Smart Traffic Signs to Support Infrastructure-To-Vehicle Communication in the Rural Settings

Connected automated vehicles are undeniably important for advanced safety of our future transportation. However, assisting these vehicles through infrastructure to vehicle (I2V) communication requires substantial investment in wireless infrastructure. Furthermore, access to the power and fiber optic lines is imperative. Therefore, the availability of this technology will be limited to urban settlements in the near-term plans of the transportation authorities. In order to support I2V in rural and underprivileged areas, this project explored an artificial intelligence embedded on-board machine vision system which essentially generates the same I2V messages that are typically sent from the roadside equipment. The system recognizes the message identifiers placed on the traffic signs and activates the associated message while communicating with the vehicle’s on-board equipment, thereby eliminates the need for a wireless infrastructure in these areas. The proposed affordable device solution uses a long-distance stereo vision system to detect in real-time the roadway entities such as traffic lights, traffic signs, vehicles, cyclists, pedestrians and crossing animals. Then, the real-time object locations are accurately estimated by fusing the depth information from the camera and the surveyed road geometry information obtained from the message signs. Some of the example message applications that were proven to be supported by the proposed system include MapData Message for roadway intersections, Traveler Information Message for work zones, Personal Safety Message for vulnerable road users and red-light violation warning messages.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Photos; References; Tables;
  • Pagination: 18p

Subject/Index Terms

Filing Info

  • Accession Number: 01763959
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-03585
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:16AM