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- W636403068 abstract "Advanced Traveler Information System (ATIS) has attracted world-wide interest as a promising program to improve efficiency of road transportation systems. An optimal route guidance is an important feature of ATIS. Information regarding the level of congestion in a given roadway system is vital for deriving an optimal route guidance strategy. Characterization of level of congestion in a given roadway system requires integration of localized sensor information that can be accomplished by mapping the set of localized information into a higher dimensional space. The diagnosis of integrated information requires partitioning of the higher dimensional space into multiple regions. This paper describes a supervised learning approach, based on potential functions, to partition the higher dimensional space into regions that represent pre-determined levels of congestion in a given portion of a road network or freeway segment. (A) For the covering abstract see IRRD 873901." @default.
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- W636403068 date "1995-01-01" @default.
- W636403068 modified "2023-09-24" @default.
- W636403068 title "TRAFFIC CONGESTION DETECTION FROM SUPERVISED LEARNING" @default.
- W636403068 hasPublicationYear "1995" @default.
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