The hotspot recognition algorithm is proposed based on a potential collision in order to study the
aircraft taxi conflicts in large airports. The spatial and temporal distribution characteristics of hotspots are analyzed
based on the risk assessment model of hotspot constructed in this paper. Firstly, approaches for monitoring
of the aerodrome movement were compared. The hotspot recognition algorithm taken into account of whether
aircrafts’ taxi track has spatial and temporal overlap based on the aerodrome surveillance radar (ASR) data was
presented, by identifying the hotspots through analyzing whether the aircrafts’ time of entering and exiting the
same taxiway is overlap or not, and the heading difference and distance of the two aircrafts satisfy the specified
threshold constraint condition. Then, the ASR data were divided into several parts, and then airport hotspots
were recognized and the spatial and temporal distribution characteristics were analyzed. The risk assessment
model of airport safety hotspots was constructed which is taken into account of the conflict probability and its
severity consequence. Finally, based on the risk grade assessment criteria and hotspots’ risk value, the risk grade
ranking of hotspot in one airport of China was evaluated and designated. According to the result, the spatial and
temporal distribution characteristics of airport hotspots were varied with the variation of airport traffic flow and
operational mode of runway, which shows that the hotspots have the characteristics of dynamic periodicity and
diurnal variation. And the risk assessment results were consistent with experts’ opinions and actual operation
condition, which verified the rationality of the hotspot recognition algorithm, risk assessment model as well as the
risk grade ranking criteria.
XIA Zhenghong (夏正洪)
,
ZHENG Bo (郑波)
,
WAN Jian (万健)
,
ZHU Xinping (朱新平)
. Recognition Algorithm and Risk Assessment of Airport Hotspots[J]. Journal of Shanghai Jiaotong University(Science), 2019
, 24(6)
: 769
-774
.
DOI: 10.1007/s12204-019-2110-6
[1] International Civil Aviation Organization. Proceduresfor air navigation services: Air traffic management:Doc 4444 [S]. Montreal, Canada: International CivilAviation Organization, 2007: 1-9.
[2] Federal Aviation Administration. Airport diagramedhotspots [EB/OL]. [2018-07-20]. http://aeronav.faa.gov/afd/12Dec2013/NE hotspot 12Dec 2013.pdf.
[3] GONG S L, WANG B F, WU H L. Tracking of movingtargets on airport surface based on IMM Algorithm[J]. Systems Engineering and Electronics, 2011,33(10): 2322-2326 (in Chinese).
[4] HUO Z Q. Research on hotspots identification in aerodromethrough the triple selection method [J]. ChinaSafety Science Journal, 2012, 22(3): 92-96 (in Chinese).
[5] WANG Y Y, CAO Y H, LI J. Civil aviation risk modelbased on RON neural network [C]// 12th COTA InternationalConference of Transportation Professionals.Beijing, China: American Society of Civil Engineers,2012: 1828-1836.
[6] COLL B, MOUTARI S, MARSHALL A H. Hotspotsidentification and ranking for road safety improvement:An alternative approach [J]. Accident Analysisand Prevention, 2013, 59: 604-617.
[7] MOU Q F, FENG X L. Collision detection technologyof taxiing aircraft [J]. China Safety Science Journal,2013, 23(12): 84-89 (in Chinese).
[8] MOU Q F, FENG X L, XIANG S L. Design and realizationof conflict detection alarm system for airportsurface [J]. Journal of Sichuan University (EngineeringScience Edition), 2015, 47(4): 104-110 (in Chinese).
[9] PAN W J, WANG X, XIA Z H. Aircraft taxiingmethod for skirting around airport hotspots [J].Computer Engineering and Design, 2015, 36(12):3324-3327 (in Chinese).
[10] PAN W J, LUO X L, KANG R. Assessment modelof conflict probability at airport surface intersection[J]. Journal of System Simulation, 2016, 28(12): 2918-2924 (in Chinese).
[11] WANG J N, ZHAO X P. Research on ontology modelingand intelligent level ranking of airport safetyhotspots [J]. China Safety Science Journal, 2016,26(5): 47-52 (in Chinese).
[12] XIA Z H, PAN W J, KANG R, et al. Research on theidentification and level ranking approaches of airportconflict hotspots [J]. Science Technology and Engineering,2014, 14(21): 297-301 (in Chinese).
[13] XIA Z H,WU Y Z, PANWJ. Research on aircraft taxiconflict detecting based on multi camera [J]. ComputerMeasurement & Control, 2015, 23(9): 2979-2982 (inChinese).
[14] XIA Z H, WU Y Z, LU G P. The detection of aircraftconflicts based on video image processing [J]. Science& Technology Review, 2015, 33(12): 24-28 (in Chinese).
[15] XIA Z H, WAN J, ZHU X P. Airport hotspot recognitionmethod considering spatial and temporal overlapof aircraft taxiing track [J]. China Safety Science Journal,2017, 27(5): 76-80 (in Chinese).
[16] WANG L, SUN R S,WU C X, et al. A flight QAR databased model for hard landing risk quantitative evaluation[J]. China Safety Science Journal, 2014, 24(2):88-92 (in Chinese).
