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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
18.02.2022
LICENSE
Copyright (c) 2024 Hongzhi Lin

Optimal On‑Ramp Metering of Urban Freeway Network for the Coronavirus Disease Control

Authors:

Hongzhi Lin
Southeast University

Keywords:cordon sanitaire, on-ramp control, bi-level programming model, heuristic algorithm, queuing theory

Abstract

The outbreak of COVID-19 disrupted our everyday life. Many local authorities enforced a cordon sanitaire for the protection of sensitive areas. Travellers can only pass the cordon after tested. This paper aims to propose a method to design an on-ramp control scheme to maximise urban freeway network throughput with a predetermined queuing delay constraint at all off-ramps around cordon sanitaire. A bi-level programming model is formulated where the lower-level is a transportation system equilibrium to predict traffic flow, and the upper-level is onramp metering optimisation that is nonlinear programming. A stochastic queuing model is used to represent the waiting phenomenon at each off-ramp where testing is conducted, and a heuristic algorithm is designed to solve the proposed bi-level model where a method of successive averages (MSA) is adopted for the lower-level model; A genetic algorithm (GA) with elite strategy is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that the methods can find a good heuristic optimal solution. These methods are useful for freeway operators to determine the optimal on-ramp control for disease control and prevention.

References

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How to Cite
Lin, H. (et al.) 2022. Optimal On‑Ramp Metering of Urban Freeway Network for the Coronavirus Disease Control. Traffic&Transportation Journal. 34, 1 (Feb. 2022), 1-12. DOI: https://doi.org/10.7307/ptt.v34i1.3745.

SPECIAL ISSUE IS OUT

Guest Editor: Eleonora Papadimitriou, PhD

Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD


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