58 research outputs found
AUTHOR CORRECTION - ERS International Congress 2019:highlights from Best Abstract awardees
No full textLorna E. Latimer, Marieke Duiverman, Mahmoud I. Abdel-Aziz, Gulser Caliskan, Sara M. Mensink-Bout, Alberto Mendoza-Valderrey, Aurelien Justet, Junichi Omura, Karthi Srikanthan, Jana De Brandt. Breathe 2019; 15: e143–e149. This article from the December 2019 issue of Breathe was published with an error in the name of one of the authors. The corrected author list is shown above. The article has been corrected and republished online.</p
A hierarchical approach for splitting truck platoons near network discontinuities
No full textTruck platooning has attracted substantial attention due to its pronounced benefits in saving energy and promising business model in freight transportation. However, one prominent challenge for the successful implementation of truck platooning is the safe and efficient interaction with surrounding traffic, especially at network discontinuities where mandatory lane changes may lead to the decoupling of truck platoons. This contribution puts forward an efficient method for splitting a platoon of vehicles near network merges. A model-based bi-level control strategy is proposed. A supervisory tactical strategy based on a first-order car-following model with bounded acceleration is designed to maximize the flow at merge discontinuities. The decisions taken at this level include optimal vehicle order after the merge, new equilibrium gaps of automated trucks at the merging point, and anticipation horizon that the platoon members start to track the new equilibrium gaps. The lower-level operational layer uses a third-order longitudinal dynamics model to compute the optimal truck accelerations so that new equilibrium gaps are created when merging vehicles start to change lane and the transient maneuvers are efficient, safe and comfortable. The tactical decisions are derived from an analytic car-following model and the operational accelerations are controlled via model predictive control with guaranteed stability. Simulation experiments are provided in order to test the feasibility and demonstrate the performance and robustness of the proposed strategy.Transport and Plannin
Halphen distribution system, toolbox for modeling travel time variability: Some insights from mesoscopic simulation
No full textThis paper introduces the Halphen system as a toolbox for modeling travel time variability. We present the three distributions of the Halphen family and the Moment-Ratio Diagram (MRD), a graphical tool for selecting the best distribution given a specific data set. Then, we explore the mapping between the positions of travel time samples on the MRD and traffic conditions based on mesoscopic traffic simulation. A comprehensive supply-demand scenario enables the comparison between day-to-day and hour-by-hour travel time variability in terms of selection of the optimal distribution. The results highlight the capability of the Halphen system to model a wide range of traffic conditions. This flexible tool has the potential to be integrated into a practice-ready decision support system for modeling travel time variability at the network scale
Parametrized cosmological mass maps dataset
No full textParametrized cosmological mass maps dataset
This dataset consists of the non-tomographic training and testing set without noise and intrinsic alignments.
It was introduced in the following paper
Fluri, Janis, et al. "Cosmological constraints with deep learning from KiDS-450 weak lensing maps." Physical Review D 100.6 (2019): 063514.
Furthermore, this dataset is released with the following paper:
Perraudin, Nathanaël, et al. "Emulation of cosmological mass maps with conditional generative adversarial networks." arXiv preprint arXiv:2004.08139 (2020).
Code related to this dataset can be found in https://renkulab.io/projects/nathanael.perraudin/darkmattergan
Description
The simulation grid consists of different cosmologies assuming a flat LambdaCDM universe.
Each of these 57 configurations was run with different values of Omega_m and sigma_8, resulting in the following parameter grid.| Omega_m, sigma_8
0.101, 1.304
0.102, 1.125
0.103, 0.947
0.120, 1.178
0.123, 1.006
0.127, 0.836
0.137, 1.230
0.142, 1.063
0.148, 0.900
0.154, 1.281
0.156, 0.741
0.161, 1.119
0.169, 0.961
0.171, 1.331
0.178, 0.807
0.179, 1.173
0.188, 1.019
0.189, 0.659
0.196, 1.225
0.199, 0.870
0.207, 1.075
0.212, 0.727
0.219, 0.930
0.225, 1.129
0.227, 0.591
0.233, 0.791
0.238, 0.988
0.250, 0.658
0.254, 0.852
0.257, 1.043
0.269, 0.534
0.271, 0.723
0.273, 0.910
0.291, 0.601
0.291, 0.783
0.292, 0.966
0.311, 0.842
0.312, 0.664
0.314, 0.487
0.330, 0.898
0.332, 0.724
0.335, 0.552
0.352, 0.782
0.356, 0.614
0.370, 0.838
0.376, 0.673
0.382, 0.510
0.395, 0.730
0.402, 0.570
0.413, 0.784
0.421, 0.628
0.431, 0.475
0.440, 0.683
0.450, 0.533
0.458, 0.737
0.469, 0.589
0.487, 0.643
Each zip file in the dataset corresponds to 1 of these combinations and contains 12 files containing 1000 images.
The source galaxy redshift distribution corresponding to these maps is the full, non-tomographic redshift distribution n(z) from Fluri et. al.
The projected matter distribution was pixelised into images of size 128px x 128px, which correspond to 5deg x 5deg of the sky.
