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148 Big Data Analytics for Connected Vehicles and Smart Cities The Practical Application of Analytics to Transportation 149

7.15 Transit Management Analytics and Their Practical
Application

Transit management involves the application of advanced technologies to tran-
sit fleet management, the delivery of passenger information, and the support for
electronic payment services for transit. Table 7.4 captures candidate analytics
that can be used for transit management applications. Table 7.4 also contains
a column that provides a brief overview of how these analytics can be used in a
practical situation.

7.16 Performance Management—What Is It?

Performance management involves the measurement of performance param-
eters for various aspects of transportation service delivery, followed by the de-
velopment of insight and understanding based on these measures. The overall
objective is to improve transportation service delivery based on a detailed un-
derstanding of how things work and prevailing operating conditions. A com-
prehensive approach to performance management would address each stage of
the transportation delivery process, listed as follows:

Table 7.4
Candidate Analytics for Transit Management
Candidate Analytics Application Notes
Travel times for each passenger Makes use of movement analytics; travel times for each
passenger on the transit network are measured and analyzed.
Travel time variability for each As above focusing on travel time variability for each passenger.
passenger
Bus utilization This analytic can include the number of passengers per bus and
the miles traveled by the bus, so the hours of service and support
service optimization.
Revenue per bus This analytic makes use of data from the integrated payment
system to determine revenue per passenger in revenue per bus.
Passenger satisfaction index Makes use of social media analysis of passenger satisfaction; an
index can be developed that characterizes customer perception
of service levels.
Revenue per passenger Uses integrated payment system and movement analytics data
to determine the revenue per passenger for service and payment
structure optimization.
Revenue per route Uses integrated payment system data and revenue per route
service and payment structure optimization.
Comparison between schedule Schedule variation analytic is determined by comparing the
data and actual performance scheduled to the actual performance as a measure of system
data reliability.