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Titre : A world model enabling information integrity for autonomous vehicles Type de document : Thèse/HDR Auteurs : Corentin Sanchez, Auteur ; Philippe Bonnifait, Directeur de thèse ; Philippe Xu, Directeur de thèse Editeur : Compiègne : Université de Technologie de Compiègne UTC Année de publication : 2022 Importance : 198 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse de Doctorat de l'Université de Technologie de Compiègne, Spécialité Automatique et RobotiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] carte routière
[Termes IGN] données multisources
[Termes IGN] information sémantique
[Termes IGN] intégrité des données
[Termes IGN] milieu urbain
[Termes IGN] navigation autonome
[Termes IGN] raisonnement
[Termes IGN] réseau routier
[Termes IGN] robot mobile
[Termes IGN] sécurité routière
[Termes IGN] véhicule sans pilote
[Termes IGN] vision par ordinateurIndex. décimale : THESE Thèses et HDR Résumé : (auteur) To drive in complex urban environments, autonomous vehicles need to understand their driving context. This task, also known as the situation awareness, relies on an internal virtual representation of the world made by the vehicle, called world model. This representation is generally built from information provided by multiple sources. High definition navigation maps supply prior information such as road network topology, geometric description of the carriageway, and semantic information including traffic laws. The perception system provides a description of the space and of road users evolving in the vehicle surroundings. Conjointly, they provide representations of the environment (static and dynamic) and allow to model interactions. In complex situations, a reliable and non-misleading world model is mandatory to avoid inappropriate decision-making and to ensure safety. The goal of this PhD thesis is to propose a novel formalism on the concept of world model that fulfills the situation awareness requirements for an autonomous vehicle. This world model integrates prior knowledge on the road network topology, a lane-level grid representation, its prediction over time and more importantly a mechanism to control and monitor the integrity of information. The concept of world model is present in many autonomous vehicle architectures but may take many various forms and sometimes only implicitly. In some work, it is part of the perception process when in some other it is part of a decisionmaking process. The first contribution of this thesis is a survey on the concept of world model for autonomous driving covering different levels of abstraction for information representation and reasoning. Then, a novel representation is proposed for the world model at the tactical level combining dynamic objects and spatial occupancy information. First, a graph based top-down approach using a high-definition map is proposed to extract the areas of interests with respect to the situation from the vehicle's perspective. It is then used to build a Lane Grid Map (LGM), which is an intermediate space state representation from the ego-vehicle point of view. A top-down approach is chosen to assess and characterize the relevant information of the situation. Additionally to classical free-occupied states, the unknown state is further characterized by the notions of neutralized and safe areas that provide a deeper level of understanding of the situation. Another contribution to the world model is an integrity management mechanism that is built upon the LGM representation. It consists in managing the spatial sampling of the grid cells in order to take into account localization and perception errors and to avoid misleading information. Regardless of the confidence on localization and perception information, the LGM is capable of providing reliable information to decision making in order not to take hazardous decisions.The last part of the situation awareness strategy is the prediction of the world model based on the LGM representation. The main contribution is to show how a classical object-level prediction fits this representation and that the integrity can also be extended at the prediction stage. It is also depicted how a neutralized area can be used in the prediction stage to provide a better situation prediction. The work relies on experimental data in order to demonstrate a real application of a complex situation awareness representation. The approach is evaluated with real data obtained thanks to several experimental vehicles equipped with LiDAR sensors and IMU with RTK corrections in the city of Compi_egne. A high-definition map has also been used in the framework of the SIVALab joint laboratory between Renault and Heudiasyc CNRS-UTC. The world model module has been implemented (with ROS software) in order to fulfll real-time application and is functional on the experimental vehicles for live demonstrations. Note de contenu : General introduction
1- World model for autonomous vehicules
2- An architecture for WM
3- A lane level world model
4- Set-based LGM prediction
General conclusionNuméro de notice : 24089 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Automatique et Robotique : UTC Compiègne : 2022 Organisme de stage : Laboratoire Heudiasyc DOI : sans En ligne : https://www.theses.fr/2022COMP2683 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102509 Adaptive feature weighted fusion nested U-Net with discrete wavelet transform for change detection of high-resolution remote sensing images / Congcong Wang in Remote sensing, vol 13 n° 24 (December-2 2021)
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Titre : Adaptive feature weighted fusion nested U-Net with discrete wavelet transform for change detection of high-resolution remote sensing images Type de document : Article/Communication Auteurs : Congcong Wang, Auteur ; Wenbin Sun, Auteur ; Deqin Fan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] détection de changement
[Termes IGN] fusion de données
[Termes IGN] image à haute résolution
[Termes IGN] pondération
[Termes IGN] réseau neuronal siamois
