Vehicular Ad hoc Networks


Vehicular Ad Hoc Networks

Vehicle-to-Vehicle (V2V) communication is a promising research area that can affect different areas, from road safety, to driving comfort, entertainment, ubiquitous connectivity, and so on. To provide a communication platform for safety critical applications, as well as for added value services, QoS properties like medium access delay, reliability, latency, packet delivery ratio and spatial information redundancy are fundamental.

Although some recent research projects have advanced the state of the art in this area, many problems still remain to be solved. In particular, the optimization of the systems to the context of use (e.g., including the vehicle speed and density, interference, noise, application requirements, etc.) is still an open research problem.

In this context, our activity is aimed at designing and analyzing cognitive optimization techniques for automotive communication. We adopt an divide et impera approach: first break down the system into smaller parts easier to model and analyze; second, resort to machine learning and artificial intelligence techniques to investigate and control the interactions among those basic elements.

Some of the issues that we consider in our research follows:

  • MAC/PHY parameter optimization in the presence of (group) mobility
  • Reconstruction & representation of road context position, speed and direction of vehicles in a given area
  • Context-driven protocol optimization
  • Dynamic management of heterogeneous interfaces maintain connectivity with time-varying inter-vehicle distances

People involved
Andrea Zanella