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MTLM: a multi-task learning model for travel time estimation / Saijun Xu in Geoinformatica [en ligne], vol 26 n° 2 (April 2022)  

Public [article]  inGeoinformatica [en ligne] > vol 26 n° 2 (April 2022) . - pp 379 - 395 Titre : MTLM: a multi-task learning model for travel time estimation Type de document : Article/Communication Auteurs : Saijun Xu, Auteur ; Ruoqian Zhang, Auteur ; Wanjun Cheng, Auteur ; Jiajie Xu, Auteur Année de publication : 2022 Article en page(s) : pp 379 - 395 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse coût-avantage [Termes IGN] apprentissage automatique [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] durée de trajet [Termes IGN] modèle de simulation [Termes IGN] transport collectif [Termes IGN] transport intermodal Résumé : (auteur) Travel time estimation (TTE) is an important research topic in many geographic applications for smart city research. However, existing approaches either ignore the impact of transportation modes, or assume the mode information is known for each training trajectory and the query input. In this paper, we propose a multi-task learning model for travel time estimation called MTLM, which recommends the appropriate transportation mode for users, and then estimates the related travel time of the path. It integrates transportation-mode recommendation task and travel time estimation task to capture the mutual influence between them for more accurate TTE results. Furthermore, it captures spatio-temporal dependencies and transportation mode effect by learning effective representations for TTE. It combines the transportation-mode recommendation loss and TTE loss for training. Extensive experiments on real datasets demonstrate the effectiveness of our proposed methods. Numéro de notice : A2022-325 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : https://doi.org/10.1007/s10707-020-00422-x Date de publication en ligne : 15/08/2020 En ligne : https://doi.org/10.1007/s10707-020-00422-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100488 [article]

Emerging technologies for smart cities’ transportation: Geo-information, data analytics and machine learning approaches / Li-Minn Ang in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 2 (February 2022) . - n° 85 Titre : Emerging technologies for smart cities’ transportation: Geo-information, data analytics and machine learning approaches Type de document : Article/Communication Auteurs : Li-Minn Ang, Auteur ; Jasmine Kah Phooi Seng, Auteur ; Ericmoore Ngharamike, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] données massives [Termes IGN] planification urbaine [Termes IGN] système de transport intelligent [Termes IGN] trafic routier [Termes IGN] transport collectif [Termes IGN] transport urbain [Termes IGN] ville intelligente [Termes IGN] zone urbaine Résumé : (auteur) With the recent increase in urban drift, which has led to an unprecedented surge in urban population, the smart city (SC) transportation industry faces a myriad of challenges, including the development of efficient strategies to utilize available infrastructures and minimize traffic. There is, therefore, the need to devise efficient transportation strategies to tackle the issues affecting the SC transportation industry. This paper reviews the state-of-the-art for SC transportation techniques and approaches. The paper gives a comprehensive review and discussion with a focus on emerging technologies from several information and data-driven perspectives including (1) geoinformation approaches; (2) data analytics approaches; (3) machine learning approaches; (4) integrated deep learning approaches; (5) artificial intelligence (AI) approaches. The paper contains core discussions on the impacts of geo-information on SC transportation, data-driven transportation and big data technology, machine learning approaches for SC transportation, innovative artificial intelligence (AI) approaches for SC transportation, and recent trends revealed by using integrated deep learning towards SC transportation. This survey paper aimed to give useful insights to researchers regarding the roles that data-driven approaches can be utilized for in smart cities (SCs) and transportation. An objective of this paper was to acquaint researchers with the recent trends and emerging technologies for SC transportation applications, and to give useful insights to researchers on how these technologies can be exploited for SC transportation strategies. To the best of our knowledge, this is the first comprehensive review that examines the impacts of the various five driving technological forces—geoinformation, data-driven and big data technology, machine learning, integrated deep learning, and AI—in the context of SC transportation applications. Numéro de notice : A2022-118 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11020085 Date de publication en ligne : 24/01/2022 En ligne : https://doi.org/10.3390/ijgi11020085 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99649 [article]

Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata: a case study on city of Toronto / Xiaocong Xu in Geo-spatial Information Science, vol 25 n° inconnu ([01/01/2022])  

Public [article]  inGeo-spatial Information Science > vol 25 n° inconnu [01/01/2022] Titre : Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata: a case study on city of Toronto Type de document : Article/Communication Auteurs : Xiaocong Xu, Auteur ; Dachuan Zhang, Auteur ; Xiaoping Liu, Auteur ; Jinpei Ou, Auteur ; Xinxin Wu, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] durée de trajet [Termes IGN] modèle de simulation [Termes IGN] outil d'aide à la décision [Termes IGN] Toronto [Termes IGN] transport collectif Résumé : (auteur) The accessibility provided by the transportation system plays an essential role in driving urban growth and urban functional land use changes. Conventional studies on land use simulation usually simplified the accessibility as proximities and adopted the grid-based simulation strategy, leading to the insufficiencies of characterizing spatial geometry of land parcels and simulating subtle land use changes among urban functional types. To overcome these limitations, an Accessibility-interacted Vector-based Cellular Automata (A-VCA) model was proposed for the better simulation of realistic land use change among different urban functional types. The accessibility at both local and zonal scales derived from actual travel time data was considered as a key driver of fine-scale urban land use changes and was integrated into the vector-based CA simulation process. The proposed A-VCA model was tested through the simulation of urban land use changes in the City of Toronto, Canada, during 2012–2016. A vector-based CA without considering the driving factor of accessibility (VCA) and a popular grid-based CA model (Future Land Use Simulation, FLUS) were also implemented for comparisons. The simulation results reveal that the proposed A-VCA model is capable of simulating fine-scale urban land use changes with satisfactory accuracy and good morphological feature (kappa = 0.907, figure of merit = 0.283, and cumulative producer’s accuracy = 72.83% ± 1.535%). The comparison also shows significant outperformance of the A-VCA model against the VCA and FLUS models, suggesting the effectiveness of the accessibility-interactive mechanism and vector-based simulation strategy. The proposed model provides new tools for a better simulation of fine-scale land use changes and can be used in assisting the formulation of urban and transportation planning. Numéro de notice : A2022-451 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/10095020.2022.2043730 Date de publication en ligne : 16/03/2022 En ligne : https://doi.org/10.1080/10095020.2022.2043730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100397 [article]

Urban Wi-Fi fingerprinting along a public transport route / Guenther Retscher in Journal of applied geodesy, vol 14 n° 4 (October 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 4 (October 2020) . - pp 379 – 392 Titre : Urban Wi-Fi fingerprinting along a public transport route Type de document : Article/Communication Auteurs : Guenther Retscher, Auteur ; Aizhan Bekenova, Auteur Année de publication : 2020 Article en page(s) : pp 379 – 392 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] accès sans fils à l'internet [Termes IGN] cartographie et localisation simultanées [Termes IGN] centrale inertielle [Termes IGN] empreinte [Termes IGN] itinéraire [Termes IGN] migration pendulaire [Termes IGN] positionnement par WiFi [Termes IGN] programmation par contraintes [Termes IGN] qualité du signal [Termes IGN] service fondé sur la position [Termes IGN] téléphone intelligent [Termes IGN] transport collectif [Termes IGN] zone urbaine Résumé : (auteur) The outreach of Wi-Fi localization is extended in this study for urban wide applications as they provide the high potential to employ them for numerous applications for localization and guidance in urban environments. The selected application presented in this paper is the localization and routing of public transport smartphone users. For the conducted investigations, Received Signal Strength Indicator (RSSI) values are collected for users who are travelling from home in a residential neighbourhood to work in the city centre and return along the same route. Special tramway trains are selected which provide two on-board Wi-Fi Access Points (APs). Firstly, the availability, visibility and RSSI stability of the Wi-Fi signal behavior of these APs and the APs in the surrounding environment along the routes is analyzed. Then the trajectories are estimated based on location fingerprinting. A first analyses reveals that significant differences exists between the six employed smartphones as well as times of the day, e. g. in the morning at peak hours or at off-peak hours. From the long-time observations it is seen that the two on-board APs show a high stability of the RSSI signals at the same times of the day and along the whole route. It is therefore currently investigated how they can confirm and validate user localization along the route and if they can contribute to constrain the overall positioning solution in combination with the inertial smartphone sensors. Moreover, the railway track can serve as a further constraint. As an outlook on future work, the development of a Simultaneous Localization and Mapping (SLAM) solution with a fusion with the smartphone inertial sensors is proposed. Numéro de notice : A2020-676 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0015 Date de publication en ligne : 16/07/2020 En ligne : https://doi.org/10.1515/jag-2020-0015 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96168 [article]

