Airport Arrival Passengers Trip Chain Generating Method Based on Multiple Spatiotemporal Traveling Segments

Intelligent passenger guidance systems are able to improve travel experience for passengers, and to enhance airport operating efficiency. In this paper, an airport arrival passengers trip chain generating method based on multiple spatiotemporal traveling segments is proposed. Trip chain is divided into two spatiotemporal segments: in and out of the airport terminal building. For the in-door segment, the cost time is calculated with walking time between different infrastructures and waiting time in the transit. For the segment of out-door situation, carrying time on carriers has been estimated. BPR model and queue theory are applied to estimate the walking time, and BP neural network is adopted for carrying time. A passenger guidance platform is built to verify the proposed method, and the real scenario test is conducted. It’s found the method can accurately estimate time cost comparing with passenger historical data, and the optimized trip chain can notably reduce passenger travel time.

Language

  • English

Media Info

  • Media Type: Web
  • Pagination: pp 700-712
  • Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

Filing Info

  • Accession Number: 01767359
  • Record Type: Publication
  • ISBN: 9780784483053
  • Files: TRIS, ASCE
  • Created Date: Dec 9 2020 3:02PM