Publication Details
Analysis of Vehicle Trajectories for Determining Cross-Sectional Load Density Based on Computer Vision
Juránek Roman, Ing., Ph.D. (DCGM)
Herout Adam, prof. Ing., Ph.D. (DCGM)
NOVÁK, J.
HAVRÁNEK, P.
Road Safety, Lane Markings, Trajectory Analysis, Computer Vision, Vehicle
Tracking
The goal of this work was to analyze the behavior of vehicles on third-grade
roads with and without horizontal lane markings with small curvature (R <=
200m). The roads are not frequented by many vehicles, and therefore, a general
short-term study would not be able to provide enough data. We used recording
devices for long-term (weeks) recording of the traffic and designed a system for
analyzing the trajectories of the vehicles employing computer vision. We
collected a dataset at 6 distinct locations, containing 1 010 hours of day-time
video. In this dataset, we tracked over 12 000 cars and analyzed their
trajectories. The results show that the selected approach is functional and
provides information that would be hard to mine otherwise. After application of
the horizontal markings, the drivers slowed down and shifted slightly towards the
outer side of the curvature.
@inproceedings{BUT161457,
author="ŠPAŇHEL, J. and JURÁNEK, R. and HEROUT, A. and NOVÁK, J. and HAVRÁNEK, P.",
title="Analysis of Vehicle Trajectories for Determining Cross-Sectional Load Density Based on Computer Vision",
booktitle="2019 22th International Conference on Intelligenet Transportation Systems (ITSC)",
year="2019",
pages="1001--1006",
publisher="Institute of Electrical and Electronics Engineers",
address="Auckland",
doi="10.1109/ITSC.2019.8917374",
isbn="978-1-5386-7024-8",
url="https://ieeexplore.ieee.org/document/8917374"
}