Journal Information
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Impact Factor:

Call For Papers
The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the fields of systems engineering. It includes issue formulation, analysis and modeling, decision making, and issue interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems. In addition, it includes systems management, systems engineering processes, and a variety of systems engineering methods such as optimization, modeling and simulation.
Last updated by Dou Sun in 2016-09-25
Special Issues
Special Issue on Intelligent Sensing, Planning and Control for Autonomous Driving Vehicles
Submission Date: 2017-07-31

The IEEE Transactions on Systems, Man, and Cybernetics: Systems calls for research paper submissions for considering in a Special Issue publication featuring on intelligent sensing, planning and control for autonomous driving vehicles. Unpublished original contributions from prospective authors are invited for consideration by the special issue, subject to blind reviews, with main focus on new theory and technologies for improving the performance of autonomous driving vehicles in complex, uncertain environments. Comprehensive case studies and in-depth review papers will also be considered. In the past decades, intelligent vehicles have received increasingly significant attention due to their great potential in enhancing vehicle safety and performance, and traffic efficiency. One of the key objectives of intelligent vehicles is to realize a high degree of autonomy under dynamic, complex environments. From multi-disciplinary perspectives including robotics, computer vision, artificial intelligence, control theory, et al, many research efforts have been devoted to improving the performance of autonomous sensing, planning and control abilities for intelligent vehicles. Furthermore, due to the requirements of unknown complex environments, it is necessary for intelligent vehicles to have improved learning ability such as online learning and driving skill learning from past experiences for sensing, planning and motion control. In real-world traffic, there are various uncertainties and complexities in road and weather conditions, objects and obstacles are dynamic, as is the interaction between the tires and the driving terrain, etc. An autonomous vehicle has to deal with the following technical challenges: (i) to rapidly and accurately detect, recognize and track dynamic objects with complex backgrounds, (ii) to build accurate maps and realize self-localization in uncertain, dynamic environments, (iii) to implement motion planning and avoid dynamic obstacles with multiple goals such as safety, agility, and traffic efficiency, and (iv) to learn from past experience and reuse the learned knowledge to continually improve driving performance. This special issue seeks to explore the areas related to these challenges.
Last updated by Dou Sun in 2017-01-19
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