Centre dedocumentation
scientifique

Multi-agent reinforcement learning to unify order-matching and vehicle-repositioning in ride-hailing services / Mingyue Xu in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 2 (February 2023) . - pp 380 - 402 Titre : Multi-agent reinforcement learning to unify order-matching and vehicle-repositioning in ride-hailing services Type de document : Article/Communication Auteurs : Mingyue Xu, Auteur ; Peng Yue, Auteur ; Fan Yu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 380 - 402 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] appariement de données localisées [Termes IGN] apprentissage profond [Termes IGN] autopartage [Termes IGN] Chine [Termes IGN] distribution spatiale [Termes IGN] interaction humain-espace [Termes IGN] modèle de Markov [Termes IGN] système d'information urbain [Termes IGN] système multi-agents [Termes IGN] taxi [Termes IGN] transmission de données [Termes IGN] zone d'activité économique Résumé : (auteur) The popularity of ride-hailing platforms has significantly improved travel efficiency by providing convenient and personalized transportation services. Designing an effective ride-hailing service generally needs to address two tasks: order matching that assigns orders to available vehicles and proactive vehicle repositioning that deploys idle vehicles to potentially high-demand regions. Recent studies have intensively utilized deep reinforcement learning to solve the two tasks by learning an optimal dispatching strategy. However, most of them generate actions for the two tasks independently, neglecting the interactions between the two tasks and the communications among multiple drivers. To this end, this paper provides an approach based on multi-agent deep reinforcement learning where the two tasks are modeled as a unified Markov decision process, and the colossal state space and competition among drivers are addressed. Additionally, a modifiable agent-specific state representation is proposed to facilitate knowledge transferring and improve computing efficiency. We evaluate our approach on a public taxi order dataset collected in Chengdu, China, where a variable number of simulated vehicles are tested. Experimental results show that our approach outperforms seven existing baselines, reducing passenger rejection rate, driver idle time and improving total driver income. Numéro de notice : A2023-058 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2119477 Date de publication en ligne : 07/09/2022 En ligne : https://doi.org/10.1080/13658816.2022.2119477 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102396 [article]

Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (October 2021)  

Public [article]  inJournal of applied geodesy > vol 15 n° 4 (October 2021) . - pp 279 - 291 Titre : Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm Type de document : Article/Communication Auteurs : Sumitra Iyer, Auteur ; Alka Mahajan, Auteur Année de publication : 2021 Article en page(s) : pp 279 - 291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] auto-régression [Termes IGN] déformation temporelle dynamique (algorithme) [Termes IGN] format RINEX [Termes IGN] Inde [Termes IGN] modèle de simulation [Termes IGN] modèle ionosphérique [Termes IGN] série temporelle [Termes IGN] signal GPS [Termes IGN] tempête magnétique [Termes IGN] teneur totale en électrons [Termes IGN] teneur verticale totale en électrons Résumé : (auteur) The ionospheric total electron content (TEC) severely impacts the positional accuracy of a single frequency Global Positioning System (GPS) receiver at the equatorial latitudes. The ionosphere causes a frequency-dependent group delay in the GPS-ranging signals, which reduces the receiver’s accuracy. Further, the variations in TEC due to various space weather phenomena make the ionosphere’s behaviour nonhomogeneous and complex. Hence, developing an accurate forecast model that can track the dynamic behaviour of the ionosphere remains a challenge. However, advances in emerging data-driven algorithms have been found helpful in tracking non-stationary behavior in TEC. These models help forecast the delays in advance. The multivariate Vector Autoregression model (VAR) predicts the Ionospheric TEC in the proposed model. The prediction model uses input data compiled in real-time from the lag values of incoming TEC data and features extracted from TEC. The TEC is predicted in real-time and tested for different prediction intervals. The metrics – Mean Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used for testing and validating the accuracy of the model statistically. Testing the predicted output accuracy is also done with the dynamic time warping (DTW) algorithm by comparing it with the actual value obtained from the dual-frequency receiver. The model is tested for storm days of the year 2015 for Bangalore and Hyderabad stations and found to be reliable and accurate. A prediction interval of twenty-minute shows the highest accuracy with an error within 10 TECU for all the storm days. Numéro de notice : A2021-745 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0015 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1515/jag-2021-0015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98717 [article]

The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones / Zun Niu in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 699 Titre : The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones Type de document : Article/Communication Auteurs : Zun Niu, Auteur ; Fugui Guo, Auteur ; Qiangqiang Shuai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 699 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] C++ [Termes IGN] centrale inertielle [Termes IGN] filtre de Kalman [Termes IGN] format RINEX [Termes IGN] odomètre [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par BeiDou [Termes IGN] positionnement par GNSS [Termes IGN] précision du positionnement [Termes IGN] programmation informatique [Termes IGN] robot [Termes IGN] téléphone intelligent [Termes IGN] vision par ordinateur Résumé : (auteur) The real-time kinematic positioning technique (RTK) and visual–inertial odometry (VIO) are both promising positioning technologies. However, RTK degrades in GNSS-hostile areas, where global navigation satellite system (GNSS) signals are reflected and blocked, while VIO is affected by long-term drift. The integration of RTK and VIO can improve the accuracy and robustness of positioning. In recent years, smartphones equipped with multiple sensors have become commodities and can provide measurements for integrating RTK and VIO. This paper verifies the feasibility of integrating RTK and VIO using smartphones, and we propose an improved algorithm to integrate RTK and VIO with better performance. We began by developing an Android smartphone application for data collection and then wrote a Python program to convert the data to a robot operating system (ROS) bag. Next, we established two ROS nodes to calculate the RTK results and accomplish the integration. Finally, we conducted experiments in urban areas to assess the integration of RTK and VIO based on smartphones. The results demonstrate that the integration improves the accuracy and robustness of positioning and that our improved algorithm reduces altitude deviation. Our work can aid navigation and positioning research, which is the reason why we open source the majority of the codes at our GitHub. Numéro de notice : A2021-800 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100699 Date de publication en ligne : 14/10/2021 En ligne : https://doi.org/10.3390/ijgi10100699 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98852 [article]

