On the Use of Case-based Working-Principles of Self-optimization for Intelligent Shuttle Transportation Systems

P. Scheideler and A. Schmidt (Germany)


Application Transportation, Case-Based Reasoning, Intelligent Agents


The demand for flexible and individualized passenger and cargo transportation becomes more and more apparent. Considering modern railway-systems this development provokes a modular approach for optimum operation from the top logistics-level down to the low-level of mechatronic components. The resulting vision comprises innovative vehicles so called shuttles that behave autonomously within changing environments and requests from passengers. The shuttles require inherent intelligence to fulfill these demands. We propose working-principles of self-optimization as basic building blocks for intelligent self-optimizing transportation systems. An approach for a knowledge model together with a process model of self-optimizing systems shall direct the experience-based behavior of each system element. The prediction of a shuttle's negotiation-strategy when crossing a switch acts as an application case for the forwarded idea of working-principles of self-optimization within modular autonomous shuttle transportation systems.

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