自动驾驶

Navigating in the Dark -- Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments

Lashawnda Bynum, Jay Parker, Kristy Lee, Nia Nitschke, Melanie LaFlam, Jennifer Marcussen, Jana Taleb, Aleyna Dogan, Lisa J. Molnar, Feng Zhou

专题命中 规划控制 ：autonomous driving(title)

Optimal Trajectory Planning for Connected and Automated Vehicles in Lane-free Traffic with Vehicle Nudging

Venkata Karteek Yanumula, Panagiotis Typaldos, Dimitrios Troullinos, Milad Malekzadeh, Ioannis Papamichail, Markos Papageorgiou

专题命中 规划控制 ：trajectory planning(title)

Managing Sets of Flying Base Stations Using Energy Efficient 3D Trajectory Planning in Cellular Networks

Mohammad Javad Sobouti, Amir Hossein Mohajerzadeh, Seyed Amin Hosseini Seno, Halim Yanikomeroglu

专题命中 规划控制 ：trajectory planning(title)

Comments This paper is a draft of a submitted paper to the IEEE Sensors journal

A Safe Control Architecture Based on Robust Model Predictive Control for Autonomous Driving

Maryam Nezami, Ngoc Thinh Nguyen, Georg Männel, Hossam Seddik Abbas, Georg Schildbach

专题命中 规划控制 ：autonomous driving(title)

Control of site occupancy by variation of the Zn and Al content in NiZnAl ferrite epitaxial films with low magnetic damping

Julia Lumetzberger, Verena Ney, Anna Zhakarova, Daniel Primetzhofer, Kilian Lenz, Andreas Ney

专题命中 规划控制 ：occupancy(title)

Comments 13 pages, 7 figures

Interpretable AI-based Large-scale 3D Pathloss Prediction Model for enabling Emerging Self-Driving Networks

Usama Masood, Hasan Farooq, Ali Imran, Adnan Abu-Dayya

专题命中 规划控制 ：self-driving(title)

Comments Accepted at IEEE Transactions on Mobile Computing

Joint Cluster Head Selection and Trajectory Planning in UAV-Aided IoT Networks by Reinforcement Learning with Sequential Model

Botao Zhu, Ebrahim Bedeer, Ha H. Nguyen, Robert Barton, Jerome Henry

专题命中 规划控制 ：trajectory planning(title)

Comments This paper has been accepted in IEEE IoT-J

Fast Spline Trajectory Planning: Minimum Snap and Beyond

Declan Burke, Airlie Chapman, Iman Shames

专题命中 规划控制 ：trajectory planning(title)

Comments 11 pages, 5 figures, to be submitted to IEEE Transactions on Robotics

Robot Trajectory Planning With QoS Constrained IRS-assisted Millimeter-Wave Communications

Cristian Tatino, Nikolaos Pappas, Di Yuan

专题命中 规划控制 ：trajectory planning(title)

Tube-based Guaranteed Cost Model Predictive Control Applied to Autonomous Driving Up to the Limits of Handling

Carlos M. Massera, Tiago C. dos Santos, Marco H. Terra, Denis F. Wolf

专题命中 规划控制 ：autonomous driving(title)

Fuel and Time Optimal USV Trajectory Planning under Flexible Refueling Constraints

Aaron Kandel, Chu Xu, David Cardona, Carey Whitehair

专题命中 规划控制 ：trajectory planning(title)

Comments 6 pages

Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing

Liang Wang, Kezhi Wang, Cunhua Pan, Wei Xu, Nauman Aslam, Lajos Hanzo

专题命中 规划控制 ：trajectory planning(title)

Comments Accepted by IEEE Transactions on Cognitive Communications and Networking

What-If Motion Prediction for Autonomous Driving

Siddhesh Khandelwal, William Qi, Jagjeet Singh, Andrew Hartnett, Deva Ramanan

专题命中 规划控制 ：autonomous driving(title)

Comments 16 pages, 6 tables, 6 figures

Possibility of Land Movement Prediction for Creep or before Earthquake Using Lidar Geodetic Data in a Machine Learning Scheme

M. Kiani

专题命中 规划控制 ：LiDAR(title)

Online Verification Concept for Autonomous Vehicles -- Illustrative Study for a Trajectory Planning Module

Tim Stahl, Matthis Eicher, Johannes Betz, Frank Diermeyer

专题命中 规划控制 ：trajectory planning(title)

Comments Accepted at The 23rd IEEE International Conference on Intelligent Transportation Systems, September 20 - 23, 2020

Trajectory Planning and Control for Automatic Docking of ASVs with Full-Scale Experiments

Glenn Bitar, Andreas B. Martinsen, Anastasios M. Lekkas, Morten Breivik

专题命中 规划控制 ：trajectory planning(title)

