Exploring the Range of Possible Outcomes by means of Logical Scenario Analysis and Reduction for Testing Automated Driving Systems

With the implementation of the new EU regulation 2022/1426 regarding the type-approval of the automated driving system (ADS) of fully automated vehicles, scenario-based testing has gained significant importance in evaluating the performance and safety of advanced driver assistance systems and automated driving systems. However, the exploration and generation of concrete scenarios from a single logical scenario can often lead to a number of similar or redundant scenarios, which may not contribute to the testing goals. This paper focuses on the the goal to reduce the scenario set by clustering concrete scenarios from a single logical scenario. By employing clustering techniques, redundant and uninteresting scenarios can be identified and eliminated, resulting in a representative scenario set. This reduction allows for a more focused and efficient testing process, enabling the allocation of resources to the most relevant and critical scenarios. Furthermore, the identified clusters can provide valuable insights into the scenario space, revealing patterns and potential problems with the system's behavior.Comment: submitted to IEEE ITSC 202

1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey

Scenario generation is one of the essential steps in scenario-based testing and, therefore, a significant part of the verification and validation of driver assistance functions and autonomous driving systems. However, the term scenario generation is used for many different methods, e.g., extraction of scenarios from naturalistic driving data or variation of scenario parameters. This survey aims to give a systematic overview of different approaches, establish different categories of scenario acquisition and generation, and show that each group of methods has typical input and output types. It shows that although the term is often used throughout literature, the evaluated methods use different inputs and the resulting scenarios differ in abstraction level and from a systematical point of view. Additionally, recent research and literature examples are given to underline this categorization.Comment: accepted at IEEE IV 202

Fingerprint of a Traffic Scene: an Approach for a Generic and Independent Scene Assessment

A major challenge in the safety assessment of automated vehicles is to ensure that risk for all traffic participants is as low as possible. A concept that is becoming increasingly popular for testing in automated driving is scenario-based testing. It is founded on the assumption that most time on the road can be seen as uncritical and in mainly critical situations contribute to the safety case. Metrics describing the criticality are necessary to automatically identify the critical situations and scenarios from measurement data. However, established metrics lack universality or a concept for metric combination. In this work, we present a multidimensional evaluation model that, based on conventional metrics, can evaluate scenes independently of the scene type. Furthermore, we present two new, further enhanced evaluation approaches, which can additionally serve as universal metrics. The metrics we introduce are then evaluated and discussed using real data from a motion dataset

Inverse Universal Traffic Quality -- a Criticality Metric for Crowded Urban Traffic Scenes

An essential requirement for scenario-based testing the identification of critical scenes and their associated scenarios. However, critical scenes, such as collisions, occur comparatively rarely. Accordingly, large amounts of data must be examined. A further issue is that recorded real-world traffic often consists of scenes with a high number of vehicles, and it can be challenging to determine which are the most critical vehicles regarding the safety of an ego vehicle. Therefore, we present the inverse universal traffic quality, a criticality metric for urban traffic independent of predefined adversary vehicles and vehicle constellations such as intersection trajectories or car-following scenarios. Our metric is universally applicable for different urban traffic situations, e.g., intersections or roundabouts, and can be adjusted to certain situations if needed. Additionally, in this paper, we evaluate the proposed metric and compares its result to other well-known criticality metrics of this field, such as time-to-collision or post-encroachment time.Comment: accepted at IEEE IV 202

The decline of the Greek Polis Atarneus near the Eastern Aegean Coast: Consequence of a landscape change?

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Criticality Metrics for Automated Driving: A Review and Suitability Analysis of the State of the Art

