A Family-Based Approach to Safety Cases for Controlled Airspaces in Small Uncrewed Aerial Systems

TL;DR

This work addresses the challenge of safely integrating numerous sUAS into controlled airspace by introducing SafeSPLE, a Safety Case Software Product Line Engineering approach that combines hazard analysis, a safety-case feature model, and parameterized safety cases to generate on-demand, flight-specific safety arguments. The method enables automated, context-aware safety-case instantiation for each sUAS request, potentially supporting real-time UTM decision-making. The case study demonstrates a practical pipeline from hazard analysis through feature modeling to per-flight safety-case instances, illustrating how evidence requirements can be tailored and how decisions might be made (deny, delay, or proceed with mitigations). The work highlights the potential for reusability across flights and UTM implementations, while acknowledging uncertainties when data is missing and the need for further tooling and broader validation.

Abstract

As small Uncrewed Aircraft Systems (sUAS) increasingly operate in the national airspace, safety concerns arise due to a corresponding rise in reported airspace violations and incidents, highlighting the need for a safe mechanism for sUAS entry control to manage the potential overload. This paper presents work toward our aim of establishing automated, customized safety-claim support for managing on-entry requests from sUAS to enter controlled airspace. We describe our approach, Safety Case Software Product Line Engineering (SafeSPLE), which is a novel method to extend product-family techniques to on-entry safety cases. It begins with a hazard analysis and design of a safety case feature model defining key points in variation, followed by the creation of a parameterized safety case. We use these together to automate the generation of instances for specific sUAS. Finally we use a case study to demonstrate that the SafeSPLE method can be used to facilitate creation of safety cases for specific flights.

Figures (8)

• Figure 1: Partial feature model representing heuristics for a safety-case software product line with 51 features. This represents 288,202 different variants -- combinations of flights, vehicles, operators, and weather conditions. Additional variants such as terrain and its altitude are not shown.
• Figure 2: Partial parameterized safety case. Represents the top level goal (G1) and strategies. The Context nodes (C1 and C2) have parameters which can be instantiated with a defined set of concrete values.
• Figure 3: Overall vision for SafeSPLE. Step one creates a feature model for the safety case product line. Step two designs the parameterized safety case, and Step three generates an instance for a specific sUAS and its characteristics (pilot, vehicle, mission, weather, etc.)
• Figure 4: Two parts of the feature model that we focus on for this case study.
• Figure 5: Pilot Safety Case: A safety case based only on whether the pilot is certified and has sufficient experience.