Document presents research on Safety Performance Indicators (SPIs) for continuous monitoring and evaluation of Automated Driving Systems safety. Leading indicators anticipate outcomes through metrics including time-based, distance-based, probability-based and deceleration-based measures; lagging indicators confirm outcomes after occurrence such as crashes and injuries. Analysis of 21 datasets identified SHRP2 as primary source with 1402 crashes and 5262 near-crashes. Performance evaluation using Distance Headway and Time-to-Collision achieved Area Under the Curve close to 0.9 distinguishing crashes and near-crashes from normal driving. Main bottleneck identified is data quality and scarcity of reliable safety event labels.
Concerns from legal experts towards ensuring that revisions to the 1958 Agreement pursuant to the implementation of the International Whole Vehicle Type Approval system would be agreed by all Contracting Parties.