自动驾驶

An NCAP-like Safety Indicator for Self-Driving Cars

Jimy Cai Huang, Hanna Kurniawati

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

Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss

Ross Greer, Nachiket Deo, Mohan Trivedi

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

Comments 8 pages, 18 figures

Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation

Kaouther Messaoud, Nachiket Deo, Mohan M. Trivedi, Fawzi Nashashibi

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

Comments Revised submission for RA-L

Deep Learning-based Vehicle Behaviour Prediction For Autonomous Driving Applications: A Review

Sajjad Mozaffari, Omar Y. Al-Jarrah, Mehrdad Dianati, Paul Jennings, Alexandros Mouzakitis

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

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving

Jiachen Li, Wei Zhan, Yeping Hu, Masayoshi Tomizuka

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

Comments IEEE Transactions on Intelligent Transportation Systems

See, Attend and Brake: An Attention-based Saliency Map Prediction Model for End-to-End Driving

Ekrem Aksoy, Ahmet Yazıcı, Mahmut Kasap

专题命中 规划控制 ：end-to-end driving(title)；分类 cs.CV、eess.IV

VisionNet: A Drivable-space-based Interactive Motion Prediction Network for Autonomous Driving

Yanliang Zhu, Deheng Qian, Dongchun Ren, Huaxia Xia

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

Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars

Ana I. Maqueda, Antonio Loquercio, Guillermo Gallego, Narciso Garcia, Davide Scaramuzza

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

Comments 9 pages, 8 figures, 6 tables. Video: https://youtu.be/_r_bsjkJTHA

Journal ref IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, 2018

Risk-averse Behavior Planning for Autonomous Driving under Uncertainty

Mohammad Naghshvar, Ahmed K. Sadek, Auke J. Wiggers

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

Comments 7 pages, accepted to NeurIPS 2018 Workshop on Machine Learning for Intelligent Transportation Systems (MLITS)

Improving Motion Forecasting for Autonomous Driving with the Cycle Consistency Loss

Titas Chakraborty, Akshay Bhagat, Henggang Cui

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

Comments Accepted at NeurIPS 2022 Machine Learning for Autonomous Driving Workshop

MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving

Stepan Konev, Kirill Brodt, Artsiom Sanakoyeu

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

Comments CVPR Workshop on Autonomous Driving 2021. Waymo Motion Prediction Challenge 2021

Optimal Trajectory Planning for Cinematography with Multiple Unmanned Aerial Vehicles

Alfonso Alcántara, Jesús Capitán, Rita Cunha, Aníbal Ollero

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

Comments This paper has been published as: Optimal trajectory planning for cinematography with multiple Unmanned Aerial Vehicles. Alfonso Alcantara and Jesus Capitan and Rita Cunha and Anibal Ollero. Robotics and Autonomous Systems. 103778 (2021) 10.1016/j.robot.2021.103778

Journal ref Robotics and Autonomous Systems. 103778 (2021)

Joint Interaction and Trajectory Prediction for Autonomous Driving using Graph Neural Networks

Donsuk Lee, Yiming Gu, Jerrick Hoang, Micol Marchetti-Bowick

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

Comments Accepted in Machine Learning for Autonomous Driving NeurIPS 2019 Workshop

Vision and Language: Novel Representations and Artificial intelligence for Driving Scene Safety Assessment and Autonomous Vehicle Planning

视觉与语言：新颖的表示方法和人工智能用于驾驶场景安全评估与自动驾驶规划

Ross Greer, Maitrayee Keskar, Angel Martinez-Sanchez, Parthib Roy, Shashank Shriram, Mohan Trivedi

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

AI总结 本文研究了视觉-语言表示在自动驾驶安全评估和规划中的应用，提出轻量级危险检测、轨迹规划框架整合及自然语言约束方法，强调表示-任务对齐的重要性。

DriveMRP: Enhancing Vision-Language Models with Synthetic Motion Data for Motion Risk Prediction

Zhiyi Hou, Enhui Ma, Fang Li, Zhiyi Lai, Kalok Ho, Zhanqian Wu, Lijun Zhou, Long Chen, Chitian Sun, Haiyang Sun, Bing Wang, Guang Chen, Hangjun Ye, Kaicheng Yu

机构 * Westlake University（西湖大学） ； Xiaomi EV（小米汽车） ； Zhejiang University（浙江大学） 纠错

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

Comments 12 pages, 4 figures. Code available at https://github.com/hzy138/DriveMRP

GPD-1: Generative Pre-training for Driving

Zixun Xie, Sicheng Zuo, Wenzhao Zheng, Yunpeng Zhang, Dalong Du, Jie Zhou, Jiwen Lu, Shanghang Zhang

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

Comments Code is available at: https://github.com/wzzheng/GPD

Neural Fields in Robotics: A Survey

Muhammad Zubair Irshad, Mauro Comi, Yen-Chen Lin, Nick Heppert, Abhinav Valada, Rares Ambrus, Zsolt Kira, Jonathan Tremblay

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

Comments 20 pages, 20 figures. Project Page: https://robonerf.github.io

Efficient Perception, Planning, and Control Algorithm for Vision-Based Automated Vehicles

Der-Hau Lee

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

Comments 14 figures, 14 pages

Journal ref Applied Intelligence (2024)

Automatic driving lane change safety prediction model based on LSTM

Wenjian Sun, Linying Pan, Jingyu Xu, Weixiang Wan, Yong Wang

专题命中 规划控制 ：autonomous driving(abstract)；trajectory planning(abstract)；分类 cs.RO、eess.IV、cs.AI

