Validation of Collision Detection and Avoidance Methods for Urban Air Mobility through Simulation

TL;DR

This paper validates a collision detection and avoidance system for Urban Air Mobility using simulation, focusing on safety and efficiency in scenarios with uncooperative airspace entities like birds and drones.

Contribution

It introduces a decision tree-based collision avoidance system tailored for UAM vehicles and validates its effectiveness through fast-time simulation scenarios.

Findings

The system effectively prevents collisions with uncooperative airspace users.

Simulation results show improved safety margins and minimal impact on flight efficiency.

The approach is adaptable to various UAM aircraft configurations.

Abstract

Urban Air Mobility is a new concept of regional aviation that has been growing in popularity as a solution to the issue of ever-increasing ground traffic. Electric vehicles with vertical take-off and landing capabilities are being developed by numerous market companies as a result of the push toward environmentally sustainable aviation. The next stage in the eVTOL development process would be to define the concept of operation of these conceptual aircraft and then to integrate them with the existing airspace once they are airborne. In addition to coordinating with conventional air traffic and other Urban Air Mobility (UAM) vehicles, collision avoidance with uncooperative airspace users has to be addressed. Birds and drones of all sizes could be dangerous for these low-flying aircraft. Innovative collision detection and avoidance techniques need to be employed due to the uncooperative nature of these airspace users and different performance characteristics of urban air mobility vehicles compared to classical fixed-wing aircraft. The aim of this study is to validate one such system by means of fast-time solutions. This system uses a decision tree and safety envelopes to prevent collisions with non-cooperative airspace members. The system is designed to work with different aircraft configurations used for Urban Air Mobility (UAM) operations. Various scenarios are modelled by varying intruder type, location, flight path among others. Changes in flight time and closest point of approach are assessed to evaluate the system with regard to safety and efficiency.