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130 Big Data Analytics for Connected Vehicles and Smart Cities What Are Analytics? 131

Effective transportation management must address the same challenges
as defined under transportation governance. Services are currently delivered by
a range of autonomous transportation agencies, with the exception of a few of
the largest cities in the world, where a single unitary transportation authority
has been established. Examples include Seoul and London. As smart cities will
face the additional challenge of integrating other services, such as smart energy
and smart places to live and work, with transportation, there may be a need to
revisit transportation management models within smart cities.
Traveler information services within a smart city will involve the delivery
of decision-quality travel information to both citizens and visitors. A traveler
satisfaction index could be used to measure citizens’ and visitors’ perceptions of
the quality of traveler information services. A decision-quality information in-
dex could also be used to characterize the effectiveness of the travel information
in terms of change and efficient use of the services within the smart city. This
type of sophisticated decision-quality information delivery could be viewed as
the equivalent of a user manual for the smart city transportation network, or
as a soft form of transportation management that influences user behavior and
makes system use more effective.

Urban Analytics

Urban analytics are used to characterize trends, patterns, and insights gained
from the big data set collected by a smart city. However, this does not mean
that we should not apply analytics to the performance of the analytics. Suitable
analytics to characterize the performance of urban analytics would be the num-
ber of analytics in use, the value of services managed by analytics, and money
saved through efficiencies gained by analytics. The total cost of applying urban
analytics could also be compared to the value delivered and the money saved
through the use of the analytics.
The definition of costs and benefits for smart cities, based on prior imple-
mentation experience, is a very important aspect of the business and financial
aspects of the smart city. The identification of early winners along with the
quantification and estimation of the value that can be realized is central to the
justification of further investment in smart city analytics. This is discussed in
more detail in Chapter 11.
Urban Automation

Urban automation includes the use of automated vehicles for transit, freight,
and private vehicle travel. The main reasons to apply urban automation to the
smart city would be to achieve benefits in terms of safety, efficiency, and en-
hanced user experience. Therefore, analytics could be defined for each category.
With respect to safety, the number of crashes avoided or mitigated compared
to the investment in urban automation would yield insight into improvements