A Knowledge Driven Decision Support Framework to Aid Autonomous Vehicle Systems ’ Mission

The success of Autonomous Vehicle (AV) systems largely depends on fast alignment of their resources, to meet (and exceed) the actual (and perceived) requirements of the changing operational environment. A review of key literature applicable to AV practices and planning issues provides a short assessment of planning scenarios, highlighting their complexity, limitations and the possible scope for improvement through the use of decision support systems (DSSs). As a result, a framework is proposed for knowledge based DSSs for mission objectives of AVs, supporting both autonomous and cooperative learning between the vehicles and helping to improve the efficiency of the autonomous system. Anticipated benefits from this DSS model include: flexibility and interoperability in terms of supporting different architectures and ranges of autonomous systems with scope for reusing and maintaining the captured knowledge, learning from past events and sharing that knowledge in the future. The final section of this paper discusses further work and the next phases of our project research.