Task force in-session amendments to the proposal to insert a new introduction paragraph accounting for vehicles of category X and Y, amend para. 6.1.5. to clarify that the exemption for driver assistance systems does not fully apply to automated driving systems where the perception system forms part of the driving function, and make editorial improvements replacing ‘disoriented’ with ‘misaligned’ and ‘driver assist systems’ with ‘driver assistance systems’. The amendment enables application of UN R42 to vehicles equipped with an Automated Driving System.

Task force in-session amendments to the proposal to amend para. 0. to introduce provisions for vehicles of category Y and Automated Driving Systems, amend para. 1.4. to exclude category Y vehicles and exempt certain category N₁ vehicles, add sentences to paras. 2.8., 2.22., 2.29., 2.32., 2.45. defining or clarifying applicability for category Y vehicles, amend para. 2.44. to define windscreen test area for category Y vehicles without windscreens, and replace language in para. 5.3.1.2. to refer to active ADS rather than ADS performing the Dynamic Driving Task.

Agenda for the 22nd session of the ADS informal working group and the 20th GRVA Workshop on ADS, to be held 6-9 October 2026 in Sydney. The session will address adoption of the agenda and previous session report, status of work on GTR 26, UN R185, and the GID, highlights from the 26th GRVA session, Interpretation H4 on electromagnetic compatibility, ADS Phase 2 context and programme, refinement and allocation of Phase 2 work items, integration into 2026-2029 strategy, ADS2 schedule and coordination with other groups, and various change requests to GTR, UNR, and GID.

Document identifies open questions regarding MRC definition, risk assessment, feature deactivation, and post-MRC obligations. Discusses reasons for MRC including collisions, faults, remote termination, ODD exits, and fallback user transition failures. Addresses post-MRC reporting and data recording under DSSAD and ISMR. Examines feature deactivation following MRC and ODD exit scenarios, with three possible solutions for ADSF-2 post-ODD exit recording.

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.