Model Development and Simulation for Predicting Proportional Changes in Traffic Volume as a Consequence of Natural Weather Hazards

Hyuk-Jae Roh
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Abstract

This study used a model to calculate the proportional drop for every vehicle class based on 266 climate patterns consisting of seven temperature groups and varied snowfalls. The winter traffic models use weigh-in-motion (WIM) traffic collected on the commuter roadway for 5 years. The marginal impact and combined effect of meteorological conditions on the proportional decrease in winter traffic volume are evaluated. The predicted percentage decrease in traffic for all three vehicle classes increases as temperature decreases and snowfall increases. Mathematical functions are fitted for the decreased patterns for the considered vehicle type. Roadway authorities may utilize traffic percentage decrease to identify weather-related traffic changes when planning winter highway operation and maintenance.
用于预测自然灾害导致的交通流量比例变化的模型开发与模拟
该研究使用一个模型,根据由 7 个温度组和不同降雪量组成的 266 种气候模式,计算出每类车辆的比例降幅。冬季交通模型使用了 5 年来在通勤道路上收集的移动称重(WIM)交通量。评估了气象条件对冬季交通量减少比例的边际影响和综合影响。随着气温的降低和降雪量的增加,所有三种车辆类别的预测交通量减少比例都会增加。对考虑的车辆类型的减少模式进行了数学函数拟合。公路管理部门在规划冬季公路运营和维护时,可利用交通量下降百分比来识别与天气有关的交通变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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