Search Results

Surrogate targets are used throughout the automotive industry to safely and repeatably test Advanced Driver Assistance Systems (ADAS) and will likely find similar applications in tests of Automated Driving Systems. For those test results to be applicable to real-world scenarios, the surrogate targets must be representative of the real-world objects that they emulate. Early target development efforts were generally divided into those that relied on sophisticated radar measurement facilities and those that relied on ad-hoc measurements using automotive grade equipment. This situation made communication and interpretation of results between research groups, target developers and target users difficult. SAE J3122, “Test Target Correlation - Radar Characteristics”, was developed by the SAE Active Safety Systems Standards Committee to address this and other challenges associated with target development and use. J3122 addresses four topics.

This paper describes the development and application of a newly developed metric for evaluating and quantifying the capability of a vehicle/controller (e.g., Automated Vehicle or human driver) to avoid collisions in nearly any potential scenario, including those involving multiple potential collision partners and roadside objects. At its core, this Collision Avoidance Capability (CAC) metric assesses the vehicle’s ability to avoid potential collisions at any point in time. It can also be evaluated at discrete points, or over time intervals. In addition, the CAC methodology potentially provides a real-time indication of courses of action that could be taken to avoid collisions. The CAC calculation evaluates all possible courses of action within a vehicle’s performance limitations, including combinations of braking, accelerating and steering.