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20222026
most citedGrid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review

9 citations · 28 across the 30 of their papers we have counts for

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12 papers · 1 filter

cs.RO2026

nuTruck: Benchmarking Autonomous Driving Planning for Distributed Electric-drive Trucks

Jinyu Miao, Pu Zhang, Yifei He +5

The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches. While learning-based planners have achieved consider…

cs.RO2026

4DLidarOpen: An Open 4D FMCW Lidar Dataset for Motion-Aware Autonomous Driving

Kane Qian, Xin Zhao, Yining Shi +7

We present 4DLidarOpen, a large-scale open multi-modal dataset for autonomous driving, centered on 4D frequency-modulated continuous-wave (FMCW) Lidar sensing. Unlike conventional…

cs.RO2026

Physics-informed Deep Mixture-of-Koopmans Vehicle Dynamics Model with Dual-branch Encoder for Distributed Electric-drive Trucks

Jinyu Miao, Pu Zhang, Rujun Yan +8

Advanced autonomous driving systems require accurate vehicle dynamics modeling. However, identifying a precise dynamics model remains challenging due to strong nonlinearities and t…

cs.RO2025

MTRDrive: Memory-Tool Synergistic Reasoning for Robust Autonomous Driving in Corner Cases

Ziang Luo, Kangan Qian, Jiahua Wang +13

Vision-Language Models(VLMs) have demonstrated significant potential for end-to-end autonomous driving, yet a substantial gap remains between their current capabilities and the rel…

cs.RO2025

Multimodal HD Mapping for Intersections by Intelligent Roadside Units

Zhongzhang Chen, Miao Fan, Shengtong Xu +4

High-definition (HD) semantic mapping of complex intersections poses significant challenges for traditional vehicle-based approaches due to occlusions and limited perspectives. Thi…

cs.RO2025

AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving

Kangan Qian, Sicong Jiang, Yang Zhong +18

Vision-Language Models (VLMs) show promise for autonomous driving, yet their struggle with hallucinations, inefficient reasoning, and limited real-world validation hinders accurate…

cs.RO2025

FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback

Kangan Qian, Ziang Luo, Sicong Jiang +16

Ensuring safe, comfortable, and efficient planning is crucial for autonomous driving systems. While end-to-end models trained on large datasets perform well in standard driving sce…

cs.RO2025

RAVE: End-to-end Hierarchical Visual Localization with Rasterized and Vectorized HD map

Jinyu Miao, Tuopu Wen, Kun Jiang +8

Accurate localization serves as an important component in autonomous driving systems. Traditional rule-based localization involves many standalone modules, which is theoretically f…

cs.RO2025

Residual Learning towards High-fidelity Vehicle Dynamics Modeling with Transformer

Jinyu Miao, Rujun Yan, Bowei Zhang +6

The vehicle dynamics model serves as a vital component of autonomous driving systems, as it describes the temporal changes in vehicle state. In a long period, researchers have made…

cs.RO2024★ 1 cited

High Definition Map Mapping and Update: A General Overview and Future Directions

Benny Wijaya, Kun Jiang, Mengmeng Yang +6

Along with the rapid growth of autonomous vehicles (AVs), more and more demands are required for environment perception technology. Among others, HD mapping has become one of the m…

cs.RO2023

Poses as Queries: Image-to-LiDAR Map Localization with Transformers

Jinyu Miao, Kun Jiang, Yunlong Wang +6

High-precision vehicle localization with commercial setups is a crucial technique for high-level autonomous driving tasks. Localization with a monocular camera in LiDAR map is a ne…

cs.RO2022★ 2 cited

Map Container: A Map-based Framework for Cooperative Perception

Kun Jiang, Yining Shi, Benny Wijaya +4

The idea of cooperative perception is to benefit from shared perception data between multiple vehicles and overcome the limitations of on-board sensors on single vehicle. However,…