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Showing 1 to 4 of 4 for “"Driver Heterogeneity"”.

  1. The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models

    … to adequately capture naturalistic behavioral heterogeneity are largely missing from the literature. For this dissertation, a sample from the second Strategic Highway Research Program Naturalistic Driving Study was analyzed. This sample contains 665 trips completed on freeways in clear weather …

    texas Repository record for The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models (opens in a new tab)

  2. Incorporating Perceptions, Learning Trends, Latent Classes, and Personality Traits in the Modeling of Driver Heterogeneity in Route Choice Behavior

    Driver heterogeneity in travel behavior has repeatedly been cited in the literature as a limitation that needs to be addressed. In this work, driver heterogeneity is addressed from four different perspectives. First, driver heterogeneity is addressed by models of driver perceptions of travel …

    vt Repository record for Incorporating Perceptions, Learning Trends, Latent Classes, and Personality Traits in the Modeling of Driver Heterogeneity in Route Choice Behavior (opens in a new tab)

  3. Towards Developing an Integrated Microscopic Traffic Simulation Model for Large Road Networks

    … productivity, increase CO2 emissions and affect driver stress, travel time predictability and increased wear and tear on vehicles. To test possible countermeasures, optimise existing infrastructure or develop new Intelligent Transport Systems (ITS), traffic has to be modelled. The inherent …

    auckland-ms Repository record for Towards Developing an Integrated Microscopic Traffic Simulation Model for Large Road Networks (opens in a new tab)

  4. Modeling Naturalistic Driver Behavior in Traffic Using Machine Learning

    This research is focused on driver behavior in traffic, especially during car-following situations and safety critical events. Driving behavior is considered as a human decision process in this research which provides opportunities for an artificial driver agent simulator to learn according to …

    vt Repository record for Modeling Naturalistic Driver Behavior in Traffic Using Machine Learning (opens in a new tab)