Criticality Analysis for the Verification and Validation of Automated Vehicles

Christian Neurohr,Martin Herbert Bollmann,Martin Butz,Ulrich Eberle,Lukas Westhofen,Roland Galbas

doi:10.1109/access.2021.3053159

Abstract

The process of verification and validation of automated vehicles poses a multi-faceted challenge with far-reaching societal, economical and ethical consequences. In particular, fully automated vehicles at SAE Level 4 and 5 will be expected to operate safely in an arbitrarily complex, infinite-dimensional domain called open context . In order to give structure to the open context, we propose a methodical criticality analysis that maps an infinite-dimensional domain onto a finite and manageable set of artifacts that capture and explain the emergence of critical situations for automated vehicles. We propose a combined approach of expert-based and data-driven methods to identify relevant phenomena and explain the underlying causalities. Leveraging on abstraction, we define a clearly laid out process that converges towards a manageable set of artifacts based on two assumptions on the nature of traffic. A criticality analysis precedes the design phase of an automated vehicle and is therefore located outside the V-model. As the open context is analyzed independently of a concrete realization, it is relevant for any automated vehicle operating within that domain. Therefore, its results can subsequently be used to derive safety principles and mitigation mechanisms for automated driving and to set up a coherent safety argument for the homologation process.

Highlights

Automated vehicles (AVs) at SAE Level 4 and 5 [70] are complex systems operating in open context [68]
Based on the above definition of criticality, we propose a break down into six high level goals in order to accomplish the analytical examination of criticality. (G1) Extract criticality phenomena, i.e. observations of traffic that are associated with increased criticality. (G2) Deliver explanations of the criticality phenomena by analyzing the possible underlying causalities. (G3) Derive a structuring of the open context according to these causalities. (G4) Construct a catalog of abstract scenarios based on the classification, including representative instances. (G5) Find an adequate level of abstraction for the criticality phenomena, explanations and scenarios. (G6) Achieve a convergence towards a manageable set of criticality phenomena
The method proposed in this work, called criticality analysis, provides a blueprint for structuring the open context with the goal of safe operation of automated vehicles at SAE Level 4 and 5 under manageable effort

Summary

INTRODUCTION

Automated vehicles (AVs) at SAE Level 4 and 5 [70] are complex systems operating in open context [68] Their verification and validation principally necessitates the consideration of all possible traffic situations and influencing factors during the design- and testing phase of such systems. C. Neurohr et al.: Criticality Analysis for the Verification and Validation of Automated Vehicles (iii) using abstraction and classification of causal relations for scenario space condensation. Long-term goals include the derivation of safety principles and mitigation mechanisms for automated vehicles based on the results of the criticality analysis, in particular on causal relations. This will be the focus of future work. The results shall adhere to certain quality requirements, for example, with respect to their explanatory depth

BASIC CONCEPT

CRITICALITY ANALYSIS METHOD

Findings

CONCLUSION