Real- World Maneuver Extraction for Autonomous Vehicle Validation: A Comparative Study

Erdoğan, Ahmetcan; Ugranli, Burak; Adali, Erkan; Şentaş, Ali; Mungan, Eren; Kaplan, Emre; Leitner, Andrea

doi:10.1109/ivs.2019.8814254

Cited by 18 publications

(11 citation statements)

References 6 publications

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“…2) Semantic Maneuver Classification: We use a rulebased approach for maneuver classification as all driving situations in highway traffic can be distinguished with a manageable amount of rules. Furthermore as [23] claims, the rule-based performance is almost as good as with learning-based approaches. For each TP in the scenario, a rule-based decision tree is used to define the maneuver with respect to the ego-vehicle.…”

Section: ) Hierarchical Clusteringmentioning

confidence: 88%

Identification of Challenging Highway-Scenarios for the Safety Validation of Automated Vehicles Based on Real Driving Data

Ponn

Breitfus

et al. 2020

2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)

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For a successful market launch of automated vehicles (AVs), proof of their safety is essential. Due to the open parameter space, an infinite number of traffic situations can occur, which makes the proof of safety an unsolved problem. With the so-called scenario-based approach, all relevant test scenarios must be identified. This paper introduces an approach that finds particularly challenging scenarios from real driving data (RDD) and assesses their difficulty using a novel metric. Starting from the highD data, scenarios are extracted using a hierarchical clustering approach and then assigned to one of nine pre-defined functional scenarios using rulebased classification. The special feature of the subsequent evaluation of the concrete scenarios is that it is independent of the performance of the test vehicle and therefore valid for all AVs. Previous evaluation metrics are often based on the criticality of the scenario, which is, however, dependent on the behavior of the test vehicle and is therefore only conditionally suitable for finding "good" test cases in advance. The results show that with this new approach a reduced number of particularly challenging test scenarios can be derived.

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Section: ) Hierarchical Clusteringmentioning

confidence: 88%

Identification of Challenging Highway-Scenarios for the Safety Validation of Automated Vehicles Based on Real Driving Data

Ponn

Breitfus

et al. 2020

2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)

View full text Add to dashboard Cite

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“…The extraction of concrete scenarios from real driving data and their assignment to one of the eight considered categories of logical scenario is shown by [68]. Only parameters of dynamic objects (Layer 4 of the five-layer model [21]) are considered.…”

Section: Scenario Classificationmentioning

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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“…Scenarios can be generated using different approaches. A widespread practice in the automotive industry is the generation of scenarios by experts based on their existing domain knowledge [21]. However, these scenarios are generated only by existing subjective and restricted knowledge.…”

Section: Scenario Generationmentioning

confidence: 99%

A Credibility Assessment Approach for Scenario-Based Virtual Testing of Automated Driving Functions

Stadler¹,

Montanari²,

Baron

et al. 2022

IEEE Open J. Intell. Transp. Syst.

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An immense test space is pushing the development and testing of automated driving functions from real to virtual environments. The virtual world is provided by interconnected simulation models representing sensors, vehicle dynamics, and both static and dynamic environment. For the virtual validation of automated driving, special attention must be paid to the simulation's credibility, which can be impaired by inappropriate or inaccurate simulation models and tools. Therefore, in this work a method is proposed to assess the credibility of simulation-based testing for automated driving. The approach allows a qualitative and relatively quantitative comparisons between scenarios as well as between different simulation setups. Therefore, several uni-and multivariate metrics are applied towards a scoring of similarity of the behavior between simulation and real test drive. This is achieved by using ground truth data in form of simulation scenarios from real world measurement data. In this way, the virtual automated vehicle encounters the same conditions and surroundings than its counterpart in the real world for evaluating their similarity. The practical applicability of the proposed credibility assessment approach is demonstrated in a case study, in which the credibility of an exemplary simulation-based test bench is inferred.

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Real- World Maneuver Extraction for Autonomous Vehicle Validation: A Comparative Study

Cited by 18 publications

References 6 publications

Identification of Challenging Highway-Scenarios for the Safety Validation of Automated Vehicles Based on Real Driving Data

Identification of Challenging Highway-Scenarios for the Safety Validation of Automated Vehicles Based on Real Driving Data

Survey on Scenario-Based Safety Assessment of Automated Vehicles

A Credibility Assessment Approach for Scenario-Based Virtual Testing of Automated Driving Functions

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