Measuring accessibility of bus system based on multi-source traffic data / Yufan Zuo in Geo-spatial Information Science, vol 23 n° 3 (September 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 3 (September 2020) . - pp 248 - 257 Titre : Measuring accessibility of bus system based on multi-source traffic data Type de document : Article/Communication Auteurs : Yufan Zuo, Auteur ; Zhiyuan Liu, Auteur ; Xiao Fu, Auteur Année de publication : 2020 Article en page(s) : pp 248 - 257 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] approche holistique [Termes IGN] données multisources [Termes IGN] données spatiotemporelles [Termes IGN] modélisation spatio-temporelle [Termes IGN] planification urbaine [Termes IGN] point d'intérêt [Termes IGN] Shenzhen [Termes IGN] trafic routier [Termes IGN] transport collectif Résumé : (auteur) Accessibility is a representative indicator for evaluating the supply of bus system. Traditional studies have evaluated the accessibility from different aspects. Considering the interaction among land use, bus timetable arrangement and individual factors, a more holistic accessibility measurement is proposed to combine static and dynamic characteristics from multisource traffic data. The rationale of the proposed model is verified by a case study of bus system in Shenzhen, China, which is carried out to find the spatial and temporal discrepancy of service of bus system. It is found that the adjustment of bus schedule to time-varying travel demand can affect accessibility of bus system and that Land-use development, average bus speed and bus facilities all have positive effects on accessibility of bus system. These findings provide significant reference for transport planning and policy-making. The proposed model is not limited to accessibility measuring of bus system, but also applicable to other travel modes. Numéro de notice : A2020-564 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1783189 Date de publication en ligne : 24/07/2020 En ligne : https://doi.org/10.1080/10095020.2020.1783189 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95881 [article]

Generation of crowd arrival and destination locations/times in complex transit facilities / Brian Ricks in The Visual Computer, vol 36 n° 8 (August 2020)  

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Projet infos usagers et projet transport à la demande / Oriane Sobreira (2020) 

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Desserte des villes du territoire métropolitain Buenos Aires – Rosario par le réseau ferroviaire de voyageurs entre 1951 et 2008 / Thomas Massin in Mappemonde [en ligne], n° 126 ([01/05/2019])  

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Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns / Zhixiang Fang in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)  

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A viewpoint based approach to the visual exploration of trajectory / Jie Li in Journal of Visual Languages and Computing, vol 41 (August 2017)  

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SIG et transports / Françoise de Blomac in Géomatique expert, n° 115 (mars - avril 2017)

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Mobilités à la loupe / Françoise de Blomac in DécryptaGéo le mag, n° 179 (septembre 2016)

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The use of anamorphic images in the development of transit maps / Tomasz Stepien in Geodesy and cartography, vol 65 n° 1 (June 2016)  

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Exploitation de relevés scanner 3D dans un SIG / Joris Vidalenche in Géomatique expert, n° 99 (01/07/2014) 

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Optimisation de transport à la demande dans des territoires polarisés / Rémy Chevrier in Cartes & Géomatique, n° 215 (mars 2013)  

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