Exploiting Live Plus Archive Data for Intelligent Transportation Systems

Portland State University, Portland OR

Investigators

Abstract

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 through the use of tools such as adaptive ramp meters and traffic signals, and expanded traffic information systems. 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). Current DSMS technology is not adequate for ITS applications; ITS data is disordered, dirty and bursty and can arrive from widely varied sources (embedded detectors, active vehicles, passive transponders). Further, the live data must be compared with archived historical data and other types of information sources. In addition to the current focus on temporal aggregation, ITS data requires spatial and potentially spatio-temporal aggregation. Finally, any DSMS that processes ITS data must scale to thousands or tens of thousands of simultaneous queries. 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 (http://datalab.cs.pdx.edu/) of the Computer Science Department and in the Intelligent Transportation Systems Laboratory (http://www.its.pdx.edu/) of the Civil & Environmental Engineering Department in the Maseeh College of Engineering and Computer Science at Portland State University.