Cover Image

Temporal Sampling Frequency Matters: A Capacity-Aware Study of End-to-End Driving Trajectory Prediction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yumao, Liu, Tao, Li, Xiangyu, Li, Jiaxiang, Ma, Ke
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PAVE: An End-to-End Dataset for Production Autonomous Vehicle Evaluation
by: Li, Xiangyu, et al.
Published: (2025)

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving
by: Li, Yongkang, et al.
Published: (2025)

Collision Risk Estimation via Loss Prediction in End-to-End Autonomous Driving
by: Xiong, Ziliang, et al.
Published: (2025)

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

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

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

MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving
by: Wang, Junli, et al.
Published: (2026)

ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Driving
by: Zheng, Zhiyu, et al.
Published: (2025)

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

Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
by: Sun, Jiangxin, et al.
Published: (2026)

Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving
by: Ge, Junhao, et al.
Published: (2025)

DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning
by: Yao, Wenhao, et al.
Published: (2025)

HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models
by: Cho, Hoonhee, et al.
Published: (2026)

DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving
by: Wang, Tianqi, et al.
Published: (2024)

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
by: Zhao, Rui, et al.
Published: (2026)

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
by: Wu, Yanhao, et al.
Published: (2026)

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
by: Zhang, Lingjun, et al.
Published: (2026)

ZTRS: Zero-Imitation End-to-end Autonomous Driving with Trajectory Scoring
by: Li, Zhenxin, et al.
Published: (2025)

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

DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
by: Shang, Shuyao, et al.
Published: (2025)

METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance
by: Guo, Ziang, et al.
Published: (2024)

RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning
by: Gao, Hao, et al.
Published: (2025)

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

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

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
by: Wang, Junli, et al.
Published: (2026)

What Matters for Scalable and Robust Learning in End-to-End Driving Planners?
by: Holtz, David, et al.
Published: (2026)

Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
by: Jia, Xiaosong, et al.
Published: (2024)

An End-to-End Decision-Aware Multi-Scale Attention-Based Model for Explainable Autonomous Driving
by: Azad, Maryam Sadat Hosseini, et al.
Published: (2026)

From Human Intention to Action Prediction: Intention-Driven End-to-End Autonomous Driving
by: Zheng, Huan, et al.
Published: (2025)

Fast-SmartWay: Panoramic-Free End-to-End Zero-Shot Vision-and-Language Navigation
by: Shi, Xiangyu, et al.
Published: (2025)

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
by: Jiang, Bo, et al.
Published: (2024)

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

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
by: Jiang, Bo, et al.
Published: (2024)

Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
by: Wang, Linbo, et al.
Published: (2026)

HAD: Combining Hierarchical Diffusion with Metric-Decoupled RL for End-to-End Driving
by: Yao, Wenhao, et al.
Published: (2026)

Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Driving
by: Han, Jianhua, et al.
Published: (2025)

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
by: Song, Ziying, et al.
Published: (2025)

Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving
by: Rowe, Luke, et al.
Published: (2025)

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

Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
by: Geng, Jiaheng, et al.
Published: (2025)