Alternative Methods for Estimating Seasonal Factors and Accuracy of Daily Volumes They Yield

Monney, Mamaa G.; Badoe, Daniel A.; Lee, David Jung-Hwi

doi:10.1061/jtepbs.0000324

Cited by 1 publication

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“…They can be temporary or permanent. The permanent count stations are necessary to know the variability in the traffic volumes, which is observed between seasons, months of the year, days of the week, hours of the day, and even during short-term periods below an hour [6]. The most common output from a count station is the average annual daily traffic (AADT), which can be calculated dividing by 365 the total number of vehicles passing a given point during a year.…”

Section: Introductionmentioning

confidence: 99%

Managing Traffic Data through Clustering and Radial Basis Functions

Hernández¹,

Alberdi

Pérez-Acebo

et al. 2021

Sustainability

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Due to the importance of road transport an adequate identification of the various road network levels is necessary for an efficient and sustainable management of the road infrastructure. Additionally, traffic values are key data for any pavement management system. In this work traffic volume data of 2019 in the Basque Autonomous Community (Spain) were analyzed and modeled. Having a multidimensional sample, the average annual daily traffic (AADT) was considered as the main variable of interest, which is used in many areas of the road network management. First, an exploratory analysis was performed, from which descriptive statistical information was obtained continuing with the clustering by various variables in order to standardize its behavior by translation. In a second stage, the variable of interest was estimated in the entire road network of the studied country using linear-based radial basis functions (RBFs). The estimated model was compared with the sample statistically, evaluating the estimation using cross-validation and highest-traffic sectors are defined. From the analysis, it was observed that the clustering analysis is useful for identifying the real importance of each road segment, as a function of the real traffic volume and not based on other criteria. It was also observed that interpolation methods based on linear-type radial basis functions (RBF) can be used as a preliminary method to estimate the AADT.

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Section: Introductionmentioning

confidence: 99%