EFFECTS OF STOCHASTIC TRAFFIC FLOW MODEL ON EXPECTED SYSTEM PERFORMANCE

In 2010 Naval Surface Warfare Center - Panama City Division (NSWC-PCD) developed a System Performance and Layered Analysis Tool (SPLAT) that evaluates candidate threat detection systems. Given a sensor deployment pattern, SPLAT combines sensor performances, scenario data, and pedestrian flow to analytically compute expected probability of detection (pd) and false alarm (pfa). Because the 2010 pedestrian flow model describes all possible trips through the detection area as straight-line paths, SPLAT can enumerate all possible trips and explicitly determine the maximum pd along each trip. NSWC-PCD's new 2011 flow model now accommodates stochastic pedestrian motion defined as a Markov process. However, stochastic flow modeling has created a combinatorial explosion; there are now too many paths to explicitly enumerate. Addressing this problem, NSWC-PCD has developed a unique expected maximum probability technique which approximates results obtained by enumerating all possible paths while still preserving spatial correlations created by sensor deployment patterns.