[Termes IGN] transformation en ondelettesRésumé : (auteur) The characteristics of a wide variety of scales about objects and complex texture features of high-resolution remote sensing images make deep learning-based change detection methods the mainstream method. However, existing deep learning methods have problems with spatial information loss and insufficient feature representation, resulting in unsatisfactory effects of small objects detection and boundary positioning in high-resolution remote sensing images change detection. To address the problems, a network architecture based on 2-dimensional discrete wavelet transform and adaptive feature weighted fusion is proposed. The proposed network takes Siamese network and Nested U-Net as the backbone; 2-dimensional discrete wavelet transform is used to replace the pooling layer; and the inverse transform is used to replace the upsampling to realize image reconstruction, reduce the loss of spatial information, and fully retain the original image information. In this way, the proposed network can accurately detect changed objects of different scales and reconstruct change maps with clear boundaries. Furthermore, different feature fusion methods of different stages are proposed to fully integrate multi-scale and multi-level features and improve the comprehensive representation ability of features, so as to achieve a more refined change detection effect while reducing pseudo-changes. To verify the effectiveness and advancement of the proposed method, it is compared with seven state-of-the-art methods on two datasets of Lebedev and SenseTime from the three aspects of quantitative analysis, qualitative analysis, and efficiency analysis, and the effectiveness of proposed modules is validated by an ablation study. The results of quantitative analysis and efficiency analysis show that, under the premise of taking into account the operation efficiency, our method can improve the recall while ensuring the detection precision, and realize the improvement of the overall detection performance. Specifically, it shows an average improvement of 37.9% and 12.35% on recall, and 34.76% and 11.88% on F1 with the Lebedev and SenseTime datasets, respectively, compared to other methods. The qualitative analysis shows that our method has better performance on small objects detection and boundary positioning than other methods, and a more refined change map can be obtained. Numéro de notice : A2021-920 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13244971 Date de publication en ligne : 07/12/2021 En ligne : https://doi.org/10.3390/rs13244971 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99244
in Remote sensing > vol 13 n° 24 (December-2 2021) . - n°[article]Application of a hand-held LiDAR scanner for the urban cadastral detail survey in digitized cadastral area of Taiwan urban city / Shih-Hong Chio in Remote sensing, vol 13 n° 24 (December-2 2021)
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Titre : Application of a hand-held LiDAR scanner for the urban cadastral detail survey in digitized cadastral area of Taiwan urban city Type de document : Article/Communication Auteurs : Shih-Hong Chio, Auteur ; Kai-Wen Hou, Auteur Année de publication : 2021 Article en page(s) : n° 4981 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] cadastre numérique
[Termes IGN] chevauchement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage
[Termes IGN] étude de faisabilité
[Termes IGN] lidar mobile
[Termes IGN] milieu urbain
[Termes IGN] plan cadastral
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] TaïwanRésumé : (auteur) The cadastral detail data is used for overlap analysis with digitized graphic cadastral maps to solve the problem of inconsistencies between cadastral maps and the current land situation. This study investigated the feasibility of a handheld LiDAR scanner to collect 3D point clouds in an efficient way for a detail survey in urban environments with narrow and winding streets. Then, urban detail point clouds were collected by the handheld LiDAR scanner. After point cloud filtering and the ranging systematic error correction that was determined by a plane-based calibration method, the collected point clouds were transformed to the TWD97 cadastral coordinate system using control points. The land detail line data were artificially digitized and the results showed that about 97% error of the digitized detail positions was less than 15 cm compared to the check points surveyed by a total station. The results demonstrated the feasibility of using a handheld LiDAR scanner to perform an urban cadastral detail survey in digitized graphic areas. Therefore, the handheld LiDAR scanner could be used for the production of the detail lines for urban cadastral detail surveying for digitized cadastral areas in Taiwan. Numéro de notice : A2021-888 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13244981 Date de publication en ligne : 08/12/2021 En ligne : https://doi.org/10.3390/rs13244981 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99242
in Remote sensing > vol 13 n° 24 (December-2 2021) . - n° 4981[article]Mapping temperate forest tree species using dense Sentinel-2 time series / Jan Hemmerling in Remote sensing of environment, vol 267 (December-15 2021)
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Titre : Mapping temperate forest tree species using dense Sentinel-2 time series Type de document : Article/Communication Auteurs : Jan Hemmerling, Auteur ; Dirk Pflugmacher, Auteur ; Patrick Hostert, Auteur Année de publication : 2021 Article en page(s) : n° 112743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte de la végétation
[Termes IGN] espèce végétale
[Termes IGN] Europe centrale
[Termes IGN] filtrage numérique d'image
[Termes IGN] forêt tempérée
[Termes IGN] image Sentinel-MSI
