摘要
模型标定和模型验证是微观交通流仿真建模理论中非常重要的两个方面。人们往往注重前者而忽略后者,或因数据采集困难等原因,注重从宏观角度、而忽略从微观角度进行模型验证,从而导致模型在进一步应用过程中的失效。针对上述情况,文章运用五轮仪实验系统所采获的实际数据,结合了一种基于综合认知结构的车辆跟驰模型的构建过程,从微观角度研究了模型检验和确认的关键技术。研究表明,直观对比和统计推断都是模型验证过程中行之有效的方法。
Model calibration and model validation are two important aspects for microscopic traffic simulation modeling theory.People often pay attention to the former one but ignore the latter one,or pay attention to the macroscopic validation procedure but ignore microscopic validation procedure because of the difficulties of field data collection.This way often leads to failure in model applications.In this paper,the key technology for model verification and validation is studied with the field data collected by'Five-Wheel experiment system' and the establishing procedure of a new integrated cognitive car-following model.The results indicate that the straight comparison technique and the statistical inference technique are all effective method for model verification and validation.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第8期188-192,共5页
Computer Engineering and Applications
基金
国家自然科学基金资助项目(编号:50378042)
山东理工大学博士基金项目
关键词
微观仿真
模型验证
跟驰模型
五轮仪实验系统
microscopic simulation,model verification and validation,car-following model,Five-Wheel experiment system
