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Towards generating network of bikeways from Mapillary data / Xuan Ding in Computers, Environment and Urban Systems, vol 88 (July 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 88 (July 2021) . - n° 101632 Titre : Towards generating network of bikeways from Mapillary data Type de document : Article/Communication Auteurs : Xuan Ding, Auteur ; Hongchao Fan, Auteur ; Jianya Gong, Auteur Année de publication : 2021 Article en page(s) : n° 101632 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] approche participative [Termes IGN] cycliste [Termes IGN] données localisées des bénévoles [Termes IGN] gestion des itinéraires [Termes IGN] Mapillary [Termes IGN] OpenStreetMap [Termes IGN] Suède [Termes IGN] système d'information géographique Résumé : (auteur) Nowadays, biking is flourishing in many Western cities. While many roads are used for both cars and bicycles, buffered bike lanes are marked for the safety of cyclists. In many cities, segregated paths are built up to have physical separation from motor vehicles. These types of biking ways are regarded as attributes in geographic information system (GIS) data. This information is required and important in the service of route planning, as cyclists may prefer certain types of bikeways. This paper presents a framework for generating networks of bikeways with attribute information from the data collected on the collaborative street view data platform Mapillary. The framework consists of two layers: The first layer focuses on constructing a bikeway road network using Global Positioning System (GPS) information of Mapillary images. Mapillary sequences are classified into walking, cycling, driving (ordinary road), and driving (motorway) trajectories based on the transportation mode with a trained XGBoost classifier. The bikeway road network is then extracted from cycling and driving (ordinary road) trajectories using a raster-based method. The second layer focuses on extracting attribute information from Mapillary images. Cycling-specific information (i.e., bicycle signs/markings) is extracted using a two-stage detection and classification model. A series of quantitative evaluations based on a case study demonstrated the ability and potential of the framework for extracting bikeway road information to enrich the existing OSM cycling road data. Numéro de notice : A2021-432 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101632 Date de publication en ligne : 17/04/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97798 [article]

An improved ant colony optimization-based algorithm for user-centric multi-objective path planning for ubiquitous environments / Zohreh Masoumi in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 137 - 154 Titre : An improved ant colony optimization-based algorithm for user-centric multi-objective path planning for ubiquitous environments Type de document : Article/Communication Auteurs : Zohreh Masoumi, Auteur ; John L. Van Genderen, Auteur ; Sadeghi Niaraki Abolghasem, Auteur Année de publication : 2021 Article en page(s) : pp 137 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] gestion des itinéraires [Termes IGN] informatique ubiquitaire [Termes IGN] méthode heuristique [Termes IGN] optimisation par colonie de fourmis [Termes IGN] planification [Termes IGN] recherche du chemin optimal [Termes IGN] réseau routier Résumé : (auteur) One of the important issues in ubiquitous geographic information science (GIS) is designing user-centric path finding algorithms to meet user needs. Mostly, in a route planning problem, the user’s purpose is optimization of two or more objective functions simultaneously. Thus, the problem is a multi-objective problem. In the present study, having considered multi-objective optimization methods in path finding, we developed an algorithm for solving this problem using an improved multi-objective ant colony optimization (ACO) algorithm. Modifications are introduced for various components of the ant colony metaheuristics; specifically, for those associated with the ‘ant decision rule’. The proposed algorithm was tested on the studied network. The results demonstrate that the proposed approach has acceptable settings, repeatability and run time. In addition, one of the important research outputs is a pareto-front which allows the user to select the final path according to the desired priorities. Numéro de notice : A2021-081 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595176 Date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595176 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96823 [article]

Machine‐learning prediction models for pedestrian traffic flow levels: Towards optimizing walking routes for blind pedestrians / Achituv Cohen in Transactions in GIS, Vol 24 n° 5 (October 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 5 (October 2020) . - pp 1264-1279 Titre : Machine‐learning prediction models for pedestrian traffic flow levels: Towards optimizing walking routes for blind pedestrians Type de document : Article/Communication Auteurs : Achituv Cohen, Auteur ; Sagi Dalyot, Auteur Année de publication : 2020 Article en page(s) : pp 1264-1279 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] classification par forêts aléatoires [Termes IGN] données localisées des bénévoles [Termes IGN] données spatiotemporelles [Termes IGN] gestion des itinéraires [Termes IGN] handicap [Termes IGN] individu non-voyant [Termes IGN] itinéraire piétionnier [Termes IGN] modèle de simulation [Termes IGN] navigation pédestre [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] trafic routier Résumé : (Auteur) Navigation and orientation while walking in urban spaces pose serious challenges for blind pedestrians, sometimes even on a daily basis. Research shows the practicability of computerized weighted network route planning algorithms based on OpenStreetMap mapping data for calculating customized routes for blind pedestrians. While data about pedestrians and vehicle traffic flow at different times throughout the day influence the route choices of blind pedestrians, such data do not exist in OpenStreetMap. Quantifying the correlation between spatial structure and traffic flow could be used to fill this gap. As such, we investigated machine‐learning methods to develop a computerized model for predicting pedestrian traffic flow levels, with the objective of enriching the OpenStreetMap database. This article presents prediction results by implementing six machine‐learning algorithms based on parameters relating to the geometrical and topological configuration of streets in OpenStreetMap, as well as points‐of‐interest such as public transportation and shops. The Random Forest algorithm produced the best results, whereby 95% of the testing data were successfully predicted. These results indicate that machine‐learning algorithms can accurately generate necessary temporal data, which when combined with the available crowdsourced open mapping data could augment the reliability of route planning algorithms for blind pedestrians. Numéro de notice : A2020-700 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12674 Date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1111/tgis.12674 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96210 [article]

