Advanced Algorithms for Mission Planning and Collision Avoidance of Autonomous Vehicles
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".
Deadline for manuscript submissions: closed (15 February 2024) | Viewed by 2693
Special Issue Editors
Interests: control theory and applications; adaptive control and system identification; modelling and simulation; machine learning; autonomous vehicles; systems engineering
Special Issue Information
Dear Colleagues,
In the rapidly evolving world of autonomous vehicles (AVs), the importance of effective mission planning cannot be overstated. As the "brain" of an AV, mission planning involves considering numerous critical factors that impact the success of AV operations. These factors include mission objectives, global and local planning, vehicle capabilities and limitations, environmental conditions and disturbances, the risks associated with maneuvers, collision avoidance, and motion regulations. By addressing these factors, advanced AV mission planning algorithms can ensure the optimized operation of autonomous vehicles in various scenarios. Therefore, the success of AV technology highly depends on the development and implementation of elaborate mission planning systems. This Special Issue aims to promote novel mission planning algorithms with a significant interest in collision avoidance.
Topics of interest include but are not limited to:
- Mission planning in autonomous (aerospace, marine and ground) vehicles.
- Rules-based collision avoidance algorithms based on: the Traffic Alert and Collision Avoidance System (TCAS), COLREGS—International Regulations for Preventing Collisions at Sea, ISO SOTIF, and so forth.
- Modern online collision risk assessment approaches.
- Novel collision avoidance techniques and their implementations.
- Machine learning and other advanced algorithms for mission planning and collision avoidance.
- Implementation and test results.
Dr. Pouria Sarhadi
Prof. Dr. Benoît Clément
Guest Editors
Manuscript Submission Information
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