A clustering approach to developing car-to-two-wheeler test scenarios for the assessment of Automated Emergency Braking in China using in-depth Chinese crash data

Sui, Bo; Lübbe, Nils; Bärgman, Jonas

doi:10.1016/j.aap.2019.07.018

Cited by 40 publications

(40 citation statements)

References 16 publications

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“…Sequences of events were extracted from 168 AV collision reports' text narratives and analyzed using sequence analysis methods. Crash sequences, in combination with variables describing crash outcomes and variables describing the environment, can be used to design abstract semantic scenarios (Nitsche et al, 2017;Sander and Lubbe, 2018;Sui et al, 2019). A scenario-based AV testing framework, with crash sequence embedded as a core component, is proposed at the end of this study.…”

Section: Introductionmentioning

confidence: 99%

Automated vehicle crash sequences: Patterns and potential uses in safety testing

Song

Chitturi

Noyce

2021

Accident Analysis & Prevention

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With safety being one of the primary motivations for developing automated vehicles (AVs), extensive field and simulation tests are being carried out to ensure AVs can operate safely on roadways. Since 2014, the California Department of Motor Vehicles (DMV) has been collecting AV collision and disengagement reports, which are valuable data sources for studying AV crash patterns. A crash sequence of events describes the AV's interactions with other road users before a collision in a temporal manner. In this study, sequence of events data extracted from California AV collision reports were used to investigate patterns and how they may be used to develop AV test scenarios. Employing sequence analysis methods and clustering, this study evaluated 168 AV crashes (with AV in automatic driving mode before disengagement or collision) reported to the California DMV from 2015 to 2019. Analysis of subsequences showed that the most representative pattern in AV crashes was "collision following AV stop". Analysis of event transition showed that disengagement, as an event in 24% of all studied AV crash sequences, had a transition probability of 68% to an immediate collision. Cluster analysis characterized AV crash sequences into seven groups with distinctive crash dynamic features. Cross-tabulation analysis showed that sequence groups were significantly associated with variables measuring crash outcomes and describing environmental conditions. Crash sequences are useful for developing AV test scenarios. Based on the findings, a scenario-based AV safety testing framework was proposed with sequence of events embedded as a core component.

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Section: Introductionmentioning

confidence: 99%

Automated vehicle crash sequences: Patterns and potential uses in safety testing

Song

Chitturi

Noyce

2021

Accident Analysis & Prevention

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“…This algorithm's parameter tuning must consider several factors. In this study, the clustering algorithm considered the similarity (distance) measuring method, the proximity (linkage) measuring method, and the optimal number of clusters [24].…”

Section: Hierarchical Clustering Agglomerative Clustering Algorithmmentioning

confidence: 99%

Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests

Hwang

Youn

2021

JMSE

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The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) or are arbitrary. Therefore, the purpose of this study is to identify and systematize objective navigation situation scenarios for the validation of autonomous ship collision avoidance algorithms. A data-driven approach was applied to collect 12-month Automatic Identification System data in the west sea of Korea, to extract the ship’s trajectory, and to hierarchically cluster the data according to navigation situations. Consequently, we obtained the hierarchy of navigation situations and the frequency of each navigation situation for ships that sailed the west coast of Korea during one year. The results are expected to be applied to develop a collision avoidance test environment for MASS.

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“…The articles [54], [55], [56], [73], [99], [100], [100], [110] used accident database (e.g., NHTSA [150], GIDAS [151], IGLAD [152] to find the critical pre-crash scenarios. The used data type of the data source can be mainly grouped into sensor data, unstructured accident records (e.g., natural language document) and structured accident records (e.g., meta-data database).…”

Section: Data Typementioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

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Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic literature review in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

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A clustering approach to developing car-to-two-wheeler test scenarios for the assessment of Automated Emergency Braking in China using in-depth Chinese crash data

Cited by 40 publications

References 16 publications

Automated vehicle crash sequences: Patterns and potential uses in safety testing

Automated vehicle crash sequences: Patterns and potential uses in safety testing

Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

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