Mileage Accumulation Target Identification For AEBS Validation for Medium & Heavy Trucks Considering Real-World Accidents In India

Robust validation of Advanced Driver Assistance Systems (ADAS) considering real-world conditions is a vital for ensuring safety. Mileage accumulation is a one of the validation method for ensuring ADAS system robustness. By subjecting systems to diverse real-world driving environments and edge-case scenarios, engineers can evaluate performance, reliability, and safety under realistic conditions. In accordance with ISO 21448 (SOTIF), known hazardous scenarios are explicitly tested during robustness validation in combination of virtual and physical testing at component, sub system and vehicle level, while unknown hazards may emerge through extended mileage by running vehicles on roads, allowing them to be identified and classified. However, defining a mileage target that ensures comprehensive safety remains a significant engineering challenge. This paper proposes a data-driven approach to define mileage accumulation targets for validating Autonomous Emergency Braking Systems (AEBS), using detailed analysis of real-world accident data in India along with ISO 21448 (SOTIF) validation framework. National-level accident data from MoRTH and the RASSI database, along with statistics for medium and heavy commercial vehicles, are utilized to derive the base incident rate for frontal collisions that AEBS is intended to mitigate. The framework integrates critical factors such as hazardous behavior probability, controllability, and severity to calculate a target incident rate, which then informs the required test mileage needed to statistically validate AEBS performance at a specified confidence level. The study outlines the derivation of mileage requirements by considering both accident and fatality reduction as primary safety metrics. This approach provides engineering guidance for defining test mileage requirements with respective to the defined acceptance criteria that ensure AEBS system robust validation considering the real world scenarios in India.