多模态信息融合 - arXivDaily 专题

2606.28274 2026-06-29 cs.LG cs.AI 新提交 50%

Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration

参数高效混合Transformer（PEHT）用于通过动态城市拥堵整合进行网络流量预测

Abdolazim Rezaei, Mehdi Sookhak, Mahboobeh Haghparast

机构 * National Science Foundation（国家科学基金会）； U.S. Department of Transportation（美国交通部）； University Transportation Center (UTC)（大学交通中心）； Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE)（交通网络安全高级研究与教育中心）； NVIDIA Academic Grant Program（NVIDIA学术资助计划）

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

AI总结提出参数高效混合Transformer（PEHT），通过低秩适应和多模态融合整合城市移动性与拥堵信息，在减少参数的同时提升网络流量预测精度。

2606.09532 2026-06-09 cs.CY cs.CL 新提交 50%

Interpretable Crisis Behavior Analysis Using Mobility and Social Media Data

基于移动性和社交媒体数据的可解释危机行为分析

Muhammad Hamza Arshad Majeed, Sidahmed Benabderrahmane, Talal Rahwan

机构 * New York University (NYUAD)（纽约大学（NYUAD））

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

AI总结提出统一可解释流水线，融合移动性和社交媒体数据，通过形式概念分析和关联规则挖掘，识别危机中跨域行为模式，并在洛杉矶山火和COVID-19案例中验证，生成可操作的政策简报。

1809.01271 2026-06-04 eess.SY cs.SY math.OC 50%

A Framework for Robust Assimilation of Potentially Malign Third-Party Data, and its Statistical Meaning

一种用于稳健融合可能有害第三方数据的框架及其统计意义

Matthew A. Wright, Roberto Horowitz

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

AI总结本文提出了一种基于模型的数据融合方法，结合假设检验组件来拒绝可能有故障或有害的数据。该框架基于经典粒子滤波算法的扩展，用于实时估计具有非线性动态和部分噪声观测的不确定系统的状态。通过将Fisher显著性检验和Neyman-Pearson假设检验框架应用于蒙特卡洛和传感器融合场景，提出了一种稳健的蒙特卡洛状态估计方案，能够有效处理故障或异常数据。

Comments IEEE Intelligent Transportation Systems Magazine, special issue on GNSS-based positioning

Journal ref IEEE Intelligent Transportation Systems Magazine, vol. 12, no. 3, pp. 147-156, Fall 2020

2507.09095 2026-03-09 cs.LG 50%

Temporal Misalignment Attacks against Multimodal Perception in Autonomous Driving

针对自动驾驶多模态感知的时序错位攻击

Md Hasan Shahriar, Md Mohaimin Al Barat, Harshavardhan Sundar, Ning Zhang, Naren Ramakrishnan, Y. Thomas Hou, Wenjing Lou

机构 * Amazon.com, Inc.（亚马逊公司）； Washington University in St. Louis（华盛顿大学）

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

AI总结本文提出DejaVu攻击，通过制造时序错位破坏自动驾驶多模态感知，导致目标检测和跟踪性能显著下降。

Comments 19 pages, 18 Figures

2510.05840 2026-01-27 cs.LG 50%

Multimodal Trajectory Representation Learning for Travel Time Estimation

多模态轨迹表示学习用于旅行时间估计

Zhi Liu, Xuyuan Hu, Xiao Han, Zhehao Dai, Zhaolin Deng, Guojiang Shen, Xiangjie Kong

机构 * Zhejiang University of Technology（浙江工业大学）； Zhejiang University of Technology College of Computer Science（浙江工业大学计算机科学学院）

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

AI总结本文提出多模态动态轨迹整合框架，通过整合GPS、网格轨迹和道路网络约束，提升旅行时间估计的性能和泛化能力。

2506.06301 2025-12-10 cs.AI 50%

Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Review

大语言模型及其在道路安全与出行提升中的应用：全面综述

Muhammad Monjurul Karim, Yan Shi, Shucheng Zhang, Bingzhang Wang, Mehrdad Nasri, Yinhai Wang

机构 * Department of Civil and Environmental Engineering, University of Washington（土木与环境工程系，华盛顿大学）

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

AI总结本文综述了大语言模型在道路安全与出行提升中的应用，探讨其在交通领域的适应策略及面临的挑战。

Journal ref Artificial Intelligence for Transportation, 1, 100004, 2025

2510.21451 2025-10-31 cs.SE 50%

Scalpel: Automotive Deep Learning Framework Testing via Assembling Model Components

Yinglong Zou, Juan Zhai, Chunrong Fang, An Guo, Jiawei Liu, Zhenyu Chen

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

Comments Accepted by the 48th IEEE/ACM International Conference on Software Engineering (ICSE 2026)

2504.14833 2025-04-22 cs.NI cs.CR 50%

IoT-AMLHP: Aligned Multimodal Learning of Header-Payload Representations for Resource-Efficient Malicious IoT Traffic Classification

