Developing Models for Managing Drones in the Transportation System in Smart Cities

Authors

DOI:

https://doi.org/10.2478/ecce-2019-0010

Keywords:

Air transportation, Mathematical model, Path planning, Safety management, Vehicle routing

Abstract

Unmanned aerial vehicles (UAVs), especially drones, have advantages of having applications in different areas, including agriculture, transportation, such as land use surveys and traffic surveillance, and weather research. Many network protocols are architected for the communication between multiple drones. The present study proposes drone-following models for managing drones in the transportation management system in smart cities. These models are based on the initial idea that drones flight towards a leading drone in the traffic flow. Such models are described by the relative distance and velocity functions. Two types of drone-following models are presented in the study. The first model is a safe distance model (SD model), in which a safe distance between a drone and its ahead is maintained. By applying the stochastic diffusion process, an improved model, called Markov model, is deduced. These drone-following models are simulated in a 2D environment using numerical simulation techniques. With the simulation results, it could be noted that: i) there is no accident and no unrealistic deceleration; ii) the velocity of the followed drone is changed according to the speed of the drone ahead; iii) the followed drones keep a safe distance to drone ahead even the velocities are changed; iv) the performance of the Markov model is better than that of the SD model.

References

F. Castaldi, F. Pelosi, S. Pascucci, and R. Casa, “Assessing the Potential of Images from Unmanned Aerial Vehicles (UAV) to Support Herbicide Patch Spraying in Maize,” Precision agriculture, vol. 18, no. 1, pp. 76–94, Aug. 2016. https://doi.org/10.1007/s11119-016-9468-3

A. Capolupo, S. Pindozzi, C. Okello, N. Fiorentino, and L. Boccia, “Photogrammetry for Environmental Monitoring: The Use of Drones and Hydrological Models for Detection of Soil Contaminated by Copper,” Science of the Total Environment, vol. 514, pp. 298–306, May 2015. https://doi.org/10.1016/j.scitotenv.2015.01.109

P. Chamberlain, Drones and Journalism: How the Media is Making Use of Unmanned Aerial Vehicles. Routledge, 2017.

A. Puri, “A Survey of Unmanned Aerial Vehicles (UAV) for Traffic Surveillance,” Department of computer science and engineering, University of South Florida – internal report, pp. 1–29, Jan. 2005.

C. A. Thiels, J. M. Aho, S. P. Zietlow, and D. H. Jenkins, “Use of Unmanned Aerial Vehicles for Medical Product Transport,” Air Medical Journal, vol. 34, iss. 2, pp. 104–108, Mar. 2015. https://doi.org/10.1016/j.amj.2014.10.011

F. Mohammed, A. Idries, N. Mohamed, J. Al-Jaroodi, and I. Jawhar, “UAVs for Smart Cities: Opportunities and Challenges,” in Proc. 2014 Int. Conf. Unmanned Aircr. Syst. (ICUAS), 2014, pp. 267–273. https://doi.org/10.1109/ICUAS.2014.6842265

E. Vattapparamban, İ. Güvenç, A. İ. Yurekli, K. Akkaya, and S. Uluağaç, “Drones for Smart Cities: Issues in Cybersecurity, Privacy, and Public Safety,” in 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), Sep. 2016, pp. 216–221. https://doi.org/10.1109/IWCMC.2016.7577060

D. Wu, D. I. Arkhipov, M. Kim, C. L. Talcott, A. C. Regan, J. A. McCann, and N. Venkatasubramanian, 2016. “ADDSEN: Adaptive Data Processing and Dissemination for Drone Swarms in Urban Sensing,” IEEE Trans. Comput., pp. 1–1, 2016. http://dx.doi.org/10.1109/TC.2016.2584061

K. R. Sapkota, S. Roelofsen, A. Rozantsev, V. Lepetit, D. Gillet, P. Fua, and A. Martinoli, “Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems,” in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1556–1561, Oct. 2016. https://doi.org/10.1109/IROS.2016.7759252

Y. Zhao and H. Pei, “An Improved Vision-Based Algorithm for Unmanned Aerial Vehicles Autonomous Landing,” Phys. Procedia, vol. 33, pp. 935–941, 2012. http://dx.doi.org/10.1016/j.phpro.2012.05.157

E. Vattapparamban, İ. Güvenç, A. İ. Yurekli, K. Akkaya, and S. Uluağaç, “Drones for Smart Cities: Issues in Cybersecurity, Privacy, and Public Safety,” in 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), Sep. 2016, pp. 216–221. https://doi.org/10.1109/IWCMC.2016.7577060

“Commercial Drone Shipments to Surpass 2.6 Million Units Annually by 2025” [Online]. Tractica. Available: https://www.tractica.com/newsroom/press-releases/commercial-drone-shipments-to-surpass-2-6-million-units-annually-by-2025-according-totractica/ [Accessed: 21 Mar. 2019].

R. M. Thompson, Drones in Domestic Surveillance Operations: Fourth Amendment Implications and Legislative Responses. Congressional Research Service, Library of Congress, Sep. 2012.

International Civil Aviation Organization (ICAO), Unmanned aircraft systems (UAS), ICAO Cir 328 AN/190, 2011. Available: https://www.icao.int/Meetings/UAS/Documents/Circular%20328_en.pdf [Accessed: 22 June 2019].

International Civil Aviation Organization (ICAO), DOC 9859 AN/460 Safety Management Manual (SMM), 1st ed., 2006.

Z. Sándor, “Challenges Caused by the Unmanned Aerial Vehicle in the Air Traffic Management”, Periodica Polytechnica Transportation Engineering, vol. 47, iss. 2, pp. 96–105, Dec 2017. https://doi.org/10.3311/PPtr.11204

T. Péter and K. Szabó, “A New Network Model for the Analysis of Air Traffic Networks”, Periodica Polytechnica Transportation Engineering, vol. 40, iss. 1, pp. 39–44, 2012. https://doi.org/10.3311/pp.tr.2012-1.07

G. Fedorko, V. Žofčinová, and V. Molnár, “Legal Aspects Concerning Use of Drones in the Conditions of the Slovak Republic Within the Sphere of Intra-Logistics”, Periodica Polytechnica Transportation Engineering, vol. 46, iss. 4, pp. 17–84, Mar. 2018. https://doi.org/10.3311/PPtr.12131

E. N. Barmpounakis, E. I. Vlahogianni, and J. C. Golias, “Unmanned Aerial Aircraft Systems for Transportation Engineering: Current Practice and Future Challenges,” International Journal of Transportation Science and Technology, vol. 5, no. 3, pp. 111–122, Oct. 2016. https://doi.org/10.1016/j.ijtst.2017.02.001

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Published

01.12.2019

How to Cite

Dung, N. D. (2019). Developing Models for Managing Drones in the Transportation System in Smart Cities. Electrical, Control and Communication Engineering, 15(2), 71-78. https://doi.org/10.2478/ecce-2019-0010