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Calibration of Traffic Flow Models under Adverse Weather andApplication in Mesoscopic Network Simulation Procedures

机译：恶劣天气和天气条件下交通流模型的标定在介观网络仿真程序中的应用

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摘要

The weather-sensitive Traffic Estimation and Prediction System (TrEPS) aims to accuratelyestimate and predict traffic state under inclement weather conditions. Successful applicationof weather-sensitive TrEPS requires detailed calibration of weather effects on traffic flowmodel. In this paper, systematic procedures of the entire calibration process are developed,from data collection, through model parameter estimation, to model validation. Following theprocedures, dual-regime modified Greenshields model and weather adjustment factors arecalibrated for four metropolitan areas across the United States (Irvine, Chicago, Salt LakeCity, and Baltimore), using freeway loop detector traffic data and weather data obtained fromAutomated Surface Observing System (ASOS) stations. It is observed that visibility andprecipitation (rain/snow) intensity have significant impacts on the value of some traffic flowmodel parameters, such as free flow speed and maximum flow rate; while these impacts canbe included in weather adjustment factors. The calibrated models are fed as input intoweather integrated dynamic traffic assignment simulation system. The results show that thecalibrated models are capable of capturing the weather effects on traffic flow morerealistically than TrEPS without weather integration.
机译：天气敏感的交通估算和预测系统（TrEPS）旨在准确地 估计和预测恶劣天气条件下的交通状态。成功申请 天气敏感的TrEPS要求对天气对交通流量的影响进行详细校准 模型。在本文中，开发了整个校准过程的系统程序， 从数据收集到模型参数估计，再到模型验证。继 程序，双系统修改的Greenshields模型和天气调整因子为 已针对全美四个大都市区（尔湾，芝加哥，盐湖城）进行校准 市和巴尔的摩），使用高速公路环路探测器的交通数据和气象数据 自动化地面观测系统（ASOS）站。据观察，可见度和 降雨（雨/雪）强度对某些交通流量的值具有重大影响 模型参数，例如自由流速和最大流速;这些影响可以 包括在天气调整因素中。校准后的模型作为输入输入 天气综合动态交通分配模拟系统。结果表明 校准的模型能够更好地捕获天气对交通流量的影响 实际上比没有天气整合的TrEPS要好。

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