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Modeling human–human interaction with attention-based high-order GCN for trajectory prediction / Yanyan Fang in The Visual Computer, vol 38 n° 7 (July 2022)
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Titre : Modeling human–human interaction with attention-based high-order GCN for trajectory prediction Type de document : Article/Communication Auteurs : Yanyan Fang, Auteur ; Zhiyu Jin, Auteur ; Zhenhua Cui, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2257 - 2269 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] détection de cible
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] interaction spatiale
[Termes IGN] modèle de simulation
[Termes IGN] objet mobile
[Termes IGN] piéton
[Termes IGN] réseau neuronal de graphes
[Termes IGN] trajet (mobilité)Résumé : (auteur) This paper presents a novel high-order graph convolutional network (GCN) for pedestrian trajectory prediction. Specifically, the walking state of a target pedestrian depends on both its historical trajectory, which encodes its speed, walking direction and acceleration information, as well as the movement of its neighbors. Thus we propose to leverage GCNs to aggregate the trajectory features of the target pedestrian and its neighbors to predict the movement of the target pedestrian. Considering that the movement of the neighbors’ neighbors affects the movement of the target pedestrian’s neighbors, thus indirectly affecting the movement of the target pedestrian, we propose to use a high-order GCN for human–human interaction modelling. Such a high-order GCN considers the target pedestrian’s neighbors as well as its neighbors’ neighbors. Further, a pedestrian avoids collision with others by estimating its locations and its neighbors’ upcoming locations, and it slows down or changes direction if it believes a collision may occur, especially in very crowded scenes. In light of this, we propose to model such anticipation-based decision making behavior as attention and combine it with our high-order GCN. Thus we first roughly estimate the future trajectories of all pedestrians with a simple method. By using the coarse predicted future trajectory and GCN outputs, we calculate the attention in our attention-based high-order GCN and predict future trajectory. Extensive experiments validate the effectiveness of our approach. In addition, our model shows a higher data efficiency. On the ETH&UCY dataset, using only 5% of the training data for each training epoch, our model outperforms the state of the art. Numéro de notice : A2022-507 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02109-2 Date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.1007/s00371-021-02109-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101040
in The Visual Computer > vol 38 n° 7 (July 2022) . - pp 2257 - 2269[article]Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata / Aditya Tafta Nugraha in Computers, Environment and Urban Systems, vol 92 (March 2022)
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Titre : Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata Type de document : Article/Communication Auteurs : Aditya Tafta Nugraha, Auteur ; Ben J. Waterson, Auteur ; Simon P. Blainey, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] dynamique spatiale
[Termes IGN] Grande-Bretagne
[Termes IGN] interaction spatiale
[Termes IGN] modèle orienté agent
[Termes IGN] morphologie urbaine
[Termes IGN] planification urbaine
[Termes IGN] port
[Termes IGN] transport urbain
[Termes IGN] utilisation du solRésumé : (auteur) The urban morphology is characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Port-urban relationship added to the complexity of port cities' urban form. Most urban cellular automata (CA) models simulate land-use evolution through transition rules representing multi-factored local interactions. However, calibration of CA-based urban land use and transport interaction (LUTI) models often utilise manual methods due to complexity of the process. This limits insights on urban interactions to a few explored settlements and prevents applications for planning and assessment of transport policies in other contexts. This paper, therefore, addresses three main points. The paper (i) demonstrates an improved method for the calibration of CA-based LUTI models, (ii) contributes to a better understanding of the urban dynamics in port city systems by quantifying generalizable interactions from a wide range of port-urban settlements, and (iii) illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions. These were done by formulating a model in a similar structure as a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between land-use, geographic, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Cluster analysis of the calibrated interactions in the study areas was conducted to examine the variations of these interactions. This produced two main groups. In the first group, consisting larger settlements, connections between ports and other urban activities were weaker than in the second group which consisted of smaller port-settlements. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions. Numéro de notice : A2022-084 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101733 Date de publication en ligne : 25/11/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99489
