Title

Influence-Aware Predictive Density Queries under Road-Network Constraints

Abstract

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.

Meeting Name

14th International Symposium on Spatial and Temporal Databases (2015: Aug. 26-28, Hong Kong, China)

Department(s)

Computer Science

Second Department

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)

9783319223629; 9783319223636

International Standard Serial Number (ISSN)

0302-9743; 1611-3349

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 Springer Verlag, All rights reserved.

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