Shockwave detection for electronic vehicle detectors

Hsun-Jung Cho*, Ming Te Tseng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Although Shockwaves have been extensively adopted in traditional traffic flow theory, how to detect Shockwaves using an electronic vehicle detector has not been explored. Therefore, this study illustrates, for the first time, not only how to detect Shockwaves, but also how to obtain Shockwaves from three new traffic parameters: Stopped, Moving, and Empty. The Stopped parameter attempts to identify a newly arrived Shockwave equation when a traffic queue approaches the electronic vehicle detector. The Moving and Empty parameters derive another new arrival Shockwave equation when the electronic vehicle detector fails to identify any queue. An algorithm is also created to demonstrate how to use these parameters and equations to detect Shockwaves. Additionally, numerous simulations are conducted to identify the behaviors of new traffic parameters and the effectiveness of the proposed algorithm. Results of this study demonstrate that the computing algorithm for electronic vehicle detectors can accurately detect Shockwaves.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2007 - 7th International Conference, Proceedings
Pages275-282
Number of pages8
EditionPART 4
DOIs
StatePublished - 1 Dec 2007
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: 27 May 200730 May 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume4490 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computational Science, ICCS 2007
CountryChina
CityBeijing
Period27/05/0730/05/07

Keywords

  • Electronic vehicle detector
  • Empty
  • Moving
  • Shockwave
  • Stopped

Fingerprint Dive into the research topics of 'Shockwave detection for electronic vehicle detectors'. Together they form a unique fingerprint.

  • Cite this

    Cho, H-J., & Tseng, M. T. (2007). Shockwave detection for electronic vehicle detectors. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings (PART 4 ed., pp. 275-282). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4). https://doi.org/10.1007/978-3-540-72590-9_39