Models of ship fuel consumption and emissions play an essential role in estimating global shipping’s greenhouse gas emissions. They are also widely used for verification of reported CO2 emissions for systems like EU MRV (Monitoring, Reporting and Verification) or IMO DCS (Data Collection System). Such models achieve high accuracy using historical spatiotemporal information about each ship from AIS data. However, this approach requires substantial computing capacity. To reduce the computational load, trajectory simplification algorithms are frequently applied. In this work, we evaluate their impact on CO2 estimations by comparing various trajectory simplification methods, including Fixed Time Downsampling, Douglas-Peucker, Top-Down Time Ratio and Optimized Equivalent Passage Plan. Through simulation and a random selection of real ship trajectories we demonstrate that by choosing the right method both, the amount of data as well the computation time can be significantly reduced while maintaining acceptable estimations of CO2 emissions.
Authors
- Tadeusz Balcer,
- dr hab. inż. Rafał Szłapczyński link open in new tab ,
- Thomas Mestl
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1016/j.oceaneng.2024.117905
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach
- Language
- angielski
- Publication year
- 2024
