Forecasting Short Term Traffic Conditions using Vehicular Ad-hoc Network

Abstract

Vehicular ad hoc networks (VANETs) represent a particularly challenging class of mobile ad-hoc networks (MANETs) which enable vehicles to communicate with each other. In VANETs, vehicles are restricted in their range of communication and tend to move in an organized pattern. A virtual stationary automaton (VSA) is a static infrastructure consists of fixed, timed virtual machines, and they are tiled over the entire plane. Our project can be categorized as an information dissemination system which applies in VANETs by providing surrounding information to road user. We use the pre-defined VSAs to predict traffic condition in each VSA region in a short given term. The challenges are how to get the information to predict and how to analyze the data. We implemented new message in VSA deployment and studied the performances of our design in a mathematic way. The application domains of our project include dynamic geographical information system (GIS) and improved communication networks.