Context-Aware ubiquitous data mining based agent model for intersection safety

Authors:
Flora Dilys Salim;Shonali Krishnaswamy;Seng Wai Loke;Andry Rakotonirainy
Affiliations:
Caulfield School of Information Technology, Monash University, Caulfield East, VIC, Australia;Caulfield School of Information Technology, Monash University, Caulfield East, VIC, Australia;Caulfield School of Information Technology, Monash University, Caulfield East, VIC, Australia;Centre for Accident Research and Road Safety Queensland, Queensland University of Technology, Carseldine, QLD, Australia
Venue:
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Year:
2005

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Abstract

In USA, 2002, approximately 3.2 million intersection-related crashes occurred, corresponding to 50 percent of all reported crashes. In Japan, more than 58 percent of all traffic crashes occur at intersections. With the advances in Intelligent Transportation Systems, such as off-the-shelf and in-vehicle sensor technology, wireless communication and ubiquitous computing research, safety of intersection environments can be improved. This research aims to investigate an integration of intelligent software agents and ubiquitous data stream mining, for a novel context-aware framework that is able to: (1) monitor an intersection to learn for patterns of collisions and factors leading to a collision; (2) learn to recognize potential hazards in intersections from information communicated by road infrastructures, approaching and passing vehicles, and external entities; (3) warn particular threatened vehicles that are approaching the intersection by communicating directly to the in-vehicle system.