Title
Safety Validation of Sense and Avoid Algorithms Using Simulation and Evolutionary Search
Abstract
We present a safety validation approach for Sense and Avoid (SAA) algorithms aboard Unmanned Aerial Vehicles (UAVs). We build multi-agent simulations to provide a test arena for UAVs with various SAA algorithms, in order to explore potential conflict situations. The simulation is configured by a series of parameters, which define a huge input space. Evolutionary search is used to explore the input space and to guide the simulation towards challenging situations, thus accelerating the process of finding dangerous faults of SAA algorithms and supporting the safety validation process. We applied our approach to the recently published Selective Velocity Obstacles (SVO) algorithm. In our first experiment, we used both random and evolutionary search to find mid-air collisions where UAVs have perfect sensing ability. We found evolutionary search can find some faults (here, interesting problems with SVO) that random search takes a long time to find. Our second experiment added sensor noise to the model. Random search found similar problems as it did in experiment one, but the evolutionary search found some interesting new problems. The two experiments show that the proposed approach has potential for safety validation of SAA algorithms.
Year
DOI
Venue
2014
10.1007/978-3-319-10506-2_3
SAFECOMP
Keywords
Field
DocType
safety validation,unmanned aerial vehicles,sense and avoid,multi-agent simulation,genetic algorithm,evolutionary search
Random search,Computer science,Algorithm,Artificial intelligence,Sense and avoid,Genetic algorithm
Conference
Volume
ISSN
Citations 
8666
0302-9743
2
PageRank 
References 
Authors
0.49
7
3
Name
Order
Citations
PageRank
Xueyi Zou1192.88
Robert Alexander2548.22
John A. Mcdermid3832145.28