自动驾驶

Diffusion Forcing Planner: History-Annealed Planning with Time-Dependent Guidance for Autonomous Driving

扩散强制规划器：基于时间依赖引导的历史退火规划用于自动驾驶

Zehan Zhang, Neng Zhang, Yaoyi Li, Jia Cai, Zhiling Wang

机构 * University of Science and Technology of China（中国科学技术大学） ； Yinwang Intelligent Technology Co., Ltd（银网智能科技有限公司） ； Hefei Institutes of Physical Science, Chinese Academy of Sciences（中国科学院合肥物质科学研究院） 纠错

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

AI总结 提出扩散强制规划器（DFP），通过历史引导控制实现异构联合扩散过程，结合退火历史的条件引导，解决运动规划中的时间不一致问题，在nuPlan上取得竞争性能。

Comments CVPR2026

Uncertainty-Aware Motion Planning for Autonomous Driving in Mixed Traffic Environment

混合交通环境下自动驾驶的不确定性感知运动规划

Ming Cheng, Hao Chen, Ziyi Yang, Ziluowen Luo, Senzhang Wang

机构 * Central South University（中南大学） ； City University of Macau（澳门城市大学） 纠错

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

AI总结 提出不确定性感知运动规划（UAMP），通过量化人类意图不确定性并引入不确定性校准值学习，提升自动驾驶在混合交通中的安全性和舒适性。

A message-passing algorithm for multi-agent trajectory planning

多智能体轨迹规划的消息传递算法

Jose Bento, Nate Derbinsky, Javier Alonso-Mora, Jonathan Yedidia

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

AI总结 本文提出基于改进交替方向乘子法的新型算法，用于计算多智能体的无碰撞全局轨迹，具有自然并行化和易整合不同成本函数的优点。

Comments In Advances in Neural Information Processing Systems (NIPS), 2013. Demo video available at http://www.youtube.com/watch?v=yuGCkVT8Bew

Temporally Decoupled Diffusion Planning for Autonomous Driving

时间解耦的扩散规划用于自动驾驶

Xiang Li, Bikun Wang, John Zhang, Jianjun Wang

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

AI总结 本文提出时间解耦扩散模型(TDDM)，通过噪声掩码方法解决动态城市环境中即时安全与长期目标的平衡问题，改进轨迹生成并提升复杂场景下的规划性能。

Comments icaps

DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving

DynVLA：为自动驾驶中的动作推理学习世界动态

Shuyao Shang, Bing Zhan, Yunfei Yan, Yuqi Wang, Yingyan Li, Yasong An, Xiaoman Wang, Jierui Liu, Lu Hou, Lue Fan, Zhaoxiang Zhang, Tieniu Tan

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.CV

AI总结 DynVLA提出一种新的Coot方法Dynamics CoT，通过预测紧凑世界动态来提升决策质量，实验表明其优于Textual CoT和Visual CoT。

Comments 18 pages, 10 figures. Project Page: https://yaoyao-jpg.github.io/dynvla

GIANT - Global Path Integration and Attentive Graph Networks for Multi-Agent Trajectory Planning

GIANT - 全局路径整合与注意力图网络用于多智能体轨迹规划

Jonas le Fevre Sejersen, Toyotaro Suzumura, Erdal Kayacan

机构 * Artificial Intelligence in Robotics Laboratory (AiR Lab), Department of Electrical and Computer Engineering, Aarhus University（人工智能机器人实验室（AiR实验室），电气与计算机工程系，奥胡斯大学） ； Foundation Models for Artificial Intelligence group, Department of Information and Communication Engineering, Tokyo University（人工智能基础模型组，信息与通信工程系，东京大学） ； Automatic Control Group, Department of Electrical Engineering and Information Technology, Paderborn University（自动控制组，电气工程与信息科技系，波德恩大学） 纠错

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

AI总结 GIANT通过结合全局路径规划与注意力图网络，提升多智能体在复杂动态环境中的避障与导航性能。

Comments Published in: 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

FlowDrive: moderated flow matching with data balancing for trajectory planning

FlowDrive: 带数据平衡的流量匹配用于轨迹规划

Lingguang Wang, Ömer Şahin Taş, Marlon Steiner, Christoph Stiller

机构 * Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院） ； FZI Research Center for Information Technology（弗劳恩霍夫信息技术研究中心） 纠错

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

AI总结 FlowDrive通过数据平衡和流量匹配技术，提升轨迹规划在稀有场景下的性能，实现最先进的规划效果。

GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language Models

GPT-4增强的多模态接地用于自动驾驶：利用跨模态注意力与大语言模型

Haicheng Liao, Huanming Shen, Zhenning Li, Chengyue Wang, Guofa Li, Yiming Bie, Chengzhong Xu

机构 * Univ City（大学城市） 纠错

专题命中 规划控制 ：autonomous driving(title)；分类 cs.CV、cs.AI

AI总结 本文提出了一种结合GPT-4的大语言模型的多模态接地框架，用于提升自动驾驶中的视觉理解和指令执行能力。

Journal ref Communications in Transportation Research 4 (2024) 100116

Are LLMs The Way Forward? A Case Study on LLM-Guided Reinforcement Learning for Decentralized Autonomous Driving

