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.

本文介绍了亚特兰大高速公路走廊最佳ALINEA匝道计量系统模型的案例研究。基于实际交通数据，本研究估算了走廊的起点-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，我们确定了结合ALINEA坡道计量系统与排队冲洗系统的最佳参数值，该系统将车辆总行驶时间降至最低。我们发现具有优化参数的斜坡计量的性能非常敏感，这可能是因为瓶颈相关，在减少总行程时间方面，其优化参数优于无控制模型。