Genetic algorithm-based simulation optimization of the ALINEA ramp metering system: a case study in Atlanta |
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| Authors: | Hyun Woong Cho Bhargava R Chilukuri Jorge A Laval Angshuman Guin Wonho Suh |
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| Institution: | 1. Virginia Transportation Research Council, Charlottesville, VA, USA;2. Department of Civil Engineering, Indian Institute of Technology, Madras IIT, Chennai, India;3. School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA;4. Department of Transportation &5. Logistics Engineering, Hanyang University, ERICA Campus, Ansan, South Korea |
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| Abstract: | 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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| Keywords: | Ramp metering ALINEA genetic algorithm total vehicle travel time Atlanta freeway |
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