Analysis of Yearly Traffic Fluctuation on Latvian Highways

2nd International Conference on Innovative Materials, Structures and Technologies

Freimanis, A.^1 ; Paeglitis, A.^1

Riga Technical University, Faculty of Civil Engineering, Kalku Str. 1, Riga

LV-1658, Latvia^1

关键词: Additional datum;    Average annual daily traffics;    Counting device;    Number of vehicles;    Road management;    Standard deviation;    Traffic fluctuations;    Visual perception;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/96/1/012064/pdf
DOI  :  10.1088/1757-899X/96/1/012064

来源: IOP

【 摘 要 】

Average annual daily traffic and average annual truck traffic are two most used metrics for road management decisions. They are calculated from data gathered by continuous counting stations embedded in road pavement, manual counting sessions or mobile counting devices. Last two usually do not last longer than a couple of weeks so the information gathered is influenced by yearly traffic fluctuations. Data containing a total of 8,186,871 vehicles or 1989 days from 4 WIM stations installed on highways in Latvia were used in this study. Each of the files was supposed to contain data from only 1 day and additional data were deleted. No other data cleaning steps were performed, which increased the number of vehicles as counting systems sometimes split vehicles into two. Weekly traffic and weekly truck traffic was normalized against respective average values. Each weekly value was then plotted against its number in a year for better visual perception. Weekly traffic amplitudes were used to assess differences between different locations and standard deviations for fluctuation comparison of truck and regular traffic at the same location. Results show that truck traffic fluctuates more than regular traffic during a year, especially around holidays. Differences between counting locations were larger for regular traffic than truck traffic. These results show that average annual daily traffic could be influenced more if short term counting results are adjusted by factors derived from unsuitable continuous counting stations, but truck traffic is more influenced by the time of year in which counting is done.