Eventually, the resulting dataset consists of 57 sets of 12'000 sky convergence maps for a total of samples.
Citations
If you use this dataset, please cite:
@article{perraudin2020emulation,
title={Emulation of cosmological mass maps with conditional generative adversarial networks},
author={Perraudin, Nathana{\"e}l and Marcon, Sandro and Lucchi, Aurelien and Kacprzak, Tomasz},
journal={arXiv preprint arXiv:2004.08139},
year={2020}
}
and
@article{fluri2019cosmological,
title={Cosmological constraints with deep learning from KiDS-450 weak lensing maps},
author={Fluri, Janis and Kacprzak, Tomasz and Lucchi, Aurelien and Refregier, Alexandre and Amara, Adam and Hofmann, Thomas and Schneider, Aurel},
journal={Physical Review D},
volume={100},
number={6},
pages={063514},
year={2019},
publisher={APS}
Cosmological N-body simulations: a challenge for scalable generative models: Tensorflow checkpoints
No full text<p><strong>Tensorflow checkpoints: Cosmological N-body simulations: a challenge for scalable generative models</strong></p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper <strong>Cosmological N-body simulations: a challenge for scalable generative models</strong> by Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<pre><code>@inproceedings{perraudin2019cosmological,
title = {Cosmological N-body simulations: a challenge for scalable generative models},
author = {Nathana\"el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
year = {2019},
archivePrefix = {arXiv},
eprint = {1908.05519},
url = {https://arxiv.org/abs/1908.05519},
}
</code></pre>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper<br>
**Cosmological N-body simulations: a challenge for scalable generative models** by<br>
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
Hierarchical multi-injection strategy and platoon manoeuvres at network junctions
No full textInternational audienceDuring the recent years, connected automated vehicles (CAV) have shown to be a crucial technology for the upcoming developments towards the improvement of traffic conditions [2, 8, 9]. Considerable efforts have been concentrated in the development of automated strategies for longitudinal formation, a.k.a. cooperative adaptive cruise control (CACC), where inter-vehicle distance can be shortened, in order to maximize network flow and improve fuel efficiency [1, 10]. Nevertheless, one challenge prevailing in the design of such strategies is their robustness and flexibility to a variety of network configurations and traffic conditions, which implies CAV platoons should allow active platooning manoeuvers such as split, merge, join according to interactions with conventional vehicles in the network. Despite all efforts on the subject, few concrete strategies have been proposed in order to tackle the interactions between vehicle platoons and traffic. Interaction protocols among CAVs for situations of merges and lane reductions were presented in [5]. The strategies herein detail two main scenarios: the first one establishes protocols mimicking human driver interaction within the V2V layer of communication in order to achieve a merge of a single vehicle. The second scenario studies the same type of protocols when lane reduction exists in the network
Hierarchical multi-injection strategy and platoon manoeuvres at network junctions
No full textInternational audienceDuring the recent years, connected automated vehicles (CAV) have shown to be a crucial technology for the upcoming developments towards the improvement of traffic conditions [2, 8, 9]. Considerable efforts have been concentrated in the development of automated strategies for longitudinal formation, a.k.a. cooperative adaptive cruise control (CACC), where inter-vehicle distance can be shortened, in order to maximize network flow and improve fuel efficiency [1, 10]. Nevertheless, one challenge prevailing in the design of such strategies is their robustness and flexibility to a variety of network configurations and traffic conditions, which implies CAV platoons should allow active platooning manoeuvers such as split, merge, join according to interactions with conventional vehicles in the network. Despite all efforts on the subject, few concrete strategies have been proposed in order to tackle the interactions between vehicle platoons and traffic. Interaction protocols among CAVs for situations of merges and lane reductions were presented in [5]. The strategies herein detail two main scenarios: the first one establishes protocols mimicking human driver interaction within the V2V layer of communication in order to achieve a merge of a single vehicle. The second scenario studies the same type of protocols when lane reduction exists in the network
Author Correction: QUAREP-LiMi: a community endeavor to advance quality assessment and reproducibility in light microscopy
No full textComparison of a piezoceramic transducer and an EMAT for the omnidirectional transduction of SH0
No full textCalibration and impact of control strategies for splitting truck platoons at on-ramps
No full textTRB 2020, Transportation Research Board Annual Meeting, Washington, ETATS-UNIS, 12-/01/2020 - 16/01/2020Heavy-duty vehicles or trucks contribute in a significant share with global green house emissions and energy consumption in transportation systems. Truck platoon coordination strategies have introduced new technologies for better coordination and management of those intelligent transportation systems (ITS) to account for environmental efficiency. Current control strategies focus their attention on specific factors such as fuel efficiency or safety while 6 neglecting the intrinsic combined effect when interactions exist with conventional vehicles. In this work, a study considering fuel consumption and environmental effects is presented when platooning strategies are operated near merging areas (on-ramps), a consumption model that considers dynamic conditions on each one of the vehicles is calibrated from real data, and a suitable adaptation is provided to the platooning case to taking into drag effect. Different scenarios at the control level are studied to analyze the impact of splitting maneuver
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