  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.
