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Mobile operations and highway maintenance work is among the riskiest activities of state highway agencies. Over the past ten years 1,323 fatal-major crashes occurred in Iowa due to the intermittent and moving work zones. Additionally, another 8,234 minor injury crashes, 11,447 possible injury crashes, and 34,038 property damage type of crashes occurred in Iowa in the same time frame (as reported in Iowa DOT crash database). A literature review of research in risk mitigation of mobile operations in other states has indicated that the topic has been addressed, but typically in very narrow areas (e.g. weather or nighttime operations). Few studies have analyzed risk in moving operations and maintenance work using an integrated, system-level analysis. This study provides a broad examination of the different risks that are identified and assessed through expert panel review and analysis of the statewide crash data from 2001 to 2010. A model was developed to identify the significant factors and an analysis of severity and frequency of those factors resulted in the development of the Integrated Risk Management Model. The statistical analysis along with the Integrated Risk Management Model resulted in six factors that bear critical risk potential and catastrophic risk potential for maintenance and mobile operations in highways. They are passenger vehicles, vision not obscured by moving vehicles or frosted windows / wind-shield, region located within or adjacent to the work activity, region located between the advance warning sign and work area, cloudy weather and foggy or misty or partly cloudy weather. Several risk mitigation strategies are recommended in this research study that should be adopted by transportation agencies while planning for a mobile work zone or during the maintenance and operation activities on highway in order to render a safer work zone both for the public and the working crews.

Identification, assessment and proposing mitigation strategies for the risks involved in operations and maintenance activities on highways - crash data analysis and development of integrated risk management model