Comments 12 pages, 7 figures. Accepted to the IFAC World Congress 2020

Predicting Model Failure using Saliency Maps in Autonomous Driving Systems

Sina Mohseni, Akshay Jagadeesh, Zhangyang Wang

专题命中 规划控制 ：autonomous driving(title)

Comments Presented at ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning

Speed trajectory planning at signalized intersections using sequential convex optimization

Xianan Huang, Huei Peng

专题命中 规划控制 ：trajectory planning(title)

Comments 2017 American Control Conference, May 24-26, Seattle, WA, USA

Analytic Model of Variable Characteristic of Coefficient of Restitution and Its Application to Soccer Ball Trajectory Planning

Hwan-Taek Ryu, Byung-Ju Yi, Younghun Kwon

专题命中 规划控制 ：trajectory planning(title)

Inexact trajectory planning and inverse problems in the Hamilton--Pontryagin framework

Christopher L. Burnett, Darryl D. Holm, David M. Meier

专题命中 规划控制 ：trajectory planning(title)

Comments 32 pages, 3 figures, comments welcome!

Robot-Body-Aware Traversal Risk Graph Planning for Wheeled-Legged Robots in Complex Terrain

面向复杂地形中轮腿式机器人的机器人本体感知遍历风险图规划

Zhiqiao Guo, Bichi Zhang, Sören Schwertfeger

机构 * ShanghaiTech University（上海科技大学） ； Key Laboratory of Intelligent Perception and Human-Machine Collaboration（智能感知与人机协同重点实验室） 纠错

专题命中 规划控制 ：LiDAR(abstract,abstract_cn)；分类 cs.RO

AI总结 该研究针对轮腿式机器人复杂地形导航的TRG规划缺陷，提出RB-TRG方法，提升了导航成功率，获IEEE ICRA 2026挑战赛奖项，代码已开源。

Marker-Constrained Pose-Graph Correction for Cross-Platform Georeferencing in GNSS-Denied Environments

GNSS拒止环境下跨平台地理配准的标记约束位姿图校正

Marco Giberna, Jose Luis Sanchez Lopez, Holger Voos

机构 * University of Luxembourg（卢森堡大学） ； Interdisciplinary Centre for Security, Reliability and Trust (SnT)（安全、可靠性与信任跨学科中心（SnT）） ； Faculty of Science, Technology and Medicine, University of Luxembourg（卢森堡大学科学、技术与医学院） 纠错

专题命中 规划控制 ：LiDAR(abstract,abstract_cn)；分类 cs.RO

AI总结 该研究提出基于胆固醇球形反射器伪装标记的框架，通过标记约束位姿图优化实现 GNSS 拒止环境下跨平台地理配准，大幅降低轨迹漂移，提升重建一致性。

Comments 14 pages, 5 figures, 5 tables, submitted to SPIE Security + Defence conference

G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance

G2DP: 基于时空网格引导的扩散规划

Hang Yu, Ye Jin, Alessandro Canevaro, Julian Schmidt, Julian Jordan, Peizheng Li, Marc Kaufeld, Silvan Lindner, Johannes Betz, Wilhelm Stork

机构 * Mercedes-Benz AG（梅赛德斯-奔驰集团） ； Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院） ； TU Munich（慕尼黑工业大学） ； University of Tübingen（图宾根大学） 纠错

专题命中 规划控制 ：autonomous driving(abstract)；occupancy(abstract)；分类 cs.RO

AI总结 针对自动驾驶扩散规划器随机性导致的安全与路线保持问题，提出G2DP，通过可微时空代价体积在去噪过程中注入密集梯度，实现无碰撞与路径最优的轨迹生成，在nuPlan等基准上取得最优性能。

Comments 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)

Unifying Decision-Making and Trajectory-Planning in Unsignalized Intersections Using Time-Varying Potential Fields

使用时变势场统一无信号交叉口自动驾驶车辆的决策与轨迹规划

David Costa, Francesco Cerrito, Massimo Canale, Carlo Novara

机构 * Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino（电子工程与电信学院，托斯卡纳理工学院） ； Dipartimento di Automatica e Informatica, Politecnico di Torino（自动化与信息学院，托斯卡纳理工学院） 纠错

专题命中 规划控制 ：occupancy(abstract)；trajectory planning(abstract)；分类 cs.RO

AI总结 针对无信号交叉口自动驾驶车辆，提出用有限时域最优控制问题结合时变人工势场的新框架统一决策与轨迹规划，利用短视运动预测等考虑潜在碰撞，仿真验证了该方法可生成可行安全参考轨迹。

Comments Published in the "2026 34th Mediterranean Conference on Control and Automation (MED)". v2 adds the final IEEE citation and DOI; technical content unchanged

Journal ref 2026 34th Mediterranean Conference on Control and Automation (MED), Ancona, Italy, 2026, pp. 251-256

