TY - GEN
T1 - A deviation flow refueling location model for continuous space
T2 - 13th International Conference on Advances in Geocomputation, Geocomputation 2015
AU - Hong, Insu
AU - Kuby, Michael
AU - Murray, Alan
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2017.
PY - 2017
Y1 - 2017
N2 - Drones, which refer to a range of small-sized unmanned aerial vehicles propelled by multiple rotors, recently have been utilized for various purposes, such as military, surveillance, photography, and entertainment. Delivery service for small products is one of their potential applications, and optimal path planning is essential for operational efficiency of such a delivery service. Because a drone’s movement is not limited to existing transportation networks, path planning needs to be conducted in continuous space while taking into account obstacles for flight.However, due to the limited flight range of battery-powered drones, multiple recharging stations are required in large urban areas to complete delivery without running out of power. In this chapter, we present a new coverage model that can optimize the location of recharging stations for delivery drones as well as ensure construction of a feasible delivery network that connects the stations and covered demand based on continuous space shortest paths. A heuristic solution technique is utilized for the optimization of station locations. Application results show the effectiveness of our model for construction of a drone delivery network that covers a large urban area.
AB - Drones, which refer to a range of small-sized unmanned aerial vehicles propelled by multiple rotors, recently have been utilized for various purposes, such as military, surveillance, photography, and entertainment. Delivery service for small products is one of their potential applications, and optimal path planning is essential for operational efficiency of such a delivery service. Because a drone’s movement is not limited to existing transportation networks, path planning needs to be conducted in continuous space while taking into account obstacles for flight.However, due to the limited flight range of battery-powered drones, multiple recharging stations are required in large urban areas to complete delivery without running out of power. In this chapter, we present a new coverage model that can optimize the location of recharging stations for delivery drones as well as ensure construction of a feasible delivery network that connects the stations and covered demand based on continuous space shortest paths. A heuristic solution technique is utilized for the optimization of station locations. Application results show the effectiveness of our model for construction of a drone delivery network that covers a large urban area.
KW - Coverage location model
KW - Drone
KW - Euclidean shortest path
UR - http://www.scopus.com/inward/record.url?scp=85010065626&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85010065626&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-22786-3_12
DO - 10.1007/978-3-319-22786-3_12
M3 - Conference contribution
AN - SCOPUS:85010065626
SN - 9783319227856
T3 - Advances in Geographic Information Science
SP - 125
EP - 132
BT - Advances in Geocomputation - Geocomputation 2015—The 13th International Conference
A2 - Griffith, Daniel A.
A2 - Chun, Yongwan
A2 - Dean, Denis J.
PB - Springer Heidelberg
Y2 - 20 May 2015 through 23 May 2015
ER -