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196 Big Data Analytics for Connected Vehicles and Smart Cities Practical Applications and Concepts for Transportation Data Analytics 197

Figure 10.1 Word cloud for Chapter 10.

10.2 Chapter Word Cloud

A word cloud, shown in Figure 10.1, has been prepared for this chapter to pro-
vide an overview of content.

10.3 Introduction

This chapter describes implementations and concepts for the application of
analytics to transportation. One of the challenges in explaining big data and
analytics in transportation is to show a strong connection between user needs
or the real situation to be addressed, with the capabilities of data science and
analytics. While it is likely that data science and analytics can address almost
every transportation problem, experience has shown that most progress is made
in the application of data science to transportation when a narrower focus is
placed on specific areas of need. To narrow down the focus to the practical
application of big data and analytics techniques, five concepts have been iden-
tified: freeway speed variability analysis, smart city accessibility analysis, toll
return index for toll road performance, arterial performance management, and
decision support for bus acquisition. The concept of freeway speed variability,
which was implemented in cooperation with a client, has been the subject of
extensive development and application. In the other cases, the concepts have
been developed in coordination with a range of potential users but have not
yet been implemented. In any event, all the concepts shed significant light on
how data science can be applied to practical needs within the smart city and
transportation realms.