Determine the near-miss to critical-occurrence ratio for automated vehicles

Determine the exact ratio between near misses and critical occurrences involving automated vehicles, using recorded operational data to overcome the current lack of evidence.

Background

Event Data Recorders and Data Storage Systems for Automated Driving provide objective evidence for analysing safety-critical events, but they do not capture near misses—events that do not cause damage or injury but could have done so—or support proactive anticipation of critical events. The paper notes that safety pyramids commonly suggest that near misses substantially outnumber actual critical scenarios.

Establishing the exact relationship between near misses and critical occurrences is important for developing effective anticipative and corrective safety measures for automated vehicles. The authors identify the absence of recorded data as the reason this ratio remains unresolved; operational data collected from automated driving systems could help address the problem.