TY - GEN
T1 - Capacity estimation for airspaces with convective weather constraints
AU - Krozel, Jimmy
AU - Mitchell, Joseph S.B.
AU - Polishchuk, Valentin
AU - Prete, Joseph
PY - 2007
Y1 - 2007
N2 - We estimate the capacity of a generic airspace region given convective weather constraints and various operational conditions. We model en route airspace for future operations where jetway routing is removed and aircraft paths may conform with the geometry of hazardous weather constraints. Within a constant flight level, decentralized and centralized control of traffic are considered. Decentralized, Free Flight operational conditions consider aircraft flying in any direction vs alternating altitude rules. Centralized operational conditions consider traffic that monotonically progresses in one primary direction and a unidirectional flow where all traffic must remain within pre-defined flows (e.g., from West to East). Under these conditions, we compute the theoretical maximum capacity and compare it to algorithmic solutions. Additionally, we compute the capacity when aircraft fly in platoons - two or more aircraft flying in the same direction in close proximity - in order to understand the effect of platooning on airspace capacity. Finally, we define a complexity metric, and compare the complexity of the resulting traffic flows under each experimental condition.
AB - We estimate the capacity of a generic airspace region given convective weather constraints and various operational conditions. We model en route airspace for future operations where jetway routing is removed and aircraft paths may conform with the geometry of hazardous weather constraints. Within a constant flight level, decentralized and centralized control of traffic are considered. Decentralized, Free Flight operational conditions consider aircraft flying in any direction vs alternating altitude rules. Centralized operational conditions consider traffic that monotonically progresses in one primary direction and a unidirectional flow where all traffic must remain within pre-defined flows (e.g., from West to East). Under these conditions, we compute the theoretical maximum capacity and compare it to algorithmic solutions. Additionally, we compute the capacity when aircraft fly in platoons - two or more aircraft flying in the same direction in close proximity - in order to understand the effect of platooning on airspace capacity. Finally, we define a complexity metric, and compare the complexity of the resulting traffic flows under each experimental condition.
UR - https://www.scopus.com/pages/publications/37249053291
M3 - Conference contribution
AN - SCOPUS:37249053291
SN - 1563479044
SN - 9781563479045
T3 - Collection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007
SP - 1518
EP - 1532
BT - Collection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007
T2 - AIAA Guidance, Navigation, and Control Conference 2007
Y2 - 20 August 2007 through 23 August 2007
ER -