Automatic Evaluation of Automatically Derived Semantic Scenario Instance Descriptions

Kolb, Nicola; Jordan, Claudius; Huber, Florian; Pretschner, Alexander

doi:10.1109/itsc55140.2022.9922013

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…Possibilities to apply the maneuver-based approach are presented in [6] and [28]. The approach of [6] is taken up in [27] and transferred from highway to intersection scenarios. In all cases, the recorded trajectory is abstracted into a sequence of maneuvers without gaps.…”

Section: A Resimulationmentioning

confidence: 99%

“…In all cases, the recorded trajectory is abstracted into a sequence of maneuvers without gaps. In [6] and [27] the approach proposed in [30] is applied, and a vehicle's state is at any time defined by two overlapping maneuvers: one for the lateral and one for the longitudinal direction. In case of [28], instead, exactly one maneuver is assigned to a vehicle at any time.…”

Section: A Resimulationmentioning

confidence: 99%

“…Current scenario descriptions are mainly trajectory-based [22]- [26]. An advancement of this is the maneuver-based approach [6], [27], [28], which forms the basis for this paper.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Literature Review on Maneuver-Based Scenario Description for Automated Driving Simulations

Neis,

Beyerer

2023

2023 IEEE Intelligent Vehicles Symposium (IV)

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The increasing complexity of automated driving functions and their growing operational design domains imply more demanding requirements on their validation. Classical methods such as field tests or formal analyses are not sufficient anymore and need to be complemented by simulations. For simulations, the standard approach is scenario-based testing, as opposed to distance-based testing primarily performed in field tests. Currently, the time evolution of specific scenarios is mainly described using trajectories, which limit or at least hamper generalizations towards variations. As an alternative, maneuverbased approaches have been proposed. We shed light on the state of the art and available foundations for this new method through a literature review of early and recent works related to maneuver-based scenario description. It includes related modeling approaches originally developed for other applications. Current limitations and research gaps are identified.Index Terms-automated driving, AI, maneuver-based, simulation, scenario-based testing *This publication was written in the context of the AVEAS research project (www.aveas.org), funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) within the program "New Vehicle and System Technologies".

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Section: A Resimulationmentioning

confidence: 99%

Section: A Resimulationmentioning

confidence: 99%