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Simulated Intersection Environment and Learning of Collision and Traffic Data in the U&I Aware Framework

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Ubiquitous Intelligence and Computing (UIC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4611))

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Road intersections have become the places of high road incidents and car collisions. Our hypothesis is that a system can be made aware of dangerous situations at road intersections and warn drivers accordingly. Moreover, over time, the system can learn (or re-learn) such “patterns” of danger for specific intersections given a history of rich collision data collected via sensors (that exist today). Based on the assumption that such a history of sensory data about colliding vehicles can be obtained, we show useful patterns that can be extracted. This paper presents our framework for intersection understanding, presenting simulated results suggesting that a fragment of the world (i.e. intersections) can be more deeply understood by mining appropriate sensor data. The simulated environment of the road intersections forming the basis of a real-world implementation and testing of the framework are discussed here. The recent results of mining traffic and collision data generated by the simulation are also included in this paper.

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Jadwiga Indulska Jianhua Ma Laurence T. Yang Theo Ungerer Jiannong Cao

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© 2007 Springer-Verlag Berlin Heidelberg

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Salim, F.D., Loke, S.W., Rakotonirainy, A., Krishnaswamy, S. (2007). Simulated Intersection Environment and Learning of Collision and Traffic Data in the U&I Aware Framework. In: Indulska, J., Ma, J., Yang, L.T., Ungerer, T., Cao, J. (eds) Ubiquitous Intelligence and Computing. UIC 2007. Lecture Notes in Computer Science, vol 4611. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73548-9

  • Online ISBN: 978-3-540-73549-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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