Cao, J.H.[Jin-Hui],
Di, X.Q.[Xiao-Qiang],
Liu, X.[Xu],
Li, J.Q.[Jin-Qing],
Li, Z.[Zhi],
Zhao, L.[Liang],
Hawbani, A.[Ammar],
Guizani, M.[Mohsen],
Anomaly Detection for In-Vehicle Network Using Self-Supervised
Learning With Vehicle-Cloud Collaboration Update,
ITS(25), No. 7, July 2024, pp. 7454-7466.
IEEE DOI
2407
Anomaly detection, Feature extraction, Predictive models, Data models,
Transformers, Intrusion detection, vehicle-cloud collaboration
BibRef
Liu, Q.[Qi],
Tang, Y.J.[Yu-Jie],
Li, X.Y.[Xue-Yuan],
Du, G.D.[Guo-Dong],
Li, Z.[Zirui],
Enhancing the Collaborative Decision-Making Performance of Connected
and Autonomous Vehicles: A Multi-Modal Failure-Aware Graph
Representation Approach,
ITS(26), No. 5, May 2025, pp. 6601-6620.
IEEE DOI
2505
Decision making, Robustness, Autonomous vehicles, Safety,
Feature extraction, Vectors, Transportation, Aggregates, Training,
mixed autonomy traffic
BibRef
Huang, T.[Tao],
Liu, J.A.[Jian-An],
Zhou, X.[Xi],
Nguyen, D.C.[Dinh C.],
Azghadi, M.R.[Mostafa Rahimi],
Xia, Y.X.[Yu-Xuan],
Han, Q.L.[Qing-Long],
Sun, S.[Sumei],
Vehicle-to-Everything Cooperative Perception for Autonomous Driving,
PIEEE(113), No. 5, May 2025, pp. 443-477.
IEEE DOI
2510
Vehicle-to-everything, Collaboration, Autonomous vehicles, Surveys,
Sensors, Feature extraction, Accuracy, Artificial intelligence,
vehicle-to-everything (V2X) communication
BibRef
Shi, J.Y.[Jing-Yue],
Zhao, J.H.[Jun-Hui],
Zhuo, L.[Li],
Wang, X.M.[Xiao-Ming],
Zhan, X.H.[Xiao-Huang],
Liu, H.T.[Hai-Tao],
V2V Cooperative Perception With Adaptive Communication Loss for
Autonomous Driving,
ITS(26), No. 10, October 2025, pp. 14866-14878.
IEEE DOI
2511
Collaboration, Signal to noise ratio, Autonomous vehicles, Cameras,
Gaussian distribution, Accuracy, Vehicular ad hoc networks,
multi-vehicle collaborative
BibRef
Chen, J.C.[Jin-Chao],
Shu, Q.[Qiuhao],
Lu, Y.T.[Yan-Tao],
Zhang, Y.[Ying],
Wang, Y.[Yang],
QCTF: A Quantized Communication and Transferable Fusion Framework for
Multi-Agent Collaborative Perception,
ITS(26), No. 10, October 2025, pp. 15013-15027.
IEEE DOI
2511
Collaboration, Feature extraction, Bandwidth, Codes, Quantization (signal),
Accuracy, Point cloud compression, multi-agent perception
BibRef
Li, W.[Wei],
Ma, L.[Lin],
Chang, H.[Haoze],
He, X.Y.[Xiang-Yun],
Huang, L.T.[Long-Teng],
Efficient Collaborative Perception With Integrated Uncertainty
Estimation via Evidence Regression,
ITS(26), No. 11, November 2025, pp. 20976-20989.
IEEE DOI Code:
WWW Link.
2511
Uncertainty, Collaboration, Accuracy, Point cloud compression,
Object detection, Autonomous vehicles, Training, multi-task loss function
BibRef
Huang, J.H.[Jia-Hao],
Zhu, J.H.[Jian-Hang],
Li, R.P.[Rong-Peng],
Zhao, Z.F.[Zhi-Feng],
Zhang, H.G.[Hong-Gang],
Select2Drive: Pragmatic Communications for Real-Time Collaborative
Autonomous Driving,
ITS(26), No. 12, December 2025, pp. 21939-21953.
IEEE DOI
2512
Collaboration, Vehicle-to-everything, Decision making,
Autonomous vehicles, Semantics, Pragmatics, Real-time systems,
connected and autonomous vehicles
BibRef
Yang, C.Z.[Chang-Zhi],
Pan, H.H.[Hui-Hui],
Wang, Y.C.[Yi-Chen],
Wang, J.[Jue],
Hong, Y.[Yuanduo],
Communication-Efficient Collaborative Perception via Trajectory and
Region-Aware Feature Sharing,
ITS(27), No. 7, July 2026, pp. 8755-8765.
