Page 28 - Big Data Analytics for Connected Vehicles and Smart Cities

8 Big Data Analytics for Connected Vehicles and Smart Cities Introduction 9

have on transportation. The big data and analytics aspects of connected vehicles
include managing the volume of data coming from the vehicle, conducting
analytics in the back office, and then projecting those analytics and results back
to drivers and other people associated with traffic and transportation operations
and management. Chapter 4 also explains autonomous vehicles, with feature
the ability to operate without a driver.

Chapter 5
Chapter 5 discusses the concept of a smart city. Smart City initiatives have com-
menced in many cities around the world. With respect to the United States, a
recent smart city challenge issued by the U.S. Department of Transportation [2]
attracted 78 responses from U.S. cities, with the city of Columbus, Ohio, se-
lected as the winning applicant. It is obvious that smart cities go beyond trans-
portation and incorporate social services, social networks, energy grids, and
smart places to live and work. Chapter 5 aims to take a close look at smart cities
from a transportation perspective, especially as one of the core features of the
smart city will be extensive use of big data and analytics. Chapter 5 also briefly
outlines other services that could be expected in a smart city, showing how big
data and analytics along with transportation services fit into the bigger picture.

Chapter 6
Chapter 6 explains data analytics, with particular attention to its transporta-
tion aspects. Good analytics go beyond even world-class reporting and provide
transportation professionals with the opportunity to influence the performance
of their organizations. Accordingly, Chapter 6 discusses the nature of data ana-
lytics and presents a few examples from outside of transportation to afford
readers a solid understanding of this topic.

Chapter 7
Chapter 7 builds on Chapter 6 by detailing information regarding analytics that
can be applied to transportation. The intention is to bring the term analytic to
life from a transportation perspective. Accordingly, Chapter 7 includes descrip-
tions of analytics that have been applied and analytics that could be applied in
the future. These are analytics that can be directly related to safety, efficiency, or
user experience improvements. Chapter 7 also discusses the relevance of these
applications to different aspects of smart city transportation such as planning,
operations, and maintenance.
Chapter 8
Chapter 8 adopts the system engineering term use cases to capture systematically
what can be done with big data and analytics. In addition, Chapter 8 presents a