基于单纯形算法的交通微观仿真模型标定

Kyu-Ok Kim, L. Rilett
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引用次数: 1

摘要

近年来,微观仿真在交通运输系统建模中发挥着越来越重要的作用。一个持续存在的问题是,它们是否充分地代表了现实,以及是否存在足够的数据来校准这些模型。幸运的是,在过去的十年里,智能交通技术在北美的大多数城市地区得到了迅速的部署。虽然智能交通系统主要是为实时交通操作而开发的,但数据通常是存档的,可用于交通微观模拟校准。提出了一种基于顺序单纯形算法的基于ITS数据的微仿真模型标定方法。试验台位于德克萨斯州休斯顿10号州际公路23公里处。两个微模拟模型(CORSIM和TRANSIMS)对两种不同外径矩阵的AM峰进行了校准。结果发现,单纯形算法比默认值或简单的手动校准效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calibration of traffic micro-simulation models using the simplex algorithm
In recent years micro-simulation has become increasingly important in transportation system modeling. An on-going question is whether they adequately represent reality and whether adequate data exists with which to calibrate these models. Fortunately, over the last ten years there has been a rapid deployment of ITS technologies in most urban areas of North America. While the ITS are developed primarily for real-time traffic operations the data typically are archived and is available for traffic micro-simulation calibration. This paper presents a calibration approach for micro-simulation model which uses ITS data and is based on the sequential simplex algorithm. The test bed is a 23 kilometer section of Interstate 10 in Houston, Texas. Two micro-simulation models (CORSIM and TRANSIMS) were calibrated for the AM Peak for two different OD matrices. It was found that the simplex algorithm had better results then either the default values or a simple, manual calibration.
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