Collisions between birds and aircraft pose a severe threat to aviation and avian safety. To understand and prevent these bird strikes, knowledge about the factors leading to these bird strikes is vital. However, even though it is a global issue, data availability strongly varies and is difficult to put into a global picture. This paper aims to close this gap by providing an in-depth review of studies and statistics to obtain a concise overview of the bird strike problem in commercial aviation on an international level. The paper illustrates the factors contributing to the occurrence and the potential consequences in terms of effect on flight and damage. This is followed by a presentation of the risk-reducing measures currently in place as well as their limitations. The paper closes with an insight into current research investigating novel methods to prevent bird strikes.

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In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity. Optimal workload conditions are important for assuring employee's health and safety of other persons. This is particularly relevant in safety-critical occupations, such as air traffic control. For measuring mental workload using the EEG, we have developed the method of Dual Frequency Head Maps (DFHM). The method was tested and validated already under laboratory conditions. However, validation of the method regarding reliability and reproducibility of results under realistic settings and real world scenarios was still required. In our study, we examined 21 air traffic controllers during arrival management tasks. Mental workload variations were achieved by simulation scenarios with different number of aircraft and the occurrence of a priority-flight request as an exceptional event. The workload was assessed using the EEG-based DFHM-workload index and instantaneous self-assessment questionnaire. The DFHM-workload index gave stable results with highly significant correlations between scenarios with similar traffic-load conditions (r between 0.671 and 0.809, p ≤ 0.001). For subjects reporting that they experienced workload variation between the different scenarios, the DFHM-workload index yielded significant differences between traffic-load levels and priority-flight request conditions. For subjects who did not report to experience workload variations between the scenarios, the DFHM-workload index did not yield any significant differences for any of the factors. We currently conclude that the DFHM-workload index reveals potential for applications outside the laboratory and yields stable results without retraining of the classifiers neither regarding new subjects nor new tasks.

Annually, thousands of birds collide with aircraft. The impact usually has lethal consequences for the bird, the involved aircraft can experience severe damage. The highest bird strike risk occurs at low altitudes. Therefore, aircraft within the airport area as well as the adjacent approach and departure corridors are especially vulnerable to collisions with birds. To analyse risk-reducing measures in these areas, a fast-time bird strike simulation environment was developed. An open-source Air Traffic Management simulator was enhanced with a model to represent bird movements and to recognize bird strikes. To confirm the reproducibility of the outcome, Monte Carlo simulations were performed. They included bird movement data from one year and air traffic flight plans for various air traffic volumes. The number of strikes and near misses showed an expected variance within the individual replications. The results indicate that the predictability of the number of strikes and near misses increases with rising number of birds, and rising air traffic intensity. Thus, by considering simulation scenarios including bird movement information from all seasons and a sufficient air traffic volume, the described set-up leads to stable results.