Radar Sensor Model for the Virtual Development Process

Bernsteiner, Stefan; Magosi, Zoltán Ferenc; Lindvai-Soos, Daniel; Eichberger, Arno

doi:10.1007/s38314-015-0521-1

Cited by 32 publications

(20 citation statements)

References 2 publications

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“…For sensor models this implies, that the shape of the PDF differs depending on the position in the state-space X sim . In parametric sensor models this is sometimes treated heuristically by a linear increasing standard deviation at the borders (Bernsteiner et al, 2013(Bernsteiner et al, , 2015. The non-parametric model provides a more accurate adaption: the PDFp Z sim |X sim is calculated solely using measurements close to the current state of the simulation x sim,T (i.e.…”

Section: Critical Discussion Of the Non-parametric Modelmentioning

confidence: 99%

“…A further motivation of virtual testing and sensor models for driving simulators is presented in Hanke et al (2015); Hirsenkorn et al (2015); Bernsteiner et al (2013Bernsteiner et al ( , 2015 and Schubert et al (2014).…”

Section: Introductionmentioning

confidence: 99%

“…Former statistical approaches mainly focused on simple parametric sensor models (Schubert et al, 2014;Bernsteiner et al, 2013Bernsteiner et al, , 2015Rasshofer et al, 2005;Hanke et al, 2015). However, as shown in the subsequent section, nonparametric models present various benefits regarding realism, changes in dimensionality of the simulated quantities and generic applicability.…”

Section: Introductionmentioning

confidence: 99%

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Virtual sensor models for real-time applications

et al. 2016

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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 estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

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Section: Critical Discussion Of the Non-parametric Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Virtual sensor models for real-time applications

et al. 2016

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“…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%

Environment perception simulation for radar stimulation in automated driving function testing

Maier

Makkapati

Horn

2018

Elektrotech. Inftech.

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Automated driving is seen as one of the key technologies that shape our future mobility. Testing these automated driving functions (ADF) in virtual environments has the potential to speed up their development and homologation. As the automated driving functions rely on sensors to perceive the environment, a key requirement for virtual testing is the ability to simulate the environment perception of the involved sensors. In this paper we present a concept for environment perception simulation of radar sensors (EPSR)-namely radar signature and stimulation input generation (RASIG)-to be employed in the context of vehicle-in-the-loop (ViL) tests in conjunction with over-the-air (OTA) stimulation hardware. The requirements on environment perception simulation of radar sensors for integration into such a test set-up and its real-time capability along with some validation results are discussed.Keywords: RCS; testing; automotive radar; automated driving functions; environment perception simulation for radar; Phong Simulation der Umgebungswahrnehmung von Radar-Sensoren für deren Stimulation in Tests von automatisierten Fahrfunktionen. Automatisiertes Fahren wird als eine der Schlüsseltechnologien gesehen, welche unsere zukünftige Mobilität formen werden. Ein Testen dieser automatisierten Fahrfunktionen in virtuellen Umgebungen könnte deren Entwicklung und Homologation beschleunigen. Da automatisierte Fahrfunktionen ihre Umgebung mittels Sensoren wahrnehmen, sind Simulationen der Umgebungswahrnehmung, im folgenden kurz Simulationen genannt, aller involvierter Sensoren eine essentielle Voraussetzung für virtuelles Testen. In diesem Artikel präsentieren wir ein Konzept zur Simulation von Radar Sensoren zum Einsatz in Vehicle-in-the-Loop Tests mit over-the-air

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“…N 0, σ 2 d and N 0, σ 2 θ represent random numbers with a mean of 0 and standard deviations of σ d and σ θ . The standard deviations are linearly dependent on the distance and angle from the sensor, and more detail is given in [34].…”

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confidence: 99%

Vehicle-in-the-Loop in Global Coordinates for Advanced Driver Assistance System

2020

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Most vehicle controllers are developed and verified with V-model. There are several traditional methods in the automotive industry called “X-in-the-Loop (XIL)”. However, the validation of advanced driver assistance system (ADAS) controllers is more complicated and needs more environmental resources because the controller interacts with the external environment of the vehicle. Vehicle-in-the-Loop (VIL) is a recently being developed approach for simulating ADAS vehicles that ensures the safety of critical test scenarios in real-world testing using virtual environments. This new test method needs both properties of traditional computer simulations and real-world vehicle tests. This paper presents a Vehicle-in-the-Loop topology for execution in global Coordinates system. Also, it has a modular structure with four parts: synchronization module, virtual environment, sensor emulator and visualizer, so each part can be developed and modified separately in combination with other parts. This structure of VIL is expected to save maintenance time and cost. This paper shows its acceptability by testing ADAS on both a real and the VIL system.

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Radar Sensor Model for the Virtual Development Process

Cited by 32 publications

References 2 publications

Virtual sensor models for real-time applications

Virtual sensor models for real-time applications

Environment perception simulation for radar stimulation in automated driving function testing

Vehicle-in-the-Loop in Global Coordinates for Advanced Driver Assistance System

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