Local Evaluation Report: State of Alabama (2001), Automated Crash Notification System, UAB
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Local Evaluation Report: State of Alabama (2001), Automated Crash Notification System, UAB

Filetype[PDF-36.06 KB]


English
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Details:

  • Corporate Creators:
    Alabama. Dept. of Public Health
  • Corporate Contributors:
    University of Alabama
  • Subject/TRT Terms:
  • Publication/ Report Number:
    FHWA-JPO-06-022
  • Resource Type:
    Tech Report
  • Geographical Coverage:
  • Corporate Publisher:
    Alabama
  • NTL Classification:
    NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Collision Notification Systems (Vehicles);NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Emergency Management;NTL-SAFETY AND SECURITY-Accidents;NTL-SAFETY AND SECURITY-Highway Safety;
  • Abstract:
    This project is the pilot phase of a longer-term project to integrate ACN and AACN technology into a comprehensive trauma system. Such a system exists in Alabama’s central Birmingham Regional EMS System (BREMSS). The project involves three tasks: the development of an electronic data collection system, EMS data collection in the field, and analysis of collected data for purposes of injury prediction in motor vehicle collisions. Project participants include the Center for Injury Sciences at UAB, the EMS Division of the State of Alabama Department of Public Health, BREMSS and its central Trauma Communications Center, local EMS agencies, and General Dynamics’ Advanced Information Engineering Services. Negative institutional issues have been minimal among these organizations primarily due to already existing relationships. These relationships allow most technical issues to be overcome. The greatest challenge experienced to date has been the assessment of data collection tools in the field. Feedback from end users has been limited, and hardware and software configurations (e.g. device size) may be viewed quite differently by different users. One method to overcome limitations to field data collections by EMS personnel is the employment of a trained crash investigator and the development of a system in which data is retrieved from OnStar-equipped vehicles. As the bank of data grows through more equipped vehicles and greater geographical distribution of project activities, injury predictors may be developed and tested against real-world findings.
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