自动驾驶

Optimal Vehicle Trajectory Planning for Static Obstacle Avoidance using Nonlinear Optimization

Yajia Zhang, Hongyi Sun, Ruizhi Chai, Daike Kang, Shan Li, Liyun Li

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

TOFG: A Unified and Fine-Grained Environment Representation in Autonomous Driving

Zihao Wen, Yifan Zhang, Xinhong Chen, Jianping Wang

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

Comments Accepted by ICRA 2023

Towards Safe, Explainable, and Regulated Autonomous Driving

Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.AI

Comments Accepted for publication in the Explainable AI for Intelligent Transportation Systems book

We Need to Talk: Identifying and Overcoming Communication-Critical Scenarios for Self-Driving

Nathaniel Moore Glaser, Zsolt Kira

专题命中 规划控制 ：self-driving(title,abstract)；trajectory planning(abstract)；分类 cs.RO

Comments Submitted to ICRA 2023 Workshop on Collaborative Perception

Experimental Validation of Safe MPC for Autonomous Driving in Uncertain Environments

Ivo Batkovic, Ankit Gupta, Mario Zanon, Paolo Falcone

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.RO

Comments 16 pages, 20 figures, accepted to IEEE Transactions on Control Systems Technology

Road Traffic Law Adaptive Decision-making for Self-Driving Vehicles

Jiaxin Liu, Wenhui Zhou, Hong Wang, Zhong Cao, Wenhao Yu, Chengxiang Zhao, Ding Zhao, Diange Yang, Jun Li

专题命中 规划控制 ：self-driving(title,abstract)；autonomous driving(abstract)；分类 cs.RO

An Ethical Trajectory Planning Algorithm for Autonomous Vehicles

Maximilian Geisslinger, Franziska Poszler, Markus Lienkamp

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

Efficient Game-Theoretic Planning with Prediction Heuristic for Socially-Compliant Autonomous Driving

Chenran Li, Tu Trinh, Letian Wang, Changliu Liu, Masayoshi Tomizuka, Wei Zhan

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

Comments IEEE Robotics and Automation Letters 2022 (RA-L with IROS option)

Real Time Motion Planning Using Constrained Iterative Linear Quadratic Regulator for On-Road Self-Driving

Changxi You

专题命中 规划控制 ：self-driving(title,abstract)；autonomous driving(abstract)；分类 cs.RO

Comments 10 pages with 10 figures and 2 tables

Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning

Zeyu Zhu, Nan Li, Ruoyu Sun, Huijing Zhao, Donghao Xu

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

Local Trajectory Planning For UAV Autonomous Landing

Yossi Magrisso, Ehud Rivlin, Hector Rotstein

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

A Survey on Deep-Learning Approaches for Vehicle Trajectory Prediction in Autonomous Driving

Jianbang Liu, Xinyu Mao, Yuqi Fang, Delong Zhu, Max Q. -H. Meng

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.RO

Comments Accepted by ROBIO2021

Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving

Xuanchi Ren, Tao Yang, Li Erran Li, Alexandre Alahi, Qifeng Chen

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

Comments Accepted to ICCV 2021

Roadside-assisted Cooperative Planning using Future Path Sharing for Autonomous Driving

Mai Hirata, Manabu Tsukada, Keisuke Okumura, Yasumasa Tamura, Hideya Ochiai, Xavier Défago

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.RO

Comments Accepted to IEEE 94th Vehicular Technology Conference (VTC2021-Fall)

DL-IAPS and PJSO: A Path/Speed Decoupled Trajectory Optimization and its Application in Autonomous Driving

Jinyun Zhou, Runxin He, Yu Wang, Shu Jiang, Zhenguang Zhu, Jiangtao Hu, Jinghao Miao, Qi Luo

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

Comments 8 pages, 11 figures

A Survey of Deep Learning Techniques for Autonomous Driving

Sorin Grigorescu, Bogdan Trasnea, Tiberiu Cocias, Gigel Macesanu

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.RO

Comments 28 pages, 7 figures. arXiv admin note: text overlap with arXiv:1709.02435, arXiv:1610.01256 by other authors

Journal ref Journal of Field Robotics, Online ISSN:1556-4967, 2019

Self-driving scale car trained by Deep reinforcement learning

Qi Zhang, Tao Du, Changzheng Tian

专题命中 规划控制 ：self-driving(title,abstract)；autonomous driving(abstract)；分类 cs.AI

Synchronous Maneuver Searching and Trajectory Planning for Autonomous Vehicles in Dynamic Traffic Environments

Lilin Qian, Xin Xu, Yujun Zeng, Xiaohui Li, Zhenping Sun, Hang Song

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

Comments This work has been accepted by IEEE Intelligent Transportation System Magazine

Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks

Marcel Schreiber, Stefan Hoermann, Klaus Dietmayer

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

Comments 8 pages, 10 figures

GridSim: A Vehicle Kinematics Engine for Deep Neuroevolutionary Control in Autonomous Driving

Bogdan Trasnea, Andrei Vasilcoi, Claudiu Pozna, Sorin Grigorescu

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

Journal ref Int. Conf. on Robotic Computing IRC 2019, Naples, Italy, February 25-27, 2019

Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving

Xi Xiong, Jianqiang Wang, Fang Zhang, Keqiang Li

专题命中 规划控制 ：autonomous driving(title,abstract)；self-driving(abstract)；分类 cs.RO

Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving

Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua

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

Planning-aligned Token Compression for Long-Context Autonomous Driving

面向长上下文自动驾驶的规划对齐令牌压缩

Zhixuan Liang, Yuxiao Chen, Yurong You, Peter Karkus, Wenhao Ding, Boyi Li, Alexander Popov, Yan Wang, Maximilian Igl, Yiming Li, Danfei Xu, Nikolai Smolyanskiy, Boris Ivanovic, Ping Luo, Marco Pavone

