Sensor Models for V2X Situational Awareness Learning

Abstract

Generating real-time data for autonomous vehicle is important to evaluate the vehicular system performance. However, such data may require high cost and safety concerns. In a virtual proving ground, complex vehicular scenario can be created, and novel beam selection and beam tracking algorithms can be developed. The important aspect of the virtual proving ground is the ability to produce realistic sensor measurement inside the simulated environment. In this paper, we present methods to generate situation awareness information using GPS and IMU through simulations.