Dubins-Based Trajectories: Enhancing Smart Air Traffic Management for Energy-Efficient Environments
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-55787-3_1
Reference11 articles.
1. Guan, X., Lv, R., Sun, L., Liu, Y.: A study of 4D trajectory prediction based on machine deep learning. In: Proceedings of the World Congress on Intelligent Control and Automation (WCICA), pp. 24–27, 2016. https://doi.org/10.1109/WCICA.2016.7578458
2. Hammad, A.W.A., David, R., Bu-Qammaz, A., Grzybowska, Hanna, Akbarnezhad, A.: Mathematical optimization in enhancing the sustainability of aircraft trajectory: A review. Int. J. Sustain. Transp. 14(6), 413–436 (2020)
3. Klooster, J.K., Wichman, K.D., Bleeker, O.F.: 4D trajectory and time-of-arrival control to enable Continuous Descent Arrivals. AIAA Guid. Navig. Control. Conf. Exhib. (2008). https://doi.org/10.2514/6.2008-7402
4. Lin, Y., Saripalli, S.: “Path planning using 3D Dubins Curve for Unmanned Aerial Vehicles. In: 2014 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 296–304, 2014. https://doi.org/10.1109/ICUAS.2014.6842268.
5. Mohanad Al Nuaimi, Analysis and comparison of clothoid and Dubins algorithms for UAV trajectory generation, West Virginia University, 2014
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