Vehicular network rerouting autonomy with a V2V, I2V, and V2I communication matrix classification

Abstract

Intelligent Transportation Systems allow for broad implementation approaches regarding the distribution of data and the processing of that data for use in a particular framework. In this paper, we provide an analysis and approach in describing methods of vehicular network autonomy incorporating concepts that include V2I, I2V and V2V communications. Specifically, we provide validity to concepts that are taken for granted by providing simulations to support these considerations. We also provide a discussion of the architecture implementations that define these concepts that capture classification methods negating the problem with open interpretation as to where the data are being collected from as well as being processed. We provide a refinement within the scope of ITS by systematically classifying the roles and interaction between processing and data collection. Furthermore, we then utilize key classifications of processing and data collection that includes either a centralized or distributed framework approaches. These approaches illustrate how vehicles can be used to accomplish dynamic rerouting by applying knowledge of network state but also network composition to achieve lower travel times when incidents occur.