[Termes IGN] série temporelleRésumé : (auteur) Precise information on tree species composition is critical for forest management and conservation, but mapping tree species with satellite data over large areas is still a challenge. Since 2017, Sentinel-2A/B provide multi-spectral time series with global coverage at an unprecedented spatial and temporal resolution. This is a new opportunity for mapping tree species over large areas that has not yet been fully explored. Because of the high spatial and temporal resolution, Sentinel-2 time series improve the characterization of vegetation phenology and canopy structure, parameters that are intrinsically linked to tree species. The objective of this study was to test the utility of a Sentinel-2 time-series based approach for mapping tree species in a temperate forest region in Central Europe. Using stand-wise forest inventory data for single species stands we assess how well main and minor tree species can be mapped, and if the addition of environmental variables and spatial texture metrics improves the classification accuracy. Our time series approach utilizes all available Sentinel-2 observations and an ensemble of radial basis convolution filters to build cloud-free 5-day time series for each spectral band. The time series are then used as input features to classify seventeen tree species. Our results show the potential of Sentinel-2 time-series based classification, but they also show the challenges associated with mapping a diverse portfolio of tree species. Accuracy of the nine main species, with an area proportion greater than 0.5%, ranged between 98.9% and 66.8%, which is promising for a large area. Adding detailed environmental data and texture metrics to the spectral model only marginally increased the accuracy of a few minor tree species. Overall, the eight minor tree species with area proportions less than 0.5% were most strongly affected by classification errors. Although the absolute mapped area of minor species correlated well with the estimated reference area, the small class areas of minor species lead to high classification errors in relative terms. Mapping minor tree species is challenging for statistical reasons (i.e., class imbalance, small sample size and class variance). Using all available Sentinel-2 data allows building dense time series at high spatial resolution that are mandatory for improved tree species mapping. We were able to show that the spectral time series is the prime explanatory information, even when complementing our analyses with texture information and various environmental data. The results suggest that with the applied data harmonization approach precise regional tree species mapping is feasible. Numéro de notice : A2021-939 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112743 Date de publication en ligne : 13/10/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112743 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99748
in Remote sensing of environment > vol 267 (December-15 2021) . - n° 112743[article]Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps / Batistin Bour in Forest ecology and management, vol 502 (December-15 2021)
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Titre : Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps Type de document : Article/Communication Auteurs : Batistin Bour, Auteur ; Victor Danneyrolles, Auteur ; Yan Boucher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] carte forestière
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt boréale
[Termes IGN] forêt de production
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] Picea mariana
[Termes IGN] productivité
[Termes IGN] Québec (Canada)
[Termes IGN] récolte de bois
[Termes IGN] semis de pointsRésumé : (auteur) Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which drives global carbon dynamics and timber allocation. This study presents a method that combines a single airborne LiDAR acquisition and time since harvest maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model in which forest height at a 20 m × 20 m pixel resolution is a function of stand age, combined with environmental variables (e.g., slope, site moisture, surface deposit). Our results highlight the model's strong predictive power: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.74; relative RMSE = 19%). Environmental variables thus allowed to accurately predict forest productivity with a high spatial resolution (20 m × 20 m pixels) and predicted forest height growth in the first 50 years after logging ranged between 16 and 27 cm·year−1 across the whole study area, with a mean of 20.5 cm·year−1. The spatial patterns of potential height growth were strongly linked to the effect of topographical variables, with better growth rates on mesic slopes compared to poorly drained soils. Such models could have key implications in forest management, for example to maintain forest ecosystem services by adjusting the harvesting rates depending on forest productivity across the landscapes. Numéro de notice : A2021-708 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2021.119697 Date de publication en ligne : 25/09/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98819
in Forest ecology and management > vol 502 (December-15 2021) . - n° 119697[article] PermalinkBaseline-dependent clock offsets in VLBI data analysis / Hana Krásná in Journal of geodesy, vol 95 n° 12 (December 2021)
PermalinkBuilding fuzzy areal geographical objects from point sets / Jifa Guo in Transactions in GIS, vol 25 n° 6 (December 2021)
PermalinkComparative analysis for methods of building digital elevation models from topographic maps using geoinformation technologies / Vadim Belenok in Geodesy and cartography, vol 47 n° 4 (December 2021)
PermalinkEstimation of individual tree stem biomass in an uneven-aged structured coniferous forest using multispectral LiDAR data / Nikos Georgopoulos in Remote sensing, vol 13 n° 23 (December-1 2021)
PermalinkEvaluating narrative in geoportals for territorial public policies / Luis Manuel Batista in Cartographica, vol 56 n° 4 (Winter 2021)
PermalinkPermalinkExtensification and afforestation of cultivated mineral soil for climate change mitigation in Finland / Boris Tupek in Forest ecology and management, vol 501 (December-1 2021)
PermalinkFast estimation for robust supervised classification with mixture models / Erwan Giry Fouquet in Pattern recognition letters, vol 152 (December 2021)
PermalinkA generic information framework for decision-making in a forest-based bio-economy / Jean-Baptiste Pichancourt in Annals of Forest Science, vol 78 n° 4 (December 2021)
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