The ADVANCE project in the Chicago metropolitan area is one of the several IVHS operational tests currently underway in the USA. Detection of links with traffic congestion is a critical task for ADVANCE operational efficiency. In this paper we apply the Fuzzy Operator Logic (FOpL) formalism to automatically detect congestion in a transportation network under IVHS system. The knowledge base (facts and rules) for congestion detection forms three distinct domains of discourse: probes, detectors and temporal relationship. A conclusion about congestion is to be derived from each domain separately and then fused to obtain a final conclusion. A simulation modeling approach has been applied to produce a data set for preliminary evaluation of the algorithm. The developed algorithm is applied to an example road link with downstream traffic signals. The confidence about congestion derived from imprecise knowledge (data from detector and 1 % equipped vehicles) is in good accordance with the level of congestion estimated using ful knowledge about traffic conditions. Results of a preliminary evaluation indicate that the proposed algorihtm produces reasonable output, what means that the Fuzzy Operator Logic provides a promising approach to automated congestion detection where data sparsity prevails. Simplicity of the proposed congestion detection algorithm and fast program execution allow its on-line implementation.
Detection of traffic congestion using fuzzy operator logic in ADVANCE-like systems
Ermittlung von Verkehrsstaus mit der Fuzzy-Operatorlogik in ADVANCE-ähnlichen Systemen
Intelligent Vehicles, Symposium, 1993 ; 189-194
1993
6 Seiten, 3 Bilder, 8 Quellen
Aufsatz (Konferenz)
Englisch
Stadt , Stadtverkehr , Leitsystem , Probe , Algorithmus , Kraftfahrzeug , Verkehrsstau
Detection of Traffic Congestion Using Fuzzy Operator Logic in ADVANCE-like Systems
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