Timur Anvar, Jeffrey Chen, Yuyan Wang, Rohan Chandra

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Zero-Shot Trajectory Planning for Signal Temporal Logic Tasks

Ruijia Liu, Ancheng Hou, Xiao Yu, Xiang Yin

机构 * Department of Automation（自动化系） ； Shanghai Jiao Tong University（上海交通大学） ； Institute of Artificial Intelligence（人工智能研究院） ； Xiamen University（厦门大学） 纠错

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

Decision Transformer-Based Drone Trajectory Planning with Dynamic Safety-Efficiency Trade-Offs

Chang-Hun Ji, SiWoon Song, Youn-Hee Han, SungTae Moon

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

Comments Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2025. Copyright 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses

Advanced Longitudinal Control and Collision Avoidance for High-Risk Edge Cases in Autonomous Driving

Dianwei Chen, Yaobang Gong, Xianfeng Yang

机构 * Department of Civil and Environmental Engineering, University of Maryland（大学工程学院） 纠错

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Next-Best-Trajectory Planning of Robot Manipulators for Effective Observation and Exploration

Heiko Renz, Maximilian Krämer, Frank Hoffmann, Torsten Bertram

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.CV

Comments Accepted for publication at the IEEE International Conference on Robotics and Automation (ICRA), 2025

Resilient UAV Trajectory Planning via Few-Shot Meta-Offline Reinforcement Learning

Eslam Eldeeb, Hirley Alves

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

doScenes: An Autonomous Driving Dataset with Natural Language Instruction for Human Interaction and Vision-Language Navigation

Parthib Roy, Srinivasa Perisetla, Shashank Shriram, Harsha Krishnaswamy, Aryan Keskar, Ross Greer

专题命中 规划控制 ：autonomous driving(title)；分类 cs.CV、cs.AI

PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning

Fangze Lin, Ying He, Fei Yu

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comments IROS 2024 Accepted

Solution Concepts in Hierarchical Games under Bounded Rationality with Applications to Autonomous Driving

Atrisha Sarkar, Krzysztof Czarnecki

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comments Behavioral Game Theory, Motion and Path Planning, Simulating Humans

Journal ref Proceedings of the AAAI Conference on Artificial Intelligence, 35(6), 5698-5708 (2021)

Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation

Yuchun Wang, Cheng Gong, Jianwei Gong, Peng Jia

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Journal ref Journal of Field Robotics,2024,1-22

Boosting Offline Reinforcement Learning for Autonomous Driving with Hierarchical Latent Skills

Zenan Li, Fan Nie, Qiao Sun, Fang Da, Hang Zhao

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving

Jayabrata Chowdhury, Vishruth Veerendranath, Suresh Sundaram, Narasimhan Sundararajan

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comparison of Pedestrian Prediction Models from Trajectory and Appearance Data for Autonomous Driving

Anthony Knittel, Morris Antonello, John Redford, Subramanian Ramamoorthy

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.CV

Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

Siyu Teng, Xuemin Hu, Peng Deng, Bai Li, Yuchen Li, Dongsheng Yang, Yunfeng Ai, Lingxi Li, Zhe Xuanyuan, Fenghua Zhu, Long Chen

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comments 21 pages, 15 figures and 5 tables, in IEEE Transactions on Intelligent Vehicles

MAVERIC: A Data-Driven Approach to Personalized Autonomous Driving

Mariah L. Schrum, Emily Sumner, Matthew C. Gombolay, Andrew Best

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

Zihao Sheng, Yunwen Xu, Shibei Xue, Dewei Li

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comments 11 pages, 9 figures, 8 tables, submitted to IEEE Trans. Intelligent Transportation Systems

Journal ref IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 17654-17665, 2022

A Learning-Based Trajectory Planning of Multiple UAVs for AoI Minimization in IoT Networks

Eslam Eldeeb, Dian Echevarría Pérez, Jean Michel de Souza Sant'Ana, Mohammad Shehab, Nurul Huda Mahmood, Hirley Alves, Matti Latva-aho

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

Journal ref 2022 Joint EuCNC/6G Summit, 2022, pp. 172-177

S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous Driving

Weihuang Chen, Fangfang Wang, Hongbin Sun

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.CV

Comments Accepted by ACML2021

Safer Autonomous Driving in a Stochastic, Partially-Observable Environment by Hierarchical Contingency Planning

Ugo Lecerf, Christelle Yemdji-Tchassi, Pietro Michiardi

专题命中 规划控制 ：autonomous driving(title)；分类 cs.RO、cs.AI

Comments To appear in Generalizable Policy Learning in the Physical World workshop (ICLR 2022)

Enhanced Behavioral Cloning with Environmental Losses for Self-Driving Vehicles

Nelson Fernandez Pinto, Thomas Gilles

专题命中 规划控制 ：self-driving(title)；分类 cs.RO、cs.AI

Real-Time Optimal Trajectory Planning for Autonomous Vehicles and Lap Time Simulation Using Machine Learning

Sam Garlick, Andrew Bradley

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.AI

Real-World Application of Various Trajectory Planning Algorithms on MIT RACECAR

Oguzhan Kose

专题命中 规划控制 ：trajectory planning(title)；分类 cs.RO、cs.CV