Reliability, Robustness, and Resilience Modeling for Surveillance System in Advanced Air Mobility Operations

TL;DR

This paper presents a comprehensive 3R modeling framework for designing and operating surveillance systems in Advanced Air Mobility, focusing on reliability, robustness, and resilience to ensure safety and efficiency.

Contribution

It introduces a novel 3R framework tailored for AAM surveillance systems, optimizing sensor network design under normal and adverse conditions.

Findings

Reliability model determines optimal sensor types and placement.

Robustness model identifies additional sensor needs under perturbations.

Resilience model develops backup strategies for sensor failures.

Abstract

Ensuring the safe and efficient operation of Advanced Air Mobility (AAM) in low-altitude airspace requires a reliable, robust, and resilient surveillance system capable of continuously detecting, identifying, and tracking aircraft under both normal and off-nominal conditions. To address this need, this study develops a comprehensive 3R modeling framework, reliability, robustness, and resilience, for the Surveillance for Advanced Air Mobility (SAM) system, with a focus on the optimal design and operation of a multi-type sensor network. Under normal operating conditions, the reliability model determines the baseline sensor types, quantities, and locations required to satisfy surveillance coverage and detection requirements. To address external perturbations, such as adverse weather conditions or sudden increases in AAM traffic demand, the robustness model identifies additional sensor requirements needed to maintain system performance. Furthermore, for surveillance outages caused by primary sensor failures, the resiliency model develops backup sensor deployment and dispatch strategies to provide temporary surveillance coverage, minimize operational disruptions, and support the safe continuation of AAM operations.