IEEE DOI
2607
Feature extraction, Collaboration, Trajectory,
Point cloud compression, Autonomous vehicles, Object detection,
region decoupling
BibRef
Zhang, H.K.[Hong-Kun],
Wu, Y.[Yan],
Zhang, Z.B.[Zheng-Bin],
What2Keep: A communication-efficient collaborative perception
framework for 3D detection via keeping valuable information,
CVIU(263), 2026, pp. 104572.
Elsevier DOI Code:
WWW Link.
2601
Collaborative perception, V2X communication,
3D object detection, Autonomous driving
BibRef
Wang, T.H.[Tian-Hang],
Lu, F.[Fan],
Qu, S.Q.[San-Qing],
Li, B.[Bin],
Wu, Y.[Ya],
Cao, H.[Hu],
Knoll, A.[Alois],
Chen, G.[Guang],
An Online-Training-Free Adaptor for Open Heterogeneous Collaborative
Perception via Diffusion Model,
CirSysVideo(36), No. 4, April 2026, pp. 5729-5741.
IEEE DOI
2604
Collaboration, Training, Adaptation models, Diffusion models, Videos,
Costs, Robot sensing systems, Laser radar, diffusion model
BibRef
Chen, J.C.[Jin-Chao],
Shu, Q.[Qiuhao],
Lu, Y.T.[Yan-Tao],
Zhang, Y.[Ying],
Wang, Y.[Yang],
CEST: Enhancing Multi-Agent Perception via Communication-Efficient
Spatial-Temporal Fusion,
ITS(27), No. 5, May 2026, pp. 5972-5987.
IEEE DOI
2605
Collaboration, Feature extraction, Delays, Bandwidth,
Point cloud compression, Sensors, Metadata, Object detection,
multi-agent communication
BibRef
Tian, Y.H.[Yi-Han],
Zhang, X.[Xuan],
Zhuo, S.[Shuaichen],
Zhang, D.[Dong],
Tian, Z.Q.[Zhi-Qiang],
Liu, Y.Y.[Yu-Ying],
Du, S.Y.[Shao-Yi],
Uncertainty-guided and reliable collaborative perception for open
heterogeneous systems,
PRL(204), 2026, pp. 127-133.
Elsevier DOI
2605
Collaborative perception, Autonomous driving,
Heterogeneous systems, Communication efficiency
BibRef
Hu, Y.[Yue],
Pang, X.[Xianghe],
Qin, X.Q.[Xiao-Qi],
Eldar, Y.C.[Yonina C.],
Chen, S.[Siheng],
Zhang, P.[Ping],
Zhang, W.J.[Wen-Jun],
Pragmatic Communication in Multi-Agent Collaborative Perception,
PAMI(48), No. 8, August 2026, pp. 9279-9296.
IEEE DOI
2607
Broadcasting, Broadcast technology, Filtering, Filters,
Kalman filters, Feedback, Receivers, Vehicle-to-everything,
tracking
BibRef
Hong, S.X.[Shi-Xin],
Liu, Y.[Yu],
Li, Z.[Zhi],
Li, S.H.[Shao-Hui],
He, Y.[You],
Multi-Agent Collaborative Perception via Motion-Aware Robust
Communication Network,
CVPR24(15301-15310)
IEEE DOI Code:
WWW Link.
2410
Micromechanical devices, Noise, Semantics, Collaboration,
Interference, Object detection
BibRef
Zhang, J.Y.[Jing-Yu],
Yang, K.[Kun],
Wang, Y.L.[Yi-Lei],
Wang, H.Q.[Han-Qi],
Sun, P.[Peng],
Song, L.[Liang],
ERMVP: Communication-Efficient and Collaboration-Robust Multi-Vehicle
Perception in Challenging Environments,
CVPR24(12575-12584)
IEEE DOI
2410
Location awareness, Industries, Soft sensors, Semantics,
Collaboration, Information filters, collaborative perception,
object detection
BibRef
Song, R.[Rui],
Liang, C.W.[Chen-Wei],
Cao, H.[Hu],
Yan, Z.[Zhiran],
Zimmer, W.[Walter],
Gross, M.[Markus],
Festag, A.[Andreas],
Knoll, A.[Alois],
Collaborative Semantic Occupancy Prediction with Hybrid Feature
Fusion in Connected Automated Vehicles,
CVPR24(17996-18006)
IEEE DOI
2410
Visualization, Solid modeling, Roads, Semantics, Collaboration,
Object detection, Collaborative Perception, Robotics
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Vehicle Networks, Implementations, VANET .