Traffic Simulation at Airport Terminal Roadway and Curbside

2000 ◽  
Author(s):  
Kuo-Yang Chang ◽  
Ali Haghani ◽  
Gloria G. Bender
Keyword(s):  
Traffic Simulation ◽  
Airport Terminal

Airport Terminal Traffic Simulation Applying Reduced Wake Vortex Separation

2010 ◽  
Author(s):  
Naoki Matayoshi ◽  
Yoshinori Okuno ◽  
Masahiko Sugiura ◽  
Mitsuru Kono ◽  
Tsutomu Yoshii ◽  
...  
Keyword(s):  
Traffic Simulation ◽  
Wake Vortex ◽  
Vortex Separation ◽  
Airport Terminal

scholarly journals COVID-19 international border surveillance at Toronto’s Pearson Airport: a cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e050714
Author(s):  
Vivek Goel ◽  
David Bulir ◽  
Eric De Prophetis ◽  
Munaza Jamil ◽  
Laura C Rosella ◽  
...  
Keyword(s):  
Well Being ◽  
Primary Objective ◽  
Control Measures ◽  
Subjective Well Being ◽  
Final Destination ◽  
Reverse Transcription Pcr ◽  
Support Strategies ◽  
Airport Terminal ◽  
International Border ◽  
Border Surveillance

ObjectivesThe primary objective was to estimate the positivity rate of air travellers coming to Toronto, Canada in September and October 2020, on arrival and on day 7 and day 14. The secondary objectives were to estimate the degree of risk based on country of origin and to assess knowledge and attitudes towards COVID-19 control measures and subjective well-being during the quarantine period.DesignProspective cohort of arriving international travellers.SettingToronto Pearson Airport Terminal 1, Toronto, Canada.ParticipantsParticipants of this study were passengers arriving on international flights. Inclusion criteria were those aged 18 or older who had a final destination within 100 km of the airport, spoke English or French, and provided consent. Excluded were those taking a connecting flight, had no internet access, exhibited symptoms of COVID-19 on arrival or were exempted from quarantine.Main outcome measuresPositive for SARS-CoV-2 virus on reverse transcription PCR with self-administered oral-nasal swab and general well-being using the WHO-5 Well-being Index.ResultsOf 16 361 passengers enrolled, 248 (1.5%, 95% CI 1.3% to 1.7%) tested positive. Of these, 167 (67%) were identified on arrival, 67 (27%) on day 7, and 14 (6%) on day 14. The positivity rate increased from 1% in September to 2% in October. Average well-being score declined from 19.8 (out of a maximum of 25) to 15.5 between arrival and day 7 (p<0.001).ConclusionsA single arrival test will pick up two-thirds of individuals who will become positive by day 14, with most of the rest detected on the second test on day 7. These results support strategies identified through mathematical models that a reduced quarantine combined with testing can be as effective as a 14-day quarantine.

Intelligent control of complex traffic conditions based on machine learning

2021 ◽  
pp. 1-12
Author(s):  
Zhe Li
Keyword(s):  
Machine Learning ◽  
Simulation Model ◽  
Traffic Simulation ◽  
Learning Algorithms ◽  
Control Model ◽  
Machine Learning Algorithms ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Conditions ◽  
Simulation Control

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.

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