Abstract
Evaluation of the passenger departure efficiency of a comprehensive transport hub is essential for traffic managers. Through the evaluation, security risks in the hub can be found in time to ensure the safe departure of passengers. The attention of existing studies has focused on the analysis of the overall situation of the hub, and the quantitative description of departure status in different connection areas inside the hub is insufficient. In this study, a multilayer hybrid model based on an analytic hierarchy process and entropy weight method was established. The data collected using Wi-Fi probe technology were clustered by a K-means algorithm. The first level of the model was divided according to the connection areas of the passenger hub, and the second level was based on the number of stranded people, wait time and departure time in each connection area. It was found that the SP index has the greatest impact on departure efficiency. In addition, the impact of passenger flow aggregation on each connection area is different, and the management department should treat it accordingly. The applicability of the proposed multilayer hybrid model was verified in the example of the Chongqing north railway station.
Highlights
With the urbanization and population concentration stemming from social development, the passenger volume of transportation hubs is increasing, as is passengers’ demand for travel comfort and convenience
It can be seen from the above figure that the departure efficiency at the Chongqing north railway station has an obvious time distribution, and the overall departure level of passenger flow is concentrated at level 2 and level 3
The passenger evacuation capacity of the Chongqing north railway station is above the medium level, which is consistent with our investigation
Summary
With the urbanization and population concentration stemming from social development, the passenger volume of transportation hubs is increasing, as is passengers’ demand for travel comfort and convenience. Departure efficiency is the most intuitive measure to reflect departure performance and is the most convenient measure for managers to collect data It can quantitatively evaluate the passenger flow in hubs of different transport organizations within a given period of time and provide clear guidance for the adjustment of transport capacity under different situations. We summarize the relevant studies on the analysis of passenger departure efficiency, select the appropriate detection technology to collect data, use the representative indicators to characterize passenger departure efficiency, and quantitatively evaluate the departure efficiency of hubs. Analysis shows that the flow of passenger departures in the station is a complex and continuous process, and there is a certain correlation between its operation efficiency, the connection area classification and the feelings of individual passengers.
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