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Analysing Connected Car Data to Understand Vehicular Route Choice

Autor: Karikari, Elliot, Prédhumeau, Manon, Baudains, Peter, Manley, Ed

This paper motivates the use of GPS traces to better understand the complexities of driver behaviour and movement, and introduces a new car trajectories dataset. This dataset, provided via the ESRC Consumer Data Research Centre, consist of connected

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06d0380db11d1cbbefef2078f30ecebd

Agent-Based Modeling for Predicting Pedestrian Trajectories Around an Autonomous Vehicle

Autor: Prédhumeau, Manon, Mancheva, Lyuba, Dugdale, Julie, Spalanzani, Anne

Publikováno v: Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research, 2022, 73, pp.1385-1433. ⟨10.1613/jair.1.13425⟩

International audience; This paper addresses modeling and simulating pedestrian trajectories when interacting with an autonomous vehicle in a shared space. Most pedestrian-vehicle interaction models are not suitable for predicting individual trajecto

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a845e5e81494fff53ef682616e23cbc2
https://doi.org/10.1613/jair.1.13425

Modélisation et simulation de comportements piétons réalistes en espace partagé avec un véhicule autonome

Autor: Prédhumeau, Manon

Publikováno v: Intelligence artificielle [cs.AI]. Université Grenoble Alpes [2020-..], 2021. Français. ⟨NNT : 2021GRALM070⟩

In the near future, autonomous vehicles will have to navigate in dense and dynamic urban environments like shared spaces. In such spaces, segregation between pedestrians and vehicles is minimized and users must negotiate their passage without explici

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::33ec197af3891df28934d1b4b5223093
https://hal.science/tel-03518751v2/file/PREDHUMEAU_2021_archivage.pdf

Un modèle à base d'agents pour prédire les trajectoires des piétons dans des espaces partagés avec un véhicule autonome

Autor: Prédhumeau, Manon, Mancheva, Lyuba, Dugdale, Julie, Spalanzani, Anne

Publikováno v: Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)
AAMAS 2021-20th International Conference on Autonomous Agents and Multiagent Systems
AAMAS 2021-20th International Conference on Autonomous Agents and Multiagent Systems, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), May 2021, Online, France. pp.1-9
20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)
20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), May 2021, Online, France

International audience; This paper addresses modeling and simulating pedestrian trajectories when interacting with an autonomous vehicle in a shared space. Pedestrian motion models integrating pedestrians interactions with an autonomous vehicle alrea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::656f295fd0bba16e443483636d28e4c7
https://hal.archives-ouvertes.fr/hal-03113422v2/file/AAMAS_2021_camera_ready.pdf