Abstract
When passengers are oversaturated in the urban rail transit system and a further increase of train frequency is impossible, passenger flow control strategy is an indispensable approach to avoid congestion and ensure safety. To make the best use of train capacity and reduce the passenger waiting time, coordinative flow control is necessary at each station on a line. In most published studies, the equilibrium of passenger distributions among different stations and periods is not considered. As a result, two issues occur making it hard to implement in practical. First, a large number of passengers are held up outside a small number of stations for very long time. Second, there is a large variation of controlled flows for successive time intervals. To alleviate this problem, a single-line equilibrium passenger flow control model is constructed, which minimizes the total passenger delay. By applying different forms of the delay penalty function (constant and linear), flow control strategies such as independent flow control and equilibrium flow control can be reproduced. An improved simulated annealing algorithm is proposed to solve the model. A numerical case is studied to analyze the sensitivity of the functions, and the best parameter relationship in different functions could be confirmed. A real-world case from Batong Line corridor in Beijing subway is used to test the applicability of the model and algorithm, and the result shows that the solution with linear delay penalty functions can not only reduce the total passenger delay but also equilibrate the number of flow control passengers on spatial and temporal.
Highlights
(3) An improved simulated annealing algorithm was constructed to solve the proposed models, which was based on the random disturbance operator. e algorithm could solve the model with high accuracy and high efficiency
Different from coordination strategy, the equilibrium strategy may waste the efficiency, but it makes the boarding probability of passengers in different stations similar. e flow control strategy we proposed contains two aspects of equilibrium, the temporal and spatial equilibrium. e temporal equilibrium means that the number of
It is important to develop an easy methodology which can provide a good solution within acceptable computation time. erefore, we develop a heuristic algorithm, namely, improved simulated annealing (ISA) algorithm, to obtain a feasible solution for the passenger flow control problem
Summary
It is in east-west direction and has a total length of 18.964 km. 8 stations of Batong line were controlled to carry out flow control strategy in morning peak period since 2015, so we select the down direction of the Batong Line and use the 7:00∼9:00 (120 minutes horizon) of the morning peak on May 20, 2015 (Wednesday) as a case. E capacity of platform at each station CapPs is shown, which is the product of the platform active area and the maximum passenger gathering density. Except for the terminal station (Sihui station), the platforms of all stations on the Batong line are side type instead of island type, which is easy to control the inflow in down direction by setting up the fencing facility at the halls. e arrival time of train 1 at each station of Batong Line is shown in Table 12. e train departure headway f is 3 minutes; we can get the train departure time parameters Ls,r(t). e capacity of platform at each station CapPs is shown in Table 12, which is the product of the platform active area and the maximum passenger gathering density. e platform active area is the passenger usable area that is the total platform area minus the occupied area by the infrastructures, and the data are from the on-site survey. e maximum passenger gathering density is 2 pax/m2, because the passengers may be in
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