Copertina

UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Song, Ziyi, Xia, Chen, Wang, Chenbing, Yu, Haibao, Zhou, Sheng, Niu, Zhisheng
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Robotics Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

End-to-End Autonomous Driving through V2X Cooperation
di: Yu, Haibao, et al.
Pubblicazione: (2024)

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
di: Hao, Ruiyang, et al.
Pubblicazione: (2025)

StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving
di: Hao, Ruiyang, et al.
Pubblicazione: (2025)

UniSTPA: A Safety Analysis Framework for End-to-End Autonomous Driving
di: Kou, Hongrui, et al.
Pubblicazione: (2025)

GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving
di: Liu, Shuai, et al.
Pubblicazione: (2025)

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems
di: Coscoy, Marco, et al.
Pubblicazione: (2026)

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
di: You, Junwei, et al.
Pubblicazione: (2024)

DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation
di: Yu, Haibao, et al.
Pubblicazione: (2025)

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization
di: Lin, Changhong, et al.
Pubblicazione: (2025)

PIE: Perception and Interaction Enhanced End-to-End Motion Planning for Autonomous Driving
di: Yuan, Chengran, et al.
Pubblicazione: (2025)

SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving
di: Zheng, Peiru, et al.
Pubblicazione: (2025)

ComDrive: Comfort-Oriented End-to-End Autonomous Driving
di: Wang, Junming, et al.
Pubblicazione: (2024)

Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
di: Duan, Yiqun, et al.
Pubblicazione: (2024)

Exploring Contextual Representation and Multi-Modality for End-to-End Autonomous Driving
di: Azam, Shoaib, et al.
Pubblicazione: (2022)

Enhancing End-to-End Autonomous Driving with Risk Semantic Distillaion from VLM
di: Qin, Jack, et al.
Pubblicazione: (2025)

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
di: Hua, Zhihua, et al.
Pubblicazione: (2026)

Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
di: Zheng, Yupeng, et al.
Pubblicazione: (2024)

Enhancing End-to-End Autonomous Driving Systems Through Synchronized Human Behavior Data
di: Duan, Yiqun, et al.
Pubblicazione: (2024)

GMF-Drive: Gated Mamba Fusion with Spatial-Aware BEV Representation for End-to-End Autonomous Driving
di: Wang, Jian, et al.
Pubblicazione: (2025)

Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
di: Song, Ziying, et al.
Pubblicazione: (2025)

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving
di: Oh, Haesung, et al.
Pubblicazione: (2026)

UniUncer: Unified Dynamic Static Uncertainty for End to End Driving
di: Gao, Yu, et al.
Pubblicazione: (2026)

Utilizing Navigation Paths to Generate Target Points for Enhanced End-to-End Autonomous Driving Planning
di: Shen, Yuanhua, et al.
Pubblicazione: (2024)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
di: Jiang, Hao, et al.
Pubblicazione: (2025)

Embodied Cognition Augmented End2End Autonomous Driving
di: Niu, Ling, et al.
Pubblicazione: (2025)

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
di: Yang, Zhenjie, et al.
Pubblicazione: (2025)

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving
di: Yasarla, Rajeev, et al.
Pubblicazione: (2026)

Exploring the Causality of End-to-End Autonomous Driving
di: Li, Jiankun, et al.
Pubblicazione: (2024)

FocalAD: Local Motion Planning for End-to-End Autonomous Driving
di: Sun, Bin, et al.
Pubblicazione: (2025)

DriveSafer: End-to-End Autonomous Driving with Safety Guidance
di: Sural, Shounak, et al.
Pubblicazione: (2026)

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving
di: Liu, Haochen, et al.
Pubblicazione: (2025)

Risk Map As Middleware: Towards Interpretable Cooperative End-to-end Autonomous Driving for Risk-Aware Planning
di: Lei, Mingyue, et al.
Pubblicazione: (2025)

SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving
di: Wolters, Philipp, et al.
Pubblicazione: (2025)

Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving
di: Guo, Yipin, et al.
Pubblicazione: (2024)

Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
di: Zhang, Bozhou, et al.
Pubblicazione: (2025)

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving
di: Zhao, Seth Z., et al.
Pubblicazione: (2026)

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
di: Liao, Bencheng, et al.
Pubblicazione: (2024)

NetRoller: Interfacing General and Specialized Models for End-to-End Autonomous Driving
di: Xin, Ren, et al.
Pubblicazione: (2025)

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
di: Feng, Renju, et al.
Pubblicazione: (2025)

IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving
di: Zhang, Chenghao, et al.
Pubblicazione: (2026)