Testing and validating high level components for automated driving: simulation framework for traffic scenarios

Zofka, Marc René; Klemm, Sebastian; Klunker, Florian; Schamm, Thomas; Zöllner, J. Marius

doi:10.1109/ivs.2016.7535378

Cited by 48 publications

(14 citation statements)

References 20 publications

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“…Another approach that aims to tackle the coverage challenge has been the utilization of multiple types of virtual prototyping. Zofka et al [20] integrated a vehicle mechanics simulation, sensor simulation, and traffic flow simulation and used them in both software and vehicle in the loop simulations. While vehicle mechanics and sensor simulation provide noisy information access, the traffic simulator provides the real-world traffic scenarios that the AV can come across.…”

Section: A Related Workmentioning

confidence: 99%

Autonomous Vehicles Scenario Testing Framework and Model of Computation: On Generation and Coverage

2021

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Autonomous vehicle (AV) technology started to shift the perception of the transportation systems. However, for AVs to operate at their optimum capabilities, they need to go through a comprehensive testing and verification process. While a large amount of research and funding has been provided for solving this problem, there is still a lack of a systematic method to develop standardized tests that can be used to judge if the decision-making capability functions are within acceptable parameters. To that end, the tests need to cover all possible situations that an AV may run into. This paper focuses on defining the notion of coverage mathematically when using pseudo-randomly generated simulations for testing. The approach defines new equivalence relations between scenes, which are the systems' various states, to achieve this goal. Considering the substantial need for computation, even with the obtained coverage, we also introduce the mathematical definition of a sub-scene and additional strategies, such as expanding the equivalence classes of scenes and combining actors in scenes, to reduce the amount of testing required to certify AVs.

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Section: A Related Workmentioning

confidence: 99%

Autonomous Vehicles Scenario Testing Framework and Model of Computation: On Generation and Coverage

2021

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“…Interest in this kind of platform has increased recently, but most studies focus only on either communication or automation. For example, the platform presented in [4] adopts the well-known simulation of urban mobility (SUMO) [5] with a VUT virtually interacting through advanced sensors with surrounding simulated vehicles without considering any wireless communications between the vehicles. And the HiL-based platform in [6] takes the real hardware electronic control unit (ECU) of a self-driving vehicle as a part of the simulation platform to verify the validity of self-driving algorithms in virtual scenes, including perception, planning, decision-making, and control but no connectivity is considered.…”

Section: Related Workmentioning

confidence: 99%

CarLink: A Real-Time V2X Validation Platform for a Safe and Sustainable Mobility

Mafakheri¹,

gonnella²,

Masini³

et al. 2021

Preprint

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<div>In this article, we present CarLink, a new simulation platform with hardware-in-the-loop (HiL), designed and implemented to reduce the time spent on field tests through the emulation of a complex vehicular scenario in a controlled laboratory environment. Specifically, CarLink can simulate a generic traffic scenario and let each vehicle in it communicate with a vehicle under test (VUT), which is actually physically available HiL and equipped with long- and short-range wireless communication capabilities. Communication between simulated vehicles and the VUT is provided by an external management unit (EMU) that integrates the virtual world with the physical one. The architecture is also designed to allow the integration of advanced driver assistance systems (ADAS) testing for the validation of future connected and automated vehicles.</div>

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“…Increased capabilities of driver assistance systems cause a more time-consuming calibration process since the complexity and dimensionality of parameter spaces grow. While safety assessments and validation studies are already widely conducted virtually [2], [3], [4], [5], calibration tests are mainly performed on the target hardware. However, simulation environments can be used to efficiently obtain solutions with high maturity levels as starting points for a manual calibration in the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Efficient Simulation Based Calibration of Automated Driving Functions Based on Sensitivity Based Optimization

Fraikin

Funk

Frey

et al. 2020

IEEE Open J. Intell. Transp. Syst.

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Testing and validating high level components for automated driving: simulation framework for traffic scenarios

Cited by 48 publications

References 20 publications

Autonomous Vehicles Scenario Testing Framework and Model of Computation: On Generation and Coverage

Autonomous Vehicles Scenario Testing Framework and Model of Computation: On Generation and Coverage

CarLink: A Real-Time V2X Validation Platform for a Safe and Sustainable Mobility

Efficient Simulation Based Calibration of Automated Driving Functions Based on Sensitivity Based Optimization

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