Development of a Scenario Simulation Platform to Support Autonomous Driving Verification

Pilz, Christoph; Steinbauer, Gerald; Schratter, Markus; Watzenig, Daniel

doi:10.1109/iccve45908.2019.8964914

Cited by 16 publications

(4 citation statements)

References 10 publications

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“…In this paper, the virtual environment is provided by the software Virtual Test Drive (Pilz et al , 2019), and the autonomous driving SUT is also configured by it. The SUT has functions like emergency braking, emergency lane change and others with high intelligence.…”

Section: Design Of Experimentsmentioning

confidence: 99%

Multimodal critical-scenarios search method for test of autonomous vehicles

Liu

Xing

Chen

2022

JICV

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Purpose The purpose of this paper is to search for the critical-scenarios of autonomous vehicles (AVs) quickly and comprehensively, which is essential for verification and validation (V&V). Design/methodology/approach The author adopted the index F1 to quantitative critical-scenarios' coverage of the search space and proposed the improved particle swarm optimization (IPSO) to enhance exploration ability for higher coverage. Compared with the particle swarm optimization (PSO), there were three improvements. In the initial phase, the Latin hypercube sampling method was introduced for a uniform distribution of particles. In the iteration phase, the neighborhood operator was adapted to explore more modals with the particles divided into groups. In the convergence phase, the convergence judgment and restart strategy were used to explore the search space by avoiding local convergence. Compared with the Monte Carlo method (MC) and PSO, experiments on the artificial function and critical-scenarios search were carried out to verify the efficiency and the application effect of the method. Findings Results show that IPSO can search for multimodal critical-scenarios comprehensively, with a stricter threshold and fewer samples in the experiment on critical-scenario search, the coverage of IPSO is 14% higher than PSO and 40% higher than MC. Originality/value The critical-scenarios' coverage of the search space is firstly quantified by the index F1, and the proposed method has higher search efficiency and coverage for the critical-scenarios search of AVs, which shows application potential for V&V.

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Section: Design Of Experimentsmentioning

confidence: 99%

Multimodal critical-scenarios search method for test of autonomous vehicles

Liu

Xing

Chen

2022

JICV

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“…Menzel et al [22] presented an automation process to detail a keyword-based scenario description for execution, both OpenDRIVE and OpenSCENARIO file formats were used to set the concrete scenario parameters and integrate to the simulator. Pilz et al [32] used OpenSCENARIO format to construct the dynamic elements of a scenario, integrated and executed the OpenSCENARIO file in a simulator.…”

Section: Related Workmentioning

confidence: 99%

Scenario Description Language for Automated Driving Systems: A Two Level Abstraction Approach

Khastgir

Jennings

2020

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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“…Finally, we decided to expose our API initially intended to bind OpenScenario as actual scenario definition interface. [18] compares OpenScenario with other scenario specification formats.…”

Section: B Openscenariomentioning

confidence: 99%

Scenario Definition for Prototyping Cooperative Advanced Driver Assistance Systems

Massow

Thiele

Schrab

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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Today's Advanced Driver Assistance Systems (ADAS) adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. In order to further enhance their benefit, ADAS need to cooperate in the future. This enables, for instance, to solve hazardous situations by coordinated maneuvers for safety intervention on multiple vehicles at the same point in time. Our prototyping environment presented in previous work addresses developing such cooperative ADAS. Its underlying approach is to either bring ideas for cooperative ADAS through the prototyping stage towards plausible candidates for further development, or to discard them as quickly as possible. This is enabled by an iterative process of refining and assessment. In this paper, we focus on handling the application specific parameter space, and more precisely on the scenario related aspects. As a part of our iterative prototyping process, defining and tuning scenarios and application parameters are highly repetitive tasks which needs to be designed very efficiently. We, therefore, strive to create a scenario definition methodology, which provides best flexibility and a minimal expenditure of time on the developer side.

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Development of a Scenario Simulation Platform to Support Autonomous Driving Verification

Cited by 16 publications

References 10 publications

Multimodal critical-scenarios search method for test of autonomous vehicles

Multimodal critical-scenarios search method for test of autonomous vehicles

Scenario Description Language for Automated Driving Systems: A Two Level Abstraction Approach

Scenario Definition for Prototyping Cooperative Advanced Driver Assistance Systems

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