TY - GEN
T1 - Simulation of Real-time Routing for UAS traffic Management with Communication and Airspace Safety Considerations
AU - Jin, Zhao
AU - Zhao, Ziyi
AU - Luo, Chen
AU - Basti, Franco
AU - Solomon, Adrian
AU - Gursoy, M. Cenk
AU - Caicedo, Carlos
AU - Qiu, Qinru
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
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 routing and management functions are needed to coordinate the launching of sUAS from different launch sites and determine 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 airborne 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 and simulation platform for sUAS trajectory management in a high density urban area that plans sUAS movements in a spatial and temporal maze taking into account 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 other 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, conflict rate and communication resource utilization. The results demonstrate that our proposed algorithm can be used to address the airspace and communication resource utilization needs for a 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 routing and management functions are needed to coordinate the launching of sUAS from different launch sites and determine 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 airborne 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 and simulation platform for sUAS trajectory management in a high density urban area that plans sUAS movements in a spatial and temporal maze taking into account 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 other 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, conflict rate and communication resource utilization. The results demonstrate that our proposed algorithm can be used to address the airspace and communication resource utilization needs for a next generation smart city and smart transportation.
KW - UTM
KW - sUAS
KW - smart city
KW - temporal-spatial traffic management
KW - trajectory routing
UR - http://www.scopus.com/inward/record.url?scp=85084740433&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084740433&partnerID=8YFLogxK
U2 - 10.1109/DASC43569.2019.9081675
DO - 10.1109/DASC43569.2019.9081675
M3 - Conference contribution
AN - SCOPUS:85084740433
T3 - AIAA/IEEE Digital Avionics Systems Conference - Proceedings
BT - DASC 2019 - 38th Digital Avionics Systems Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th IEEE/AIAA Digital Avionics Systems Conference, DASC 2019
Y2 - 8 September 2019 through 12 September 2019
ER -