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Research on Taxiway Path Optimization Based on Conflict Detection.

Zhou H, Jiang X - PLoS ONE (2015)

Bottom Line: Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety.The results indicate that the model established in this paper is effective and feasible.Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages.

View Article: PubMed Central - PubMed

Affiliation: Nanjing University of Aeronautics and Astronautics, College of Civil Aviation, Nanjing, 210016, Jiangsu, China.

ABSTRACT
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

No MeSH data available.


The flow chart of improved A* algorithm.
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pone.0134522.g004: The flow chart of improved A* algorithm.

Mentions: Prior to taking measures, it is needed to calculate the price of the passing node. The price of the mth optimal node is D(m), so the price of the most optimal node is D(1). Then, check whether there is a suboptimal node. If there is, m = m + 1, do the retrieval of the schedule for the mth optimal node. Then judge whether there is conflict or not, if there is, calculate the waiting cost at this node then turn to its suboptimal node. If there is not, calculate the price of the node, and store in the D(m) function. Repeat the process until there is no conflict in the mth optimal node or no suboptimal node, then evaluate the price of each node. At the same time, record D(m), and make a selection to choose the measure with minD(m). The process is shown in Fig 4.


Research on Taxiway Path Optimization Based on Conflict Detection.

Zhou H, Jiang X - PLoS ONE (2015)

The flow chart of improved A* algorithm.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4520455&req=5

pone.0134522.g004: The flow chart of improved A* algorithm.
Mentions: Prior to taking measures, it is needed to calculate the price of the passing node. The price of the mth optimal node is D(m), so the price of the most optimal node is D(1). Then, check whether there is a suboptimal node. If there is, m = m + 1, do the retrieval of the schedule for the mth optimal node. Then judge whether there is conflict or not, if there is, calculate the waiting cost at this node then turn to its suboptimal node. If there is not, calculate the price of the node, and store in the D(m) function. Repeat the process until there is no conflict in the mth optimal node or no suboptimal node, then evaluate the price of each node. At the same time, record D(m), and make a selection to choose the measure with minD(m). The process is shown in Fig 4.

Bottom Line: Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety.The results indicate that the model established in this paper is effective and feasible.Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages.

View Article: PubMed Central - PubMed

Affiliation: Nanjing University of Aeronautics and Astronautics, College of Civil Aviation, Nanjing, 210016, Jiangsu, China.

ABSTRACT
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

No MeSH data available.