TY  - JOUR
A1  - Laarmann, Lukas
A1  - Thoma, Andreas
A1  - Misch, Philipp
A1  - Röth, Thilo
A1  - Braun, Carsten
A1  - Watkins, Simon
A1  - Fard, Mohammad
T1  - Automotive safety approach for future eVTOL vehicles
JF  - CEAS Aeronautical Journal
N2  - The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including  mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL’s crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.
KW  - eVTOL development
KW  - eVTOL safety
KW  - Crashworthiness
KW  - Automotive safety approach
KW  - Full-vehicle crash test
Y1  - 2023
U6  - http://dx.doi.org/10.1007/s13272-023-00655-0
SN  - 1869-5590 (Online)
SN  - 1869-5582 (Print)
N1  - Corresponding author: Lukas Laarmann
PB  - Springer Nature
ER  - 
TY  - JOUR
A1  - Thomessen, Karolin
A1  - Thoma, Andreas
A1  - Braun, Carsten
T1  - Bio-inspired altitude changing extension to the 3DVFH* local obstacle avoidance algorithm
JF  - CEAS Aeronautical Journal
N2  - Obstacle avoidance is critical for unmanned aerial vehicles (UAVs) operating autonomously. Obstacle avoidance algorithms either rely on global environment data or local sensor data. Local path planners react to unforeseen objects and plan purely on local sensor information. Similarly, animals need to find feasible paths based on local information about their surroundings. Therefore, their behavior is a valuable source of inspiration for path planning. Bumblebees tend to fly vertically over far-away obstacles and horizontally around close ones, implying two zones for different flight strategies depending on the distance to obstacles. This work enhances the local path planner 3DVFH* with this bio-inspired strategy. The algorithm alters the goal-driven function of the 3DVFH* to climb-preferring if obstacles are far away. Prior experiments with bumblebees led to two definitions of flight zone limits depending on the distance to obstacles, leading to two algorithm variants. Both variants reduce the probability of not reaching the goal of a 3DVFH* implementation in Matlab/Simulink. The best variant, 3DVFH*b-b, reduces this probability from 70.7 to 18.6% in city-like worlds using a strong vertical evasion strategy. Energy consumption is higher, and flight paths are longer compared to the algorithm version with pronounced horizontal evasion tendency. A parameter study analyzes the effect of different weighting factors in the cost function. The best parameter combination shows a failure probability of 6.9% in city-like worlds and reduces energy consumption by 28%. Our findings demonstrate the potential of bio-inspired approaches for improving the performance of local path planning algorithms for UAV.
KW  - UAV
KW  - Obstacle avoidance
KW  - Autonomy
KW  - Local path planning
Y1  - 2023
U6  - http://dx.doi.org/10.1007/s13272-023-00691-w
SN  - 1869-5590 (Online)
SN  - 1869-5582 (Print)
N1  - Corresponding author: Karolin Thomessen
PB  - Springer
CY  - Wien
ER  -