AbstractThe use of an automated collision notification (ACN) device in vehicles can greatly reduce the time between crash occurrence and notification of emergency medical services (EMSs). Most ACN devices rely on cellular technology to report important crash information to the proper authorities. The objective of this study was to examine the ability of the existing western New York cellular analog system to support ACN systems. The first task was to develop a model predicting the probability of successfully completing an emergency ACN call at attenuated levels of received signal strength indicator (RSSI), a measurement of the bond between cell phone and tower. Then, empirical estimates were made of the time necessary for call completion at given levels of the RSSI. The RSSI is sampled at locations throughout Erie County, New York, and this information is used to determine the probability of successful call completion for different locations within the county. This model was then applied to historic data for selected past crashes. Finally, the findings were compared with real-world crash data obtained from the ACN Field Operational Test program, where 750 ACN devices were installed in cars and their performance examined over time. An interpolated map of the sampled RSSI values suggests that cellular coverage in Erie County is adequate to support the automated collision network technology. The models and techniques described here are applicable to other areas and regions of the country.


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    Titel :

    Evaluating the reliability of automated collision notification systems


    Beteiligte:
    Akella, Mohan R (Autor:in) / Bang, Chaewon (Autor:in) / Beutner, Rob (Autor:in) / Delmelle, Eric M (Autor:in) / Batta, Rajan (Autor:in) / Blatt, Alan (Autor:in) / Rogerson, Peter A (Autor:in) / Wilson, Glenn (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    18.12.2001


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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