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原文传递 Genetic Algorithms Assisted DDHV Prediction Models Based on Victoria Day Traffic Flows for Major Rural Highways

题名：	Genetic Algorithms Assisted DDHV Prediction Models Based on Victoria Day Traffic Flows for Major Rural Highways
正文语种：	中文
作者：	Zhaobin Liu Satish Sharma
作者单位：	Ph. andidate,EVSE Faculty of Engineering,University of Regina,Regina,SK anada,S4S0 2 Professor,Faculty of Engineering,University of Regina
关键词：	遗传算法预测模型交通流农村公路交通工程
摘要：	Estimation of design hourly volume (DHV), commonly the 30th highest hourly volume (30HV) in a year, from sample counts is an important aspect in traffic engineering practice. Directional design hourly volume (DDHV) is usually obtained by multiplying a parameter of directional split to DHV. The normally used methodology to estimate DHV is developing a consistent and predictable relationship between the annual average daily traffic (AADT) and the DHV. However, highway designers have questioned this method's validity and its limitations have been well discussed. Due to the fact that recreational travel on most holidays in developed countries is very active and leads to vast increases in highway traffic volumes. The main objective of this paper is to develop more accurate and efficient DDHV prediction models based on directional hourly volumes occurring in holiday periods. In this paper, the conventional method is reviewed first. Then, holiday traffic peaking characteristics are investigated based on past 20 years of data from permanent traffic counters on primary rural highways in Alberta, Canada. With the recognition of holiday traffic peaking phenomena, genetic algorithms (GAs) are employed to assist in developing a number of Victoria Day based DDHV prediction models corresponding to different types of roads. At the end of this paper, discussions regarding these models are presented.
会议日期：	20050625
会议举办地点：	西安
会议名称：	第五届交通运输领域国际学术会议
出版日期：	2005-06-25
母体文献：	第五届交通运输领域国际学术会议论文集
分类号：	U491.14 TP301.6