A Comprehensive Safety Assessment Methodology for Highly Automated Vehicles in Operation: Development and Demonstration Based on Road Test Data

The article presents a comprehensive methodology for assessing the safety of highly automated vehicles (HAVs) based on operational data collected on public roads. The methodology includes a qualitative classification of safety violations according to three criteria: impact on functionality, extent of coverage by safety mechanisms, and frequency of occurrence. Based on the sum of these criteria, a criticality matrix is constructed, distinguishing four risk zones: critical (requiring immediate remediation), unacceptable (requiring planned remediation), tolerable, and acceptable. The quantitative assessment includes a system of key performance indicators (operational efficiency, number of accidents, detection and elimination of threats, and frequency of driver/operator interventions) and an integral safety indicator. The applicability of the methodology was demonstrated using operational data from a Level 3 HAV collected over 1413 km of automated driving on Russian highways. In this demonstration, most of the recorded failures were classified in the critical zone, which made it possible to prioritize system improvements. The proposed methodology can be used by developers for the objective assessment of safety and by regulators for developing reporting requirements. From the perspective of sensor and actuator networks, this work makes three contributions: (1) the multimodal sensor network of the HAV (4 cameras, 4 radars, GNSS RTK) is analyzed as a networked system with redundancy and overlapping fields of view; (2) the CAN bus is treated as an actuator network whose reliability is critical for safety; (3) it is shown that 10 of 17 recorded failures (59%) are related specifically to network equipment, making the monitoring of sensor and actuator networks a central element of the proposed methodology.