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Predicting imbalanced taxi and passenger queue contexts in airport

conference contribution
posted on 2023-12-12, 03:07 authored by Mohammad Saiedur Rahaman, M Hamilton, FD Salim
The taxi and passenger queue contexts indicate the various states of queues related to taxis and passengers (i.e. taxis are waiting for passengers, passengers are waiting for taxis, both are waiting for each other, none is waiting). Predicting these queue contexts in a future time is very important for better airport ground transport operations. However, queue context prediction at the airport is a challenging problem due to the presence of different contextual factors i.e., time, weather, taxi trips, flight arrivals and many more. Also these taxi and passenger queue contexts at the airport are imbalanced since some of the contexts are very infrequently occurring compared to others. In this paper, we address the problem of predicting imbalanced taxi and passenger queue contexts at the airport. First, we investigate different contextual factors, including time, taxi trips, passengers and weather for queue context prediction. Then we propose a detailed step by step solution to address this problem. To support the effectiveness of our detailed approach, we generate a queue context dataset by fusing three real world datasets including taxi trip, passenger wait time and weather condition that represent the taxi and passenger queue contexts at a major international airport in the New York City. The experimental results demonstrate that our developed queue context prediction framework provides detailed solutions to deliver higher accuracy in queue context prediction.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1

End Page

12

Number of Pages

12

Start Date

2017-07-16

Finish Date

2017-07-20

Location

Langkawi Island, Malaysia

Publisher

Association for Information Systems

Place of Publication

Online

Peer Reviewed

  • Yes

Open Access

  • No

Era Eligible

  • Yes

Name of Conference

21st Pacific Asia Conference on Information Systems

Parent Title

Proceedings of the 21st Pacific Asia Conference on Information Systems (PACIS 2017)

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