IEEE Transactions on Intelligent Vehicles Journal Impact Factor

IEEE Transactions on Intelligent Vehicles | 2024 Impact Factor:14.3 | Cite Score:17.0 | Q1

IEEE Transactions on Intelligent Vehicles Journal With Cite Score

Impact Factor and Journal Rank of IEEE Transactions on Intelligent Vehicles

About: IEEE Transactions on Intelligent Vehicles is a peer-reviewed journal published by the IEEE. It focuses on research in the field of intelligent vehicles, encompassing autonomous and connected vehicle technologies. The journal provides a platform for scholars, researchers, and practitioners to publish original research articles, reviews, and case studies that advance the understanding and application of intelligent vehicle systems.
Objective: The primary objective of IEEE Transactions on Intelligent Vehicles is to promote research and innovation in intelligent vehicle technologies. The journal aims to explore theories, methodologies, and applications that enhance the capabilities of autonomous and connected vehicles. By publishing high-quality research, the journal contributes to the advancement of intelligent vehicle systems and their deployment in various transportation settings.
Interdisciplinary Focus: IEEE Transactions on Intelligent Vehicles adopts an interdisciplinary approach, welcoming contributions from various fields related to intelligent vehicles, including but not limited to, Autonomous Navigation, Vehicle Perception, Artificial Intelligence, Vehicle-to-Vehicle Communication, Vehicle-to-Infrastructure Communication, Advanced Driver Assistance Systems, Human-Vehicle Interaction, Transportation Planning and Management, Safety and Security. This interdisciplinary perspective fosters collaboration and innovation, leading to the development of advanced intelligent vehicle technologies that address complex transportation challenges.
Global Reach and Impact: With a broad international readership and authorship, IEEE Transactions on Intelligent Vehicles has a global reach and impact. Its publications contribute to the dissemination of knowledge and advancements in intelligent vehicle technologies worldwide. The journal content influences both academic research and practical applications, driving progress in areas such as autonomous driving, connected vehicle systems, smart transportation infrastructure, and urban mobility.
High Standards and Rigorous Review: Maintaining high academic standards, IEEE Transactions on Intelligent Vehicles conducts a rigorous peer-review process. Each submitted manuscript undergoes thorough evaluation by experts in the field to ensure the quality, originality, and scientific rigor of the research. This stringent review process upholds the integrity and reputation of the journal, ensuring that only high-quality and impactful research is published.
Significance: IEEE Transactions on Intelligent Vehicles plays a significant role in advancing research and practice in the field of intelligent transportation. By providing a platform for the publication of cutting-edge research findings, the journal contributes to the growth of knowledge and innovation in intelligent vehicle technologies. It serves as an essential resource for researchers, practitioners, and policymakers seeking to leverage intelligent transportation systems to improve safety, efficiency, and sustainability in modern transportation networks.

Journal Home: Journal Homepage

Editor-in-Chief: Fei-Yue Wang

Scope: The IEEE Transactions on Intelligent Vehicles (T-IV) journal is a prestigious peer-reviewed publication focusing on the advancement of intelligent vehicle technologies. It serves as a crucial platform for researchers, engineers, and practitioners to disseminate their latest research findings, methodologies, and innovations in the field of intelligent vehicles. Here is an overview of its key focus areas and scope:
1. Autonomous Driving Systems:
Research on autonomous vehicle technologies, including perception, decision-making, and control algorithms for self-driving cars.
Advancements in sensor fusion, localization, mapping, and navigation systems for autonomous driving.
2. Vehicle-to-Everything (V2X) Communication:
Exploration of communication technologies enabling vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) interactions.
Research on V2X protocols, networking architectures, and security mechanisms for cooperative and connected vehicles.
3. Intelligent Transportation Systems (ITS):
Advancements in ITS applications leveraging intelligent vehicle technologies for traffic management, congestion mitigation, and road safety.
Research on adaptive cruise control, lane departure warning, collision avoidance systems, and cooperative driving.
4. Human-Vehicle Interaction:
Exploration of user interfaces, driver assistance systems, and human factors in intelligent vehicles.
Research on driver behavior modeling, trust in automation, and the impact of autonomous driving on human cognition and behavior.
5. Perception and Sensing Technologies:
Advancements in vehicle perception systems, including cameras, LiDAR, radar, and ultrasonic sensors.
Research on sensor fusion techniques, object detection, tracking, and environmental perception for autonomous vehicles.
6. Machine Learning and Artificial Intelligence in Vehicles:
Exploration of machine learning algorithms, deep learning models, and reinforcement learning techniques for intelligent vehicles.
Research on AI-driven decision-making, predictive analytics, and adaptive control in autonomous driving systems.
7. Vehicle Control and Navigation:
Advancements in vehicle control systems, including adaptive cruise control, lane-keeping assistance, and automated parking.
Research on trajectory planning, motion control, and path following algorithms for autonomous and semi-autonomous vehicles.
8. Cybersecurity and Safety:
Exploration of cybersecurity threats, vulnerabilities, and countermeasures in intelligent vehicles.
Research on secure communication protocols, intrusion detection systems, and resilient architectures for connected and autonomous vehicles.
9. Energy Efficiency and Sustainability:
Advancements in energy-efficient driving strategies, eco-routing algorithms, and vehicle electrification technologies.
Research on the environmental impact of intelligent vehicles, including emissions reduction and sustainability measures.
10. Testing, Verification, and Validation:
Exploration of methodologies for testing and validating intelligent vehicle systems, including simulation, field trials, and real-world testing.
Research on safety standards, certification processes, and regulatory frameworks for autonomous and connected vehicles.
11. Legal, Ethical, and Societal Implications:
Advancements in policy, ethics, and societal acceptance of intelligent vehicle technologies.
Research on legal frameworks, liability issues, and public perception of autonomous driving systems.
12. Emerging Technologies and Future Trends:
Exploration of emerging technologies shaping the future of intelligent vehicles, including vehicle electrification, shared mobility, and urban air mobility.
Research on the integration of AI, IoT, and edge computing in next-generation vehicle platforms.