IEEE Transactions on Intelligent Vehicles

Papers
(The H4-Index of IEEE Transactions on Intelligent Vehicles is 41. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
Attention Based Vehicle Trajectory Prediction152
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving152
AI-IMU Dead-Reckoning145
A Survey on Trajectory-Prediction Methods for Autonomous Driving140
Future Directions of Intelligent Vehicles: Potentials, Possibilities, and Perspectives125
Securing Vehicle-to-Everything (V2X) Communication Platforms120
Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys116
Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control101
Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives90
A Survey of Personalization for Advanced Driver Assistance Systems77
MetaVehicles in the Metaverse: Moving to a New Phase for Intelligent Vehicles and Smart Mobility75
Scene Understanding With Automotive Radar73
HYDRO-3D: Hybrid Object Detection and Tracking for Cooperative Perception Using 3D LiDAR71
MPC-Based Cooperative Control Strategy of Path Planning and Trajectory Tracking for Intelligent Vehicles70
Prediction-Uncertainty-Aware Decision-Making for Autonomous Vehicles66
Quality-Aware Feature Aggregation Network for Robust RGBT Tracking66
Requirements-Driven Test Generation for Autonomous Vehicles With Machine Learning Components65
Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control62
A Multimodality Fusion Deep Neural Network and Safety Test Strategy for Intelligent Vehicles61
Driving Performance Under Violations of Traffic Rules: Novice vs. Experienced Drivers60
A Survey on Attack Detection and Resilience for Connected and Automated Vehicles: From Vehicle Dynamics and Control Perspective60
Parallel Driving OS: A Ubiquitous Operating System for Autonomous Driving in CPSS58
Robust Lane Change Decision Making for Autonomous Vehicles: An Observation Adversarial Reinforcement Learning Approach58
Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles58
Driver Behavior Modeling Using Game Engine and Real Vehicle: A Learning-Based Approach56
Set-Based Prediction of Traffic Participants Considering Occlusions and Traffic Rules54
A Novel Algorithm of Multi-AUVs Task Assignment and Path Planning Based on Biologically Inspired Neural Network Map54
Predicting Pedestrian Crossing Intention With Feature Fusion and Spatio-Temporal Attention54
Parallel Vision for Long-Tail Regularization: Initial Results From IVFC Autonomous Driving Testing51
Tractor-Trailer Vehicle Trajectory Planning in Narrow Environments With a Progressively Constrained Optimal Control Approach49
Towards Computationally Efficient and Realtime Distracted Driver Detection With MobileVGG Network49
An Optimization-Based Path Planning Approach for Autonomous Vehicles Using the DynEFWA-Artificial Potential Field48
Improved Path Planning by Tightly Combining Lattice-Based Path Planning and Optimal Control48
Cross-Domain Object Detection for Autonomous Driving: A Stepwise Domain Adaptative YOLO Approach48
Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective47
Using Reachable Sets for Trajectory Planning of Automated Vehicles47
Path Planning Based on Deep Reinforcement Learning for Autonomous Underwater Vehicles Under Ocean Current Disturbance47
Real-Time Driver Maneuver Prediction Using LSTM46
A Progressive Review: Emerging Technologies for ADAS Driven Solutions45
Digital Twin-Assisted Cooperative Driving at Non-Signalized Intersections45
Learning to Drive by Imitation: An Overview of Deep Behavior Cloning Methods44
Provably-Correct and Comfortable Adaptive Cruise Control41
Soft-Weighted-Average Ensemble Vehicle Detection Method Based on Single-Stage and Two-Stage Deep Learning Models41
Cooperative Driving of Automated Vehicles Using B-Splines for Trajectory Planning41
Intelligent Vehicle Self-Localization Based on Double-Layer Features and Multilayer LIDAR41
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