Artificial Reasoning in the Streetscape

Abstract

Army Research Laboratory’s Content Understanding Branch, Artificial Reasoning Team research objective is to enable systems to reason given existing and future information supporting shared understanding and providing enhanced capabilities for choices and decisions. Various reasoning approaches are used to form the “best” hypothesis from multiple modalities of data generating use cases and assessing their impact on decisions given multiple criteria. The NSF Engineering Research Center for Smart Streetscapes (CS3) convergent research is inspired by potential streetscape applications. Thus, real-time understanding of complex streetscapes correspondingly requires progress in fundamental engineering knowledge and enables exciting opportunities for deploying technology: A “smart streetscape” could instantly sense human behavior and safely guide individual within the environment, amplify emergency services, and protect people against threats and dangers. The ARL and CS3 collaboration centers around the overlapping challenge for situational awareness in complex environments and how the joint research efforts can generate potential capabilities. This paper will present concepts from existing research and ideas for new research to address these common questions and challenges.