Di Ciccio, Claudio and van der Aa, Han and Cabanillas Macias, Cristina and Mendling, Jan and Prescher, Johannes. 2016. Detecting flight trajectory anomalies and predicting diversions in freight transportation. Decision Support Systems 88 S. 1-17.
BibTeX
Abstract
Timely identifying flight diversions is a crucial aspect of efficient multi-modal transportation. When an airplane diverts, logistics providers must promptly adapt their transportation plans in order to ensure proper delivery despite such an unexpected event. In practice, the different parties in a logistics chain do not exchange real-time information related to flights. This calls for a means to detect diversions that just requires publicly available data, thus being independent of the communication between different parties. The dependence on public data results in a challenge to detect anomalous behavior without knowing the planned flight trajectory. Our work addresses this challenge by introducing a prediction model that just requires information on an airplane's position, velocity, and intended destination. This information is used to distinguish between regular and anomalous behavior. When an airplane displays anomalous behavior for an extended period of time, the model predicts a diversion. A quantitative evaluation shows that this approach is able to detect diverting airplanes with excellent precision and recall even without knowing planned trajectories as required by related research. By utilizing the proposed prediction model, logistics companies gain a significant amount of response time for these cases.
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Status of publication | Published |
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Affiliation | WU |
Type of publication | Journal article |
Journal | Decision Support Systems (DSS) |
Citation Index | SCI |
Language | English |
Title | Detecting flight trajectory anomalies and predicting diversions in freight transportation |
Volume | 88 |
Year | 2016 |
Page from | 1 |
Page to | 17 |
Reviewed? | Y |
URL | http://www.sciencedirect.com/science/article/pii/S016792361630077X |
DOI | http://dx.doi.org/10.1016/j.dss.2016.05.004 |
Associations
- Projects
- European Wide Service Platform for Green European Transportation
- People
- Di Ciccio, Claudio (Former researcher)
- Cabanillas Macias, Cristina (Former researcher)
- Mendling, Jan (Details)
- Prescher, Johannes (Former researcher)
- External
- van der Aa, Han (VU University, Amsterdam, Netherlands)
- Organization
- Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
- Research areas (Ă–STAT Classification 'Statistik Austria')
- 1105 Computer software (Details)
- 1108 Informatics (Details)
- 1109 Information and data processing (Details)
- 1112 Logistics (Details)
- 1122 Artificial intelligence (Details)
- 1127 Information science (Details)