confirm transfer time
assumptions and conclusions from smartcard data. In the
long term, availability of smartcard data may lead to
revised, potentially more targeted survey sampling
techniques.
Smartcard data yields valuable information about actual
travel behaviour over time and potentially real-time
information about network usage. On the other hand, as
with any system, smartcard data has its limitations. Contrary
to survey data, it does not provide socioeconomic
information about the cardholders, nor details of their
journey purpose. Information about people's choice
between public transportation and other modes is also
lacking. Finally, the volume of data available poses
some data management challenges and barriers to
implementation as part of a day-to-day planning system.
Despite these limitations, the breadth of smartcard
data would be prohibitively expensive to replicate with
any travel survey. Moreover there may be opportunities
in the future to complement smartcard data with other
new systems, for example TfL's `iBus' system that uses
GPS to locate buses on the network in real-time. This
study has provided an initial exploration of potential
applications of smartcard data to bus network planning
but there are many exciting opportunities for further,
practice-orientated research.
Modal patterns of journeys on Route 221 with Underground
interchange
Mode 1 Mode 2 Mode 3 Share of All Journeys on Route 221, %
U B � 6
B U � 5
B U B 3
U B B <1
B B U <1
U = underground
B = bus
Table 5
Daily interchange volumes between Route 221 and top three
Underground stations
Underground station Daily Interchanges with Route 221
Bounds Green 1,057 74%
Wood Green 255 18%
Turnpike Lane 110 8%
Table 6
Top 10 routes in journeys on Route 293
Route no Share of top 10 routes in Station intersection Road intersection with
journeys on route 293, % with route 293 route 293
93 29 Morden Stonecot Hill*
213 16 � Malden Road/London Road
118 11 Morden �
163 10 Morden Hillcross Avenue*
151 8 � Malden Road/London Road
80 5 Morden �
164 5 Morden �
201 5 Morden �
406 5 Epsom rail Epsom Road*
157 5 Morden �
* Indicates shared corridor with Route 293
Table 4
Probable return journeys on case study routes
Route no Passengers with 2+ daily journeys Share of all journeys on
on route, % route, %
293 34 52
221 40 60
69 28 47
Table 3
CILT TRANSPORT
29
www.ciltuk.org.uk
Top five stations in journeys on Route 69
Underground station Share of top five stations, %
Leyton 43
Stratford 21
Walthamstow Central 12
Plaistow 12
Canning Town 11
Table 7

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