Analytical Approximation-Based Approach for Passenger Flow Control Strategy in Oversaturated Urban Rail Transit Systems

Focusing on a heavily congested urban rail corridor, this study investigates the passenger flow control strategy optimization problem from a mesoscopic perspective to reduce platform congestion and enhance service quality. Based on a quadratic functional approximation for passenger arrival rates, an...

Full description

Saved in:
Bibliographic Details
Published inJournal of advanced transportation Vol. 2023; pp. 1 - 21
Main Authors Zhu, Qian, Zhu, Xiaoning, Shang, Pan, Meng, Lingyun
Format Journal Article
LanguageEnglish
Published London Hindawi 23.06.2023
John Wiley & Sons, Inc
Hindawi Limited
Wiley
Subjects
Algorithms
Analysis
Approximation
Collaboration
Design
Efficiency
Exact solutions
Flow control
Frequency setting
Heuristic
Integer programming
Light rail transit
Linear programming
Mathematical analysis
Mathematical programming
Mixed integer
Nonlinear programming
Optimization
Optimization models
Passengers
Queuing theory
Transportation
Transportation corridors
Urban rail
China
Beijing China
Online AccessGet full text

Cover

More Information
Summary:Focusing on a heavily congested urban rail corridor, this study investigates the passenger flow control strategy optimization problem from a mesoscopic perspective to reduce platform congestion and enhance service quality. Based on a quadratic functional approximation for passenger arrival rates, an analytical formula for calculating passenger waiting time is derived based on the classic deterministic queueing theory. We formulate the problem as a continuous nonlinear programming model to minimize the total passenger waiting time within transportation capacity constraints. A Lagrangian relaxation approach effectively transforms the original complex problem into an unconstrained minimization program. The analytical solution relating to optimal flow control strategy is derived by directly solving the unconstrained program. To further provide an integrated optimization framework from both the supply and demand sides, we extend the abovementioned passenger flow control optimization model into an integrated mixed-integer nonlinear programming model to jointly optimize the passenger-flow control strategy and train frequency setting. Numerical examples are presented to demonstrate the applicability and effectiveness of the proposed models. The computational results show that the produced high-quality passenger flow control strategy significantly reduces total passenger delay.
ISSN:0197-6729
2042-3195
DOI:10.1155/2023/3513517