Radar Sensor Plugin for Game Engine Based Autonomous Vehicle Simulators

Abstract

Simulations play an essential role in developing autonomous vehicles and verifying their safe operation. They enable research in sensor fusion with synthetic data and allow low-cost experimentation with different design decisions, like the number, location, and specifications of various sensors on vehicles. Apart from industrial simulation tools, researchers have been using game engine based simulators, mainly to generate training data for artificial intelligence systems and to test their decision making in virtual worlds. These simulators currently support camera and lidar sensors but lack a physics-based radar implementation. Automotive radars that serve for advanced driver-assistance systems today are evolving into imaging radar systems for autonomous vehicles. Therefore it is critical to be able to simulate them in the same environment together with other sensors. In this thesis, we aim to develop a generic radar sensor plugin using a ray-tracing method and to integrate it into one of the game engine based autonomous vehicle simulators.