Genetic algorithm-based simulation optimization of the ALINEA ramp metering system: a case study in Atlanta

被引：1

作者：

Cho, Hyun Woong ^{[1
]}

Chilukuri, Bhargava R. ^{[2
]}

Laval, Jorge A. ^{[3
]}

Guin, Angshuman ^{[3
]}

Suh, Wonho ^{[4
]}

Ko, Joonho ^{[5
]}

机构：

[1] Virginia Transportat Res Council, Charlottesville, VA USA

[2] Madras IIT, Dept Civil Engn, Indian Inst Technol, Chennai, Tamil Nadu, India

[3] Georgia Inst Technol, Sch Civil & Environm Engn, Atlanta, GA 30332 USA

[4] Hanyang Univ, Dept Transportat & Logist Engn, ERICA Campus, Ansan, South Korea

[5] Hanyang Univ, Grad Sch Urban Studies, Seoul Campus,222 Wangsimni Ro, Seoul 04763, South Korea

来源：

TRANSPORTATION PLANNING AND TECHNOLOGY | 2020年 / 43卷 / 05期

关键词：

Ramp metering; ALINEA; genetic algorithm; total vehicle travel time; Atlanta freeway;

D O I：

10.1080/03081060.2020.1763655

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

This paper presents a case study of the optimal ALINEA ramp metering system model of a corridor of the metro Atlanta freeway. Based on real-world traffic data, this study estimates the origin-destination matrix for the corridor. Using a stochastic simulation-based optimization framework that combines a micro-simulation model and a genetic algorithm-based optimization module, we determine the optimal parameter values of a combined ALINEA ramp metering system with a queue flush system that minimizes total vehicle travel time. We found that the performance of ramp metering with optimized parameters, which is very sensitive possibly because bottlenecks are correlated, outperforms the no control model with its optimized parameters in terms of reducing total travel time.

引用

页码：475 / 487

页数：13

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