Intelligent Transportation Systems


Intelligent Transportation Systems Laboratory


Welcome to the ITS Lab web site at Portland State University. We've released our Annual Report for 2011-12. Read the report here.


Intelligent Transportation Systems Laboratory's Featured Project:

Exploiting Live Plus Archive Data for Intelligent Transportation Systems

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 interstate miles 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 situation presents a clear opportunity for the use of Data Stream Management Systems (DSMS) in Intelligent Transportation Systems (ITS). Several DSMS prototypes and many algorithms for data stream processing have been developed in recent years. However, an examination of the usage of existing DSMS in ITS, clearly demonstrates weaknesses in current DSMS technology that need to be addressed before DSMS can be used in ITS applications. ITS data has characteristics that have received limited study in current DSMS; it is disordered, dirty and bursty and can arrive from widely varied sources (loop detectors, active vehicles, passive transponders). Further, the live data must be compared with arch

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