A Study on Highway Classification and Traffic Characteristics by Highway Type
Sung Han Lim, Ju-Sam Oh
Abstract
Sung Han Lim, Ju-Sam Oh
Abstract
Road classification system is the first step for the determining the road function and design standards. Currently, roads are classified according to various indices including road location and function. Using various traffic indices, this study was to classify highway as well as to identify traffic characteristics for each type of road. To accomplish the objectives, factor analysis and cluster analysis were performed for classifying highway and analyzing traffic characteristics using traffic data that observed at permanent traffic count points in 2003. A total of 9 variables were applied : AADT, K coefficient, D coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and COV. The results of factor analysis showed that variables were divided into two factors, which were factor related to the fluctuational characteristics of traffic volume and factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, a total of 306 permanent traffic count points were categorized into three groups : Group I (Urban highway), Group II (Rural highway), and Group III (Recreational highway). AADT were 28,000 for urban, 11,000 for rural, and 7,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.
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Road classification system is the first step for the determining the road function and design standards. Currently, roads are classified according to various indices including road location and function. Using various traffic indices, this study was to classify highway as well as to identify traffic characteristics for each type of road. To accomplish the objectives, factor analysis and cluster analysis were performed for classifying highway and analyzing traffic characteristics using traffic data that observed at permanent traffic count points in 2003. A total of 9 variables were applied : AADT, K coefficient, D coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and COV. The results of factor analysis showed that variables were divided into two factors, which were factor related to the fluctuational characteristics of traffic volume and factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, a total of 306 permanent traffic count points were categorized into three groups : Group I (Urban highway), Group II (Rural highway), and Group III (Recreational highway). AADT were 28,000 for urban, 11,000 for rural, and 7,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.
Key concepts: Traffic volume, Transport engineering, Road traffic, Recreation, Statistics, Traffic count, Volume (thermodynamics), Geography