VideoGAN-based Trajectory Proposal for Automated Vehicles

基于VideoGAN的自动车辆轨迹提案

Annajoyce Mariani, Kira Maag, Hanno Gottschalk

机构 * Technical University of Berlin（柏林技术大学） ； Heinrich-Heine-University（海因里希-海涅大学） 纠错

专题命中 规划控制 ：BEV(abstract)；occupancy(abstract)；分类 cs.CV

AI总结 本文提出基于VideoGAN的自动车辆轨迹生成方法，利用BEV视频训练生成对抗网络，以提高轨迹生成的准确性和现实感。

Synthetic-to-Real Translation for Class-Agnostic Motion Prediction

用于类别无关运动预测的合成到真实翻译

Yizheng Wu, Hongwei Fan, Kewei Wang, Ruibo Li, Xingyi Li, Xiao Song, Zhe Wang, Chenjing Ding, Dongliang Wang, Zhiguo Cao, Guosheng Lin

机构 * Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（图像处理与智能控制教育部重点实验室，华中科技大学人工智能与自动化学院） ； Nanyang Technological University（南洋理工大学） ； SenseAuto（未知（保留英文）） 纠错

专题命中 规划控制 ：autonomous driving(abstract)；LiDAR(abstract)；分类 cs.CV

AI总结 研究针对运动预测中合成到真实翻译的问题，提出将运动知识翻译框架与目标感知运动预测、目标辅助运动增强两个组件集成的方法，还生成了Motion4D数据集，实验证明该方法有效弥合域差距，在真实场景表现优异。

Motion Planning in Dynamic Environments: A Survey from Classical to Modern Methods

动态环境中的运动规划：从经典到现代方法的综述

Zongyuan Shen, Yaming Ou, Shalabh Gupta, Shancheng Zhao, Dehua Zhou, Gao Wang, Zhongqiang Ren, Junfeng Fan, Long Cheng

机构 * College of Information Science and Technology, Jinan University（济南大学信息科学与技术学院） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； Department of Electrical and Computer Engineering, University of Connecticut（康奈尔大学电子与计算机工程系） ； Global College, Shanghai Jiao Tong University（上海交通大学全球学院） ； Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所） 纠错

专题命中 规划控制 ：LiDAR(abstract,abstract_cn)；分类 cs.RO

AI总结 本文综述了138篇文献，将动态环境中的运动规划方法分为采样、图搜索、模型预测控制、学习及经典局部规划五类，分析了各方法的原理、优缺点及动态环境特有挑战。

Neural Distance-Guided Path Integral Control for Tractor-Trailer Navigation

神经距离引导的路径积分控制用于拖拉机-挂车导航

Peng Wei, Chen Peng, Stavros Vougioukas

机构 * Department of Biological and Agricultural Engineering, University of California Davis（加州大学戴维斯分校生物与农业工程系） ； ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University（浙江大学杭州全球科技创新中心） 纠错

专题命中 规划控制 ：LiDAR(abstract,abstract_cn)；分类 cs.RO

AI总结 本文提出基于几何神经编码器的路径积分控制器，用于实现拖拉机-挂车在复杂农业环境中的安全导航，通过实时距离估计提升动态可行性。

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

DriveLaW：在潜在驾驶世界中统一规划与视频生成

Tianze Xia, Yongkang Li, Lijun Zhou, Jingfeng Yao, Kaixin Xiong, Haiyang Sun, Bing Wang, Kun Ma, Guang Chen, Hangjun Ye, Wenyu Liu, Xinggang Wang

机构 * Huazhong University of Science and Technology（华中科技大学） ； Xiaomi EV（小米电动车） 纠错

专题命中 规划控制 ：autonomous driving(abstract)；trajectory planning(abstract)；分类 cs.CV

AI总结 DriveLaW通过统一视频生成与运动规划，提升自动驾驶中的预测与规划性能，实现视频生成与轨迹规划的一致性，取得新的state-of-the-art结果。

Comments 18 pages, 6 figures, CVPR 2026

K-Gen: A Multimodal Language-Conditioned Approach for Interpretable Keypoint-Guided Trajectory Generation

K-Gen：一种多模态语言条件方法用于可解释的关键点引导轨迹生成

Mingxuan Mu, Guo Yang, Lei Chen, Ping Wu, Jianxun Cui

机构 * Harbin Institute of Technology Chongqing Research Inst. of HIT（哈尔滨工业大学重庆研究院） ； Changan Automobile Co., Ltd Chongqing, China（长安汽车有限公司重庆） 纠错

专题命中 规划控制 ：autonomous driving(abstract)；BEV(abstract)；分类 cs.AI

AI总结 K-Gen通过多模态语言模型结合关键点引导方法，提升自动驾驶轨迹生成的可解释性和准确性。