Page 260 - Big Data Analytics for Connected Vehicles and Smart Cities

240 Big Data Analytics for Connected Vehicles and Smart Cities Benefit and Cost Estimation For Smart City Transportation Services 241

Figure 11.6 Assumed configuration for integrated electronic payment systems.

The in-vehicle subsystems for private cars, urban delivery vehicles, and
rental cars/taxis are assumed to be identical and consist of a hardware and soft-
ware environment that will support management of the electric vehicle charg-
ing system and the interaction between the end vehicle subsystem and the road-
side electric vehicle charging subsystem. It is assumed that in addition to energy
transfer, data transfer is also supported regarding the performance of the vehicle
and the battery. This could also be considered as an opportunity to supply the
driver with travel information and extract probe vehicle data from the subsys-
tem in the vehicle.

Smart Land Use

Figure 11.8 illustrates the assumed configuration for the smart land-use system.
The smart land-use system is assumed to be comprised of nine separate ele-
ments: a private car in-vehicle subsystem, an urban delivery vehicle in-vehicle
subsystem, a rental car/taxi in-vehicle subsystem, a smart land-use planning
data and analytics subsystem, a movement analytics subsystem, a retail sub-
system, a smart factory subsystem, an education subsystem, and a healthcare
subsystem. The in-vehicle subsystems are assumed to be identical for all types
of vehicles. The smart land-use planning data and analytics subsystem is com-
prised of a hardware and software environment capable of handling data man-