Traffic light status detection using movement patterns of vehicles

Joseph Campbell, Hani Ben Amor, Marcelo H. Ang, Georgios Fainekos

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

6 Scopus citations

Abstract

Vision-based methods for detecting the status of traffic lights used in autonomous vehicles may be unreliable due to occluded views, poor lighting conditions, or a dependence on unavailable high-precision meta-data, which is troublesome in such a safety-critical application. This paper proposes a complementary detection approach based on an entirely new source of information: The movement patterns of other nearby vehicles. This approach is robust to traditional sources of error, and may serve as a viable supplemental detection method. Several different classification models are presented for inferring traffic light status based on these patterns. Their performance is evaluated over real and simulated data sets, resulting in up to 97% accuracy in each set.

Original languageEnglish (US)
Title of host publication2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages283-288
Number of pages6
ISBN (Electronic)9781509018895
DOIs
StatePublished - Dec 22 2016
Event19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016 - Rio de Janeiro, Brazil
Duration: Nov 1 2016Nov 4 2016

Other

Other19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016
CountryBrazil
CityRio de Janeiro
Period11/1/1611/4/16

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Traffic light status detection using movement patterns of vehicles'. Together they form a unique fingerprint.

  • Cite this

    Campbell, J., Ben Amor, H., Ang, M. H., & Fainekos, G. (2016). Traffic light status detection using movement patterns of vehicles. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016 (pp. 283-288). [7795568] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2016.7795568