机构 * NVIDIA Research（NVIDIA研究） ； School of Computing and Data Science, The University of Hong Kong（计算与数据科学学院，香港大学） 纠错

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

AI总结 提出COMPACT-VA框架，基于条件VQ-VAE将长上下文压缩为有界表示，通过规划对齐实现决策关键信息保留，在动态场景中成功率提升超6%，速度提升3.3倍。

Comments 9 pages

Using Uncertainty Data in Chance-Constrained Trajectory Planning

在机会约束下利用不确定性数据进行轨迹规划

Vasileios Lefkopoulos, Maryam Kamgarpour

专题命中 规划控制 ：trajectory planning(title,abstract)；autonomous driving(abstract)

AI总结 本文研究了在存在不确定位置障碍物的环境中进行轨迹规划问题，提出了一种在线学习分布矩的方法，并通过紧致的混合整数凸改写方法得到可行解，应用于自动驾驶领域。

Journal ref 2019 18th European Control Conference (ECC)

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving

VECTOR-Drive: 紧密耦合的视觉-语言与轨迹专家路由用于端到端自动驾驶

Rui Zhao, Jianlin Yu, Zhenhai Gao, Jiaqiao Liu, Fei Gao

机构 * College of Automotive Engineering, Jilin University（吉林大学汽车工程学院） ； The National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University（吉林大学汽车底盘集成与生物力学国家级重点实验室） ； ReeFocus AI Technology（ReeFocus人工智能技术） 纠错

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

AI总结 本文提出VECTOR-DRIVE框架，通过紧密耦合的视觉-语言与轨迹专家路由，解决端到端自动驾驶中视觉语言理解和轨迹预测之间的耦合问题，实现更高的任务性能。

Spatial-temporal risk field-based coupled dynamic-static driving risk assessment and trajectory planning in weaving segments

基于空间-时间风险场的耦合动态-静态驾驶风险评估与交织段轨迹规划

Guodong Ma, Baofeng Sun, Hongchao Liang, Wenyu Yang, Huxing Zhou

专题命中 规划控制 ：trajectory planning(title,abstract)；occupancy(abstract)

AI总结 本文提出空间-时间耦合风险评估方法，通过构建三维空间-时间风险场（STRF）量化动态障碍物未来轨迹影响，结合专用几何配置区域约束车辆方向，利用真实世界航拍数据校准参数提升准确性，并设计基于STRF的CAV轨迹规划方法，优化路径和速度以提高安全性和效率。

KnowVal: A Knowledge-Augmented and Value-Guided Autonomous Driving System

KnowVal: 一种知识增强且价值引导的自动驾驶系统

Zhongyu Xia, Wenhao Chen, Yongtao Wang, Ming-Hsuan Yang

机构 * Wangxuan Institute of Computer Technology, Peking University（北京大学王学苑计算机技术研究所） ； University of California, Merced（加州大学默塞德分校） 纠错

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

AI总结 KnowVal通过整合开放世界感知与知识检索，构建驾驶知识图谱并训练价值模型，实现价值对齐的自动驾驶系统，提升了规划性能并降低了碰撞率。

Comments Accepted to CVPR 2026

TaPD: Temporal-adaptive Progressive Distillation for Observation-Adaptive Trajectory Forecasting in Autonomous Driving

TaPD: 基于时间自适应的渐进蒸馏用于自动驾驶中的观测自适应轨迹预测

Mingyu Fan, Yi Liu, Hao Zhou, Deheng Qian, Mohammad Haziq Khan, Matthias Raetsch

机构 * College of Information and Intelligent Science, Donghua University（信息与智能科学学院，东华大学） ； School of Computing and Information Technology, Great Bay Institute for Advanced Study/Great Bay University（计算与信息技术学院，大澳研究院/大澳大学） ； Chongqing Chang’an Technology Co., Ltd（重庆长安科技有限公司） ； ViSiR, Reutlingen University（ViSiR，鲁特大学） 纠错

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

AI总结 TaPD通过时间自适应渐进蒸馏方法，实现观测自适应的轨迹预测，提升短历史观测下的预测性能。

WAM-Diff: A Masked Diffusion VLA Framework with MoE and Online Reinforcement Learning for Autonomous Driving

WAM-Diff: 一种结合MoE和在线强化学习的掩码扩散VLA框架用于自动驾驶

Mingwang Xu, Jiahao Cui, Feipeng Cai, Hanlin Shang, Zhihao Zhu, Shan Luan, Yifang Xu, Neng Zhang, Yaoyi Li, Jia Cai, Siyu Zhu

机构 * Fudan University（复旦大学） ； Yinwang Intelligent Technology Co., Ltd（云网智能科技有限公司） 纠错

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

AI总结 WAM-Diff通过结合MoE和在线强化学习的掩码扩散框架，提升自动驾驶轨迹生成的性能与灵活性。

DeeAD: Dynamic Early Exit of Vision-Language Action for Efficient Autonomous Driving

DeeAD: 视觉-语言动作的动态早期退出以实现高效的自动驾驶

Haibo HU, Lianming Huang, Nan Guan, Chun Jason Xue

机构 * City University of Hongkong（香港城市大学） ； Mohamed bin Zayed University of Artificial Intelligence（马尔代夫 bin Zayed 人工智能大学） 纠错

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

AI总结 DeeAD通过动态早期退出机制提升自动驾驶中视觉-语言动作模型的效率，实现28%的变换器层稀疏性和29%的延迟减少，同时保持规划质量和安全。