Inter-vehicle communication of warning information: an experimental study

Abstract

In this paper, we show experimentally the feasibility of intervehicle communication of warning information. Warning messages convey significant information that might improve the safety of drivers and passengers. Intervehicle communication can be achieved by the detection of important events through a vision-based detection module, and sharing them between vehicles using a transmission module. In this paper, we developed a testbed that considers both modules in order to detect, recognize and share relevant information, such as traffic signs. To the best of our knowledge, our architecture is the first that combines detection and transmission of messages in the same platform. We detect traffic signs as blobs using the Maximally Stable Extremal Regions (MSER) algorithm, and we recognize them using Random forest classifiers. In the transmission module, we used a simplied broadcasting mechanism that avoids the use of handshaking to establish a communication. In order to assess our system, a set of indoor and outdoor experiments are considered.