Model-based safety validation of the automated driving functio highway pilot

Beglerovic, Halil; Ravi, A; Wikström, Niklas; Koegeler, Hans-Michael; Leitner, Andrea; Holzinger, Jürgen

doi:10.1007/978-3-658-18459-9_21

Cited by 16 publications

(11 citation statements)

References 3 publications

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“…The latter has the advantage that the distributions provide the occurrence probability of a scenario and thus its relevance in the real world. A wide variety of sampling techniques was already applied to generate scenarios from parameter ranges, for example, Design of Experiments (DoE) [13], Satisfiability Modulo Theory (SMT) solvers [50], Rapidly Exploring Random Trees (RRTs) [12] or the In-Parameter-Order-Generalized (IPOG) algorithm [51]. Distributional sampling techniques are based on Monte Carlo methods.…”

Section: Coverage-based Methodsmentioning

confidence: 99%

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Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles

et al. 2020

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Due to the rapid progress in the development of automated vehicles over the last decade, their market entry is getting closer. One of the remaining challenges is the safety assessment and type approval of automated vehicles, as conventional testing in the real world would involve an unmanageable mileage. Scenario-based testing using simulation is a promising candidate for overcoming this approval trap. Although the research community has recognized the importance of safeguarding in recent years, the quality of simulation models is rarely taken into account. Without investigating the errors and uncertainties of models, virtual statements about vehicle safety are meaningless. This paper describes a whole process combining model validation and safety assessment. It is demonstrated by means of an actual type-approval regulation that deals with the safety assessment of lane-keeping systems. Based on a thorough analysis of the current state-of-the-art, this paper introduces two approaches for selecting test scenarios. While the model validation scenarios are planned from scratch and focus on scenario coverage, the type-approval scenarios are extracted from measurement data based on a data-driven pipeline. The deviations between lane-keeping behavior in the real and virtual world are quantified using a statistical validation metric. They are then modeled using a regression technique and inferred from the validation experiments to the unseen virtual type-approval scenarios. Finally, this paper examines safety-critical lane crossings, taking into account the modeling errors. It demonstrates the potential of the virtual-based safeguarding process using exemplary simulations and real driving tests.

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Section: Coverage-based Methodsmentioning

confidence: 99%

“…There is a large number of publications that propose scenario generation approaches for safety assessment of AVs. Some extract the scenarios from driving data [10,11], others generate the scenarios from scratch [12], for example using Design of Experiments (DoE) techniques [13].…”

Section: Introductionmentioning

confidence: 99%

Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles

et al. 2020

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“…Beglerovic et al [79] use an interactive Design of Experiments (DoE) procedure to generate concrete cut-in scenarios. They identify the system behavior and model it via a robust neural network.…”

Section: A Sampling Within Parameter Rangesmentioning

confidence: 99%

Survey on Scenario-Based Safety Assessment of Automated Vehicles

et al. 2020

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When will automated vehicles come onto the market? This question has puzzled the automotive industry and society for years. The technology and its implementation have made rapid progress over the last decade, but the challenge of how to prove the safety of these systems has not yet been solved. Since a market launch without proof of safety would neither be accepted by society nor by legislators, much time and many resources have been invested into safety assessment in recent years in order to develop new approaches for an efficient assessment. This paper therefore provides an overview of various approaches, and gives a comprehensive survey of the so-called scenario-based approach. The scenario-based approach is a promising method, in which individual traffic situations are typically tested by means of virtual simulation. Since an infinite number of different scenarios can theoretically occur in real-world traffic, even the scenario-based approach leaves the question unanswered as to how to break these down into a finite set of scenarios, and find those which are representative in order to render testing more manageable. This paper provides a comprehensive literature review of related safety-assessment publications that deal precisely with this question. Therefore, this paper develops a novel taxonomy for the scenario-based approach, and classifies all literature sources. Based on this, the existing methods will be compared with each other and, as one conclusion, the alternative concept of formal verification will be combined with the scenario-based approach. Finally, future research priorities are derived.

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“…The findings from [9] and [10] support the need for alternative testing methods to supplement real-world tests, in particular by virtual tests and vehicle simulations. Virtual validation procedures for AV have been developed in recent projects such as adaptIVe [11], PEGASUS [12], [13], ENABLE-S3 [14] or ADAS&ME [15]. However, there is little research on testing scenarios for road junction areas.…”

Section: Background and Motivationmentioning

confidence: 99%

A novel, modular validation framework for collision avoidance of automated vehicles at road junctions

Nitsche

Welsh

Genser

et al. 2018

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

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This paper presents a new validation method for automated driving systems at road junctions. The method comprises the clustering of critical traffic scenarios at junctions as well as a simulation and evaluation framework to validate those scenarios. The safety performance indicators selected and implemented in the framework can be seen as a new reference for conducting virtual tests at junctions. The applicability of the framework is demonstrated by an experiment based on a selected car-to-car collision scenario. Considering the current progression of automated transport, this work is highly relevant for virtual testing procedures and is an important step towards approval and certification of automated vehicles.

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Model-based safety validation of the automated driving functio highway pilot

Cited by 16 publications

References 3 publications

Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles

Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles

Survey on Scenario-Based Safety Assessment of Automated Vehicles

A novel, modular validation framework for collision avoidance of automated vehicles at road junctions

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