Impact of different sampling rates on precise point positioning performance using online processing service / Serdar Erol in Geo-spatial Information Science, vol 24 n° 2 (June 2021)  

Public [article]  inGeo-spatial Information Science > vol 24 n° 2 (June 2021) . - pp 302 - 312 Titre : Impact of different sampling rates on precise point positioning performance using online processing service Type de document : Article/Communication Auteurs : Serdar Erol, Auteur ; Reha Metin Alkan, Auteur ; I. Murat Ozulu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 302 - 312 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] données GNSS [Termes IGN] format RINEX [Termes IGN] instrumentation Trimble [Termes IGN] intervalle de confiance [Termes IGN] phase GNSS [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement ponctuel précis [Termes IGN] précision du positionnement [Termes IGN] rapport signal sur bruit [Termes IGN] réalité de terrain [Termes IGN] retard troposphérique zénithal [Termes IGN] taux d'échantillonnage [Termes IGN] trajet multiple [Termes IGN] Turquie Résumé : (auteur) In this study, the effect of different sampling rates (i.e. observation recording interval) on the Precise Point Positioning (PPP) solutions in terms of accuracy was investigated. For this purpose, a field test was carried out in Çorum province, Turkey, on 11 September 2019. Within this context, a Geodetic Point (GP) was established and precisely coordinated. A static GNSS measurement was occupied on the GP for about 4-hour time at 0.10 second (s)/10 Hz measurement intervals with the Trimble R10 geodetic grade GNSS receiver. The original observation file was converted to RINEX format and then decimated into the different data sampling rates as 0.2 s, 0.5 s, 1 s, 5 s, 10 s, 30 s, 60 s, and 120 s. All these RINEX observation files were submitted to the Canadian Spatial Reference System-Precise Point Positioning (CSRS-PPP) online processing service the day after the data collection date by choosing both static and kinematic processing options. In this way, PPP-derived static coordinates, and the kinematic coordinates of each measurement epoch were calculated. The PPP-derived coordinates obtained from each decimated sampling intervals were compared to known coordinates of the GP for northing, easting, 2D position, and height components. According to the static and kinematic processing results, high data sampling rates did not change the PPP solutions in terms of accuracy when compared to the results obtained using lower sampling rates. The results of this study imply that it was not necessary to collect GNSS data with high-rate intervals for many surveying projects requiring cm-level accuracy. Numéro de notice : A2021-558 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1842811 Date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1842811 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98111 [article]

Python software tools for GNSS interferometric reflectometry (GNSS-IR) / Angel Martín in GPS solutions, Vol 24 n° 4 (October 2020)  

Public [article]  inGPS solutions > Vol 24 n° 4 (October 2020) . - 7 p. Titre : Python software tools for GNSS interferometric reflectometry (GNSS-IR) Type de document : Article/Communication Auteurs : Angel Martín, Auteur ; Raquel Luján, Auteur ; Ana Belén Anquela, Auteur Année de publication : 2020 Article en page(s) : 7 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] antenne GNSS [Termes IGN] format RINEX [Termes IGN] humidité du sol [Termes IGN] Python (langage de programmation) [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS Résumé : (auteur) Global Navigation Satellite System (GNSS) interferometric reflectometry, also known as the GNSS-IR, uses data from geodetic-quality GNSS antennas to extract information about the environment surrounding the antenna. Soil moisture monitoring is one of the most important applications of the GNSS-IR technique. This manuscript presents the main ideas and implementation decisions needed to write the Python code for software tools that transform RINEX format observation and navigation files into an appropriate format for GNSS-IR (which includes the SNR observations and the azimuth and elevation of the satellites) and to determine the reflection height and the adjusted phase and amplitude values of the interferometric wave for each individual satellite track. The main goal of the manuscript is to share the software with the scientific community to introduce new users to the GNSS-IR technique. Numéro de notice : A2020-523 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01010-0 Date de publication en ligne : 20/07/2020 En ligne : https://doi.org/10.1007/s10291-020-01010-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95696 [article]

X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data / Danfeng Hong in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

Permalink

Performance of Galileo precise time and frequency transfer models using quad-frequency carrier phase observations / Pengfei Zhang in GPS solutions, vol 24 n° 2 (April 2020)  

Permalink

What, where, and how to transfer in SAR target recognition based on deep CNNs / Zhongling Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

Permalink

Mise en place d'un nouveau protocole relatif à la mise à jour de données géographiques produites par les Directions du Département des Hauts-de-Seine dans le SIG départemental / Gabriel Dousseau (2020) 

Permalink

Subsidence is determined in the heart of the Central Valley using Post Processed Static and Precise Point Positioning techniques / Y. Facio in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

Permalink

Buildings in GI: How to deal with building models in the GIS domain / Laura Knoth in Transactions in GIS, vol 23 n° 3 (June 2019)  

Permalink

WFS 3.0 dans les starting blocks / Anonyme in Géomatique expert, n° 128 (juin - juillet 2019)

Permalink

Géomatique webmapping en open source / David Collado (2019)

Permalink

Le travail invisible des données / Jérôme Denis (2018)  

Permalink

Des données à l'information / Florent Chavand (2017)

Permalink