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GIS-based survey over the public transport strategy: An instrument for economic and sustainable urban traffic planning / Gabriela Droj in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 16 Titre : GIS-based survey over the public transport strategy: An instrument for economic and sustainable urban traffic planning Type de document : Article/Communication Auteurs : Gabriela Droj, Auteur ; Laurentiu Droj, Auteur ; Ana-Cornelia Badea, Auteur Année de publication : 2022 Article en page(s) : n° 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse spatiale [Termes IGN] circulation urbaine [Termes IGN] modèle mathématique [Termes IGN] planification urbaine [Termes IGN] pollution atmosphérique [Termes IGN] Roumanie [Termes IGN] trafic routier [Termes IGN] transport public Résumé : (auteur) Traffic has a direct impact on local and regional economies, on pollution levels and is also a major source of discomfort and frustration for the public who have to deal with congestion, accidents or detours due to road works or accidents. Congestion in urban areas is a common phenomenon nowadays, as the main arteries of cities become congested during peak hours or when there are additional constraints such as traffic accidents and road works that slow down traffic on road sections. When traffic increases, it is observed that some roads are predisposed to congestion, while others are not. It is evident that both congestion and urban traffic itself are influenced by several factors represented by complex geospatial data and the spatial relationships between them. In this paper were integrated mathematical models, real time traffic data with network analysis and simulation procedures in order to analyze the public transportation in Oradea and the impact on urban traffic. A mathematical model was also adapted to simulate the travel choices of the population of the city and of the surrounding villages. Based on the network analysis, traffic analysis and on the traveling simulation, the elements generating traffic congestion in the inner city can be easily determined. The results of the case study are emphasizing that diminishing the traffic and its effects can be obtained by improving either the public transport density or its accessibility. Numéro de notice : A2022-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11010016 Date de publication en ligne : 30/12/2021 En ligne : https://doi.org/10.3390/ijgi11010016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99382 [article]

Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images / Xiao Li in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)  

Public [article]  inCartography and Geographic Information Science > vol 49 n° 1 (January 2022) . - pp 32 - 49 Titre : Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images Type de document : Article/Communication Auteurs : Xiao Li, Auteur ; Huan Ning, Auteur ; Xiao Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 32 - 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] carrefour [Termes IGN] cartographie urbaine [Termes IGN] couche thématique [Termes IGN] exploration d'images [Termes IGN] feu de circulation [Termes IGN] image Streetview [Termes IGN] Mapillary [Termes IGN] réseau routier [Termes IGN] segmentation d'image [Termes IGN] signalisation routière Résumé : (auteur) Auditing and mapping traffic infrastructure is a crucial task in urban management. For example, signalized intersections play an essential role in transportation management; however, effectively identifying these intersections remains unsolved. Traditionally, signalized intersection data are manually collected through field audits or checking street view images (SVIs), which is time-consuming and labor-intensive. This study proposes an effective protocol to identify signalized intersections using road networks and SVIs. First, we propose a six-step geoprocessing model to generate an intersection feature layer from road networks. Second, we utilize up to three nearest SVIs to capture streetscapes at each intersection. Then, a deep learning-based image segmentation model is adopted to recognize traffic light-related pixels from each SVI. Last, we design a post-processing step to generate new features characterizing SVIs’ segmentation results at each intersection and build a decision tree model to determine the traffic control type. Results demonstrate that the proposed protocol can effectively identify signalized intersections with an overall accuracy of 97.05%. It also proves the effectiveness of SVIs for auditing urban infrastructures. This study can directly benefit transportation agencies by providing a ready-to-use smart audit and mapping solution for large-scale identification and mapping of signalized intersections. Numéro de notice : A2022-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1080/15230406.2021.1992299 Date de publication en ligne : 16/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1992299 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99148 [article]

Modeling transit-assisted hurricane evacuation through socio-spatial networks / Yan Yang in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 12 (December 2021) . - pp 2424 - 2441 Titre : Modeling transit-assisted hurricane evacuation through socio-spatial networks Type de document : Article/Communication Auteurs : Yan Yang, Auteur ; Sara Metcalf, Auteur ; Liang Mao, Auteur Année de publication : 2021 Article en page(s) : pp 2424 - 2441 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] comportement [Termes IGN] Floride (Etats-Unis) [Termes IGN] modèle de simulation [Termes IGN] modèle orienté agent [Termes IGN] réseau social [Termes IGN] système multi-agents [Termes IGN] tempête [Termes IGN] trafic routier [Termes IGN] transport public [Termes IGN] urgence Résumé : (auteur) Increasing intensity and frequency of hurricane events underscores the need for efficient and inclusive evacuation plans, particularly for carless and disabled populations. Hurricane evacuation intrinsically involves both social and spatial processes. People’s decision to evacuate spreads over social networks; once their decisions are made, they flee through spatial transportation networks. This article describes a novel effort to integrate socio-spatial networks into an agent-based evacuation simulation model, taking the Florida Keys in the USA as a study area. In the model, households, as agents, were synthesized from Census data, then connected by a ‘home-workplace-neighborhood’ social network, and registered to a spatial road network. A threshold decision model was used to simulate social contagion of households’ decision to evacuate. The resulting travel demands were input into the TRANSIMS platform to generate on-road traffic. The model analyzed scenarios of automobile-only and public transit-assisted evacuation. The results show that the simulated traffic under the automobile-only scenario aligns with the observed traffic dynamics, which validates our socio-spatially integrated model. Adding public transportation capacity significantly reduces the traffic load and evacuation time, and provides a practical, accessible, and equitable route to safety for low mobility populations. Numéro de notice : A2021-874 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1828590 Date de publication en ligne : 02/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1828590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99137 [article]

