HighlightsA probabilistic sensor location model is proposed to minimize the error of performance monitoring.The proposed model is applicable to sensor deployment problem that along a one-directional corridor.A mixed-integer linear program is formulated and an efficient heuristic search solution algorithm is proposed.A case study reveals that accounting for failures is important for sensor deployment decisions.

    AbstractThis paper proposes a sensor location model to identify a sensor configuration that minimizes overall freeway performance monitoring errors while considering the consequences of probabilistic sensor failures. To date, existing sensor location models for freeway monitoring inherently assume that either deployed sensors never fail or the consequences of sensor failure are trivial matters. However, history has revealed that neither assumption is realistic, suggesting that ignoring failures in sensor allocation models may actually produce a significantly suboptimal configuration in the real world. Our work addresses this dilemma by developing a probabilistic optimization model that will minimize the error expectation by examining all possible failure scenarios, each with an occurrence probability. To ensure the scenario completeness and uniqueness, a sensor failure scenario is represented by using a binary string with 1 indicating an operational sensor at a given site and 0 for sensor failure or no sensor deployed. When applied to a case study network, it is shown that an optimal configuration that considers sensor failure is significantly different from an optimal configuration that ignores sensor failure, revealing that sensor failures pose non-trivial consequences on performance monitoring accuracy.


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    Titel :

    A probabilistic optimization model for allocating freeway sensors


    Beteiligte:
    Danczyk, Adam (Autor:in) / Di, Xuan (Autor:in) / Liu, Henry X. (Autor:in)


    Erscheinungsdatum :

    2016-02-29


    Format / Umfang :

    21 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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