VTGNet: A Vision-based Trajectory Generation Network for Autonomous Vehicles in Urban Environments

Peide Cai, Yuxiang Sun, Hengli Wang, Ming Liu

专题命中 规划控制 ：autonomous driving(abstract)；end-to-end driving(abstract)；分类 cs.RO、cs.CV、eess.IV

Comments 11 pages, 14 figures, and 4 tables. The paper is accepted by IEEE Transactions on Intelligent Vehicles (T-IV), 2020

CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception

Sibo Zhang, Yuexin Ma, Ruigang Yang

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

Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations

Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun

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

Comments European Conference on Computer Vision (ECCV) 2020

OpenSCvx: An Open-Source Modular and Extensible Nonlinear Trajectory Planning Package

OpenSCvx：开源模块化可扩展非线性轨迹规划包

Christopher R. Hayner, Griffin J. Norris, Fabio Spada, Samet Uzun, Avi Mittal, Behcet Acıkmese, Karen Leung

机构 * University of Washington（华盛顿大学） ； General Robotics（通用机器人公司） ； University of California, Berkeley（加州大学伯克利分校） ； Zoox（Zoox公司） 纠错

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

AI总结 该研究介绍开源Python框架OpenSCvx，它通过符号建模接口简化轨迹优化问题的构建与求解，支持连续时间约束等功能，助力快速开发与扩展轨迹优化方法。

Hybrid Reinforcement Learning and Search for Flight Trajectory Planning

混合强化学习与搜索的飞行轨迹规划

Alberto Luise, Michele Lombardi

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

AI总结 本文提出一种混合强化学习与搜索的方法，用于快速优化民航飞行路径，通过预计算近优路径减少求解空间，提升计算效率并保持燃油消耗相近。

Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires

基于问卷的 Clearance 约束下的个性化自动驾驶最优控制

Yongjae Lim, Dabin Kim, H. Jin Kim

机构 * Department of Mechanical Engineering, Seoul National University（机械工程系，首尔国立大学） ； Department of Aerospace Engineering, Seoul National University（航空航天工程系，首尔国立大学） 纠错

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

AI总结 本文提出基于用户问卷的个性化自动驾驶规划框架，通过将用户偏好作为约束条件，改进自动驾驶中的安全距离控制。

Entanglement-Free Trajectory Planning for Tethered Mobile Robots with a Slack Tether

带松弛系绳的系绳移动机器人的无纠缠轨迹规划

Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter

机构 * Delft University of Technology（代尔夫特理工大学） ； Delft Center for Systems and Control（代尔夫特系统与控制中心） 纠错

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

AI总结 本研究针对带松弛系绳的移动机器人，提出一种含三步流程的运动规划算法，可生成动态可行的无纠缠轨迹，经仿真验证能实现更安全可靠的导航。

Comments 19 pages, 13 figures

Agentic self-driving microscopy benchmarks support qualification but do not necessarily generalize to unseen tasks

智能体自动驾驶显微镜基准测试支持性能验证，但不一定能泛化到未见任务

Nathan S Johnson, Ian Abshire

机构 * Carl Zeiss Research Microscopy Solutions（卡尔蔡司研究显微镜解决方案） 纠错

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

AI总结 本研究开发基准框架评估显微镜智能体架构等因素的性能，发现其虽可用于验证比较，但现有基准无法预测智能体在未见显微镜任务上的表现。

Comments 20 pages, 8 figures

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition

通过扩散合成在多样场景中进行快速且安全的轨迹规划

Wule Mao, Zhouheng Li, Yunhao Luo, Fangguo Zhao, Lei Xie

机构 * College of Control Science and Engineering, Zhejiang University（浙江大学控制科学与工程学院） ； University of Michigan（密歇根大学） ； MIT（麻省理工学院） 纠错

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

AI总结 针对动态环境规划难题，提出能量参数化扩散规划框架，结合轻量级安全过滤器和场景无关的数据生成管道，实现多样场景下快速安全规划，仿真与真实实验验证了其有效性、鲁棒性和适用性。

Learning High-Level Decision Making with an Interaction-Aware Attention-Based Network in Autonomous Driving

在自动驾驶中使用基于交互感知注意力的网络学习高级决策

Marcelo Contreras, Willi Poh, Christoph Stiller, Ehsan Hashemi

机构 * NODE lab, University of Alberta（节点实验室，阿尔伯塔大学） ； MRT Institute, Karlsruhe Institute of Technology（MRT 研究所，卡尔斯鲁厄理工学院） 纠错

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

AI总结 研究自动驾驶中高级决策问题，提出DecisionPerceiver将动态代理特征投影到固定大小潜在空间，通过潜在查询数调节特征粒度，还细化动作集，经多场景评估有性能提升、泛化能力及可扩展性。

Comments 6 pages, 5 figures, 3 tables, submitted to 2026 IEEE Intelligent Transportation Systems Conference (ITSC)

Multimodal Scenario Similarity Search for Autonomous Driving

用于自动驾驶的多模态场景相似性搜索

Tamás Matuszka, András Tamásy, Balázs Szolár

机构 * aiMotive（爱莫提夫） 纠错

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

AI总结 研究自动驾驶场景相似性搜索，提出多模态框架结合视觉与轨迹表示，对比两种基于轨迹的方法与视觉基线，实验表明轨迹表示在运动事件中性能强，视觉嵌入在外观线索丰富时出色，结合二者可提升检索质量。