Page 253 - Big Data Analytics for Connected Vehicles and Smart Cities

234 Big Data Analytics for Connected Vehicles and Smart Cities Benefit and Cost Estimation For Smart City Transportation Services 235

similar operating costs to the four-wheel-drive SUV at the highest end of the
AAA cost spectrum. This may be conservative, as the number of stops incurred
by an urban delivery truck may well increase operating cost. Cost of emissions
for private cars and urban trucks were obtained from nationally published fig-
ures [5]. The value of travel time in dollars per hour [6] and the average time
spent traveling per person per day [7] were derived from published data. The
total cost of ownership of 1 TB of data per year was derived from a published
white paper [8].
Table 11.5 illustrates the estimation of the number of devices in the smart
city. Notes are provided to explain the assumptions on which the estimates are
based.
The basis on which these numbers were derived is discussed as follows.
For freeways, arterials and urban surface streets, per capita estimates were de-
veloped from national figures [9] and proportioned for a smart city population
of 1 million people. Bus routes were derived from published data from the
Chicago Transit Authority website [10], proportioned according to population.
Table 11.6 provides details of smart city characteristics used in cost es-
timation. These have either been assumed or derived from the national data
shown in Table 11.4.
The addressable population is assumed to be 1 million people. Note that
this does not include the very young and the very old and is assumed to rep-
resent the traveling population. Number of buses was derived from published
data from the Chicago Transit Authority regarding the number of buses and
population served, proportioned according to population. This is likely to cre-
ate a conservative estimate as CTA makes use of commuter rail and may be
less dependent on buses than a typical city. CTA was used as a data source as
full-service details regarding the number of buses, route miles, and population
served are available in a single table on the CTA website [10]. It is assumed that
the model smart city does not feature light rail transit or commuter rail.
The number of private cars within the smart city was derived from na-
tional figures [11] proportioned according to the smart city population.
Annual vehicle miles traveled per capita [12], proportion of VMT by pri-
vate car, and proportion of VMT by truck were derived from national figures
[13], proportioned according to the smart city population.
The number of urban delivery vehicles in the smart city is assumed to be
an additional 10% of the private car total.
The number of deliveries per day in the smart city is a conservative estimate.
The number of taxis in the smart city is derived from national statistics
[14], proportioned according to population.
Rental cars and parking spaces were also subject to the same treatment
using national figures for rental cars [15] and parking spaces [16], proportioned
according to population.