United States Department of Transportation
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Modeling Driver Behavior and Aggressiveness Using Biobehavioral Methods - Phase I
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2018-12-14
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[PDF-3.01 MB]
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Corporate Contributors:University of Kansas ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Federal Highway Administration
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Edition:Final Report (December 2016-December 2018)
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Abstract:Mathematical models of car-following, lane changing, and gap acceptance are mostly descriptive in nature and lack decision making or error tolerance. Including additional driver information with respect to behavior and cognitive characteristics would account for these lacking parameters and incorporate a human aspect to these models. Car-following, particularly in relation to the intelligent driver model (IDM), is the primary component of this research. The major objectives of this research are to investigate how psychophysiological constructs can be modeled to replicate car-following behavior, and to correlate subjective measures of behavior and aggressiveness with actual car-following behavior. To accomplish the objectives the following tasks are required: perform a thorough literature review, develop the methodological framework, set up a driving simulator study to collect relevant data, classify drivers with respect to their static and behavioral traits, and calibrate the IDM. This report presents the first part of this study, and includes the thorough literature review, and the methodological framework that will be used to incorporate biobehavioral parameters into the IDM. The data collection plan to execute the methodology involves collecting driving data from 90 participants using a driving simulator, and this will be completed in the second phase of the project. Various car-following tasks will be performed at multiple task difficulties. This will provide data on compensatory and performance effects experienced by drivers. Modification to the IDM will be made to incorporate any observed trends between driver classes, behavior, and performance.
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