Exploratory statistical and geographical freight traffic data analysis
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Exploratory statistical and geographical freight traffic data analysis

Filetype[PDF-350.06 KB]


English
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  • Creators:
  • Subject/TRT Terms:
  • Resource Type:
    Proceedings
  • Geographical Coverage:
    Mexico
  • TRIS Online Accession Number:
    811897
  • NTL Classification:
    NTL-FREIGHT-FREIGHT;NTL-FREIGHT-Freight Planning and Policy;NTL-PLANNING AND POLICY-Surveys;
  • Abstract:
    Data from freight traffic roadside surveys in Mexican highways are analyzed in order to find consistent patterns or systematic relationships between variables characterizing this traffic. Patterns traced are validated by contrasting against new data sets, allowing for a pattern's description refinement. In a first stage, truck traffic is characterized with respect to vehicle counting size, month of the year, geographical area and hourly behavior, yielding results similar to those of common analysis practices of traffic engineering. In a second stage the analysis of freight traffic variables like: traffic composition by type of freight vehicle or service class detected is followed. The prime objective in this analysis is to reveal variable relationships or tendencies of freight data sets providing helpful predictions for decision making under uncertainty. As a second objective, the analysis is extended for the most reliable patterns to statistical inference in order to support hypothesis characterizing freight variables with the typical confidence levels used in decision making for managing and controlling of road freight traffic. Techniques employed are those usual in the fields of Data Mining and Exploratory Data Analysis: frequency tables, histograms, box plots or correlation matrices. Besides, geographical representations of variable distributions with assistance of Geographic Information System (GIS) software is used. Preliminary conclusions obtained from the analysis of the hourly behavior of truck traffic from several field surveys have shown the range of vehicle counting size variations, the identification of daily peak periods or the distribution of the type of vehicles present in freight traffic, amongst other results.
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