{"id":23771,"date":"2018-04-12T11:28:02","date_gmt":"2018-04-12T15:28:02","guid":{"rendered":"https:\/\/www.tun.com\/blog\/?p=23771"},"modified":"2022-03-16T12:04:41","modified_gmt":"2022-03-16T16:04:41","slug":"ease-air-traffic-congestion-without-sacrificing-equity","status":"publish","type":"post","link":"https:\/\/www.tun.com\/blog\/ease-air-traffic-congestion-without-sacrificing-equity\/","title":{"rendered":"Scientists Develop Model to Ease Air Traffic Congestion Without Sacrificing Equity"},"content":{"rendered":"

Researchers from Dartmouth College and Carnegie Mellon University have developed a <\/span>new model for airport flight scheduling<\/span><\/a> that promises to manage air traffic congestion without systematically favoring certain airlines over others. <\/span><\/p>\n

At the busiest airports, the combination of low capacity and heavy air traffic is a major cause of delays in the U.S., costing over $30 billion annually, according to the study. As a result, there is currently a significant effort being undertaken to review scheduling guidelines and research more efficient models. <\/span><\/p>\n

Equity, the Driving Force<\/b><\/h2>\n

The new scheduling model promises to reduce delays associated with air traffic without prioritizing landing and takeoff positions for individual airlines.<\/span><\/p>\n

The study, published in the journal <\/span>Transportation Science<\/span><\/a>, focuses on \u201cequity\u201d in scheduling, ensuring that all airlines and passengers share the benefits of the reduction in air traffic congestion.<\/span><\/p>\n

\u201cPrevious studies have focused exclusively on the overall benefits to the system as a whole, including those to all airlines and all passengers,\u201d said <\/span>Vikrant Vaze<\/span><\/a>, assistant professor of engineering at Dartmouth College and co-author of the study. \u201cHowever, that is not enough, especially when there is a risk of distributing the benefits unequally. If equity is not accounted for, then all benefits might be enjoyed by a few airlines and passengers while others might gain nothing.\u201d<\/span><\/p>\n

The new model, named the Integrated Capacity Utilization and Scheduling Model with Equity Considerations (ICUSM-E), is the first to take inter-airline equity into consideration. While there are models that allocate aviation capacity on the day of operations, this model focuses on schedule interventions that occur before schedules are published and tickets are marked.<\/span><\/p>\n

The Model<\/b><\/h2>\n

In drafting the new model, the researchers compared airport capacity estimates with the preferred flight schedules that airlines requested. <\/span><\/p>\n

Using this data, they created timetables that limit over-capacity scheduling during the airports\u2019 busiest hours. These adjustments optimized scheduling primarily by shifting demand equitably among airlines. In some cases, they considered directly reducing demand through the elimination of some flights.<\/span><\/p>\n

They also considered the general case where each flight is assigned a weight based on the costs of schedule interventions, like rescheduling or cancellation, and mechanisms used by airlines to determine the relative rescheduling costs through non-monetary credit allocation or a monetary auction-based mechanism. <\/span><\/p>\n

In addition, the researchers have used game theory in their ongoing work to build on their scheduling model. Game theory helps the researchers explain the trade-offs between efficiency and fairness when making schedule changes by allowing them to weigh the incentives of each airline against those of the airports.<\/span><\/p>\n

Taking all of these considerations and variables into account, the researchers created their scheduling model. They then tested it, first mathematically, using a slightly simplified version of the model, and then using data on demand, operations and capacity at New York\u2019s John F. Kennedy Airport.<\/span><\/p>\n

\u201cTesting and validating the research model at an airport like JFK allows us to confirm that the theory of trade-offs between equity and efficiency matches the ground reality of busy airports in the U.S.,\u201d Vaze said in a statement.<\/span><\/p>\n

By testing their model at JFK airport, the researchers effectively demonstrated that they could achieve inter-airline equity without major losses in efficiency, even at the busiest airports.<\/span><\/p>\n

\u201cA single study can\u2019t eliminate all congestion challenges at airports like JFK, but this paper suggests that important opportunities exist to make the resulting processes and policies more equitable – at virtually no cost,\u201d <\/span>Alexandre Jacquillat<\/span><\/a>, assistant professor of operations research and public policy at Carnegie Mellon and co-author of the study, said in a statement.<\/span><\/p>\n

Next Steps<\/b><\/h2>\n

As the researchers move forward, they will work to incorporate the interests of individual airlines in the scheduling model.<\/span><\/p>\n

\u201c<\/span>One shortcoming of the present study is that while it accounts for equity, it does not explicitly allow airlines to provide their own inputs in designing the airport scheduling mechanisms,\u201d said Vaze. \u201cThe next steps that we are working on right now focus on designing mechanisms wherein the airlines can provide their own inputs to the scheduling process.\u201d<\/span><\/p>\n

To do so, the researchers need to find an efficient means for airlines to suggest their desired inputs and develop methods to combine these inputs to design schedules that benefit the various stakeholders, he explained.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers from Dartmouth College and Carnegie Mellon University have developed a new model for airport flight scheduling that promises to manage air traffic congestion without systematically favoring certain airlines over others. At the busiest airports, the combination of low capacity and heavy air traffic is a major cause of delays in the U.S., costing over […]<\/p>\n","protected":false},"author":61,"featured_media":45650,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[232,230,229],"tags":[],"class_list":["post-23771","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","category-news","category-lead-stories"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg",830,533,false],"thumbnail":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion-224x144.jpg",224,144,true],"medium":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion-300x193.jpg",300,193,true],"medium_large":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg",830,533,false],"large":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg",830,533,false],"1536x1536":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg",830,533,false],"2048x2048":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg",830,533,false]},"uagb_author_info":{"display_name":"Sam Benezra","author_link":"https:\/\/www.tun.com\/blog\/author\/sam-benezra\/"},"uagb_comment_info":0,"uagb_excerpt":"Researchers from Dartmouth College and Carnegie Mellon University have developed a new model for airport flight scheduling that promises to manage air traffic congestion without systematically favoring certain airlines over others. At the busiest airports, the combination of low capacity and heavy air traffic is a major cause of delays in the U.S., costing over…","featured_media_src_url":"https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/04\/Air-Traffic-Congestion.jpg","_links":{"self":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts\/23771","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/users\/61"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/comments?post=23771"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts\/23771\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/media\/45650"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/media?parent=23771"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/categories?post=23771"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/tags?post=23771"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}