One of the most serious problems in the transportation system is traffic congestion. In order to solve this problem, transportation systems should be more intelligent. An Intelligent Transportation System (ITS) uses intelligence to enhance the operation of the transportation system based on survey information. A real-time architecture for a highway vehicle detection system is presented in the article. The Laser Based Detection System (LBDS), focused on helping the ITS, measures a key quantitative parameter of vehicles moving across a link of highway, namely, travel time. Travel time is based upon the identifying and reidentifying vehicles at various points on the highway. This article provides a method to collect real-time signals from an active laser source in the LBDS and calculate vehicle parameters using a standard computer. A method of message exchange between a real-time kernel process, for real-time data acquisition, and a user space process, for computing and displaying, is given under the RTLinux environment. Experimental results from field tests have shown that the application of the real-time architecture to the LBDS provides speeds deterministically. It was found that the maximum difference of the entering velocity between the channels was 1.34% and the exiting velocity was 0.6%. The maximum difference of the vehicle's calculated length between the channels was 1.03%. At this moment in time, the optical subsystem in the LDBS cannot cover a whole lane. The next prototype of the LBDS will allow for coverage of a whole highway lane. With the new prototype, it is expected that the device will be able to utilize all of the channels even when a vehicle is changing lanes.


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    Titel :

    Real-time architecture for an electro-mech-optical system for detection of vehicles on highway


    Weitere Titelangaben:

    Realzeitarchitektur für ein elektromechanisch-optisches System für Fahrzeugerkennung auf der Autobahn


    Beteiligte:


    Erscheinungsdatum :

    2004


    Format / Umfang :

    6 Seiten, 7 Bilder, 14 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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