in Computers, Environment and Urban Systems > vol 92 (March 2022)[article]Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model / Mingwei Liu in Computers, Environment and Urban Systems, vol 91 (January 2022)
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Titre : Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model Type de document : Article/Communication Auteurs : Mingwei Liu, Auteur ; Tinggui Chen, Auteur ; Chiaki Matunaga, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101725 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] agent (intelligence artificielle)
[Termes IGN] bicyclette
[Termes IGN] comportement
[Termes IGN] cycliste
[Termes IGN] direction
[Termes IGN] interaction spatiale
[Termes IGN] modèle de dispersion
[Termes IGN] modèle orienté agent
[Termes IGN] navigation pédestre
[Termes IGN] piéton
[Termes IGN] sécurité
[Termes IGN] vitesse
[Termes IGN] zone urbaineRésumé : (auteur) As the number of bicyclists in urban areas continues to increase, the need to realistically model the movement and interactions of bicyclists in mixed urban traffic is rapidly gaining importance. Therefore, this paper presents an agent space model (ASM) to elucidate the movements of bicyclists and pedestrians on shared roads. The ASM model, via simulation, particularly illustrates the dispersion phenomenon observed for non-motorized road users. The mutual interactions and diverse bicyclist and pedestrian properties were also incorporated into this model. The mutual interactions were realised through agent spaces of different sizes in conflict and overtaking behaviours for the following combinations: bicyclist-to-pedestrian, bicyclist-to-bicyclist, pedestrian-to-bicyclist, and pedestrian-to-pedestrian, which were obtained through experiments. The hypothesis test indicated that different agent spaces exist for different types of interactions. The experimental data were used to obtain several variables that describe the elements of road user agent spaces, including longitudinal and lateral distances and the dynamic relationship between the longitudinal distance and speed. The simulation results indicated that with an increase in the number of pedestrians, the maximum capacity decreased and the dispersion degree increased. The following psychological and physiological factors affect the degree of dispersion of bicyclists: travelling speed, reaction time, intensity, probability of selecting the head-on direction, and probability of selecting the right-hand direction. In addition, lane formation was observed in all simulations. The results also demonstrated that dedicated bicycle lanes will significantly reduce the dispersion degree. Moreover, the safety and efficiency effects of different forms of bicycle lanes were analysed from the perspective of the degree of dispersion. The simulation results can provide specific guidelines for understanding the causes of phenomena such as dispersion and lane formation, as well as for studying the traffic dynamics, effects of dedicated bicycle lanes, and macroscopic characteristics according to different bicyclist-pedestrian ratios. Numéro de notice : A2021-826 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101725 Date de publication en ligne : 20/10/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98947
in Computers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101725[article]Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches / Siqin Wang in Computers, Environment and Urban Systems, vol 90 (November 2021)
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Titre : Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches Type de document : Article/Communication Auteurs : Siqin Wang, Auteur ; Mingshu Wang, Auteur ; Yan Liu, Auteur Année de publication : 2021 Article en page(s) : n° 101713 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] accessibilité
[Termes IGN] analyse en composantes principales
[Termes IGN] Australie
[Termes IGN] corrélation
[Termes IGN] distance
[Termes IGN] interaction spatiale
[Termes IGN] parc urbain
[Termes IGN] Pays-Bas
[Termes IGN] planification urbaine
