Abstract
Capacity of subway station is an important factor to ensure the safety and improve the transportation efficiency. In this paper, based on the M/G/C/C state-dependent queuing model, a probabilistic selection optimization model is proposed to assess the capacity of the station. The goal of the model is to maximize the output rate of the station, and the decision variables of the model are the selection results of the passengers. Finally, this paper takes a subway station of Shanghai Metro as a case study and calculates the optimal selection probability. The proposed model could be used to analyze the average waiting time, congestion probability, and other evaluation indexes; at the same time, it verifies the validity and practicability of the model.
Highlights
Subway station plays an important role in gathering and switching passengers
Little detailed attention has been paid to the optimal routing which could maximize the inbound capacity of subway station
Based on the analysis of the characteristics of passenger receiving service from equipment in subway station, this paper constructs a network queuing model based on M/G/ C/C
Summary
Subway station plays an important role in gathering and switching passengers. Especially during peak hours, passengers may occupy the station in high densities, which has become normal phenomenon recently. Lam and Cheung [4] proposed a simulation model to analyze the relationship between pedestrian walking speed and passenger density for walking facilities in Hong Kong. These studies focus on how to simulate the features of passengers and evaluate the capacity of subway station in a microscopic aspect. Shan et al [9] constructed a congestion intensity discriminant model based on cumulative logistic regression These studies define the subway station’s capacity as the sum of each element (facility).
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