latte
Exploiting Live Plus Archive Data for Intelligent
Transportation Systems
Research Focus
Traffic congestion and the associated delay and economic
costs it causes are a source of significant concern. In the
United States over the past twenty years, vehicle miles
traveled for passenger cars grew 44%, but miles of
interstate highway increased less than 8%! In response,
transportation departments are moving towards
intelligent transportation management.
Much of the data available for use in
intelligent transportation management is in the
form of data streams, such as inductive loop
detector data, Automatic Vehicle Location (AVL)
systems on buses, and live traffic signal data.
This project investigates the use of Data Stream
Management Systems (DSMS) for Intelligent Transportation
Systems (ITS).
The goals of this research are to extend the
NiagaraST
stream-processing system to accommodate queries that arise
in intelligent transportation management and information
systems (particularly those combining both live and
archive data), develop improved evaluation techniques
that will match transportation applications and data in
speed and scale, and then thoroughly test and evaluate the
results using the live and archival data sources available
in the Portland State University ITS lab.
This project is a collaboration between faculty, staff and
students in the
Data and Information Management Laboratory
of the Computer Science
Department and the
Intelligent Transportation Systems Laboratory
of the Civil &
Environmental Engineering Department in the Maseeh College
of Engineering and Computer Science at Portland State
University.
This project is funded by the National Science
Foundation through grant IIS-0612311 "Exploiting Live plus
Archive Data for Intelligent Transportation Systems." Any
opinions, findings, and conclusions or recommendations
expressed in this material are those of the author(s) and do
not necessarily reflect the views of the National Science
Foundation.
People
Publications and Products
Demonstrations
- Tufte, K., Li, J., Maier, D., Papadimos, V., Bertini,
R.L., Rucker, J.
Travel Time Estimation using NiagaraST and latte,
Demonstration Paper in
Proceedings onf the 2007 ACM SIGMOD Conference on
Management of Data
11-14 June 2007, Beijing, China
Demonstration Poster
Journal Publications
- Tucker, P., Maier, D., Sheard, T., Stephens, P.
Using Punctuation Schemes to Characterize Strategizes
for Querying Data Streams
IEEE Transactions on Knowledge and Data Engineering
Volume 19, 2007.
