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    Modelling perception updating of travel times

    From the output of this study, the results of our laboratory-like experiment provide a good fit to the stated data of travelers’ behavior, and may reflect the fact that the neuro-fuzzy approach can be considered a promising method in learning and perception updating models.

    Finally, the proposed learning model is embedded in a microscopic event-based simulation framework to evaluate its credibility within a day-to-day behavior of the traffic network.

    At landing, telemetry was monitored by the 2001 Mars Odyssey orbiter, Mars Reconnaissance Orbiter and ESA's Mars Express.

    Odyssey is capable of relaying UHF telemetry back to Earth in real time.

    In literature, both negative and positive effects of SDVs are listed (Litman 2015; Fagnant and Kockelman 2015).

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    Individuals’ daily travel decisions are linked to the traffic simulator SIAS-PARAMICS to create a simulation system in which both individual decision-making and system performance (and interactions between these two levels) are adequately represented.

    The model is applied in a case study that supports the feasibility of this approach.

    A micro-simulation approach is applied, in which individuals base their consecutive departure time decisions on a mental model.

    The mental model is the outcome of a continuous process of perception updating according to principles of reinforcement learning.

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