Remote Identification Trajectory Coverage in Urban Air Mobility Applications

TL;DR

This paper analyzes the coverage of Remote ID technologies like Bluetooth and Wi-Fi for urban UAS operations, providing theoretical models and case studies to guide deployment strategies in cities.

Contribution

It introduces methods to compute expected trajectory coverage of Remote ID systems and applies them to realistic urban scenarios, aiding deployment planning.

Findings

Approximately 500-5000 Bluetooth receivers achieve 50-95% coverage in San Francisco.

Approximately 10-40 Wi-Fi receivers achieve similar coverage levels.

The methods help estimate receiver requirements for effective UAS trajectory monitoring.

Abstract

As Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) continue to mature, a safety-critical system that will need to be implemented in tandem is Remote Identification (Remote ID) for uncrewed aircraft systems (UAS). To ensure successful and efficient deployment (e.g., maximal surveillance of UAS trajectories), as well as to better understand secondary impacts (e.g., consumer privacy risks in collecting real-time UAS trajectory information), the coverage of broadcast-receive Remote ID architectures needs to be characterized. Motivated by this need, we examine theoretical and empirical trajectory coverage of several common Remote ID technologies (e.g., Bluetooth, Wi-Fi) deployed for urban package delivery missions, a commonly-cited use case for UAM and AAM. We derive methods to explicitly compute expected coverage proportions under idealized geometries, as well as conduct case studies with realistic city geographies and UAS path planning algorithms. An example of results include approximate magnitudes of Remote ID receivers needed (approximately 500-5000 receivers needed to achieve 50-95\% coverage for Bluetooth Legacy, and approximately 10-40 receivers needed for the same coverage range for Wi-Fi NAN/Beacon, assuming a cruise altitude of 200 feet) to achieve specific trajectory coverage proportions for San Francisco, California. Our analyses, combined with complementary works related to Remote ID bandwidth and deployment topologies, can help guide municipal authorities and AAM stakeholders in future Remote ID system deployments and upkeep.