Inclement weather is a threat to the safety of transportation systems as well as the efficiency of their operation. A road weather information system (RWIS) is a network of environmental sensor stations (ESS) that collect a range of real-time data about weather and pavement conditions. These systems can support highway officials and civilians in making more informed transportation safety decisions, particularly in times of adverse weather, by giving them more accurate and localized weather information. This enables the proper maintenance activities to be executed and safety to be restored while using minimum resources. However, because of the range of network characteristics and geographical factors affecting the implementation of ESS, no widely adopted guidelines exist that outline where to implement ESS in a network beyond taking into the physical criteria of an appropriate site, although several methods have been suggested. This paper aims to take a practical approach to solving the location problem of RWIS by proposing a unified multi-objective optimization methodology that takes into account vehicular accident data, vehicle miles traveled, area coverage, access to power and maintenance, and existing ESS. This study produces an exact solution method that produces a Pareto set of multiple efficient solutions. The proposed methodology is applied to a real world case study focused on the deployment of additional ESS in the existing RWIS network across New York State. Further, a sensitivity analysis is conducted to examine the effects of different parameters and a nonpreference solution is proposed.


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    Titel :

    A multi-objective optimization approach to the location of road weather information system in New York State


    Beteiligte:
    Fetzer, Julie (Autor:in) / Caceres, Hernan (Autor:in) / He, Qing (Autor:in) / Batta, Rajan (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2018-11-02


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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