Situation Assessment Using Uncertain Data

Pavlik, Rick; Gerken, Mark; Houghton, Carl; Jesse, Lisa; Bussjager, Rebecca

doi:10.2514/6.2010-3317

Cited by 2 publications

(1 citation statement)

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“…Pavlik et al [182] used uncertain historical data and real-time event processing to represent and automate the activity recognition. To do this, the proposed approach utilised the power of probabilistic reasoning, fuzzy logic, and machine learning.…”

Section: ) Activity Recognition Under Uncertain Environmentsmentioning

confidence: 99%

Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

et al. 2019

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Autonomous vehicles are becoming a reality in places with advanced infrastructure to support their operations. In crowded places, harsh environments, missions that require these vehicles to be aware of the context in which they are operating, and situations requiring continuous coordination with humans such as in disaster relief, advanced-vehicle systems (AVSs) need to be better contextually aware. The vast literature referring to ''context-aware systems'' is still sparse, focusing on very limited forms of contextual awareness. It requires a structured approach to bring it together to truly realize contextual awareness in AVSs. This paper uses a human-AVSs (HAVSs) lens to polarize the literature in a coherent form suitable for designing distributed HAVSs. We group the relevant literature into two categories: contextual-awareness related to the vehicle infrastructure itself that enables AVSs to operate, and contextual-awareness related to HAVSs. The former category focuses on the communication backbone for AVSs including ad-hoc networks, services, wireless communication, radio systems, and the cyber security and privacy challenges that arise in these contexts. The latter category covers recommender systems, which are used to coordinate the actions that sit at the interface of the human and AVSs, human-machine interaction issues, and the activity recognition systems as the enabling technology for recommender systems to operate autonomously. The structured analysis of the literature has identified a number of open research questions and opportunities for further research in this area.

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Section: ) Activity Recognition Under Uncertain Environmentsmentioning

confidence: 99%

Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

et al. 2019

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Fuzzy logic for situation awareness: a systematic review

D’Aniello

2023

J Ambient Intell Human Comput

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Situation awareness is the cognitive capability of human and artificial agents to perceive, understand and predict the status of the situation in an environment. Situation awareness systems aim at supporting the situation awareness of human and artificial agents using computational techniques, models, and approaches for supporting the assessment, tracking, and prediction of critical situations. Fuzzy logic formalisms have been extensively used in situation awareness systems thanks to their capability of dealing with uncertainties while providing agents with easily understandable models of situations and decisions. This paper proposes a systematic, unbiased, and updated review of the literature on fuzzy logic for situation awareness from 2010 to 2021, conducted using the PRISMA methodology, analyzing 139 articles. An in-depth discussion of the main open challenges and future research directions is provided.

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Situation Assessment Using Uncertain Data

Cited by 2 publications

References 4 publications

Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey

Fuzzy logic for situation awareness: a systematic review

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