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ABSTRACT

The task of driving is inherently risky. Human drivers rely on their experience from interacting with other road users to build assumptions of what constitutes a reasonably foreseeable behavior of the surrounding traffic in different situations, such as highway driving and urban driving. Together with explicit traffic rules, these assumptions help human drivers to navigate safely from point A to point B. With the development of Automated Driving Systems (ADS) and the introduction of ADS-equipped vehicles to public roads, the expectation of utilizing such technologies is that they will lead to a reduction of the inherent risk of driving. But in order to enable ADS' participation in traffic as well as to outperform human drivers in terms of safety, it is not enough to only rely on traffic rules adherence; ADS-equipped vehicles need to also consider assumptions about reasonably foreseeable behavior of other road users to be able to navigate safely and naturally on public roads. This document presents a review of relevant literature (e.g., standards, regulations, and scientific publications) that investigated kinematic behavior of road users. This review is intended to serve as a key contribution to the ADS research and industry communities, as well as to current standardization efforts, such as IEEE Std 2846, IEEE Standard for Assumptions in Safety-Related Models for Automated Driving Systems.