Suggestion for Recording Methods and Data Elements of the Data Storage System for Automated Driving Based on Traffic Incident Analysis of Automated Vehicles

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Abstract
The data storage system for automated driving (DSSAD) records how an automated driving system (ADS) behaves, but current requirements leave important gaps. UN Regulation No. 157 requires only timestamped state changes, and the time-series recording recently introduced by UN Regulation No. 185 starts only when a collision is detected or the event data recorder (EDR) is triggered and covers just 7 s around the trigger. ADS behavior in near misses and in minor contacts that are not detected as collisions may therefore still go unrecorded, and this window is much shorter than the 20 s pre-crash period now required for EDRs. This study proposes an evidence-based, two-layer DSSAD recording scheme. The timestamp layer covers the entire ADS, following the event classification of the Validation Method for Automated Driving, and designates seven hazard-related events, including non-collision events, as time-series triggers. The time-series layer records perception, decision, and control data at 10 Hz or higher from 20 s before to 10 s after a trigger. The scheme was derived from eight incident investigations in South Korea and the United States, a binary logistic regression screening of 842 National Highway Traffic Safety Administration crash reports, and two rounds of review by 13 incident investigation practitioners. It allows ADS behavior to be reconstructed in hazardous events that end without a collision and over a period long enough to cover the events leading up to an incident.
Funding Information
  • Korea Agency for Infrastructure Technology Advancement (RS-2021-KA162419)

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