Fengyuan Nie, Guangjie Liu, Weiwei Liu, Jianan Huang, Bo Gao

专题命中自动驾驶多传感器融合：multimodal fusion(abstract)

2501.19070 2025-02-03 quant-ph 50%

Quantum Internet Use Case Analysis for the Automotive Industry

K. L. van der Enden, R. Kirschner, M. Krumtünger, A. Wilms

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

Comments 22 pages, 5 figures

2412.20688 2024-12-31 cs.CE 50%

Revolutionizing Mobility:The Latest Advancements in Autonomous Vehicle Technology

Venkata Sai Chandra Prasanth Narisetty, Tejaswi Maddineni

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

2412.01840 2024-12-04 cs.NE cs.AI cs.SY eess.SY 50%

Zonal Architecture Development with evolution of Artificial Intelligence

Sneha Sudhir Shetiya, Vikas Vyas, Shreyas Renukuntla

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

2405.03809 2024-05-08 cs.AI 50%

SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction

Zixu Wang, Zhigang Sun, Juergen Luettin, Lavdim Halilaj

专题命中自动驾驶多传感器融合：information fusion(abstract)

2405.00570 2024-05-02 cs.LG cs.AI 50%

WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting

Theodoros Theodoropoulos, Angelos-Christos Maroudis, Antonios Makris, Konstantinos Tserpes

专题命中自动驾驶多传感器融合：information fusion(abstract)

2310.17149 2023-10-27 cs.LG cs.AI 50%

Explainable Spatio-Temporal Graph Neural Networks

Jiabin Tang, Lianghao Xia, Chao Huang

专题命中自动驾驶多传感器融合：information fusion(abstract)

Comments 32nd ACM International Conference on Information and Knowledge Management (CIKM' 23)

2305.14872 2023-06-01 cs.LG cs.SE 50%

Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

Janek Groß, Michael Kläs, Lisa Jöckel, Pascal Gerber

专题命中自动驾驶多传感器融合：information fusion(abstract)

Comments 8 pages, 7 figures, VERDI workshop collocated with the DSN conference 2023

2305.08247 2023-05-16 eess.SY cs.SY 50%

A Fast and Robust Camera-IMU Online Calibration Method For Localization System

Xiaowen Tao, Pengxiang Meng, Bing Zhu, Jian Zhao

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

2201.00008 2022-05-05 cs.LG cs.AI 50%

A Lightweight and Accurate Spatial-Temporal Transformer for Traffic Forecasting

Guanyao Li, Shuhan Zhong, S. -H. Gary Chan, Ruiyuan Li, Chih-Chieh Hung, Wen-Chih Peng

专题命中自动驾驶多传感器融合：information fusion(abstract)

2103.00878 2021-03-02 eess.SY cs.SY 50%

Secure Estimation and Attack Isolation for Connected and Automated Driving in the Presence of Malicious Vehicles

Tianci Yang, Chen Lv

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

2010.05437 2020-10-13 cs.AI cs.SY eess.SY 50%

A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network

Jiqian Dong, Sikai Chen, Paul Young Joun Ha, Yujie Li, Samuel Labi

专题命中自动驾驶多传感器融合：information fusion(abstract)

Comments TRB 2021 Annual Meeting

1603.02373 2018-03-05 stat.OT 50%

On point processes in multitarget tracking

Ronald Mahler

专题命中自动驾驶多传感器融合：information fusion(abstract)

Comments This submission has been withdrawn by arXiv administrators for unprofessional language

1409.1917 2014-09-09 cs.LG 50%

Novel Methods for Activity Classification and Occupany Prediction Enabling Fine-grained HVAC Control

Rajib Rana, Brano Kusy, Josh Wall, Wen Hu

专题命中自动驾驶多传感器融合：sensor fusion(abstract)

1. 自动驾驶多传感器融合 261 篇

Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration

Interpretable Crisis Behavior Analysis Using Mobility and Social Media Data

A Framework for Robust Assimilation of Potentially Malign Third-Party Data, and its Statistical Meaning

Temporal Misalignment Attacks against Multimodal Perception in Autonomous Driving

Multimodal Trajectory Representation Learning for Travel Time Estimation

Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Review

Scalpel: Automotive Deep Learning Framework Testing via Assembling Model Components

IoT-AMLHP: Aligned Multimodal Learning of Header-Payload Representations for Resource-Efficient Malicious IoT Traffic Classification

Quantum Internet Use Case Analysis for the Automotive Industry

Revolutionizing Mobility:The Latest Advancements in Autonomous Vehicle Technology

Zonal Architecture Development with evolution of Artificial Intelligence

SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction

WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting

Explainable Spatio-Temporal Graph Neural Networks

Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

A Fast and Robust Camera-IMU Online Calibration Method For Localization System

A Lightweight and Accurate Spatial-Temporal Transformer for Traffic Forecasting

Secure Estimation and Attack Isolation for Connected and Automated Driving in the Presence of Malicious Vehicles

A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network

On point processes in multitarget tracking

Novel Methods for Activity Classification and Occupany Prediction Enabling Fine-grained HVAC Control