Project Overview

At Aptiv, I worked on real-time simulation environments for autonomous-vehicle testing. The work centered on reconstructing real-world driving routes and conditions inside a Unity-based simulation environment, then validating that the simulated environment matched what the vehicle actually encountered in the real world.

A core part of this validation was comparing simulated camera views directly against real vehicle camera footage captured on the same routes, to confirm that the simulated environment was accurate enough to support meaningful autonomous-vehicle testing.

My Role

I built and refined real-time simulation environments used to test autonomous-vehicle perception and behavior in a controlled virtual setting, and worked on verifying that those environments accurately represented real-world driving conditions.

Because the underlying project material from this period is confidential, this page describes the work only in general terms rather than showing specific project assets or footage.

Key Contributions

• Built and refined real-time simulation environments for autonomous-vehicle testing in Unity, using Maya, ZBrush, and Softimage for asset creation and refinement.
• Reconstructed real-world driving routes and conditions for simulation, processing photogrammetry and LiDAR capture data with tools including ReCap Pro, Agisoft, 3DReshaper, and VeloView.
• Validated simulated environments against real vehicle camera footage — using Photoshop and Premiere to prepare and compare reference imagery — to verify simulation accuracy.
• Collaborated with engineering teams on environment and simulation requirements for autonomous-vehicle development.