Influence-Aware Predictive Density Queries under Road-Network Constraints
Density query is a very useful query type that informs users about highly concentrated/dense regions, such as a traffic jam, so as to reschedule their travel plans to save time. However, existing products and research work on density queries still have several limitations which, if can be resolved, will bring more significant benefits to our society. For example, we identify an important problem that has never been studied before. That is none of the existing works on traffic prediction consider the influence of the predicted dense regions on the subsequent traffic flow. Specifically, if road A is estimated to be congested at timestamp t1, the prediction of the condition on other roads after t1 should consider the traffic blocked by road A. In this paper, we formally model such influence between multiple density queries and propose an efficient query algorithm. We conducted extensive experiments and the results demonstrate both the effectiveness and efficiency of our approach.
L. Heendaliya et al., "Influence-Aware Predictive Density Queries under Road-Network Constraints," Lecture Notes in Computer Science: Advances in Spatial and Temporal Databases, vol. 9239, pp. 80-97, Springer Verlag, Aug 2015.
The definitive version is available at http://dx.doi.org/10.1007/978-3-319-22363-6_5
14th International Symposium on Spatial and Temporal Databases (2015: Aug. 26-28, Hong Kong, China)
Electrical and Computer Engineering
Keywords and Phrases
Roads And Streets; Street Traffic Control; Traffic Congestion; Transportation; Dense Region; Effectiveness And Efficiencies; Predictive Density; Query Algorithms; Road Network; Traffic Flow; Traffic Jams; Traffic Prediction; Traffic Control
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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