A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving (2025)
- Authors:
- USP affiliated authors: WOLF, DENIS FERNANDO - ICMC ; GOMES, IAGO PACHECO - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.neucom.2025.131014
- Subjects: VEÍCULOS AUTÔNOMOS; MÉTODOS DE PREVISÃO E CORREÇÃO; TRAJETÓRIA; TOMADA DE DECISÃO
- Keywords: Trajectory prediction; Maneuver intention; Interaction
- Agências de fomento:
- Language: Inglês
- Sustainable Development Goals (GDS):
09. Industry, innovation and infrastructure
- Imprenta:
- Source:
- Título: Neurocomputing
- ISSN: 0925-2312
- Volume/Número/Paginação/Ano: v. 651, p. 1-19, 2025
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
GOMES, Iago Pachêco e WOLF, Denis Fernando. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving. Neurocomputing, v. 651, p. 1-19, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2025.131014. Acesso em: 28 dez. 2025. -
APA
Gomes, I. P., & Wolf, D. F. (2025). A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving. Neurocomputing, 651, 1-19. doi:10.1016/j.neucom.2025.131014 -
NLM
Gomes IP, Wolf DF. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving [Internet]. Neurocomputing. 2025 ; 651 1-19.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.neucom.2025.131014 -
Vancouver
Gomes IP, Wolf DF. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving [Internet]. Neurocomputing. 2025 ; 651 1-19.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.neucom.2025.131014 - Driving style recognition using interval type-2 fuzzy inference system and multiple experts decision-making
- Multi-agent interaction-aware behavior intention prediction using graph mixture of experts attention network on urban roads
- A health monitoring system with hybrid bayesian network for autonomous vehicle
- Late-fusion multimodal human detection based on RGB and thermal images for robotic perception
- Scheduling system for sultiple self-driving cars using k-means and bio-inspired optimization algorithms
- Interaction-aware maneuver intention prediction using gated mixture-of-experts attention mechanism
- Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis
- Interaction-aware maneuver prediction for autonomous vehicles using interaction graphs
- Route scheduling system for multiple self-driving cars using K-means and bio-inspired algorithms
- A Software Architecture Proposal for Autonomous Vehicles
Informações sobre o DOI: 10.1016/j.neucom.2025.131014 (Fonte: oaDOI API)
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