University of Illinois Urbana-Champaign

Unsupervised tracking algorithm for precise traffic estimation in panoramic scenes

Wu, Fangyu

Content Files
WU-THESIS-2018.pdf

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https://hdl.handle.net/2142/100926

Description

Title
Unsupervised tracking algorithm for precise traffic estimation in panoramic scenes
Author(s)
Wu, Fangyu
Issue Date
2018-04-05
Director of Research (if dissertation) or Advisor (if thesis)
Work, Daniel B.
Department of Study
Civil & Environmental Eng
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2018-09-04T20:26:50Z
Keyword(s)
  • Computer Vision
  • Vehicle Tracking
Abstract
The traffic experiment conducted by physicist Sugiyama in 2007 has been a seminal work in transportation research. In the experiment, a group of vehicles are instructed to drive on a circular track starting with uniform initial spacing. The isolated experimental environment provides a safe, economic, and controlled environment to study free flow traffic and stop-and-go waves. This dissertation introduces a novel method that automates the data collection process in such an environment. Specifically, the vehicle trajectories are measured using a 360-degree camera, and the fuel rates are recorded via on-board diagnostics (OBD) scanners. The video data from the 360-degree camera is then processed by an offline unsupervised computer vision algorithm. To validate the data collection method, the technique is then evaluated on a series of eight experiments. Validation analysis shows that the collected data are highly accurate, with a mean position bias of less than 0.002 m and a small standard deviation of 0.11 m. The positional data also yields highly reliable velocity estimates: the derived velocities are biased by only 0.02 m/s with a small standard deviation of 0.09 m/s. Beyond the experimental methodology, the produced trajectory and fuel rate data can be readily used to study human driving behaviors, to calibrate microsimulation models, to develop fuel consumption models, and to investigate engine emission. To facilitate future research, the source code and the data are made publicly available online.
Graduation Semester
2018-05
Type of Resource
text
Permalink
http://hdl.handle.net/2142/100926
Copyright and License Information
Copyright 2018 Fangyu Wu

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Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Civil and Environmental Engineering