Model Overview

This model analyzes highway construction project imagery to automatically detect and identify traffic flow control devices.

Traffic Control Device Detection

The Traffic Control Device Detection model provides an easy-to-use yet powerful way to identify the traffic flow control devices used in your highway construction project. Designed for engineers and other professionals involved in highway projects, the model allows you to quickly identify any missing or mispositioned traffic control devices and quickly replace, secure, or repair them as needed. As traffic control devices are a key element of any highway construction project, this model provides you with a speedy way to check on the overall safety of your project.

Key features include:

  • Fast analysis – Designed to ingest and analyze large sets of data, this model can return results in a matter of minutes or even seconds.
  • Improved accuracy – This model can accurately detect what the human eye may miss, including a range of traffic control devices, from cones, barricades, barriers, work vehicles, and safety fences, to automated flagger devices, floating water markers, stationary crash cushions, life float rings, and much more.
  • Annotated images and detailed reports – Bounding boxes will appear around detected traffic control devices, enabling you to quickly locate where they are within the image. The annotated images are viewable directly from our platform, for the utmost convenience, or you can download them for later viewing. The model also generates a detailed report that lists each detection along with their confidence level for further analysis.

This model detects:

  • Channelizers (drums and tubular markers)
  • Cones
  • Barricades (Type 3)
  • Concrete Barrier
  • Longitudinal channelizing Device
  • Temporary traffic control signs
  • Truck mounted attenuators
  • Jersey barriers
  • Work vehicles
  • Portable changeable message signs
  • Lights
  • Construction safety fence
  • Chain link fence
  • Floating water marker
  • Automated flagger device
  • Stationary crash cushions
  • Life float ring
  • Screens
Required Inputs

PNG or JPEG files

Note: This model is trained on oblique imagery, collected downward to an approximate 45 degree angle to the ground.

Expected Output

Annotated images

XLSX report

Cookie Statement

We collect cookies to improve your experience with BRYX.