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20232026
most citedDuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation

6 citations · 18 across the 37 of their papers we have counts for

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16 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The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches.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.RO2026

LSRE: Latent Semantic Rule Encoding for Real-Time Semantic Risk Detection in Autonomous Driving

Qian Cheng, Weitao Zhou, Cheng Jing +5

Real-world autonomous driving must adhere to complex human social rules that extend beyond legally codified traffic regulations. Many of these semantic constraints, such as yieldin…

cs.RO2025

Are All Data Necessary? Efficient Data Pruning for Large-scale Autonomous Driving Dataset via Trajectory Entropy Maximization

Zhaoyang Liu, Weitao Zhou, Junze Wen +4

Collecting large-scale naturalistic driving data is essential for training robust autonomous driving planners. However, real-world datasets often contain a substantial amount of re…

cs.RO2025

DTCCL: Disengagement-Triggered Contrastive Continual Learning for Autonomous Bus Planners

Yanding Yang, Weitao Zhou, Jinhai Wang +8

Autonomous buses run on fixed routes but must operate in open, dynamic urban environments. Disengagement events on these routes are often geographically concentrated and typically…

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

DRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy

Weitao Zhou, Bo Zhang, Zhong Cao +5

With the increasing presence of automated vehicles on open roads under driver supervision, disengagement cases are becoming more prevalent. While some data-driven planning systems…

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

Dynamically Local-Enhancement Planner for Large-Scale Autonomous Driving

Nanshan Deng, Weitao Zhou, Bo Zhang +4

Current autonomous vehicles operate primarily within limited regions, but there is increasing demand for broader applications. However, as models scale, their limited capacity beco…

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

FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback

Kangan Qian, Zhikun Ma, Yangfan He +13

Ensuring safe, comfortable, and efficient navigation is a critical goal for autonomous driving systems. While end-to-end models trained on large-scale datasets excel in common driv…

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★ 1 cited

A Survey on Monocular Re-Localization: From the Perspective of Scene Map Representation

Jinyu Miao, Kun Jiang, Tuopu Wen +8

Monocular Re-Localization (MRL) is a critical component in autonomous applications, estimating 6 degree-of-freedom ego poses w.r.t. the scene map based on monocular images. In rece…