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Prediction Method of Air-rail Transportation Passenger Flow Based on Two-stage Model: Taking Shanghai-Chengdu Corridor as an Example
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Jiuxia GUO1, Jinyu TIAN1, Qingwei ZHONG1, Qu CHEN2
Science Technology and Industry | 2025, 25(5) : 82 - 87
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Science Technology and Industry | 2025, 25(5): 82-87
• Technology Innovation •
Prediction Method of Air-rail Transportation Passenger Flow Based on Two-stage Model: Taking Shanghai-Chengdu Corridor as an Example
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Jiuxia GUO1, Jinyu TIAN1, Qingwei ZHONG1, Qu CHEN2
Affiliations
  • 1 School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, Sichuan, China
  • 2 Flight Planning Department, Civil Aviation Administration Operation Monitoring Center, Beijing 100710, China.
Published: 2025-03-10
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With the rapid construction and development of comprehensive transportation hubs, the air-rail intermodal transportation model has brought more convenience to passengers’ travel. Accurately understanding the air-rail intermodal passenger flow is crucial for improving the overall transportation service quality and ensuring transportation safety. A two-stage model combining particle swarm optimization-random forest model (PSO-RF) and Logit model is used to predict the passenger flow of travel paths in the context of air-rail intermodal transportation between urban agglomerations. Take one-way “Shifting from Railways to Aviation” as an example. In the first stage, the average daily civil aviation passenger flow of travel routes was predicted based on historical data by PSO-RF model. In the second stage, a behavioral survey was conducted through the airport outbound passengers to analyze the characteristics of passengers’ transfer mode and choice behavior. Then, a Binary Logit model of passenger travel choices was constructed based on the disaggregate theory, and the high-speed rail transfer sharing rate was calculated. Finally, the results of the two-stage model were combined to calculate the travel route passenger flow forecasts. The effectiveness and feasibility of the proposed method by constructing a case study from Shanghai to Chengdu neighboring urban agglomeration were validated. The results indicate that the accuracy of the two-stage model reaches 80.40%.

integrated transportation  /  air-rail intermodal transport  /  passenger flow forecast  /  particle swarm optimization-random forest(PSO-RF) model  /  Logit model
Jiuxia GUO, Jinyu TIAN, Qingwei ZHONG, Qu CHEN. Prediction Method of Air-rail Transportation Passenger Flow Based on Two-stage Model: Taking Shanghai-Chengdu Corridor as an Example[J]. Science Technology and Industry, 2025 , 25 (5) : 82 -87 .
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  • Receive Date：2024-09-24
  • Online Date：2025-07-21
  • Published：2025-03-10
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  • Received：2024-09-24
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Affiliations
    1 School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, Sichuan, China
    2 Flight Planning Department, Civil Aviation Administration Operation Monitoring Center, Beijing 100710, China.
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