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Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction / Jincai Huang in Transactions in GIS, vol 26 n° 2 (April 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 2 (April 2022) . - pp 735 - 754 Titre : Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction Type de document : Article/Communication Auteurs : Jincai Huang, Auteur ; Yunfei Zhang, Auteur ; Min Deng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 735 - 754 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Vedettes matières IGN] Géomatique [Termes IGN] base de données routières [Termes IGN] carrefour [Termes IGN] carte routière [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données localisées des bénévoles [Termes IGN] données routières [Termes IGN] extraction de traits caractéristiques [Termes IGN] information sémantique [Termes IGN] intégration de données [Termes IGN] navigation automobile [Termes IGN] vitesse [Termes IGN] Wuhan (Chine) Résumé : (auteur) The road map is a fundamental part of a spatial data infrastructure (SDI), and is widely applied in navigation, smart transportation, and mobile location services. Recently, with the ubiquity of positioning devices, crowdsourced trajectories have become a significant data resource for road map construction and updating. However, existing trajectory-based methods mainly place emphasis on extracting road geometry features and may ignore continuous updating of road semantic information. Hence, we propose a divide-and-conquer method to construct a spatial-semantic road map by incorporating multiple data sources (e.g., crowdsourced trajectories and geo-tagged data). The proposed method divides road map construction into two sub-tasks, road structure reconstruction and road attributes inference. The road structure reconstruction process starts to partition raw trajectory data into different cliques of roadways and road intersections, and then extracts various targeted road structures by analyzing the turning modes in different trajectory cliques. The road attributes inference process aims to infer three pieces of crucial semantic information about road speeds, turning rules, and road names from crowdsourced trajectories and geo-tagged data. The case studies in Wuhan were examined to illustrate that the proposed method can construct a routable road map with enhanced geometric structures and rich semantic information, providing a beneficial data solution for car navigation and SDI update. Numéro de notice : A2022-364 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12879 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1111/tgis.12879 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100583 [article]

Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources / Yan Lin in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 6 (October 2021) . - pp 471 - 490 Titre : Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources Type de document : Article/Communication Auteurs : Yan Lin, Auteur ; Christopher Lippitt, Auteur ; Daniel Beene, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 471 - 490 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] analyse de sensibilité [Termes IGN] ArcMap [Termes IGN] données localisées des bénévoles [Termes IGN] durée de trajet [Termes IGN] Google Maps [Termes IGN] incertitude des données [Termes IGN] indexation spatiale [Termes IGN] navigation automobile [Termes IGN] Nouveau-Mexique (Etats-Unis) [Termes IGN] OpenStreetMap [Termes IGN] plan de déplacement urbain [Termes IGN] réseau routier [Termes IGN] système d'information géographique [Termes IGN] transport public Résumé : (auteur) GIS-based spatial access measures have been used extensively to monitor social equity and to help develop policy. However, inherent uncertainties in the road datasets used in spatial access estimates remain largely underreported. These uncertainties might result in unrecognized biases within visualization products and decision-making outcomes that strive to improve social equity based on seemingly egalitarian accessibility metrics. To better understand and address these uncertainties, we evaluated variations in travel impedance for car and bus transportation using proprietary, volunteer-information-based, and free (non-volunteer-information-based) street networks. We then interpreted the measured variations through the lens of street data uncertainty and its propagation in a common E2SFCA model of spatial accessibility. Results indicated that travel impedance disagreement propagates through the modeling process to effect agreement of spatial access index (SPAI) estimates among different street sources, with larger uncertainties observed for bus travel than car travel. Higher impedance coefficients (β), a model parameter, reduced the impact of street-source variations on estimates. Less urbanized regions were found to experience higher street-source variations when compared with the core-metropolitan area. We also demonstrated that a relative spatial access measure – the spatial access ratio (SPAR) – reduced uncertainties introduced by the choice of street datasets. Careful selection of reliable street sources and model parameters (e.g. higher β), as well as consideration of the potential for bias, particularly for less urbanized areas and areas reliant on public transportation, is warranted when leveraging SPAI to inform policy. When reliable/accurate road network data are not accessible or data quality information is not available, the SPAR is a suitable alternative or supplement to SPAI for visualization and analyses. Numéro de notice : A2021-712 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1960609 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.1080/15230406.2021.1960609 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98617 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2021061	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation / Shengfeng Gu in Journal of geodesy, vol 95 n° 6 (June 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 6 (June 2021) . - n° 64 Titre : Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation Type de document : Article/Communication Auteurs : Shengfeng Gu, Auteur ; Chunqi Dai, Auteur ; Wentao Fang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] centrale inertielle [Termes IGN] correction atmosphérique [Termes IGN] couplage GNSS-INS [Termes IGN] milieu urbain [Termes IGN] navigation automobile [Termes IGN] positionnement ponctuel précis [Termes IGN] retard ionosphèrique [Termes IGN] teneur verticale totale en électrons [Termes IGN] Wuhan (Chine) Résumé : (auteur) Precise point positioning (PPP) is receiving increasing interest due to its cost-effectiveness, global coverage and high accuracy. However, its application in the urban environment is still full of challenges due to the satellite tracking sky-view. Thus, we presented a comprehensive positioning model by fusing the multi-GNSS (global navigation satellite system) combination, GNSS/INS (inertial navigation system) tightly coupled integration as well as the ionospheric and tropospheric augmentation in the undifferenced and uncombined PPP. The performance of this model in dual-frequency and single-frequency positioning was assessed with two experiments that denoted as T019 and T023, respectively, and both the experiments were carried out in a real urban environment. Particularly, the experiment T023 was carried out in the Second Ring Road of Wuhan city, which can be regarded as a typical downtown environment. Concerning the regional atmospheric augmentation, observations from 5 reference stations with an inter-station distance of about 40 km were also collected during the experimental time. The comparison between reference stations suggested that the regional tropospheric model had a precision of better than 0.6 cm in terms of zenith tropospheric delay, while the regional ionospheric model had a precision of around 0.5 total electron content unit in terms of Vertical Total Electron Content. It can be concluded that the GPS-only PPP can be improved significantly for urban vehicle navigation with these techniques, i.e., the multi-GNSS, INS tightly coupled integration and the atmospheric augmentation, through the positioning analysis, while INS tightly coupled integration makes the most contributions under the downtown environment, and the improvement of the regional atmospheric augmentation in single-frequency PPP is more significant since that single frequency is more sensitive to the ionospheric delay. In addition, it is proved that the regional atmospheric augmentation accelerates positioning convergence. The 3D positioning root-mean-square (RMS) with the comprehensive positioning model for dual frequency are 0.22 m and 0.77 m for T019 and T023, respectively. Concerning single-frequency PPP, the 3D RMS is 0.45 m and 1.17 m for T019 and T023, respectively. Moreover, taking the lane-level navigation under the downtown environment of T023 into consideration, we further presented the cumulative frequency of the horizontal positioning error less than 1 m, i.e., P(dN2+dE2−−−−−−−−−√ Numéro de notice : A2021-429 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01514-8 Date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.1007/s00190-021-01514-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97789 [article]

Multimodal scene understanding: algorithms, applications and deep learning, ch. 8. Multimodal localization for embedded systems: a survey / Imane Salhi (2019)  

