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Investigation of the factors affecting the consistency of short-period traffic counts
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作者 Solomon Yadessa Kenno Prasanta K.Sahu +1 位作者 Babak Mehran Satish Sharma 《Journal of Modern Transportation》 2017年第3期150-162,共13页
The main intent of this study is to investigate the accuracy of short-duration traffic counts conducted during winter months. The investigation is based on 11-year sample data collected using permanent traffic counter... The main intent of this study is to investigate the accuracy of short-duration traffic counts conducted during winter months. The investigation is based on 11-year sample data collected using permanent traffic counters at various locations in Alberta, Canada. Four types of road sites: commuter, regional commuter, rural long-distance, and recreational sites are studied. The sample data consti- tute six different durations of counts (12-, 24-, 48-, 72-, 96-h, and 1 week) taken during summer and winter months. The coefficient of variation (CV) is used as the relative measure of deviation for counts of different dura- tions to measure the accuracy of short-period traffic counts. The study results indicate that 48-h count seems to be the most cost-effective counting interval during both summer and winter months. It is also found that the lowest values of CV result for counts taken at commuter sites, and the highest values are observed for recreational sites. Frequent changes in temperature and other weather events cause significant variation in traffic volume, which results in an increase in CV values for counts taken during winter months. The application of an adjustment factor to remove the effect of cold and snow from short-period counts is also included in this study. Introduced adjustment factors can reduce the values of CV for all counts taken during winter months. The findings of this study can lead highway agencies to improve the cost-effectiveness of their short- period traffic counting programs. 展开更多
关键词 Short-period traffic counts average annualdaily traffic - design hourly volume
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