Unmanned vehicles are projected to reach consumer use within this decade - related legislation has already passed in California. The most significant technical challenge associated with these vehicles is their integration in transportation environments with manned vehicles. Abnormal or incorrect manipulation of the manned vehicles by their human drivers creates a highly nondeterministic environment that is difficult to consider in the control algorithms for unmanned vehicles. Our ultimate goal is to develop a Markovian model that can capture the stochastic elements of this environment, in particular failure propagation from the manned to unmanned vehicles and vice versa. The analytic model will be validated through simulation with a purpose built tool that we plan to develop in the course of the proposed work. In the nine months of the project, we expect to create a qualitative model for the environment, to begin work on the quantitative model (using Petri nets and the qualitative model as a basis), and to develop the simulation environment required.


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    Title :

    Quantitative Modeling of Failure Propagation in Intelligent Transportation Systems


    Contributors:
    S.S Sarvestani (author) / R.A Hurson (author)

    Publication date :

    2014


    Size :

    14 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English







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