Understanding the Trade-Off Between Maximum Passenger Throughput and Airline Equity in Allocating Capacity Under Severe Weather Conditions

Author(s):  
Harika Jayam ◽  
Linda K. Nozick

When the capacity at an airport is reduced because of weather conditions, a ground delay program (GDP) is implemented to resolve the discrepancy between demand for arrival slots and the available arrival slots on a given day. GDPs currently ration the available arrival slots via the proportion of arrivals that exist in the schedule by airline (this practice is termed ration by schedule) with an emphasis on equity among the airlines. Existing rationing schemes do not explicitly consider the number of passengers delayed. This study examined the passenger impacts of a focus on seat throughput in reduced capacity conditions for a GDP at a single airport with consideration for airline equity. An optimization model was developed by using the number of seats available in an aircraft as a proxy for number of passengers and an equity term to estimate airline equity implications. A comparison of the current GDP rationing scheme with one focused on seat delay showed that with no change in the total flight delay time periods, passenger throughput could be improved with a threshold placed on equity. The trade-off between airline equity and passenger throughput and the implications of these results are discussed.

2008 ◽  
Vol 42 (2) ◽  
pp. 113-134 ◽  
Author(s):  
Jonathan F. Bard ◽  
Dinesh Natarajan Mohan

Networks ◽  
2008 ◽  
Vol 53 (3) ◽  
pp. 293-306 ◽  
Author(s):  
Michael Ball ◽  
Geir Dahl ◽  
Thomas Vossen

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xun Li ◽  
Zhengfan Zhao ◽  
Li Liu ◽  
Yao Liu ◽  
Pengfei Li

We proposed a signal control optimization model for urban main trunk line intersections. Four-phase intersection was analyzed and modeled based on the Cell Transmission Model (CTM). CTM and signal control model in our study had both been improved for multi-intersections by three-phase theory and information-exchanging. To achieve a real-time application, an improved genetic algorithm (GA) was proposed finally, the DISCO traffic simulation software was used for numerical simulation experiment, and comparisons with the standard GA and CTM were reported in this paper. Experimental results indicate that our searching time is less than that of SGA by 38%, and our method needs only 1/3 iteration time of SGA. According to our DISCO traffic simulation processing, compared with SGA, if the input traffic flow is changed from free phase to synchronized phase, for example, less than 900 vel/h, the delay time can reduce to 87.99% by our method, and the minimum delay time is 77.76% of existing method. Furthermore, if input traffic volume is increased to 1200 vel/h or more at the synchronized phase, the summary and minimum values of average delay time are reduced to 81.16% and 75.83%, respectively, and the average delay time is reduced to 17.72 seconds.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Liu

A route network lays in the terminal airspace. The route network can be divided into multiple subnetworks according to sectors. When severe weather conditions occur, a controller takes measures to obtain safe operation of flights, such as navigation guidance or changing the availability of routes. In such circumstances, the route structure of a subnetwork is changed, and the controller’s attention paid to each route is also changed as well as the unit workload on it. As the subnetwork is handled by one controller, capacities of routes in it are associated. We find the way to determine the “related capacity” of a route in the conditions that whether topological structure of the terminal route network is changed or not. The capacity of the terminal route network calculated by network flow theory represents the capacity of terminal airspace. According to the analysis results, the weather factor reduces capacity of terminal airspace directly by reducing the capacities of routes blocked. Indirectly, it diverts controller’s attention to change capacities of other routes in the subnetwork.


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