arXiv subjects

Eric Armengaud

Publications and source records attributed to Eric Armengaud.

At least 19 recordsLinked to original sources

arXiv2026

Probing the matter-dominated expansion with multi-redshift Lyman-$\alpha$ BAO from DESI DR2

We present a multi-redshift Baryon Acoustic Oscillations (BAO) analysis of the DESI Data Release 2 (DR2) Lyman-$\alpha$ (Ly$\alpha$) forest, splitting the forest auto-correlation and its cross-correlation with quasars into three redshift bins. We obtain BAO measurements at effective redshifts $z_{\rm eff} = 2.13$, $2.40$, and $2.81$ with $\sim2.0$--$2.5\%$ precision per bin in the radial and transverse directions, corresponding to $\sim1.1$--$1.2\%$ precision for the isotropic BAO measurement. Using the same data products and modeling framework as the DESI DR2 Ly$\alpha$ BAO analysis, we validate the pipeline on $400$ synthetic datasets and find unbiased BAO recovery with well-calibrated uncertainties. The measurements show an increase in the isotropic dilation parameter $D_V/r_d$ from $30.26\pm0.39$ to $32.22\pm0.47$ and in the Alcock-Paczy\'nski parameter $D_M/D_H$ from $3.96\pm0.15$ to $5.63^{+0.22}_{-0.24}$. The Hubble distance $D_H/r_d$ decreases from $9.40\pm0.20$ to $7.22\pm0.17$, providing a direct measurement of the expansion history consistent with $\Lambda$CDM and the expected matter-dominated scaling, with $H(z)\propto(1+z)^n$ giving $n=1.34\pm0.16$. The redshift split also provides a self-consistent measurement of clustering evolution: the Ly$\alpha$ forest bias evolves as $(1+z)^\gamma$ with $\gamma_\alpha=3.05\pm0.16$, the RSD parameter has a redshift evolution described by $\gamma_\beta=-0.97\pm0.26$, and the quasar bias evolves with $\gamma_Q=1.56\pm0.23$, consistent with independent quasar clustering measurements. Combining these three-bin BAO measurements with DESI DR2 galaxy and quasar BAO measurements yields cosmological constraints consistent with the single-bin Ly$\alpha$ BAO analysis in flat $\Lambda$CDM and $w_0w_a$CDM and improves curvature constraints by $\sim12\%$ in $\Lambda$CDM$+\Omega_\mathrm{K}$.

astro-ph.CO↗

arXiv2025

Low-redshift 3D Lyman-{\alpha} Forest Correlations with China Space Station Telescope

While the Lyman-$\alpha$ (Ly$\alpha$) forest traces the large-scale matter distribution over a wide range of redshift, its three-dimensional (3D) clustering at $z < 2$ has not yet been measured. We investigate the prospects for measuring low-redshift Ly$\alpha$ correlations with the UV slitless spectroscopic instrument of the China Space Station Telescope (CSST). We construct mock CSST quasar spectra that reproduce the expected survey depth, spectral resolution and noise properties, and derive Ly$\alpha$ auto-correlation functions and cross-correlations with quasars (QSO) and emission-line galaxies (ELG) in the range $1.1 < z < 2.0$. We then interpret these three-dimensional correlation functions with a standard anisotropic redshift-space clustering model and obtain forecast constraints on the Ly$\alpha$ and tracer parameters. At an effective redshift $z_{\rm eff}=1.59$ (1.58 for ELGs), the Ly$\alpha$ bias parameters will be measured with a 10-30\% precision, depending on priors on other tracer's biases. We also forecast a marginal $2.5\sigma$ ($3.7\sigma$) detection of the BAO feature, corresponding to a $\sim$10\% (7\%) constraint on the isotropic BAO scale, from the combination of Ly$\alpha$ auto- and Ly$\alpha$-QSO (ELG) cross-correlations. These results show that CSST can provide the first three-dimensional characterization of the low-redshift Ly$\alpha$ forest and a complementary Ly$\alpha$-based BAO measurement at $z < 2$, helping to link galaxy clustering surveys with high-redshift Ly$\alpha$ forest studies.

