Project 05 / Vehicle AI

Forward-Collision Warning

Real-time monocular perception that identifies traffic threats, estimates range, and gives the driver time to react.

Forward-collision warning system tested inside a moving vehicleFCW / Road test

Useful warnings from a single camera.

The pre-collision warning system turns monocular video into a continuously updated picture of nearby road risk. It combines object detection and tracking with range estimation and warning logic tuned for real-time operation.

Before in-vehicle evaluation, the pipeline was simulated and tested in CARLA. This allowed repeatable validation across traffic configurations and edge cases while the algorithms were optimized for embedded deployment.

Key contributions

  1. Implemented and optimized real-time neural object detection and multi-object tracking.
  2. Developed monocular distance estimation and forward-collision warning logic.
  3. Created CARLA scenarios for repeatable simulation and algorithm validation.
  4. Supported embedded-system optimization and road testing.
Embedded display enclosure for the collision-warning system
Embedded ADAS enclosure
Forward-collision warning test in the CARLA simulator
CARLA validation
In-vehicle demonstration

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