Standards Development

Scope

This document specifies the classification, definition, and measurement of external adverse weather conditions that affect perception sensors for automotive surroundings supporting assisted or automated driving functions. This document includes specifications for equipment to measure characteristics of specific adverse weather conditions.

This document applies to any automotive perception sensors (e.g., LiDAR, RGB/FIR cameras, millimeter-wave radar) used to measure or detect the surroundings of the vehicle.

This document contains the terminology and general requirements for the series of standards on automotive perception sensor performance under adverse weather conditions.

Purpose

The global intelligent connected vehicle (ICV) market is experiencing rapid growth, with sales reaching 7.61 million units in 2024 and a compound annual growth rate of approximately 40% from 2019 to 2024. Projections indicate that global sales will soar to 41.34 million units by 2029 and further climb to 58 million units by 2030. Concurrently, the industry is witnessing a significant technological shift towards higher levels of driving automation (L2 and above), which increasingly rely on a suite of perception sensors — such as cameras, LiDAR, and millimeter-wave radar — to enable assisted or automated driving functions.

The operational safety of assisted or automated driving is critically dependent on the ability of perception systems to cope with adverse weather conditions. Adverse weather (e.g. heavy rain, fog, snow, haze and sun glare) can affect both the observed field and the sensor effect chain (e.g. dirt on sensor surface), and in consequence can degrade the capability of sensors to perceive and interpret the vehicle surrounding environment. Numerous research institutions worldwide are investigating the performance of automotive perception sensors in adverse weather, highlighting the industry's recognition of the topic. However, the absence of unified international standards for classifying adverse weather conditions and specifying corresponding test methods for automotive perception sensors leave manufacturers, suppliers and test facilities with own testing methodologies which cannot effectively compare or evaluate sensors. Moreover, the lack of standardized testing increases the risk of perception system failures once vehicles are on the road, directly impacting road safety.

This proposed series of standards aims to classify adverse weather conditions as relevant to automotive perception sensors (Cameras, LiDAR, millimeter-wave radar), to specify related measurement methods for the defined weather classes, and to standardize test methods for evaluating sensor performance under these various conditions. This intends to reduce developing and testing efforts and cost, as well as to support the development of related tool chains. By establishing consensus on terms, definitions, and test methods, this series of standards will lay the foundation for international knowledge exchange and technical cooperation, ultimately promoting the continuous enhancement of product quality and contributing to improved road vehicle safety worldwide.

The purpose of part 1 is to provide a classification, definitions, and measurement methods for adverse weather conditions that affect automotive perception sensors for assisted or automated driving functions, for performance testing on test tracks, in dedicated test facilities and on public roads.