Abstract
This paper examines the effect of weather conditions on truck type distribution using combined nonparametric chi-squared and binomial probability statistical tests. Influence of the winter conditions on truck type distribution is investigated in this paper by classifying trucks into single-unit trucks, single-trailer, and multi-trailer units. The investigation is based on 5 years Weigh-In-Motion (WIM) traffic data collected from Alberta provincial highway network in Canada. The WIM data is collected from six WIM sites located on Highway 2, Highway 2A, Highway 3, Highway 16 and Highway 44. The objective of this study is to investigate the association of three truck type distribution with month and season depending on weather conditions by means of nonparametric statistical test. The statistical results indicate that the variation of truck type distribution is influenced by type of highway facility, such as regional commuter roads and rural long distance highways. The season of the year (winter and non-winter) may also affect the truck type distribution on some types of roads. Findings of this study can benefit highway agencies in developing programs and policies related to efficient monitoring of truck traffic and maintaining highway network throughout the year.
Highlights
Highway traffic volume varies over time and locations on all roadways
This paper presents an investigation of the influence of the winter conditions on truck type distributions by classifying trucks into three classes: single-unit trucks, single-trailer, and multi-trailer units
The study findings are based on the five years spanning from 2005 to 2009 truck traffic data collected from six Weigh-In-Motion (WIM) sites located on Highway 2, Highway 2A, Highway 3, Highway 16 and Highway 44 in Alberta (Canada)
Summary
Highway traffic volume varies over time and locations on all roadways. The variations of traffic volumes could differ substantially when each vehicle class travelling in the same traffic stream is analysed separately. Datla and Sharma (2008) analysed the impact of winter weather conditions (cold temperatures and snowfall) on highway total traffic volumes They concluded that winter weather causes significant variations in traffic volumes, and the magnitude of variation depends on the time of day, day of the week, location, highway type, and severity of the weather. Liu (2006) investigated holiday effects on hourly volume changes with Permanent Traffic Counters (PTCs) data collected continuously for 10 years on highway networks in Alberta (Canada) He compared hourly traffic pattern of typical days with the hourly traffic pattern of holiday and indicated statistical significance of hourly traffic peaking in holiday with the help of combined chi-squared (c2) and binomial tests. Based on the literature, combined nonparametric chi-squared and binomial probability tests of statistical significance are used to analyse the association of winter weather with the variations of truck type volumes under different weather conditions
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