The spreading of messages in a vehicular network is an important task and finds many applications in Intelligent Transportation Systems (ITS). A common problem to this direction is to select an appropriate set of vehicles that on behalf of a sender will further rebroadcast the message and reduce redundant retransmission. Of particular interest is the use of social inspired metrics to identify potent vehicles which can set the right path for the spreading of messages and cover a wide range of a vehicular network. In this work we propose a novel approach for selecting vehicles based on the
Probabilistic Control Centrality (pCoCe)
, which accounts for the number of directed and diverse paths emanating from each individual vehicle. We evaluated our approach and compared with the standard IETF,
Optimized Link State Routing Protocol (OLSR)
. Our experimental results show that
outperforms its competitor in various network conditions by at least 10%.