astro-ph.CO↗

arXiv2025

The Lyman-$\alpha$ Forest from LBGs: First 3D Correlation Measurement with DESI and Prospects for Cosmology

The Lyman-$\alpha$ (Ly$\alpha$) forest is a key tracer of large-scale structure at redshifts z > 2, traditionally studied using spectra of quasars. Here, we explore the viability Lyman Break Galaxies (LBGs) as alternative background sources for Ly$\alpha$ forest studies. We analyze 4,151 Ly$\alpha$ forest skewers extracted from LBG spectra obtained in the DESI pilot surveys in the COSMOS and XMM-LSS fields. We present the first measurement of the Ly$\alpha$ forest auto-correlation function derived exclusively from LBG spectra, probing comoving separations up to 48 $h^{-1}$Mpc at an effective redshift of $z_\mathrm{eff}$ = 2.70. The measured signal is consistent with that from DESI DR2 quasar Ly$\alpha$ forest spectra at a comparable redshift, validating LBGs as reliable background sources. We also measure the cross-correlation between the LBG Ly$\alpha$ forest and 13,362 galaxy positions, showing that this observable serves as a sensitive diagnostic for galaxy redshift uncertainties and systematic offsets. Finally, using synthetic LBG spectra and Fisher forecasts, we show that a future wide-area survey over 5000 deg$^2$, targeting 1000 LBGs per deg$^2$ at similar signal-to-noise than our dataset, could enable Ly$\alpha$ forest baryon acoustic oscillation (BAO) measurements with 0.4% precision on the isotropic BAO scale and 1.3% on the anisotropic (Alcock-Paczynski) scale. Combining BAO with a Ly$\alpha$ forest full-shape analysis improves the AP constraint to 0.6%. These results open a new path for precision cosmology at high redshift using dense LBG samples.

astro-ph.CO↗

arXiv2025

DESI DR1 Ly{\alpha} 1D power spectrum: The Fast Fourier Transform estimator measurement

We present the one-dimensional Lyman-$\alpha$ forest power spectrum measurement derived from the data release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). The measurement of the Lyman-$\alpha$ forest power spectrum along the line of sight from high-redshift quasar spectra provides information on the shape of the linear matter power spectrum, neutrino masses, and the properties of dark matter. In this work, we use a Fast Fourier Transform (FFT)-based estimator, which is validated on synthetic data in a companion paper. Compared to the FFT measurement performed on the DESI early data release, we improve the noise characterization with a cross-exposure estimator and test the robustness of our measurement using various data splits. We also refine the estimation of the uncertainties and now present an estimator for the covariance matrix of the measurement. Furthermore, we compare our results to previous high-resolution and eBOSS measurements. In another companion paper, we present the same DR1 measurement using the Quadratic Maximum Likelihood Estimator (QMLE). These two measurements are consistent with each other and constitute the most precise one-dimensional power spectrum measurement to date, while being in good agreement with results from the DESI early data release.

astro-ph.CO↗

arXiv2024

Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: New models and constraints from the eBOSS measurement

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-$\alpha$ forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with $4096^3$ hydrodynamical cells in a 120 Mpc ($\sim$ 81Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-$\alpha$ forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters $A_{\mathrm{Ly}\alpha}$ and $n_{\mathrm{Ly}\alpha}$. While the best-fit Planck $\Lambda$CDM model has $A_{\mathrm{Ly}\alpha}=8.79$ and $n_{\mathrm{Ly}\alpha}=-2.363$, from DR14 eBOSS data we find that $A_{\mathrm{Ly}\alpha}<7.6$ (95\% CI) and $n_{\mathrm{Ly}\alpha}=-2.369 \pm 0.008$. The low value of $A_{\mathrm{Ly}\alpha}$, in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman-$\alpha$ forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find $A_{\mathrm{Ly}\alpha}=9.8\pm1.1$ in accordance with Planck.

