Genetic algorithm-based simulation optimization of the ALINEA ramp metering system: a case study in Atlanta
- Authors
- Cho, Hyun Woong; Chilukuri, Bhargava R.; Laval, Jorge A.; Guin, Angshuman; Suh, Wonho; Ko, Joonho
- Issue Date
- Jul-2020
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- Ramp metering; ALINEA; genetic algorithm; total vehicle travel time; Atlanta freeway
- Citation
- TRANSPORTATION PLANNING AND TECHNOLOGY, v.43, no.5, pp 475 - 487
- Pages
- 13
- Indexed
- SCIE
SCOPUS
- Journal Title
- TRANSPORTATION PLANNING AND TECHNOLOGY
- Volume
- 43
- Number
- 5
- Start Page
- 475
- End Page
- 487
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1002
- DOI
- 10.1080/03081060.2020.1763655
- ISSN
- 0308-1060
1029-0354
- Abstract
- 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.
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