TY - GEN
T1 - Temporal and spatial routing for large scale safe and connected UAS traffic management in urban areas
AU - Zhao, Ziyi
AU - Jin, Zhao
AU - Luo, Chen
AU - Fang, Haowen
AU - Basti, Franco
AU - Cenk Gursoy, M.
AU - Caicedo, Carlos
AU - Qiu, Qinru
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Small Unmanned Aircraft Systems (sUAS) will be an important component of the smart city and intelligent transportation environments of the near future. The demand for sUAS related applications, such as commercial delivery and land surveying, is expected to grow rapidly in next few years. In general, sUAS traffic scheduling and management functions are needed to coordinate the launching of sUAS from different launch sites and plan their trajectories to avoid conflict while considering several other constraints such as expected arrival time, minimum flight energy, and availability of communication resources. However, as the airbone sUAS density grows in a certain area, it is difficult to foresee the potential airspace and communications resource conflicts and make immediate decisions to avoid them. To address this challenge, we present a temporal and spatial routing algorithm for sUAS trajectory management in a high density urban area. It plans sUAS movements in a spatial and temporal maze with the consideration of obstacles that are either static or dynamic in time. The routing allows the sUAS to avoid static no-fly areas (i.e. static obstacles) or other in-flight sUAS and areas that have congested communication resources (i.e. dynamic obstacles). The algorithm is evaluated using an agent-based simulation platform. The simulation results show that the proposed algorithm outperforms reference route management algorithms in many areas, especially in processing speed and memory efficiency. Detailed comparisons are provided for the sUAS flight time, the overall throughput, the conflict rate and communication resource utilization. The results demonstrate that our proposed algorithm can be used as a solution to improve the efficiency of airspace and communication resource utilization for next generation smart city and smart transportation.
AB - Small Unmanned Aircraft Systems (sUAS) will be an important component of the smart city and intelligent transportation environments of the near future. The demand for sUAS related applications, such as commercial delivery and land surveying, is expected to grow rapidly in next few years. In general, sUAS traffic scheduling and management functions are needed to coordinate the launching of sUAS from different launch sites and plan their trajectories to avoid conflict while considering several other constraints such as expected arrival time, minimum flight energy, and availability of communication resources. However, as the airbone sUAS density grows in a certain area, it is difficult to foresee the potential airspace and communications resource conflicts and make immediate decisions to avoid them. To address this challenge, we present a temporal and spatial routing algorithm for sUAS trajectory management in a high density urban area. It plans sUAS movements in a spatial and temporal maze with the consideration of obstacles that are either static or dynamic in time. The routing allows the sUAS to avoid static no-fly areas (i.e. static obstacles) or other in-flight sUAS and areas that have congested communication resources (i.e. dynamic obstacles). The algorithm is evaluated using an agent-based simulation platform. The simulation results show that the proposed algorithm outperforms reference route management algorithms in many areas, especially in processing speed and memory efficiency. Detailed comparisons are provided for the sUAS flight time, the overall throughput, the conflict rate and communication resource utilization. The results demonstrate that our proposed algorithm can be used as a solution to improve the efficiency of airspace and communication resource utilization for next generation smart city and smart transportation.
KW - Smart city
KW - Temporal-spatial traffic management
KW - Trajectory routing
KW - UTM
KW - sUAS
UR - http://www.scopus.com/inward/record.url?scp=85074205669&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074205669&partnerID=8YFLogxK
U2 - 10.1109/RTCSA.2019.8864561
DO - 10.1109/RTCSA.2019.8864561
M3 - Conference contribution
AN - SCOPUS:85074205669
T3 - Proceedings - 2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2019
BT - Proceedings - 2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2019
Y2 - 18 August 2019 through 21 August 2019
ER -