Despite the advances in avionics, control systems and use of advanced flight deck automation, aviation accidents still occur. Loss of Control (LOC) is one of the fundamental contributing factors to aviation accidents. LOC is caused to complex interactions between inappropriate pilot inputs, severe weather conditions, anomalies on-board etc. The ultimate goal of the Flight Safety Assessment and Management (FSAM) system is to help prevent if not minimize risk due to LOC. FSAM serves as a passive monitoring system that interferes with the operations of the flight crew/automation only if severe anomalies are detected. Based on quantitative and qualitative metrics, FSAM can identify potential risk due to violation of the safe operating envelope of the aircraft. On assessing these risks, FSAM can choose to remain passive and continue to monitor if no significant risk is identified in a given flight condition, or FSAM can choose to warn the flight crew prompting the flight crew to avoid any imminent risk scenarios. If the actions of the flight crew are inappropriate for a given risk scenario, FSAM can issue an override directive that would activate a different control authority that is appropriate for the current risk scenario.
Each phase of flight is unique with respect to crew work load and safety requirements. Hence FSAM consists of modules that enable safety assessment and management for each phase of flight. We focus on two main approaches for developing FSAM. The first approach is deterministic. In this approach, we use tools such as deterministic finite state machines to model the underlying FSAM logic. Since, this approach enables deterministic decision making, the underlying logic modules are intuitive and facilitate easy understanding by flight crews. The deterministic models can also facilitate verification, validation and certification. However, a deterministic approach does not take into account the uncertainties in the real world. Hence, the second approach focuses on modeling FSAM as a Markov Decision Process (MDP). This enables FSAM to make decisions taking into account various uncertainties.
Current research on FSAM focuses on developing logic models that prevent LOC scenarios during takeoff. Below is a demonstration of a case study illustrating the application of a takeoff FSAM. The case study focuses on the crash of Continental Airlines FL1404. A Boeing 737 aircraft veered of the runway due to severe crosswinds. The ensuing NTSB investigation concluded the following: “The captain’s cessation of rudder input, which was needed to maintain directional control of the airplane, about four seconds before the excursion, when the airplane encountered strong gusty crosswind that exceeded the captain’s training and experience.”. The simulation below illustrates the capabilities of FSAM in detecting the imminent high risk situation and appropriately overrides the flight crew to prevent LOC.
Publications related to FSAM
- S. Balachandran and E. Atkins, “An Evaluation of Flight Safety Assessment and Management to avoid Loss of Control during Takeoff,” Guidance, Navigation, and Control Conference at SciTech 2014, AIAA, Baltimore, MD, January 13-16, 2014.
- S. Balachandran and E. Atkins, “Flight Safety Assessment and Management during Takeoff,” Infotech@Aerospace Conference, AIAA, August 2013.