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Efficient processing of intelligent probabilistic collision detection queries

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Abstract

A new type of the spatio-temporal queries is the Intelligent Probabilistic Collision Detection Query (IPCDQ for short). In this paper, we focus on efficiently processing the IPCDQ on moving objects with uncertainty. Given two sets O and Q of objects, each of which moves with uncertain speed and direction, a time instant t, and a probability threshold P, the IPCDQ returns each pair of objects (o, q) (where \(o \in O\) and \(q \in Q\)), whose probability of colliding with each other is greater than or equal to P at time t. The pairs of objects satisfying the IPCDQ are termed the collision-possible pairs (or CPPs for short). We utilize a \(R^{lsd}\)-tree, in which the spatially proximate objects with similar uncertain speeds and directions are grouped together, to effectively manage the moving objects in O. Similarly, a \(R^{lsd}\)-tree is used to index the moving objects in Q. Then, with the two \(R^{lsd}\)-trees for O and Q, respectively, we develop the specialized index traversals combined with three pruning criteria, the location-pruning criterion, the angle-pruning criterion, and the speed-pruning criterion to efficiently determine the objects that may collide with each other. Besides, to provide the more useful information to the user, we propose a probability model to quantify the possibility of each object pair being the query result. Comprehensive experiments demonstrate the efficiency and the effectiveness of the proposed methods.

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Acknowledgments

This work was supported by Ministry of Science and Technology of Taiwan (R.O.C.) under Grants MOST 104-2119-M-022-001 and MOST 105-2119-M-022-002.

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  1. Department of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung City, Taiwan, R.O.C.

    Yuan-Ko Huang

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Correspondence to Yuan-Ko Huang.

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Huang, YK. Efficient processing of intelligent probabilistic collision detection queries. Computing 99, 383–404 (2017). https://doi.org/10.1007/s00607-016-0516-7

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