detectandavoid

Detect and avoid (DAA) refers to systems and procedures that enable unmanned aircraft or autonomous vehicles to identify potential collisions with other aircraft or obstacles and take action to maintain safe separation. DAA is a key concept in aviation, especially for integrating unmanned aircraft into airspace alongside manned aircraft, and is critical for operations beyond visual line of sight (BVLOS).

DAA typically uses multiple sensors, such as radar, LiDAR or optical cameras, Automatic Dependent Surveillance–Broadcast (ADS-B) data, and other transponder information, to detect intruders and obstacles. It processes sensor data to estimate trajectories and triggers avoidance maneuvers, such as altitude or heading changes, while considering airspace constraints and, where appropriate, human oversight. The architecture may include a sense-and-avoid algorithm, decision logic, and flight-control interfaces to execute safe trajectory modifications, and it may provide alerts to pilots or operators.

Regulatory and standards context: Agencies such as the U.S. Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) emphasize the importance of DAA for BVLOS UAS operations. Standards organizations, including RTCA and ASTM, provide guidance on performance, reliability, risk assessment, and interoperability. However, there is no single universal standard, and implementations vary by vehicle and airspace.

Challenges remain in DAA, including reliability and robustness of sensor fusion, latency, false alarms, and performance in adverse weather. Other concerns include cybersecurity and integration with existing air traffic management (ATM) systems. Ongoing research explores machine learning for trajectory prediction, cooperative DAA with manned aircraft, and advanced simulation and testing environments.