Virtual safety performance assessment for automated driving in complex urban traffic scenarios

The spectrum of potentially safety-critical situations for automated driving functions (ADF) - particularly those involving vulnerable road users (VRUs) - is far too broad to test comprehensively (in conformity with ISO 26262) by naturalistic driving alone or within controlled, laboratory environments, which are subject to technical and ethical constraints. These and related challenges can be addressed by virtual, randomized controlled trial designs, utilizing detailed and validated stochastic (Monte-Carlo) simulation. Virtual trials can generate comprehensive databases and achieve the statistical power required to probe the high-dimensional traffic scenario space required for safety assessment and "stress testing" of ADF. Model validity is the crucial requirement for virtual testing; thus, the project SAVe (supported by BMVI, Germany) aims at generating a "digital twin" for the urban road network in Ingolstadt, Germany. Our CARISSMA research team is focusing on ADF-VRU interactions at urban intersections; this task requires validated (sub)-microscopic models for dynamics, cognition, and behavior (or occasional "misbehavior") of road users, including all VRU categories. As an application, the potential for enhanced intersection safety performance and reliability of ADF by communication with external sensors (e.g., "Bird's eye view" observation) and data fusion will be tested in virtual trials.