Handling Ground Risks for Road Networks in UAS Specific Operations Risk Assessment (SORA)

Bertrand, Sylvain; Raballand, Nicolas; Lala, Stéphanie · 2024 · Crossref

DOI: 10.1109/icuas60882.2024.10556970

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses a gap in the Specific Operations Risk Assessment (SORA) methodology for Unmanned Aerial Systems (UAS), which currently evaluates ground risk solely based on collision probabilities with people. The authors argue that this approach overlooks significant risks posed to vehicles on road networks, particularly for Beyond Visual Line of Sight (BVLOS) operations. To rectify this, the study proposes a modification to the SORA process that explicitly accounts for ground risks regarding road traffic alongside traditional population-based risks. The methodology introduces two distinct risk indices: the intrinsic People Risk Class (iPRC) and the intrinsic Road Risk Class (iRRC). The iPRC retains the existing SORA logic, calculating risk based on population density and the drone’s critical collision area. The novel iRRC is derived from road traffic data, specifically the Annual Average Daily Traffic (AADT). The authors define a "Critical Segment" along road networks, representing the distance over which a collision could occur during a drone’s descent and slide. Using traffic flow models to estimate peak-hour vehicle density and speed, the paper calculates the number of vehicles at risk within this segment. Following the SORA framework, the authors pre-compute lookup tables that allow operators to determine the iRRC based on drone characteristics (dimension, speed) and road traffic intensity (AADT classes). The final Ground Risk Class (GRC) is determined by taking the maximum value of the mitigated People Risk Class and Road Risk Class. The study illustrates this approach with a 65km BVLOS mission in eastern France involving a fixed-wing UAV. The example demonstrates how the proposed method identifies high-risk road segments, such as motorways, which might be overlooked if only population density were considered. The resulting tables provide a practical tool for operators to quantify road risks without complex real-time calculations, ensuring that risk assessments remain conservative by assuming worst-case traffic conditions and descent trajectories. The significance of this work lies in its integration of vehicular risk into the standardized SORA framework, enhancing the safety assurance for UAS operations over transportation networks. By providing a quantitative metric for road risks, the paper enables more accurate determination of Operational Safety Objectives. This ensures that safety requirements reflect the full spectrum of ground hazards, particularly for long-range missions where the probability of intersecting high-traffic roads is substantial. The approach maintains compatibility with existing SORA tools while expanding their applicability to complex operational environments.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• micromobility e scooter

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes