Tagging Real-World Scenarios for the Assessment of Autonomous Vehicles
Erwin de Gelder, Olaf Op den Camp

TL;DR
This paper introduces a structured tagging method using hierarchical trees to categorize real-world scenarios for testing autonomous vehicles, enhancing scenario diversity and specificity in assessments.
Contribution
It proposes a novel hierarchical tagging system for defining scenario categories, illustrated with concrete examples from Singapore traffic data.
Findings
Hierarchical tags effectively categorize diverse real-world scenarios.
The method balances scenario specificity and variety.
Examples demonstrate practical applicability in AV testing.
Abstract
The development of Autonomous Vehicles (AVs) has made significant progress in the last years. An essential aspect in the development of AVs is the assessment of quality and performance aspects of the AVs, such as safety, comfort, and efficiency. Among other methods, a scenario-based approach has been proposed. With scenario-based testing, the AV is subjected to a collection of scenarios that represent real-world situations. The collection of scenarios needs to cover the variety of what an AV can encounter in real traffic. As a result, many different scenarios are considered, that are grouped into so-called scenario categories. We propose a method for defining the scenario categories using a system of tags, where each tag describes a particular characteristic of a scenario category. There is a balance between having generic scenario categories - very specific set of scenarios, while…
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Taxonomy
TopicsAutonomous Vehicle Technology and Safety · Traffic control and management · Simulation Techniques and Applications
