A Collaborative Perception Framework for Intelligent Transportation System Applications

Advance Driver Assistance System (ADAS) and Cybercars applications are moving towards vehicle infrastructure cooperation. In such scenario, information from vehicle based sensors, roadside based sensors and a priori knowledge is generally combined thanks to wireless communications to build a probabilistic spatio-temporal model of the environment. Depending on the accuracy of such model, very useful applications from driver warning to fully autonomous driving can be performed. In this paper, we propose a framework for data acquisition, spatio-temporal localization and data sharing. Such system is based on a methodology for integrating measures from different sensors in a unique spatio-temporal frame provided by GPS receivers. Communicant entities, i.e. vehicles and roadsides exhibit and share their knowledge in a database using network access. Experimental validation of the framework was performed by sharing and combining raw sensor and perception data to improve a local model of the environment. Communication between entities was based on WiFi ad-hoc networking.

  • Corporate Authors:

    ITS America

    1100 17th Street, NW, 12th Floor
    Washington, DC  United States  20036
  • Authors:
    • Kais, Mikael
    • Bouraoui, Laurent
    • Morin, Steeve
    • Porterie, Arnaud
    • Paren, Michel
  • Conference:
  • Publication Date: 2005


  • English

Media Info

  • Media Type: Print
  • Features: CD-ROM; Figures; References;
  • Pagination: 12p
  • Monograph Title: Proceedings of the 12th World Congress on Intelligent Transport Systems

Subject/Index Terms

Filing Info

  • Accession Number: 01015864
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Dec 6 2005 1:03PM