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Traffic Control Device Location Overlay

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

5 credits (with a subscription)

10 credits (without a subscription)

Version 1.0
Free Trial available!
Traffic Control Device Location Overlay
Supervised Machine Learning
This composite vision model combines two distinct types of machine learning: object detection to detect non-linear devices like drums, cones, etc.; and instance segmentation to detect linear devices such as multiple jersey barriers and fences. It is designed to process orthophotos, locating detections in a usable space that can be measured against.
Use Case
Speed up the inspection process and ensure safety of your work zone! You can overlay model results onto the MOT plan to quickly ensure that current conditions comply with the original design plan.
Fast Analysis
The model is currently trained to detect:
  • Barricades (Type 3)
  • Concrete barriers
  • Cones
  • Construction safety fences
  • Drums
  • Jersey barriers
  • Longitudinal channelizing devices
  • Screens
  • Stationary crash cushions
  • Temporary traffic control signs

Required Inputs

  • Georeferenced TIF files

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

Expected Outputs

  • DXF file
  • Shapefiles

The Traffic Control Device Location Overlay model is designed to optimize driver safety in roadway construction work zones. This powerful machine vision model detects traffic control devices from drone imagery and generates shapefiles and DXFs that include the traffic control devices found along with their correct geolocation. Use this model to quickly ensure your project is complying with the MOT.

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