UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Bansal, SiddharthSubject: search.filters.subject.Monte Carlo

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    MODEL-BASED SYSTEMS ENGINEERING APPLIED TO THE TRAJECTORY PLANNING FOR AUTONOMOUS VEHICLES
    (2018) Bansal, Siddharth; Baras, John S.; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Passing maneuver is a complex driving maneuver and it becomes more challenging in oncoming traffic. In this study, a passing scenario with three vehicles is considered where car 1, an Autonomous Vehicle (AV), is moving behind car 2 in the same lane. The third vehicle is part of the oncoming traffic in the adjacent lane. The primary goal is to model and evaluate a measurement-based decision-making strategy for the AV satisfying driving safety constraints. This strategy is based on the optimal control with the objective to performing the passing maneuver safely. To evaluate the efficiency of the decision-making strategy – probability of safely completing passing maneuver, a model of the system was developed considering all three cars as point-masses. Two binary variables, each representing the collaborative nature of the cars 2 and 3, were defined. These variables show if the two vehicles will collaborate with the AV when they find out about its intention to overtake. Lastly, a sensitivity study and trade-off study are done to determine optimal design parameters for AV’s measurement system and decision-making strategy.