Statistical Properties and Airspace Capacity for Unmanned Aerial Vehicle Networks Subject to Sense-and-Avoid Safety Protocols

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

4 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)5890-5903
Journal / PublicationIEEE Transactions on Intelligent Transportation Systems
Volume22
Issue number9
Online published11 Dec 2020
Publication statusPublished - Sept 2021
Externally publishedYes

Abstract

Random mobility models (RMMs) capture the random mobility patterns of mobile agents, and have been widely used as the modeling framework for the evaluation and design of mobile networks. All existing RMMs in the literature assume independent movements of mobile agents, which does not hold for unmanned aircraft systems (UASs). In particular, UASs must maintain a safe separation distance to avoid collision. In this paper, we propose a new modeling framework of random mobility models equipped with physical sense-and-avoid protocols to capture the flexible, variable, and uncertain movement patterns of UASs subject to separation safety constraints. For the random direction (RD) RMM equipped with a commonly used sense-and-avoid (SA) protocol, named sense-and-stop (SS), we provide its statistical properties including stationary location distribution and stationary inter-vehicle distance distribution, using the Markov analysis. This study provides knowledge on the impact of SA protocols to critical UAS networking statistics. In addition, we define collision probabilities and airspace capacity concepts for UASs based on the inter-vehicle distance distribution, and derive their closed-form expressions. This analytical framework mathematically bridges local autonomy with global airspace capacity, and allows the impact analysis of local autonomy configurations for effective UAS airspace capacity management.

Research Area(s)

  • aerial networking, airspace capacity management, collision avoidance, Random mobility model, sense and avoid, unmanned aircraft system traffic management

Citation Format(s)

Statistical Properties and Airspace Capacity for Unmanned Aerial Vehicle Networks Subject to Sense-and-Avoid Safety Protocols. / Liu, Mushuang; Wan, Yan; Lewis, Frank L. et al.
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 22, No. 9, 09.2021, p. 5890-5903.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review