Simultaneous design of different aircraft departure routes taking community noise exposure events into account

At many airports, ground track segments may be shared by different departure routes, and the population living underneath these segments is exposed to all aircraft movements which are sent to these routes. This may cause negative community reaction to authorities and policymakers, leading to objections against the expansion of airport and...

Optimization of noise abatement aircraft terminal routes using a multi-objective evolutionary algorithm based on decomposition

Recently, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) has emerged as a potential method for solving multi-objective optimization problems (MOPs) and attracted much attention from researchers. In MOEA/D, the MOPs are decomposed into a number of scalar optimization sub-problems, and these sub-problems are optimized...

A novel machine learning model to predict abnormal Runway Occupancy Times and observe related precursors

Accidents on the runway triggered the development and implementation of mitigation strategies. Therefore, the airline industry is moving toward proactive risk management, which aims to identify and predict risk percursors and to mitigate risks before accidents occur. For certain predictions Machine Learning techniques can be used. Although many...

Evaluation of feasible machine learning techniques for predicting the time to fly and aircraft speed profile on final approach: Predictive dynamic support tool on final approach

currently, at many airports, the runway throughput is the limiting factor for the overall capacity. Among the most important constraining parameters is the separation minima expressed in distance. On the top of these minima, the difference of the leader and follower aircraft speed profiles imposes to consider buffer to cope with compression...