No abstract

No abstract

The Japan Aerospace Exploration Agency and the Japan Meteorological Agency (JMA) have jointly developed a novel system named 'Airport Low-level Wind Information' (ALWIN) to provide low-level wind information around airports. ALWIN provides wind information on aircraft final approach paths measured by JMA's airport-based Doppler radar and Doppler lidar. Pilots can request ALWIN information at any time from the cockpit by ACARS datalink. Operational evaluations by airlines demonstrated the effectiveness of ALWIN information for supporting on aircraft operations. Considering these favorable evaluations, operational use of the ALWIN system will begin in late 2016.

In this paper, a stochastic near-optimal control method is proposed for determining aircraft conflict-resolution trajectories in the presence of uncertainty in real time. The prior work developed a stochastic optimal control method for aircraft conflict resolution based on the polynomial chaos expansion and pseudospectral methods. This stochastic optimal control method is extended to generate conflict-resolution trajectories in real time without actually solving the computationally expensive stochastic optimal control problems. The proposed near-optimal conflict-resolution algorithm is based on a recently developed surrogate modeling technique called polynomial chaos kriging, which is used to construct the surrogate models of the optimal conflict-resolution trajectories from a set of precomputed optimal solutions. The near-optimal conflict-resolution trajectories can be accurately generated in real time from the surrogate models with the information of current conditions (for example, current states). Through illustrative aircraft conflict-resolution examples, the performance and effectiveness of the proposed stochastic near-optimal conflict-resolution algorithm are evaluated and demonstrated.

No abstract