Traffic Velocity Estimation from Vehicle Count Sequences

Takayuki Katsuki, Tetsuro Morimura, Masato Inoue

研究成果査読

3 被引用数 (Scopus)

抄録

Traffic velocity is a fundamental metric for inferring traffic conditions. This paper proposes a new velocity estimation approach from temporal sequences of vehicle count that does not require tracking any vehicles or using any labeled data. It is useful for measuring traffic velocities with low quality and inexpensive sensors such as web cameras in general use. We formalize the task as a density estimation problem by introducing a new model for temporal sequences of vehicle counts wherein the correlation between the sequences is directly related to the traffic velocity. We also derive a sampling-based algorithm for the density estimation. We show the effectiveness of our method on artificial and real-world data sets.

本文言語English
論文番号7782816
ページ(範囲)1700-1712
ページ数13
ジャーナルIEEE Transactions on Intelligent Transportation Systems
18
7
DOI
出版ステータスPublished - 2017 7

ASJC Scopus subject areas

  • 自動車工学
  • 機械工学
  • コンピュータ サイエンスの応用

フィンガープリント

「Traffic Velocity Estimation from Vehicle Count Sequences」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル