自动驾驶

Real-Time Rulebook-Aware Nonlinear MPC for Autonomous Driving with Priority-Biased Tiered Slacks

用于自动驾驶的具有优先级偏差分层松弛的实时规则手册感知非线性MPC

Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde, Paul Schmitt, Miguel Hurtado

机构 * TORC Robotics LLC（TORC机器人有限责任公司） ； Daimler Truck AG（戴姆勒卡车股份公司） ； MassRobotics（大众机器人协会） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

AI总结 研究自动驾驶中安全等冲突的解决，提出W-SQP加权分层松弛非线性MPC，将九个规则家族编译求解，能实时重新规划并记录残差，经评估在安全法规方面无系统性缺陷，是可审核、有优先级偏差且随时可用的NMPC原型。

Comments The manuscript is submitted to the Journal of Control Engineering Practice, A journal of The International Federation of Automatic Control (IFAC)

Track A*: Fast Visibility-Aware Trajectory Planning for Active Target Tracking

Track A*: 为主动目标跟踪的快速可见性感知轨迹规划

Hanxuan Chen, Kangli Wang, Ji Pei

机构 * Autel Robotics（奥特 Robotics） 纠错

专题命中 感知 ：trajectory planning(title)；分类 cs.RO

AI总结 本文提出Track A*，一种基于离线搜索的轨迹规划器，用于在离散的四维时空网格上实现可见性感知的目标跟踪。通过分层有向无环图搜索和三种工程优化，Track A*在保证实用性的同时提升了可扩展性，实验证明其在计算成本低的情况下具有稳健的可见性性能。

Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations

迈向合法自动驾驶：从交通法规中推导场景感知的驾驶要求

Bowen Jian, Rongjie Yu, Hong Wang, Liqiang Wang, Zihang Zou

机构 * College of Transportation, Tongji University（同济大学交通运输学院） ； The Key Laboratory of Road and Traffic Engineering, Ministry of Education（教育部道路与交通工程重点实验室） ； School of Vehicle and Mobility, Tsinghua University（清华大学车辆与移动性学院） ； College of Computer Science, University of Central Florida（佛罗里达中央大学计算机科学学院） ； Optixway AI 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.AI

AI总结 本文提出一种基于交通场景分类的新型方法，利用大语言模型推导法律要求，提升自动驾驶系统的合规性与准确性。

Cognitive-Causal Multi-Task Learning with Psychological State Conditioning for Assistive Driving Perception

具有心理状态条件的认知因果多任务学习用于辅助驾驶感知

Keito Inoshita, Nobuhiro Hayashida, Akira Imanishi

机构 * Kansai University（关西大学） ； ISUZU Advanced Engineering Center, Ltd.（五十铃先进工程中心有限公司） 纠错

专题命中 感知 ：driving perception(title)；分类 cs.AI

AI总结 本文提出CauPsi框架，通过认知因果结构建模驾驶行为，利用可学习原型嵌入实现任务链传播，并引入跨任务心理条件机制，提升驾驶感知任务的准确率。

LEO: Graph Attention Network based Hybrid Multi Sensor Extended Object Fusion and Tracking for Autonomous Driving Applications

LEO：基于图注意力网络的混合多传感器扩展物体融合与跟踪用于自动驾驶应用

Mayank Mayank, Bharanidhar Duraisamy, Florian Geiss

机构 * Research and Development, Mercedes-Benz AG, Germany（德国梅赛德斯-奔驰集团研发部） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.AI

AI总结 LEO结合图注意力网络融合多模态传感器数据，实现动态物体形状和轨迹的准确估计，具备自适应融合权重和跨传感器类型的一致性跟踪能力。

Comments 10 pages, 6 figures

Learning Image-based Tree Crown Segmentation from Enhanced Lidar-based Pseudo-labels

从增强的激光雷达伪标签中学习基于图像的树冠分割

Julius Pesonen, Stefan Rua, Josef Taher, Niko Koivumäki, Xiaowei Yu, Eija Honkavaara

机构 * Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute（遥感与摄影测量系，芬兰地理研究机构） ； Department of Computer Science, Aalto University（计算机科学系，阿alto大学） 纠错

专题命中 感知 ：LiDAR(title)；分类 cs.CV

AI总结 本文提出利用增强的激光雷达伪标签训练深度学习模型，实现基于图像的树冠分割，无需人工标注即可获得更优的分割效果。

UV-M3TL: A Unified and Versatile Multimodal Multi-Task Learning Framework for Assistive Driving Perception

UV-M3TL: 一种统一且多功能的多模态多任务学习框架用于辅助驾驶感知

Wenzhuo Liu, Qiannan Guo, Zhen Wang, Wenshuo Wang, Lei Yang, Yicheng Qiao, Lening Wang, Zhiwei Li, Chen Lv, Shanghang Zhang, Junqiang Xi, Huaping Liu

机构 * Energy and Transportation Domain, Beijing Institute of Technology（能源与交通领域，北京理工大学） ； State Key Laboratory of Intelligent Technology and Systems and Department of Computer Science and Technology, Tsinghua University（智能技术与系统国家重点实验室和清华大学计算机科学与技术系） ； School of Mechanical and Aerospace Engineering, Nanyang Technological University（机械与航空航天工程学院，南洋理工大学） ； School of Transportation Science and Engineering and the State Key Lab of Intelligent Transportation System, Beihang University（交通运输科学与工程学院和智能交通系统国家重点实验室，北京航空航天大学） ； Beijing University of Chemical Technology（北京化工大学） 纠错

专题命中 感知 ：driving perception(title)；分类 cs.CV

AI总结 UV-M3TL通过双分支结构和自适应损失机制，实现多模态多任务学习，提升辅助驾驶感知的性能与多样性。

WarNav: An Autonomous Driving Benchmark for Segmentation of Navigable Zones in War Scenes

WarNav: 一种用于战场场景中可导航区域分割的自动驾驶基准测试集

Marc-Emmanuel Coupvent des Graviers, Hejer Ammar, Christophe Guettier, Yann Dumortier, Romaric Audigier

机构 * Safran Electronics and Defense（萨弗兰电子与防御公司） ； Université Paris-Saclay（巴黎-萨克雷大学） ； CEA（法国原子能委员会） ； List 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

AI总结 WarNav是一个专为战场场景中自主车辆导航设计的语义分割基准测试集，旨在填补传统城市驾驶资源与战区独特操作场景之间的空白。

Comments Accepted at CAID (Conference on Artificial Intelligence for Defence)

RAFT -- A Domain Adaptation Framework for RGB & LiDAR Semantic Segmentation

Edward Humes, Xiaomin Lin, Boxun Hu, Rithvik Jonna, Tinoosh Mohsenin

机构 * Department of Electrical and Computer Engineering, Johns Hopkins University（约翰霍普金斯大学电气与计算机工程系） ； Department of Electrical Engineering, University of South Florida（佛罗里达州立大学电气工程系） 纠错

专题命中 感知 ：LiDAR(title)；分类 cs.CV

Comments Submitted to RA-L

ROAR: Robust Accident Recognition and Anticipation for Autonomous Driving

Xingcheng Liu, Yanchen Guan, Haicheng Liao, Zhengbing He, Zhenning Li

机构 * State Key Laboratory of Internet of Things for Smart City（物联网智能城市国家重点实验室） ； Department of Computer and Information Science（计算机与信息科学系） ； University of Macau（澳门大学） ； Senseable City Lab（可感知城市实验室） ； Massachusetts Institute of Technology（麻省理工学院） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.AI

Comments Published to Accident Analysis and Prevention

A Faster and More Reliable Middleware for Autonomous Driving Systems

Yuankai He, Weisong Shi

机构 * University of Delaware（特拉华大学） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Comments 8 pages,7 figures, 8 tables

Calibrating the Full Predictive Class Distribution of 3D Object Detectors for Autonomous Driving

Cornelius Schröder, Marius-Raphael Schlüter, Markus Lienkamp

机构 * Technical University of Munich（慕尼黑技术大学） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Journal ref 2025 IEEE Intelligent Vehicles Symposium (IV), Cluj-Napoca, Romania, 2025, pp. 187-194

CoopScenes: Multi-Scene Infrastructure and Vehicle Data for Advancing Collective Perception in Autonomous Driving

Marcel Vosshans, Alexander Baumann, Matthias Drueppel, Omar Ait-Aider, Youcef Mezouar, Thao Dang, Markus Enzweiler

机构 * Institute for Intelligent Systems（智能系统研究所） ； Faculty of Computer Science and Engineering（计算机科学与工程学院） ； University of Applied Sciences Esslingen（应用科学大学埃森堡） ； Institut Pascal ISPR（帕斯卡尔研究所） ； Universite Clermont Auvergne INP / CNRS（克勒蒙费朗大学 INP / CNRS） ； Center for Artificial Intelligence（人工智能中心） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Comments Accepted to be published at the 2025 36th IEEE Intelligent Vehicles Symposium (IV), Cluj-Napoca, Romania, June 22 - 25, 2025

AID4AD: Aerial Image Data for Automated Driving Perception

Daniel Lengerer, Mathias Pechinger, Klaus Bogenberger, Carsten Markgraf

机构 * Faculty of Electrical Engineering, Technical University of Applied Sciences Augsburg（电气工程学院，应用技术大学阿沙格市分校） ； Chair of Traffic Engineering and Control, Technical University of Munich（交通工程与控制教授职位，慕尼黑技术大学） 纠错

专题命中 感知 ：driving perception(title)；分类 cs.CV

Towards Railway Domain Adaptation for LiDAR-based 3D Detection: Road-to-Rail and Sim-to-Real via SynDRA-BBox

Xavier Diaz, Gianluca D'Amico, Raul Dominguez-Sanchez, Federico Nesti, Max Ronecker, Giorgio Buttazzo

机构 * Mobility Technologies（移动技术） ； Department of Excellence in Robotics & AI, SETLabs Research GmbH（机器人与人工智能卓越部门，SETLabs Research GmbH） ； Scuola Superiore Sant’Anna（圣安娜高等学院） 纠错

专题命中 感知 ：LiDAR(title)；分类 cs.CV

Comments IEEE International Conference on Intelligent Rail Transportation (ICIRT) 2025

HS-SLAM: A Fast and Hybrid Strategy-Based SLAM Approach for Low-Speed Autonomous Driving

Bingxiang Kang, Jie Zou, Guofa Li, Pengwei Zhang, Jie Zeng, Kan Wang, Jie Li

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Comments 11 pages, 7 figures

Optical aberrations in autonomous driving: Physics-informed parameterized temperature scaling for neural network uncertainty calibration

Dominik Werner Wolf, Alexander Braun, Markus Ulrich

机构 * Machine Vision Metrology Group of the Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院机器视觉计量组） ； Volkswagen Group（大众集团） ； Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院） ； University of Applied Sciences Duesseldorf (HSD)（杜塞尔多夫应用技术大学） 纠错

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Comments Under review at IEEE Transactions on Intelligent Transportation Systems (T-ITS)

Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving

Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Comments 50 pages, 18 figures

M2S-RoAD: Multi-Modal Semantic Segmentation for Road Damage Using Camera and LiDAR Data

Tzu-Yun Tseng, Hongyu Lyu, Josephine Li, Julie Stephany Berrio, Mao Shan, Stewart Worrall

专题命中 感知 ：LiDAR(title)；分类 cs.CV

MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception

Wenzhuo Liu, Wenshuo Wang, Yicheng Qiao, Qiannan Guo, Jiayin Zhu, Pengfei Li, Zilong Chen, Huiming Yang, Zhiwei Li, Lening Wang, Tiao Tan, Huaping Liu

专题命中 感知 ：driving perception(title)；分类 cs.CV

SSF: Sparse Long-Range Scene Flow for Autonomous Driving

Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez, Aron Asefaw, Sina Sharif Mansouri, Patric Jensfelt

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Comments 7 pages, 3 figures, accepted to International Conference on Robotics and Automation (ICRA) 2025

DINOSTAR: Deep Iterative Neural Object Detector Self-Supervised Training for Roadside LiDAR Applications

Muhammad Shahbaz, Shaurya Agarwal

专题命中 感知 ：LiDAR(title)；分类 cs.CV

Comments conference, 6 pages

Adaptive Communications in Collaborative Perception with Domain Alignment for Autonomous Driving

Senkang Hu, Zhengru Fang, Haonan An, Guowen Xu, Yuan Zhou, Xianhao Chen, Yuguang Fang

专题命中 感知 ：autonomous driving(title)；分类 cs.AI

Comments Accepted by GLOBECOM'24

A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting

Felix Assion, Florens Gressner, Nitin Augustine, Jona Klemenc, Ahmed Hammam, Alexandre Krattinger, Holger Trittenbach, Anja Philippsen, Sascha Riemer

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Knowledge Transfer from Simple to Complex: A Safe and Efficient Reinforcement Learning Framework for Autonomous Driving Decision-Making

Rongliang Zhou, Jiakun Huang, Mingjun Li, Hepeng Li, Haotian Cao, Xiaolin Song

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving

Jinpeng Lin, Zhihao Liang, Shengheng Deng, Lile Cai, Tao Jiang, Tianrui Li, Kui Jia, Xun Xu

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Comments IEEE Transactions on Intelligent Transportation Systems. Code is available at https://github.com/Linkon87/Exploring-Diversity-based-Active-Learning-for-3D-Object-Detection-in-Autonomous-Driving

Words to Wheels: Vision-Based Autonomous Driving Understanding Human Language Instructions Using Foundation Models

Chanhoe Ryu, Hyunki Seong, Daegyu Lee, Seongwoo Moon, Sungjae Min, D. Hyunchul Shim

专题命中 感知 ：autonomous driving(title)；分类 cs.RO

Comments 7 pages, 7 figures

MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving

Xiyang Wang, Shouzheng Qi, Jieyou Zhao, Hangning Zhou, Siyu Zhang, Guoan Wang, Kai Tu, Songlin Guo, Jianbo Zhao, Jian Li, Mu Yang

专题命中 感知 ：autonomous driving(title)；分类 cs.CV

Comments 14 pages, 7 figures

Deep Learning Safety Concerns in Automated Driving Perception

Stephanie Abrecht, Alexander Hirsch, Shervin Raafatnia, Matthias Woehrle

专题命中 感知 ：driving perception(title)；分类 cs.CV

Comments Added note regarding accepted version at IEEE Transactions on Intelligent Vehicles with DOI

B-TMS: Bayesian Traversable Terrain Modeling and Segmentation Across 3D LiDAR Scans and Maps for Enhanced Off-Road Navigation

Minho Oh, Gunhee Shin, Seoyeon Jang, Seungjae Lee, Dongkyu Lee, Wonho Song, Byeongho Yu, Hyungtae Lim, Jaeyoung Lee, Hyun Myung

专题命中 感知 ：LiDAR(title)；分类 cs.RO

Comments Accepted by IEEE IV'24 workshop on Off-road autonomy