Abstract
In this paper, given a query that indicates a query road segment and a query time, we intend to accurately estimate the traffic status (i.e., the driving speed) on the query road segment at the query time from traffic databases. Note that a traffic behavior in the same time usually reflects similar patterns (referring to the temporal feature), and nearby road segments have the similar traffic behaviors (referring to the spatial feature). By exploring the temporal and spatial features, more GPS data points are retrieved. In light of these GPS data retrieved, we exploit the weighted moving average approach to estimate traffic status on road networks. Experimental results show the effectiveness of our proposed algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
de Fabritiis, C., Ragona, R., Valenti, G.: Traffic estimation and prediction based on real time floating car data. In: Proc. of the 11th International IEEE Conference on Intelligent Transportation Systems, pp. 197–203 (2008)
Kriegel, H.-P., Renz, M., Schubert, M., Zuefle, A.: Statistical density prediction in traffic networks. In: Proc. of the 8th SIAM Conference on Data Mining, pp. 692–703 (2008)
Lo, C.-H., Peng, W.-C., Chen, C.-W., Lin, T.-Y., Lin, C.-S.: Carweb: A traffic data collection platform. In: Proc. of the 9th International Conference on Mobile Data Management, pp. 221–222 (2008)
Sananmongkhonchai, S., Tangamchit, P., Pongpaibool, P.: Road traffic estimation from multiple gps data using incremental weighted update. In: Proc. of the 8th International Conference on ITS Telecommunications, pp. 62–66 (2008)
Yoon, J., Noble, B., Liu, M.: Surface street traffic estimation. In: Proc. of the 5th International Conference on Mobile Systems, Applications and Services, pp. 220–232 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wei, LY., Peng, WC., Lin, CS., Jung, CH. (2009). Exploring Spatio-Temporal Features for Traffic Estimation on Road Networks. In: Mamoulis, N., Seidl, T., Pedersen, T.B., Torp, K., Assent, I. (eds) Advances in Spatial and Temporal Databases. SSTD 2009. Lecture Notes in Computer Science, vol 5644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02982-0_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-02982-0_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02981-3
Online ISBN: 978-3-642-02982-0
eBook Packages: Computer ScienceComputer Science (R0)