DocumentCode :
2758061
Title :
U&I Aware: A Framework Using Data Mining and Collision Detection to Increase Awareness for Intersection Users
Author :
Salim, Flora Dilys ; Loke, Seng Wai ; Rakotonirainy, Andry ; Krishnaswamy, Shonali
Author_Institution :
Caulfield Sch. of Inf. Technol., Monash Univ., Clayton, VIC
Volume :
2
fYear :
2007
fDate :
21-23 May 2007
Firstpage :
530
Lastpage :
535
Abstract :
An intersection safety system should adapt to the particular characteristics that identify an intersection, by mining traffic and collision data. Given the large amount of sensor data that are obtained for intersections and from sensor-equipped cars, analysis and learning of such data is essential. This paper presents a new method to improve safety at intersections using a combination of a mathematical based collision detection algorithm and data mining. A number of scenarios at a simulated intersection are explored with encouraging results from our data mining implementation. The results suggest that our approach can help improve situation awareness and automate understanding of intersections, which, in turn, can be used to increase safety at intersections.
Keywords :
automobiles; collision avoidance; data mining; learning (artificial intelligence); road accidents; road safety; road traffic; traffic information systems; U&I aware; collision detection algorithm; data learning; intersection collision warning system; intersection safety system; intersection user awareness; sensor data; sensor-equipped car; traffic data mining; ubiquitous intersection awareness; Alarm systems; Collision avoidance; Cooperative systems; Data mining; Road accidents; Road safety; Robot sensing systems; Robotics and automation; Transportation; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference on
Conference_Location :
Niagara Falls, Ont.
Print_ISBN :
978-0-7695-2847-2
Type :
conf
DOI :
10.1109/AINAW.2007.360
Filename :
4224158
Link To Document :
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