astro-ph.CO↗

arXiv2024

High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, $z>2$, a region only covered so far by Lyman-$\alpha$ forest measurements. In this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the $g,r,z$ and $u$ bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain $57\%$ of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of $83\pm3\%$, for a purity of the selected LBG sample of $90\pm2\%$. This would deliver a confirmed LBG density of $\sim 620$ deg$^{-2}$ in the range $2.3<z<3.5$ for a $r$-band limiting magnitude $r<24.2$. Selections optimised for high redshift efficiency retain $73\%$ of the observed targets after spectroscopic confirmation, with $89\pm4\%$ efficiency for $97\pm2\%$ purity. This would provide a confirmed LBG density of $\sim 470$ deg$^{-2}$ in the range $2.8<z<3.5$ for a $r$-band limiting magnitude $r<24.5$. A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of $b_{LBG} = 3.3 \pm 0.2 (stat.)$ is obtained for a mean redshift of 2.9 and a limiting magnitude in $r$ of 24.2, in agreement with results reported in the literature.

astro-ph.CO↗

arXiv2023

Measurement of the small-scale 3D Lyman-$\alpha$ forest power spectrum

Small-scale correlations measured in the Lyman-$\alpha$ (Ly$\alpha$) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, $P_{\rm 3D}$, of the Ly$\alpha$ forest at wavenumbers $k$ corresponding to small, $\sim$ Mpc scales. In order to estimate $P_{\rm 3D}$ from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Ly$\alpha$ forest, $P_{\rm 1D}$. This methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Ly$\alpha$ forest sample, providing as a proof of principle, a first $P_{\rm 3D}$ measurement averaged over two redshift bins $z=2.2$ and $z=2.4$. This work highlights the potential for forthcoming $P_{\rm 3D}$ measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of $P_{\rm 1D}$.

astro-ph.CO↗

arXiv2023

Optimal 1D Ly$\alpha$ Forest Power Spectrum Estimation -- III. DESI early data

The one-dimensional power spectrum $P_{\mathrm{1D}}$ of the Ly$\alpha$ forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of $P_{\mathrm{1D}}$ with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of $54~600$ quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with two-dimensional image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly$\alpha$ emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and implications for the upcoming DESI Year 1 analysis.

astro-ph.CO↗

arXiv2023

The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman-$\alpha$ forest samples with Fast Fourier Transform

We present the one-dimensional Lyman-$\alpha$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$, contained in the DESI Early Data Release and the first two months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated to the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on log-normal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Lyman-$\alpha$ forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.

astro-ph.CO↗

arXiv2022

First measurement of the correlation between cosmic voids and the Lyman-$\alpha$ forest

We report the first detection at a median redshift $z = 2.49$ of large-scale matter flows around cosmic voids. Voids are identified within a tomographic map of large-scale Lyman-$\alpha$ (Ly$\alpha$) transmissions, built from the eBOSS Ly$\alpha$ forest sample in the SDSS Stripe 82 field. We measure the imprint of flows around voids, known as redshift-space distortions (RSD), with a statistical significance of $8\,\sigma$. The observed quadrupole of the void-forest cross-correlation is described by a linear RSD model. The derived RSD parameter of the Ly$\alpha$ forest around voids is $\beta = 1.21 \pm 0.18$. Our model accounts for the tomographic effect induced by the Ly$\alpha$ data being located along parallel quasar lines of sight. This work presents a novel approach to observing the growth of cosmic structures at redshifts currently inaccessible to galaxy surveys.

astro-ph.CO↗

arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Prospects for obtaining Dark Matter Constraints with DESI

Despite efforts over several decades, direct-detection experiments have not yet led to the discovery of the dark matter (DM) particle. This has led to increasing interest in alternatives to the Lambda CDM (LCDM) paradigm and alternative DM scenarios (including fuzzy DM, warm DM, self-interacting DM, etc.). In many of these scenarios, DM particles cannot be detected directly and constraints on their properties can ONLY be arrived at using astrophysical observations. The Dark Energy Spectroscopic Instrument (DESI) is currently one of the most powerful instruments for wide-field surveys. The synergy of DESI with ESA's Gaia satellite and future observing facilities will yield datasets of unprecedented size and coverage that will enable constraints on DM over a wide range of physical and mass scales and across redshifts. DESI will obtain spectra of the Lyman-alpha forest out to z~5 by detecting about 1 million QSO spectra that will put constraints on clustering of the low-density intergalactic gas and DM halos at high redshift. DESI will obtain radial velocities of 10 million stars in the Milky Way (MW) and Local Group satellites enabling us to constrain their global DM distributions, as well as the DM distribution on smaller scales. The paradigm of cosmological structure formation has been extensively tested with simulations. However, the majority of simulations to date have focused on collisionless CDM. Simulations with alternatives to CDM have recently been gaining ground but are still in their infancy. While there are numerous publicly available large-box and zoom-in simulations in the LCDM framework, there are no comparable publicly available WDM, SIDM, FDM simulations. DOE support for a public simulation suite will enable a more cohesive community effort to compare observations from DESI (and other surveys) with numerical predictions and will greatly impact DM science.

