Collision Pattern Modeling and Real-Time Collision Detection at Road Intersections

Publication Year: 2007 Publication Type : ConferenceProceeding


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 bed and the results are presented.


    author = {Flora Dilys Salim and Seng Wai Loke and Andry Rakotonirainy and Bala Srinivasan and Shonali Krishnaswamy},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    booktitle = {IEEE Intelligent Transportation Systems Conference, ITSC 2007, Seattle, WA, USA, 30 September-3 October 2007},
    doi = {10.1109/ITSC.2007.4357693},
    pages = {161--166},
    publisher = {IEEE},
    timestamp = {Wed, 16 Oct 2019 14:14:57 +0200},
    title = {Collision Pattern Modeling and Real-Time Collision Detection at Road Intersections},
    url = {},
    year = {2007}


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