Vehicles in Internet of Vehicles (IoV) exchange
information about location, environment, infotainment, as well
as social information with other units via vehicular communication
networks. This makes IoV with key social entities in the
human-vehicle-infrastructure-roadside units (RSU) as integrated
intelligent transportation systems. Therefore, by identifying the
cyber-physical-social features of IoV and presenting its complexity
issues of both engineering and social dimensions, this
paper proposes and introduces the concept, architecture, and
applications of Parallel Internet of Vehicles (PIoV). Three main
components of PIoV are demonstrated, which are artificial IoV
to learn and describe the physical IoV, computation experiments
to evaluate and predict the consequences and values of driving
strategies, and parallel execution to prescribe the operation of
the physical IoV. PIoV makes it possible to achieve safe, smart,
effective, and efficient transportation management and control.
The final objective of PIoV is to equip IoV with descriptive,
predictive, and prescriptive intelligence based on the parallel
intelligence approach.