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Emergency medical services (EMS) rely on a robust road network to respond to patient demand as quickly as possible. An important measure of system effectiveness during adverse scenarios, such as heavy traffic and road closures, is ambulance response time. This project used data from the 2010 US National Census and the US Census Bureau’s 2015 Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) to construct an agent-based microsimulation using Multi-Agent Transport Simulation (MATSim version 0.10.1) software. The model included both ambulances and commuter traffic in New Windsor, NY. The average ambulance response time was recorded for an undamaged road network. Then, disaster scenarios were simulated on three sets of links: the set of four bridges in New Windsor, the most mathematically central links, and the most frequently traveled links in the control scenario. After simulating a postdisaster ambulance response, the removal of all three sets of links increased response time similarly, but the removal of the most frequently traveled links had the greatest adverse effect.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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