U&I aware: a framework using data mining and collision detection to increase awareness for intersection users

Salim, F, Loke, S, Rakotonirainy, A and Krishnaswamy, S 2007, 'U&I aware: a framework using data mining and collision detection to increase awareness for intersection users', in Leonard Barolli, Ruppa K. Thulasiram, Arjan Durresi (ed.) Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), vol 2, Niagara Falls, Ontario, Canada, May 21-23 2007, pp. 530-535.


Document type: Conference Paper
Collection: Conference Papers

Title U&I aware: a framework using data mining and collision detection to increase awareness for intersection users
Author(s) Salim, F
Loke, S
Rakotonirainy, A
Krishnaswamy, S
Year 2007
Conference name '07)21st International Conference on Advanced Information Networking and Applications Workshops (AINAW
Conference location Niagara Falls, Ontario, Canada
Conference dates May 21-23 2007
Proceedings title Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), vol 2
Editor(s) Leonard Barolli, Ruppa K. Thulasiram, Arjan Durresi
Publisher IEEE
Place of publication USA
Start page 530
End page 535
Total pages 6
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.
Subjects Distributed Computing not elsewhere classified
Technology not elsewhere classified
DOI - identifier 10.1109/AINAW.2007.360
Copyright notice © 2007 IEEE
ISBN 9780769528472
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