Estimating time-dependent speed functions using a gravity model over road network
Cintia P., Trasarti R., Macedo J. A., Almada L., Ferreira C.
Data Mining Spatio temporal data mining H.2.8 Database Applications. Data mining
The availability of inexpensive tracking devices,such as GPS- enabled devices, gives the opportunity to collect large amounts of trajectory data from vehicles. In this context, we are interested in the problem of generating the traffic information in time-dependent networks using this kind of data. This problem is not trivial since several works in liter- ature use strong assumptions on the error distribution we want to drop, proposing a gravitational model method to compute road segment aver- age speed from trajectory data. Furthermore we show how to generate travel-time functions from the computed average speeds useful for time- dependent networks routing systems. Our approach allows creating an accurate picture of the traffic conditions in time and space. The method we present in this paper tackles all this aspect showing how its perfor- mance over a synthetic dataset and a real case.
Source: SEBD 2013 - 21st Italian Symposium on Advanced Database Systems, pp. 321–328, Roccella Jonica, Reggio Calabria, Italy, 30 June - 3 July 2013
Publisher: Università della Calabria, Reggio Calabria, ITA
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@inproceedings{oai:it.cnr:prodotti:279103,
title = {Estimating time-dependent speed functions using a gravity model over road network},
author = {Cintia P. and Trasarti R. and Macedo J. A. and Almada L. and Ferreira C.},
publisher = {Università della Calabria, Reggio Calabria, ITA},
booktitle = {SEBD 2013 - 21st Italian Symposium on Advanced Database Systems, pp. 321–328, Roccella Jonica, Reggio Calabria, Italy, 30 June - 3 July 2013},
year = {2013}
}
0000-0002-8085-9338
