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...

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Published in:Journal of advanced transportation 2023-06, Vol.2023, p.1-21
Main Authors: Zhu, Qian, Zhu, Xiaoning, Shang, Pan, Meng, Lingyun
Format: Article
Language:English
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
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Zhu, Xiaoning
Shang, Pan
Meng, Lingyun
description 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.
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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
title Analytical Approximation-Based Approach for Passenger Flow Control Strategy in Oversaturated Urban Rail Transit Systems
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