2016
DOI: 10.5194/ars-14-31-2016
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Virtual sensor models for real-time applications

Abstract: Abstract. Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensormodel, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position e… Show more

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Cited by 36 publications
(25 citation statements)
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“…Yet, the update step introduces additional dependencies among objects which arise from the claim that each cluster in a measurement partition may only be assigned to one object. As observable from the sums in (32), the posterior multi-object distribution is hence composed of several hypotheses that have been updated using different partitioning and clustering possibilities.…”
Section: B Updatementioning
confidence: 99%
See 2 more Smart Citations
“…Yet, the update step introduces additional dependencies among objects which arise from the claim that each cluster in a measurement partition may only be assigned to one object. As observable from the sums in (32), the posterior multi-object distribution is hence composed of several hypotheses that have been updated using different partitioning and clustering possibilities.…”
Section: B Updatementioning
confidence: 99%
“…A statistical study on radar measurements from vehicles in dependence on the aspect angle was conducted in [30]. In [31] and [32], kernel density estimation methods are employed to learn a probabilistic measurement model for simulation.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Basic models [21,22] use monostatic RCS measurements of objects and add noise on top. More advanced models represent objects by multiple virtual scattering centers [23].…”
Section: Requirements On Radar Ota Stimulation Chainmentioning
confidence: 99%
“…Without being representative of all urban test drives the obtained values would not be comparable. Finally our analysis helps in simulating vehicle sensor data as in [13], since it gives knowledge about vehicle dynamics and the generation of common and anomalous driving scenarios.…”
Section: Introductionmentioning
confidence: 99%