astro-ph.CO↗

arXiv2021

TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence

This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges

cs.AI↗

arXiv2021

WAP: Digital Dependability Identities

Cyber-Physical Systems (CPS) provide enormous potential for innovation but a precondition for this is that the issue of dependability has been addressed. This paper presents the concept of a Digital Dependability Identity (DDI) of a component or system as foundation for assuring the dependability of CPS. A DDI is an analyzable and potentially executable model of information about the dependability of a component or system. We argue that DDIs must fulfill a number of properties including being universally useful across supply chains, enabling off-line certification of systems where possible, and providing capabilities for in-field certification of safety of CPS. In this paper, we focus on system safety as one integral part of dependability and as a practical demonstration of the concept, we present an initial implementation of DDIs in the form of Conditional Safety Certificates (also known as ConSerts). We explain ConSerts and their practical operationalization based on an illustrative example.

cs.OH↗

arXiv2020

Simulating intergalactic gas for DESI-like small scale Lyman{\alpha} forest observations

Measurements of the Ly$\alpha$ forest based on large numbers of quasar spectra from sky surveys such as SDSS/eBOSS accurately probe the distribution of matter on small scales and thus provide important constraints on several ingredients of the cosmological model. A main summary statistic derived from those measurements is the one-dimensional power spectrum, P1D, of the Ly$\alpha$ absorption. However, model predictions for P1D rely on expensive hydrodynamical simulations of the intergalactic medium, which was the limiting factor in previous analyses. Datasets from upcoming surveys such as DESI will push observational accuracy near the 1%-level and probe even smaller scales. This observational push mandate seven more accurate simulations as well as more careful exploration of parameter space. In this work we evaluate the robustness and accuracy of simulations and the statistical framework used to constrain cosmological parameters. We present a comparison between the grid-based simulation code Nyx and SPH-based code Gadget in the context ofP1D. In addition, we perform resolution and box-size convergence tests using Nyx code. We use a Gaussian process emulation scheme to reduce the number of simulations required for exploration of parameter space without sacrificing the model accuracy. We demonstrate the ability to produce unbiased parameter constraints in an end-to-end inference test using mock eBOSS- and DESI-like data, and we advocate for the usage of adaptive sampling schemes as opposed to using a fixed Latin hypercube design.

astro-ph.CO↗

arXiv2020

The impact of AGN feedback on the 1D power spectra from the Ly$\alpha$ forest using the Horizon-AGN suite of simulations

The Lyman-$\alpha$ forest is a powerful probe for cosmology, but it is also strongly impacted by galaxy evolution and baryonic processes such as Active Galactic Nuclei (AGN) feedback, which can redistribute mass and energy on large scales. We constrain the signatures of AGN feedback on the 1D power spectrum of the Lyman-$\alpha$ forest using a series of eight hydro-cosmological simulations performed with the Adaptative Mesh Refinement code RAMSES. This series starts from the Horizon-AGN simulation and varies the sub-grid parameters for AGN feeding, feedback and stochasticity. These simulations cover the whole plausible range of feedback and feeding parameters according to the resulting galaxy properties. AGNs globally suppress the Lyman-$\alpha$ power at all scales. On large scales, the energy injection and ionization dominate over the supply of gas mass from AGN-driven galactic winds, thus suppressing power. On small scales, faster cooling of denser gas mitigates the suppression. This effect increases with decreasing redshift. We provide lower and upper limits of this signature at nine redshifts between $z=4.25$ and $z=2.0$, making it possible to account for it at post-processing stage in future work given that running simulations without AGN feedback can save considerable amounts of computing resources. Ignoring AGN feedback in cosmological inference analyses leads to strong biases with 2\% shift on $\sigma_8$ and 1\% shift on $n_s$, which represents twice the standards deviation of the current constraints on $n_s$.

