Computer-Aided Civil and Infrastructure Engineering<\/em>, the new model proved more efficient than two existing techniques. It\u2019s designed to improve long-term planning, too. The system can help officials decide where to place infrastructure\u2009\u2014\u2009a new fire station, say\u2009\u2014\u2009that will prevent secondary incidents and minimize traffic congestion.<\/p>\n\n\n\nResearchers tested the new model using data collected from the N.C. Department of Transportation\u2009\u2014\u200910,983 traffic incidents in 10,672 different locations in Raleigh.<\/p>\n\n\n\n
Leila Hajibabai, assistant professor in the Edward P. Fitts Department of Industrial and Systems Engineering, co-authored the paper with Asya Atik \u201921 MS, \u201923 PHD.<\/p>\n\n\n\n
Hajibabai says the team is working on the next step for eventual deployment of the system. \u201cWe started working with a fire department in North Carolina to find the best fire station locations given their available resources and operational constraints,\u201d she says. \u201cThe work we started is promising.\u201d<\/p>\n\n\n\n
Ultimately, the model should be sufficiently flexible to work with other agencies and municipalities who want to upgrade their systems. \u201cI hope to see the impact of our work on real-world problems,\u201d Hajibabai says.<\/p>\n"},"excerpt":{"rendered":"
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