Urban traffic characterization for enabling Vehicular Clouds

The accelerated growth of applications and services in intelligent transportation systems (ITS) are driven by interests from the public and private sectors. The intent to utilize the onboard resources, along with the advanced methods of managing the available computing capabilities in the conventional cloud, has led to the high popularity of Vehicular Clouds. Likewise in Vehicular Networks, vehicles provide the building blocks for forming these particular clouds, which can enable a large number of applications and services that can benefit the whole transportation system, as well as the drivers, passengers, and pedestrians. However, due to its high mobility, Vehicular Clouds show several inherent challenges, which increase complexity and restrict the design of solutions. Determining the number of vehicles and their time of availability in a given region through a model works as a critical stepping stone for enabling vehicular clouds, as well as any other system involving vehicles moving over the traffic network. Therefore, by implementing proper traffic models, we present a comprehensive stochastic analysis about the distribution of the number of vehicles inside a road segment in this paper. According to real parameters, we show that certain classes of applications are feasible even for highly mobile scenarios.