TY - JOUR
T1 - Avionics Human-Machine Interfaces and Interactions for Manned and Unmanned Aircraft
AU - Lim, Yixiang
AU - Gardi, Alessandro
AU - Sabatini, Roberto
AU - Ramasamy, Subramanian
AU - Kistan, Trevor
AU - Ezer, Neta
AU - Vince, Julian
AU - Bolia, Robert
N1 - Funding Information:
The All Condition Operations and Innovative Cockpit Infrastructure (ALICIA) project was funded by the European Union (EU) 7th Framework Programme (FP7) [ 52 ], aimed at developing new and scalable cockpit architectures, which can extend flight operations in a wider range of degraded conditions such as weather disturbances [ 156 ] or ground perturbations. The project addressed HMI solutions in four main areas: navigation, surveillance, cockpit display and multi-modal input/output technologies. Evaluated concepts included head mounted/head up displays, touch/cursor/keyboard interfaces [ 34 , 51 , 157 , 158 ], voice inputs, 3D auditory displays as well as passive/active sensors.
Funding Information:
The authors wish to thank and acknowledge THALES ATM Australia, the Australian Defence Science and Technology (DST) Group and Northrop Grumman Corporation for separately supporting different aspects of this work under the collaborative research projects RE-02544-0200315666, RE-02826-0200316323 and RE-03163-0200317164 respectively.
Funding Information:
The authors wish to thank and acknowledge THALES ATM Australia , the Australian Defence Science and Technology ( DST ) Group and Northrop Grumman Corporation for separately supporting different aspects of this work under the collaborative research projects RE-02544-0200315666 , RE-02826-0200316323 and RE-03163-0200317164 respectively.
Publisher Copyright:
© 2018
PY - 2018/10
Y1 - 2018/10
N2 - Technological advances in avionics systems and components have facilitated the introduction of progressively more integrated and automated Human-Machine Interfaces and Interactions (HMI2) on-board civil and military aircraft. A detailed review of these HMI2 evolutions is presented, addressing both manned aircraft (fixed and rotary wing) and Remotely Piloted Aircraft System (RPAS) specificities for the most fundamental flight tasks: aviate, navigate, communicate and manage. Due to the large variability in mission requirements, greater emphasis is given to safety-critical displays, command and control functions as well as associated technology developments. Additionally, a top-level definition of RPAS mission-essential functionalities is provided, addressing planning and real-time decision support for single and multi-aircraft operations. While current displays are able to integrate and fuse information from several sources to perform a range of different functions, these displays have limited adaptability. Further development to increase HMI2 adaptiveness has significant potential to enhance the human operator's effectiveness, thereby contributing to safer and more efficient operations. The adaptive HMI2 concepts in the literature contain three common elements. These elements comprise the ability to assess the system and environmental states; the ability to assess the operator states; and the ability to adapt the HMI2 according to the first two elements. While still an emerging area of research, HMI2 adaptation driven by human performance and cognition has the potential to greatly enhance human-machine teaming through varying the system support according to the user's needs. However, one of the outstanding challenges in the design of such adaptive systems is the development of suitable models and algorithms to describe human performance and cognitive states based on real-time sensor measurements. After reviewing the state-of-research in human performance assessment and adaptation techniques, detailed recommendations are provided to support the integration of such techniques in the HMI2 of future Communications, Navigations, Surveillance (CNS), Air Traffic Management (CNS/ATM) and Avionics (CNS + A) systems.
AB - Technological advances in avionics systems and components have facilitated the introduction of progressively more integrated and automated Human-Machine Interfaces and Interactions (HMI2) on-board civil and military aircraft. A detailed review of these HMI2 evolutions is presented, addressing both manned aircraft (fixed and rotary wing) and Remotely Piloted Aircraft System (RPAS) specificities for the most fundamental flight tasks: aviate, navigate, communicate and manage. Due to the large variability in mission requirements, greater emphasis is given to safety-critical displays, command and control functions as well as associated technology developments. Additionally, a top-level definition of RPAS mission-essential functionalities is provided, addressing planning and real-time decision support for single and multi-aircraft operations. While current displays are able to integrate and fuse information from several sources to perform a range of different functions, these displays have limited adaptability. Further development to increase HMI2 adaptiveness has significant potential to enhance the human operator's effectiveness, thereby contributing to safer and more efficient operations. The adaptive HMI2 concepts in the literature contain three common elements. These elements comprise the ability to assess the system and environmental states; the ability to assess the operator states; and the ability to adapt the HMI2 according to the first two elements. While still an emerging area of research, HMI2 adaptation driven by human performance and cognition has the potential to greatly enhance human-machine teaming through varying the system support according to the user's needs. However, one of the outstanding challenges in the design of such adaptive systems is the development of suitable models and algorithms to describe human performance and cognitive states based on real-time sensor measurements. After reviewing the state-of-research in human performance assessment and adaptation techniques, detailed recommendations are provided to support the integration of such techniques in the HMI2 of future Communications, Navigations, Surveillance (CNS), Air Traffic Management (CNS/ATM) and Avionics (CNS + A) systems.
KW - Adaptive systems
KW - Avionics
KW - Cognitive ergonomics
KW - Human factors engineering
KW - Human performance assessment
KW - Human-machine interface and interaction
KW - Remotely piloted aircraft
KW - Remotely piloted aircraft system
KW - Trusted autonomy
KW - Unmanned aerial vehicle
KW - Unmanned aircraft system
UR - http://www.scopus.com/inward/record.url?scp=85050870877&partnerID=8YFLogxK
U2 - 10.1016/j.paerosci.2018.05.002
DO - 10.1016/j.paerosci.2018.05.002
M3 - Review article
AN - SCOPUS:85050870877
SN - 0376-0421
VL - 102
SP - 1
EP - 46
JO - Progress in Aerospace Sciences
JF - Progress in Aerospace Sciences
ER -