Collision avoidance tree networks

Directional collision avoidance in ad hoc networks

This paper analyzes the performance of directional collision avoidance schemes, in which antenna systems are used to direct the transmission and reception of control and data packets in channel access protocols based on four-way handshakes to try to avoid collisions. The first analytical model to consider directional reception and the possible difference in gain between omni-directional and dir...

Reactive Collision Avoidance using Evolutionary Neural Networks

Collision avoidance systems can play a vital role in reducing the number of accidents and saving human lives. In this paper, we introduce and validate a novel method for vehicles reactive collision avoidance using evolutionary neural networks (ENN). A single front-facing rangefinder sensor is the only input required by our method. The training process and the proposed method analysis and valida...

Using Heterogeneous Networks for Intersection Collision Avoidance

Vehicular Networks for Collision Avoidance at Intersections

A substantial fraction of automotive collisions occur at intersections. Statistics collected by the Federal Highway Administration (FHWA) show that more than 2.8 million intersection-related crashes occur in the United States each year, with such crashes constituting more than 44 percent of all reported crashes [12]. In addition, there is a desire to increase throughput at intersections by redu...

Beacon Frame Collision Avoidance Scheduling in Cluster-tree Wireless Sensor Networks

In beacon-enabled mode, beacon collision is a significant problem for the scalability of cluster-tree wireless sensor networks. In this paper, multichannel window scheduling (MCWS) is proposed to prevent beacon collisions and provide scalability. It enables large-scale wireless sensor networks based on a cluster tree to be scalable and effectively constructed.