A cluster based architecture for intersection collision avoidance using heterogeneous networks

With the popularity of wireless devices, the possibility of implementing vehicular safety applications has been studied for years in the context of vehicular ad-hoc networks. Dedicated Short Range Communication (DSRC) is designed to serve the needs of vehicular safety applications. However, DSRC does not offer good enough coverage and range around intersections in urban areas for certain applications such as intersection collision avoidance. Considering these drawbacks, LTE, an advanced cellular communication technology, is proposed as an alternative to DSRC. One problem is LTE bandwidth capability to support regularly transmitted cooperative awareness messages. In this paper, we propose a cluster based architecture using both Wi-Fi and LTE channels to accomplish this task. In our architecture, Wi-Fi peer to peer channels are used for cluster formation while LTE channels are used for transmitting Cooperative Awareness Messages (CAMs). A clustering algorithm specifically designed for intersection collision avoidance service is proposed in this paper. In addition, a channel allocation algorithm is applied to reduce the interference of Wi-Fi channels between different clusters. Simulations show that CAM traffic can be efficiently supported in this architecture.