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Vehicle modeling for the analysis of the response of detectors based on inductive loops.

Ferran Mocholí BelenguerAntonio Martínez MillanaAntonio Mocholí SalcedoVictor Milián Sánchez
Published in: PloS one (2019)
Magnetic loops are one of the most popular and used traffic sensors because of their widely extended technology and simple mode of operation. Nevertheless, very simple models have been traditionally used to simulate the effect of the passage of vehicles on these loops. In general, vehicles have been considered simple rectangular metal plates located parallel to the ground plane at a certain height close to the vehicle chassis. However, with such a simple model, it is not possible to carry out a rigorous study to assess the performance of different models of vehicles with the aim of obtaining basic parameters such as the vehicle type, its speed or its direction in traffic. For this reason and because computer simulation and analysis have emerged as a priority in intelligent transportation systems (ITS), this paper aims to present a more complex vehicle model capable of characterizing vehicles as multiple metal plates of different sizes and heights, which will provide better results in virtual simulation environments. This type of modeling will be useful when reproducing the actual behavior of systems installed on roads based on inductive loops and will also facilitate vehicle classification and the extraction of basic traffic parameters.
Keyphrases
  • air pollution
  • deep learning
  • machine learning
  • body mass index
  • mass spectrometry
  • virtual reality
  • liquid chromatography