astro-ph.GA↗

arXiv2019

The Sixteenth Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the sixteenth data release (DR16) from the Sloan Digital Sky Surveys; the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the southern hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey (TDSS) and new data from the SPectroscopic IDentification of ERosita Survey (SPIDERS) programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).

astro-ph.GA↗

arXiv2019

Hints, neutrino bounds and WDM constraints from SDSS DR14 Lyman-$\alpha$ and Planck full-survey data

The Ly-$\alpha$ forest 1D flux power spectrum is a powerful probe of several cosmological parameters. Assuming a $\Lambda$CDM cosmology including massive neutrinos, we find that the latest SDSS DR14 BOSS and eBOSS Ly-$\alpha$ forest data is in very good agreement with current weak lensing constraints on $(\Omega_m, \sigma_8)$ and has the same small level of tension with Planck. We did not identify a systematic effect in the data analysis that could explain this small tension, but we show that it can be reduced in extended cosmological models where the spectral index is not the same on the very different times and scales probed by CMB and Ly-$\alpha$ data. A particular case is that of a $\Lambda$CDM model including a running of the spectral index on top of massive neutrinos. With combined Ly-$\alpha$ and Planck data, we find a slight (3$\sigma$) preference for negative running, $\alpha_s= -0.010 \pm 0.004$ (68% CL). Neutrino mass bounds are found to be robust against different assumptions. In the $\Lambda$CDM model with running, we find $\sum m_\nu <0.11$ eV at the 95% confidence level for combined Ly-$\alpha$ and Planck (temperature and polarisation) data, or $\sum m_\nu < 0.09$ eV when adding CMB lensing and BAO data. We further provide strong and nearly model-independent bounds on the mass of thermal warm dark matter. For a conservative configuration consisting of SDSS data restricted to $z<4.5$ combined with XQ-100 \lya data, we find $m_X > 5.3\;\mathrm{keV}$ (95\%CL).

astro-ph.CO↗

arXiv2019

Development Framework for Longitudinal Automated Driving Functions with Off-board Information Integration

Increasingly sophisticated function development is taking place with the aim of developing efficient, safe and increasingly Automated Driving Functions. This development is possible with the use of diverse data from sources such as Navigation Systems, eHorizon, on-board sensor data, Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication. Increasing challenges arise with the dependency on large amounts of real-time data coming from off-board sources. At the core of addressing these challenges lies the concept of a Digital Dependability Identity (DDI) of a component or system. DDIs are modular, composable, and executable components in the field, facilitating: $\bullet$ efficient synthesis of component and system dependability information, $\bullet$ effective evaluation of information for safe and secure composition of highly distributed and autonomous Cyber Physical Systems. In AVL's Connected Powertrain (TM), Automated Driving Functions are tailored to Powertrain Control Strategies that predictively increase energy efficiency according to the powertrain type and its component efficiencies. Simultaneously, the burden on the driver is reduced by optimizing the vehicle velocity, whilst minimizing any journey time penalty.In this work, the development of dependable Automated Driving Functions is exemplified by the Traffic Light Assistant, an adaptive strategy that utilizes predictions of preceding traffic, upcoming road curvature, inclination, speed limits, and especially traffic light signal phase and timing information to increase the energy efficiency in an urban traffic environment. A key aspect of this development is the possibility for seamless and simultaneous development; from office simulation to human-in-the-loop and to real-time tests that include vehicle and powertrain hardware. Driver's acceptance and comfort is rated in an advanced diver simulator mounted on a hexapod, capable of emulating longitudinal and lateral acceleration of a real vehicle. Test results from real-time function validation on a Powertrain Testbed are shown, including real traffic light signal phasing information and traffic flow representation on Graz city roads.

eess.SP↗