[Termes IGN] transport urbainRésumé : (auteur) Urban parks are essential components of urban ecosystems, providing recreation and relaxation places to residents. Measuring the spatial accessibility to urban parks serves as an initial step in urban planning and developing urban development strategies to improve social and environmental justice. This study aims to evaluate measures of spatial accessibility to urban parks by comparing three geographic information systems (GIS)-based approaches, accounting for network complexity, transport modes, distance thresholds, and destination choices. Taking Ipswich City (Australia) and Enschede (the Netherlands) as two testbeds, we examine the spatial patterns of a total of 21 accessibility measures in the two cities and conduct a correlation and principal component analysis to unravel the interrelationship between these measures. The results suggest that among all measures under the three approaches, the selection of distance thresholds and transport modes matter more to accessibility measures than the destination choices. Furthermore, when distance threshold and transport mode are held constant, the network-based and entrance-based methods provide more realistic accessibility measures than other methods. We also discuss the generality of the entrance-based method we propose and suggest ways to choose the most appropriate accessibility measure for use in different contexts. Numéro de notice : A2021-698 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101713 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101713 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98558
in Computers, Environment and Urban Systems > vol 90 (November 2021) . - n° 101713[article]Predicting user activity intensity using geographic interactions based on social media check-in data / Jing Li in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)
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Titre : Predicting user activity intensity using geographic interactions based on social media check-in data Type de document : Article/Communication Auteurs : Jing Li, Auteur ; Wenyue Guo, Auteur ; Haiyan Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 555 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] interaction spatiale
[Termes IGN] mobilité humaine
[Termes IGN] modèle non linéaire
[Termes IGN] relation spatiale
[Termes IGN] réseau neuronal de graphes
[Termes IGN] réseau neuronal récurrent
[Termes IGN] utilisateurRésumé : (auteur) Predicting user activity intensity is crucial for various applications. However, existing studies have two main problems. First, as user activity intensity is nonstationary and nonlinear, traditional methods can hardly fit the nonlinear spatio-temporal relationships that characterize user mobility. Second, user movements between different areas are valuable, but have not been utilized for the construction of spatial relationships. Therefore, we propose a deep learning model, the geographical interactions-weighted graph convolutional network-gated recurrent unit (GGCN-GRU), which is good at fitting nonlinear spatio-temporal relationships and incorporates users’ geographic interactions to construct spatial relationships in the form of graphs as the input. The model consists of a graph convolutional network (GCN) and a gated recurrent unit (GRU). The GCN, which is efficient at processing graphs, extracts spatial features. These features are then input into the GRU, which extracts their temporal features. Finally, the GRU output is passed through a fully connected layer to obtain the predictions. We validated this model using a social media check-in dataset and found that the geographical interactions graph construction method performs better than the baselines. This indicates that our model is appropriate for fitting the complex nonlinear spatio-temporal relationships that characterize user mobility and helps improve prediction accuracy when considering geographic flows. Numéro de notice : A2021-588 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10080555 Date de publication en ligne : 17/08/2021 En ligne : https://doi.org/10.3390/ijgi10080555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98206
in ISPRS International journal of geo-information > vol 10 n° 8 (August 2021) . - n° 555[article]Streams and rural abandonment are related to the summer activity of the invasive pest Drosophila suzukii in protected European forests / Alberto Maceda-Veiga in Forest ecology and management, vol 485 ([01/04/2021])
PermalinkHow validation through model exploration empowers theories of spatial complexity : example of urban systems / Juste Raimbault (2021)
PermalinkNEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread / Taylor Anderson in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)
PermalinkHow do species and data characteristics affect species distribution models and when to use environmental filtering? / Lukáš Gábor in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)
PermalinkAn empirical study on the intra-urban goods movement patterns using logistics big data / Pengxiang Zhao in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)
PermalinkMapping areas of asynchronous‐temporal interaction in animal‐telemetry data / Brendan A. Hoover in Transactions in GIS, Vol 24 n° 3 (June 2020)
PermalinkMining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)
PermalinkA time‐geographic approach to quantifying wildlife–road interactions / Rebecca W. Loraamm in Transactions in GIS, vol 23 n° 1 (February 2019)
PermalinkPermalinkMethod for the analysis and visualization of similar flow hotspot patterns between different regional groups / Haiping Zhang in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)
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