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

10.4 Concepts

The concepts discussed in the following sections were defined to illustrate the
application of data analytics techniques to transportation.

Freeway Speed Variability Analysis
This concept entails the application of big data and analytics techniques to un-
derstanding speed variability in bottleneck formations on a major freeway. This
concept was applied to a major urban freeway in close cooperation with a large
Department of Transportation in the United States. The experience provided
some rich insight into the use of analytics for traffic engineering under freeway
conditions and yielded some lessons regarding the data quality and the analytic
discovery process. This concept has the largest amount of documentation in
this chapter, because of this practical experience.

Smart City Accessibility
This concept entails adopting an analytics approach to defining the ease or dif-
ficulty of movement from residential zones to work, healthcare, and education-
al opportunity zones. It was developed in close cooperation with a city in the
United States, implementing a smart city initiative. One of the core objectives
of the smart city initiative is to improve accessibility to jobs, healthcare, and
education opportunities. The concept is at an advanced stage of development
but has not yet been implemented.

Toll Return Index
This involves the creation of a composite toll return index that communicates
the benefits delivered by a toll agency in return for the toll paid. The toll paid
is divided by the total benefits delivered to create the index. The benefits are
comprised of three primary components: safety, efficiency, and user experience.
The concept has been discussed and evaluated by both current and former ex-
ecutive-level toll management, but it is still in the course of being implemented
by toll agencies.

Arterial Performance Management
This concept involves the application of analytics techniques related to traffic
turbulence to determine the technical performance of arterial corridors and
networks. It is supplemented by social sentiment analysis and context-specific
keywords analysis of Twitter feeds to determine driver perception in addition to
technical performance of the corridor.