Virtual Reality Assisted Human Perception in ADAS Development: a Munich 3D Model Study

Abstract

As the development of autonomous driving (AD) and advanced driver assistance systems (ADAS) progresses, the relevance of the comfort of users is gaining increasing interest. It becomes significant to test and validate perceived comfort performance from the early phase of system development before driving on roads. Most of the present ADAS test procedures are not efficient in performing such comfort evaluation. One of the main challenges is to integrate high-quality, realistic and predictable virtual traffic scenarios into an ADAS testing framework that has physics-based sensors capable of sensing the virtual environment. In this paper, we present our development of a virtual reality based ADAS testing framework that enhances human perception evaluation. The main contribution relies on three aspects. First, we introduce our development of a large and high-quality (realism, structure, texture) 3D traffic model of the Munich city in Germany. Second, we optimize the 3D model for virtual reality purpose, and real-time capable for human-in-the-loop ADAS testing. Finally, the model is then integrated into an ADAS framework for testing and validating ADAS functionalities and perceived comfort performance. The developed framework components are presented with illustrative examples.