U & I Aware

Ph.D Research

A Context-Aware Framework for Intersection Collision Avoidance

Start Date: 1 Jun 2005

Completion Date: 8 August 2008

Final Thesis Download

Flora Dilys Salim

Abstract

The crash rate in road intersection demonstrates the need for a fast and accurate collision detection system. Ubiquitous computing research provides a significant opportunity to develop novel ways of improving road intersection safety. The existing intersection collision warning or avoidance systems are mostly built to suit a particular intersection. We suggest that an intersection collision detection system should be able to adapt to different types of intersections by acquiring the collision patterns of the intersection through data mining. Collision patterns that are specific to that intersection are stored in a knowledge base to select vehicles which are exposed to a high risk of collision. This algorithm increases the speed of collision detection calculation, as detection is not applied on all possible pairs in an intersection. The performance and accuracy of the algorithm are evaluated. This evaluation is done on a developed simulation test bed.

Flora has moved to RMIT and this website is no longer maintained.