Prediction of RTK positioning integrity for journey planning / A. El-Mowafy in Journal of applied geodesy, vol 14 n° 4 (October 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 4 (October 2020) . - pp 431 – 443 Titre : Prediction of RTK positioning integrity for journey planning Type de document : Article/Communication Auteurs : A. El-Mowafy, Auteur ; Nobuaki Kubo, Auteur Année de publication : 2020 Article en page(s) : pp 431 – 443 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] gestion des itinéraires [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle de simulation [Termes IGN] planification [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par GNSS [Termes IGN] Receiver Autonomous Integrity Monitoring [Termes IGN] système de transport intelligent [Termes IGN] Tokyo (Japon) [Termes IGN] trajet Résumé : (auteur) Positioning integrity is crucial for Intelligent Transport Systems (ITS) applications. In this article, a method is presented for prediction of GNSS positioning integrity for ITS journey planning. This information, in addition to other route information, such as distance and time, can be utilized to choose the safest and economical route. We propose to combine the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) technique, tailored for ITS, with 3D city models. Positioning is performed by GNSS Real-Time Kinematic (RTK) method, which can provide the accuracy required for ITS. A new threat model employed for computation of the protection levels (PLs) for RTK positioning is discussed. Demonstration of the proposed approach is performed through a kinematic test in an urban area in Tokyo. The comparison between the prediction method and the actual observations show that the two estimate close satellite geometry and PLs. The method produced PLs that bounds the actual position errors all the time and they were less than the preset alert limit. Numéro de notice : A2020-678 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0038 Date de publication en ligne : 20/10/2020 En ligne : https://doi.org/10.1515/jag-2020-0038 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96174 [article]

Multi-factor of path planning based on an ant colony optimization algorithm / Mingchang Wang in Annals of GIS, vol 26 n° 2 (April 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 2 (April 2020) Titre : Multi-factor of path planning based on an ant colony optimization algorithm Type de document : Article/Communication Auteurs : Mingchang Wang, Auteur ; Chunyu Zhu, Auteur ; Fengyan Wang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] classification floue [Termes IGN] gestion des itinéraires [Termes IGN] optimisation par colonie de fourmis [Termes IGN] planification [Termes IGN] processus d'analyse hiérarchisée floue [Termes IGN] robot Résumé : (auteur) We propose an improved ant colony algorithm for avoiding obstacles in complex static environments that addresses the problems of a single evaluation factor and low path quality of the traditional ant colony algorithm in path planning. The improvements are: 1) a fuzzy planner is constructed according to the comprehensive evaluation method of fuzzy mathematics and the analytic hierarchy process to comprehensively evaluate and determine the impact of environmental factors, 2) the probability selection formula of the ant colony algorithm is optimized, 3) the pheromone update formula is optimized, and 4) the corner system mechanism is introduced as a post-processing method of path optimization to further smooth the path. Results from simulation experiments of the traditional ant colony algorithm were analysed and compared with those of the improved ant colony algorithm, showing that the latter has a stronger path planning ability and higher algorithm efficiency, resulting in a smoother path with a lower negative impact by environmental factors. Thus, the proposed algorithm is expected to provide a computational basis for effective multi-factor path planning in realistic environments, thereby saving human and material resources. Numéro de notice : A2020-320 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2020.1755725 Date de publication en ligne : 13/05/2020 En ligne : https://doi.org/10.1080/19475683.2020.1755725 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95186 [article]

Extracting urban landmarks from geographical datasets using a random forests classifier / Yue Lin in International journal of geographical information science IJGIS, vol 33 n° 12 (December 2019)  

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Gérer au mieux ses équipes d'intervention / Anonyme in Géomatique expert, n° 108 (janvier - février 2016)

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Planning unobstructed paths in traffic-aware spatial networks / Shuo Shang in Geoinformatica [en ligne], vol 19 n° 4 (October - December 2015)  

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Information géographique et dynamiques urbaines, Tome 1. Analyse et simulation de la mobilité des personnes / M. Theriault (2008)

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Mise en œuvre de l'information de la saisie et l'édition des circuits de collecte à l'aide de l'outil Sita (synoptis) / M. Cerciat (2001)

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