Double adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 639-648 Titre : Double adaptive intensity-threshold method for uneven Lidar data to extract road markings Type de document : Article/Communication Auteurs : Chengming Ye, Auteur ; Hongfu Li, Auteur ; Ruilong Wei, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 639-648 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction du réseau routier [Termes IGN] filtre adaptatif [Termes IGN] lidar mobile [Termes IGN] méthode robuste [Termes IGN] semis de points [Termes IGN] seuillage de points [Termes IGN] signalisation routière Résumé : (Auteur) Due to the large volume and high redundancy of point clouds, there are many dilemmas in road-marking extraction algorithms, especially from uneven lidar point clouds. To extract road markings efficiently, this study presents a novel method for handling the uneven density distribution of point clouds and the high reflection intensity of road markings. The method first segments the point-cloud data into blocks perpendicular to the vehicle trajectory. Then it applies the double adaptive intensity-threshold method to extract road markings from road surfaces. Finally, it performs an adaptive spatial density filter based on the density distribution of point-cloud data to remove false road-marking points. The average completeness, correctness, and F measure of road-marking extraction are 0.827, 0.887, and 0.854, respectively, indicating that the proposed method is efficient and robust. Numéro de notice : A2021-672 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00099 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.20-00099 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98834 [article]

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A multiagent systems with Petri Net approach for simulation of urban traffic networks / Mauricio Flores Geronimo in Computers, Environment and Urban Systems, vol 89 (September 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 89 (September 2021) . - n° 101662 Titre : A multiagent systems with Petri Net approach for simulation of urban traffic networks Type de document : Article/Communication Auteurs : Mauricio Flores Geronimo, Auteur ; Eduardo Gamaliel Hernandez Martinez, Auteur ; Enrique Ferreira Vasquez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] circulation urbaine [Termes IGN] Matlab [Termes IGN] Montevideo [Termes IGN] réseau routier [Termes IGN] signalisation routière [Termes IGN] système multi-agents [Termes IGN] trafic routier Résumé : (auteur)This paper presents a novel model framework for complex urban traffic systems based on the interconnection of a dynamical multi-agent system in a macroscopic level. The agents describe all the types of street segments, intersections, sources and sinks of cars, modelling the behavior of the flow of vehicles through them as simple differential equations. These agents include the phenomena of changes in the flow rate due to congestions, traffic signals and the density of the vehicles. Traffic signal changes are obtained by the evolution of Petri Nets, in order to represent a more real behavior. Therefore, a complex network can be constructed by the interconnection of the agents, in continuous time, and the Petri Nets, in a discrete-event behavior, becoming a hybrid and scalable system. In order to analyze the performance of the approach, a real set of streets and intersections in Montevideo City is studied. Also, the approach is compared with a simulation realized in the software TSIS-CORSIM, which contains real data of density of vehicles. The multi-agent system achieves comparable results, taking into account the differences in the level of details respect to TSIS-CORSIM. Thus, the results can represent the most important issues of vehicular traffic with less computational resources. Numéro de notice : A2021-536 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101662 Date de publication en ligne : 04/06/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101662 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98001 [article]

Flood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)  

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The point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

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Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)  

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A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks / Bozhao Li in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

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Evaluating the effectiveness of different cartographic design variants for influencing route choice / Stefan Fuest in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)  

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Using geometric constraints to improve performance of image classifiers for automatic segmentation of traffic signs / Roholah Yazdan in Geomatica [en ligne], vol 75 n° 1 (Mars 2021)  

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Deep traffic light detection by overlaying synthetic context on arbitrary natural images / Jean Pablo Vieira de Mello in Computers and graphics, vol 94 n° 1 (February 2021)  

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Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / Roholah Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Inferencing hourly traffic volume using data-driven machine learning and graph theory / Zhiyan Yi in Computers, Environment and Urban Systems, vol 85 (January 2021)  

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Machine learning for the distributed and dynamic management of a fleet of taxis and autonomous shuttles / Tatiana Babicheva (2021)  

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