Kevin Heaslip

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This work describes a new type of efficiency attack that can be used to degrade the performance of automated vehicular transportation systems. Next-generation transportation technologies will leverage increasing use of vehicle automation. Proposed vehicular automation systems include cooperative adaptive cruise control and vehicle platooning strategies(More)
This paper presents an algorithm that considers the influence of driver behavior on traffic flow and safety when drivers encounter and respond to changing roadway conditions found in work zones. The conditions modeled by the algorithm in this research effort are lane drops and the forced merges that are caused by the lane drop. Central to the algorithm is(More)
course is one of these courses. With typically only one required course in the transportation field in most civil engineering programs, faculty often have about 40 contact hours with students to discuss how complex transportation systems are designed, built, maintained, and operated for different types of transportation modes (1). The breadth of the(More)
In intelligent transportation systems, most of the research work has focused on lane change assistant systems. No existing work considers minimizing the interruption of traffic flow by maximizing the number of lane changes while eliminating the collisions. In this thesis, we develop qualitative and quantitative approaches for minimizing the interruption of(More)
In this work, we employ distance bounding (DB) and verifiable trilateration (VT) for secure localization in an intelligent transportation system (ITS). We first demonstrate several possible attack scenarios, and then establish an analytical framework to evaluate the security of these schemes. Results are derived in terms of the probability of a given(More)
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