The large-scale deployment of automated vehicles on public roads has the potential to vastly change the transportation modalities of today's society. Although this pursuit has been initiated decades ago, there still exist open challenges in reliably ensuring that such vehicles operate safely in open contexts. While functional safety is a well-established concept, the question of measuring the behavioral safety of a vehicle remains subject to research. One way to both objectively and computationally analyze traffic conflicts is the development and utilization of so-called criticality metrics. Contemporary approaches have leveraged the potential of criticality metrics in various applications related to automated driving, e.g. for computationally assessing the dynamic risk or filtering large data sets to build scenario catalogs. As a prerequisite to systematically choose adequate criticality metrics for such applications, we extensively review the state of the art of criticality metrics, their properties, and their applications in the context of automated driving. Based on this review, we propose a suitability analysis as a methodical tool to be used by practitioners. Both the proposed method and the state of the art review can then be harnessed to select well-suited measurement tools that cover an application's requirements, as demonstrated by an exemplary execution of the analysis. Ultimately, efficient, valid, and reliable measurements of an automated vehicle's safety performance are a key requirement for demonstrating its trustworthiness

A Mathematical Knowledge Base for Proving Theorems in Semigroup and Automata Theory

We present a mathematical knowledge base containing the factual know-ledge of the first of three parts of a textbook on semi-groups and automata,namely "P. Deussen: Halbgruppen und Automaten". Like almost all math-ematical textbooks this textbook is not self-contained, but there are somealgebraic and set-theoretical concepts not being explained. These concepts areadded to the knowledge base. Furthermore there is knowledge about the nat-ural numbers, which is formalized following the first paragraph of "E. Landau:Grundlagen der Analysis".The data base is written in a sorted higher-order logic, a variant of POST ,the working language of the proof development environment OmegaGamma mkrp. We dis-tinguish three different types of knowledge: axioms, definitions, and theorems.Up to now, there are only 2 axioms (natural numbers and cardinality), 149definitions (like that for a semi-group), and 165 theorems. The consistency ofsuch knowledge bases cannot be proved in general, but inconsistencies may beimported only by the axioms. Definitions and theorems should not lead to anyinconsistency since definitions form conservative extensions and theorems areproved to be consequences

The Global Knowledge Value Chain on Sustainability: Addressing Fragmentations through International Academic Partnerships

While research on universities’ role in sustainability transitions has flourished in recent years, explorations into the potential of academic internationalization for the promotion of sustainability transitions are still rare. This article aims at contributing to this incipient literature by emphasizing an underexplored property of international academic networks and transnational academic cooperation: their potential to break disciplinary and geographical barriers in the global debates on how transitions towards sustainability can be achieved. When realizing this potential, international partnerships are able to provide more comprehensive knowledge to inform sustainability transitions while shaping sustainability transitions in various places at the same time. This article pursues three objectives: First, it introduces the concept of the “global knowledge value chain on sustainability” and explores its value as a heuristic to understand global knowledge production relevant for sustainability transitions. Furthermore, it identifies two fragmentations in this chain resulting from global inequalities and specific dynamics within the global science community. Second, it confirms empirically the fragmentations of this global knowledge value chain on sustainability. Third, it provides good practice ideas on how international academic partnerships can overcome these fragmentations by drawing on the authors’ experience with the international partnership “trAndeS—Postgraduate Program on Social Inequalities and Sustainable Development in the Andean Region” carried out by the Institute of Latin American Studies of Freie Universität Berlin and the Department of Social Sciences of the Pontificia Universidad Católica del Peru (PUCP)

A Mathematical Knowledge Base for Proving Theorems in Semigroup and Automata Theory

We present a mathematical knowledge base containing the factual know-ledge of the first of three parts of a textbook on semi-groups and automata,namely "P. Deussen: Halbgruppen und Automaten". Like almost all math-ematical textbooks this textbook is not self-contained, but there are somealgebraic and set-theoretical concepts not being explained. These concepts areadded to the knowledge base. Furthermore there is knowledge about the nat-ural numbers, which is formalized following the first paragraph of "E. Landau:Grundlagen der Analysis".The data base is written in a sorted higher-order logic, a variant of POST ,the working language of the proof development environment OmegaGamma mkrp. We dis-tinguish three different types of knowledge: axioms, definitions, and theorems.Up to now, there are only 2 axioms (natural numbers and cardinality), 149definitions (like that for a semi-group), and 165 theorems. The consistency ofsuch knowledge bases cannot be proved in general, but inconsistencies may beimported only by the axioms. Definitions and theorems should not lead to anyinconsistency since definitions form conservative extensions and theorems areproved to be consequences