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.

中文翻译：

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基于遗传算法的 ALINEA 匝道计量系统仿真优化：亚特兰大案例研究

摘要 本文介绍了亚特兰大地铁高速公路走廊最优 ALINEA 匝道计量系统模型的案例研究。本研究基于真实世界的交通数据，估计了走廊的起点-终点矩阵。使用结合了微观模拟模型和基于遗传算法的优化模块的基于随机模拟的优化框架，我们确定了组合 ALINEA 匝道计量系统与队列冲洗系统的最佳参数值，该系统可最大限度地减少总车辆行驶时间。我们发现，在减少总行程时间方面，使用优化参数的匝道计量性能（可能因为瓶颈是相关的）而非常敏感，其性能优于使用优化参数的无控制模型。