Public Titre de série : Multimodal scene understanding: algorithms, applications and deep learning, ch. 8 Titre : Multimodal localization for embedded systems: a survey Type de document : Chapitre/Contribution Auteurs : Imane Salhi , Auteur ; Martyna Poreba , Auteur ; Erwan Piriou, Auteur ; Valérie Gouet-Brunet , Auteur ; Maroun Ojail, Auteur Editeur : Londres, New York : Academic Press Année de publication : 2019 Importance : pp 199 - 278 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] compréhension de l'image [Termes IGN] fusion de données [Termes IGN] géopositionnement [Termes IGN] instrument embarqué [Termes IGN] navigation automobile [Termes IGN] navigation pédestre [Termes IGN] réalité mixte Résumé : (Auteur) Localization by jointly exploiting multimodal information, like cameras, inertial measurement units (IMU), and global navigation satellite system (GNSS) data, is an active key research topic for autonomous embedded systems such as smart glasses or drones. These systems have become topical for acquisition, modeling, and interpretation for scene understanding. The exploitation of different sensor types improves the robustness of the localization, e.g. by merging the accuracy of one sensor with the reactivity of another one in a flexible manner. This chapter presents a survey of the existing multimodal techniques dedicated to the localization of autonomous embedded systems. Both the algorithmic and the hardware architecture sides are investigated in order to provide a global overview of the key elements to be considered when designing these embedded systems. Several applications in different domains (e.g. localization for mapping, pedestrian localization, automotive navigation and mixed reality) are presented to illustrate the importance of such systems nowadays in scene understanding. Numéro de notice : H2019-001 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.1016/B978-0-12-817358-9.00014-7 Date de publication en ligne : 02/08/2019 En ligne : https://doi.org/10.1016/B978-0-12-817358-9.00014-7 Format de la ressource électronique : URL chapitre Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93300

The future is already here / Sampo Savolainen in GEO: Geoconnexion international, vol 15 n° 10 (November - December 2016)

Public [article]  inGEO: Geoconnexion international > vol 15 n° 10 (November - December 2016) . - pp 30 - 31 Titre : The future is already here Type de document : Article/Communication Auteurs : Sampo Savolainen, Auteur ; Anita Lankinen, Auteur Année de publication : 2016 Article en page(s) : pp 30 - 31 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] acquisition de données [Termes IGN] client [Termes IGN] infrastructure urbaine de données localisées [Termes IGN] lever mobile [Termes IGN] navigation automobile Résumé : (éditeur) Sampo Savolainen and Anita Lankinen look at some of the latest technological advances and analyse how they use spatial data infrastructures, what else can and should be done, and explore what role they will play in our future. Numéro de notice : A2016-774 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82464 [article]

Quo vademus : Future automotive GNSS positioning in urban scenarios / Martin Escher in GPS world, vol 27 n° 5 (May 2016)  

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The role of contextual info-marks in navigating a virtual rural environment / Adam Rousell in Transactions in GIS, vol 20 n° 1 (February 2016)  

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A hybrid link-node approach for finding shortest paths in road networks with turn restrictions / Qingquan Li in Transactions in GIS, vol 19 n° 6 (December 2015)  

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Car navigation – computing routes that avoid complicated crossings / Jukka Mathias Krisp in International journal of geographical information science IJGIS, vol 29 n° 11 (November 2015)  

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Un monde à part / Françoise de Blomac in DécryptaGéo le mag, n° 161 (01/11/2014)

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An assisting, constrained 3D navigation technique for multiscale virtual 3D city models / Dieter Hildebrandt in Geoinformatica, vol 18 n° 3 (July 2014)  

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TARS: traffic-aware route search / Roy Levin in Geoinformatica, vol 18 n° 3 (July 2014)  

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Finding the right algorithm: low-cost, single-frequency GPS-GLONASS RTK for road users / Sébastien Carcanague in Inside GNSS, vol 8 n° 6 (November - December 2013) 

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A GIS-based vehicle mobility estimator for operational contexts / A. Homann in Transactions in GIS, vol 17 n° 1 (February 2013)  

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Intégration d'infos-trafic temps réel dans un moteur de calcul d'itinéraires : Projet des élèves ingénieur de l'ENSG / Alexandre Pauthonnier in Géomatique expert, n° 81 (01/07/2011)  

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