Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic ...Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control(PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the leastsquares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport(PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1%reduction, respectively, as compared to the traditional K-control policy.(3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%,respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.展开更多
Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajec...Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.展开更多
基金partially supported by the National Natural Science Foundation of China-Civil Aviation Joint Fund(Nos.U1533203,U1233124.)
文摘Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control(PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the leastsquares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport(PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1%reduction, respectively, as compared to the traditional K-control policy.(3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%,respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.
基金financial support from the Civil Aviation Joint Funds of the National Natural Science Foundation of China (No’s.U1533203,61179069)
文摘Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.
