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
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.
文摘采用减少航班推出时间的方法以达到减少航班延误时间的目的,分析了航空器推出过程中存在的冲突问题,通过在推出路径关键位置设置安全点来避免冲突;基于Agent建模理论,采用面向对象的赋时着色Petri网(Object orientedTimed Colored Petri net,OTCPN)的建模方法,对航空器的推出行为建模,并在仿真工具CPN Tools中对模型进行了分析,通过状态空间报告(State Space Report)可知模型是有界的、可行的,且不存在死点;最后,设计实现了相邻机位航班地面延误最少前提下的实际推出时间计算单元。
