Predictability impacts of airport surface automation

• We propose metrics for measuring predictability in airport surface operations.
• We assess predictability impacts of the Spot and Runway Departure Advisor (SARDA).
• SARDA provides significant gains in taxi-out time predictability.
• SARDA results in moderate reductions in the entropy of the airfield state.
• Departure sequence predictability is high with and without SARDA.

Past evaluations of airport surface operations automation technologies have focused on capacity utilization, delay mitigation and fuel efficiency impacts. Predictability, while recognized as an important operational performance goal, has received little attention. One reason could be that applicable predictability metrics have not been developed in the context of airport surface operations management. This research fills the gap by proposing metrics for predictability performance evaluation. Using results from a SARDA human-in-the-loop simulation conducted at NASA Ames’ Future Flight Central, we present a comprehensive assessment of the predictability impacts of airport surface automation. A wide range of the impacts is considered, which includes variability in taxi-out time, predictability of take-off time and take-off sequence, entropy of the airfield state, and perceived predictability from users.