Field Study and Analysis of Passenger Density in the Beijing Subway Transfer Hall
Abstract
:1. Introduction
2. Methodology
2.1. The Subway Transport Hub Case Study
2.2. Key Parameters Affecting Passenger Density
- (1)
- Surrounding land type: According to a previous study [39], passenger flows in transportation hubs are directly connected to the surrounding land type. Depending on the type of surrounding land, the passenger flow exhibits different time distribution characteristics, as follows:
- (a)
- Residential and office type: In this case, the transportation hub is mainly surrounded by residential districts and areas with houses and apartments, in addition to areas with office buildings and facilities. Under this condition, and following the characteristic of committing hours, the passenger flow in the corresponding transportation hub exhibits obvious morning and evening peaks.
- (b)
- Commercial and large hub types: In this case, the transportation hub is mainly surrounded by commercial buildings and facilities, airplanes, trains, and other rail transit systems. Due to the nature of these facilities and surrounding areas, there is no peak passenger flow on weekdays, and the transportation hub experiences a relatively consistent daily passenger flow distribution. On the other hand, passenger flow exhibits a significant peak on weekends or holidays compared with weekdays.
- (2)
- Dwell time: According to the study presented by Zhao et al. [5], dwell time is defined as the time that passengers will spend in a specific hall. Thus, it could be represented by a probability distribution due to the diversity of passengers’ preferences. It is noted here that the dwell time is influenced by the characteristics of different halls and areas, such as the floor areas and the service counters.
- (3)
- Population density: The population density refers to the number of people per unit area of the area or district surrounding the transportation hub or in a city. On this basis, it restricts the passenger flow of the transportation hub to a certain extent.
2.3. Questionnaire Survey
2.4. Field Measurement
2.5. Separation of Passengers Entering and Leaving
3. Results and Discussion
3.1. Dwell Time
3.2. Passenger Flow
3.3. Entering and Leaving Passenger Flow
4. Prediction of Passenger Density
4.1. Prediction Model
- The passengers in the transfer hall are assumed to be evenly distributed, with a consistent passenger density. On this basis, the passenger density is only related to the time parameter and is not related to the spatial parameters , , and ;
- It is assumed that all passengers in the transfer hall have the same diffusion rate, meaning that the diffusion is uniform;
- The passenger dwelling time is assumed to be consistent, thus the weighted average of the dwelling time of the passenger can be taken as the average residence time according to the survey data reported in Figure 3.
4.2. Simplified Calculation Model
4.3. Calculation Results and Model Validation
5. Conclusions
- (1)
- The passenger flow is not affected by the outdoor weather conditions and seasonality but is closely related to the passengers’ working hours and the scale of population in the surrounding office and residential areas. Additionally, there is a major variation between the passenger flow pattern reported on weekdays and that reported on weekends. On weekdays, there is an obvious “tidal” pattern in the morning and evening periods. In this regard, the passenger traffic reaches a peak at 07:00, and the cumulative passenger flow by 08:00 has reached 54.30%. Another small peak is reported at 18:00. It is also shown that the flow of passengers on weekends is much smaller than that on weekdays, with an even change in the flow of passengers. The flow of passengers on full-day weekends is 57.2% of that on full-day weekdays.
- (2)
- Based on the characteristics of passenger flow and residence time in the transfer hall of the subway transportation hub, a passenger density prediction model was established. The model was validated using actual measurement data, reporting that the proposed calculation method has good precision in terms of capturing peak and average values.
- (3)
- The characteristics of passenger density have significant influence on the design and operation processes of fresh air systems. The passenger density at 07:00 and 08:00 during the morning peak, as well as at 18:00 and 19:00 during the evening peak on weekdays, exceeds the design capacity, leading to insufficient fresh air. However, for most other times on weekdays and all weekend hours, the passenger density is below the design value, which demonstrates a large potential for energy saving by adjusting the amount of mechanical outdoor air with the variation of actual occupancy rates.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
A | Area of the transfer hall (m2) |
D | Diffusion rate of personnel |
Ii | Number of people entering the transfer hall per hour (person/h) |
I | Number of people entering the transfer hall per second (person/s) |
Oi | Number of people leaving the transfer hall per hour (person/h) |
O | Number of people leaving the transfer hall per second (person/s) |
P | Passenger density (person/m2) |
Average residence time of passengers in the transfer hall (s) | |
S | Change of the passenger density in the transfer hall per unit time (person/m2·s) |
x, y, z | Spatial coordinates |
τ | Time |
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Yu, N.; Wang, Y.; Zhou, Y.; Hu, Y.; Wu, J.; Zhang, L. Field Study and Analysis of Passenger Density in the Beijing Subway Transfer Hall. Buildings 2024, 14, 2504. https://doi.org/10.3390/buildings14082504
Yu N, Wang Y, Zhou Y, Hu Y, Wu J, Zhang L. Field Study and Analysis of Passenger Density in the Beijing Subway Transfer Hall. Buildings. 2024; 14(8):2504. https://doi.org/10.3390/buildings14082504
Chicago/Turabian StyleYu, Nan, Yanhu Wang, Yihui Zhou, Yukun Hu, Jinshun Wu, and Lining Zhang. 2024. "Field Study and Analysis of Passenger Density in the Beijing Subway Transfer Hall" Buildings 14, no. 8: 2504. https://doi.org/10.3390/buildings14082504