Optimizing coverage of simulated driving scenarios for the autonomous vehicle

Nabhan, Marc; Schoenauer, Marc; Tourbier, Yves; Hage, Hiba

doi:10.1109/iccve45908.2019.8965211

Cited by 8 publications

(7 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…the mean distance) on the scoring space of the input samples. Nabhan et al [78] used learningbased methods to try to maximize the distance between scenarios. It also considers non-safety-critical qualities (such as deceleration and jerk effects indicating passenger's comfort) during the scenario generation.…”

Section: Exploration Methodsmentioning

confidence: 99%

“…As discussed before, criticality assessment is a function whose input is a concrete scenario, and whose output is a quantified criticality index. Most of the studied CSI methods in this cluster implement this function deductively with analytical approaches, while the others implement it inductively with machine learning approaches [77], [78].…”

Section: Criticality Assessment Methodsmentioning

confidence: 99%

“…Apart from the safety-critical and function-critical consideration, quality of service (QoS) indices can also be applied as surrogate measures. In this cluster, the normal operations of the vehicle are assumed, and QoS is quantified to judge the performance of a system, such as by fuel consumption [77], passengers' comfort [78], and overall traffic quality [125].…”

Section: Mechanisms For Coveragementioning

confidence: 99%

See 2 more Smart Citations

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

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Exploration Methodsmentioning

confidence: 99%

Section: Criticality Assessment Methodsmentioning

confidence: 99%

Section: Mechanisms For Coveragementioning

confidence: 99%

See 1 more Smart Citation

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

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Related work has already been published by the author in [134], [135]. Gangopadhyay et al [136] use a Bayesian optimization, [137] use a random forest model and Abbas et al [138] use simulated annealing in their test harness capable of testing perception algorithms.…”

Section: Simulation-based Falsificationmentioning

confidence: 99%

Survey on Scenario-Based Safety Assessment of Automated Vehicles

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

“…Stark et al conducted a study on the generation of verification scenarios for autonomous vehicles [12], and Park et al studied approaches to generating multievent-based simulation scenarios for sensors and devices in autonomous vehicles [13], and Whlschke et al conducted a study with the aim of deriving test cases [14]. Nabhan et al conducted a study on scenario range optimization for driving scenarios for autonomous vehicles in simulations [15], and Wen et al conducted a study on the performance analysis of NDT-based Graph SLAM for autonomous vehicles based on various driving scenarios in Hong Kong [16]. Zheng…”

Section: Introductionmentioning

confidence: 99%

A Study on the Evaluation Method of Autonomous Vehicle for Fixed Targets

Kim¹,

Lee²

2021

Preprint

View full text Add to dashboard Cite

Recently, the automobile industry aims to commercialize autonomous vehicles, standardization and research and development are actively underway based on the specifications of automotive electronic control systems and the verification of functional errors. Based on this, autonomous driving technology is becoming more advanced, and it is preparing for an era of full autonomous driving through V2X technology convergence. It is also, expanding the models of ADAS applied vehicles such as FCW, BSD, LCA. Based on this, research is also actively underway to secure safety of vehicles and pedestrians, such as V2X, Localization, Fail Safe, to supplement the limitations of sensor-based autonomous driving. In this regard, this study proposes a theoretical formula for longitudinal relative distance computation for autonomous vehicles evaluation method, and uses test device such as DGPS to collects and verify data. In addition, a scenario was proposed for the fixed target, based on this, four types of test were formed to conduct the actual test, and the relative distances were compared, analyzed and verified. Comparative analysis results, in the second test of the first test scenario, the avoidance test of the fixed target in driving own lane, the minimum error rate was 0.5%, and in the second test of fourth test scenario, the avoidance test of the fixed target in driving own lane, the maximum error rate was 7.4%. The main cause of error is, it was judged as an error due to sensor recognition, depending on the scenario progress method, the condition of the test path, and the weather such as sunlight. In the future, we plan to conduct an evaluation on moving target.

show abstract

Optimizing coverage of simulated driving scenarios for the autonomous vehicle

Cited by 8 publications

References 9 publications

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

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

Survey on Scenario-Based Safety Assessment of Automated Vehicles

A Study on the Evaluation Method of Autonomous Vehicle for Fixed Targets

Contact Info

Product

Resources

About