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Browsing by Author "Ahmadi, Alidad"

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    Driver Training Research and Guidelines for Automated Vehicle Technology
    Manser, Michael P.; Noble, Alexandria M.; Machiani, Sahar Ghanipoor; Shortz, Ashley; Klauer, Charlie; Higgins, Laura L.; Ahmadi, Alidad (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-07)
    The advent of advanced driver-assistance systems presents the opportunity to significantly improve transportation safety. Complex sensor-based systems within vehicles can take responsibility for tasks typically performed by drivers, thus reducing driver-related error as a source of crashes. While there may be a reduction in driver errors, these systems fundamentally change the driving task from manual control to supervisory control. A significant challenge, given this fundamental change in the driving task, is that there are no established methods to train drivers on the use of these systems, which may be counterproductive to safety improvements. The aim of the project was to develop training protocol guidelines that could be used by advanced driver-assistance system trainers to optimize driving safety. The guidelines were developed based on the results of three activities that included the development of a taxonomy of the knowledge and skills necessary to operate advanced driver-assistance systems, a driving simulator study that examined the effectiveness of traditional training protocols, and a test track study that examined the efficacy of a vehicle-based training protocol. Results of both studies suggest that differing training protocols are most beneficial in terms of driver cognitive load and visual scanning as opposed to short-term changes in performance.
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    Safety Impact Evaluation of a Narrow-Automated Vehicle-Exclusive Reversible Lane on an Existing Smart Freeway
    Machiani, Sahar Ghanipoor; Jahangiri, Arash; Melendez, Benjamin; Katthe, Anagha; Hasani, Mahdie; Ahmadi, Alidad; Musial, Walter B. (SAFE-D: Safety Through Disruption National University Transportation Center, 2021-02)
    This study fills the gap in the limited research on the effect of emerging Automated Vehicle (AV) technology on infrastructure standards. The main objective of this research is to evaluate implications of an innovative infrastructure solution, exclusive AV lanes, for safe and efficient integration of AVs into an existing transportation system. Examining a real-world case study, this project investigates implications of adding a narrow reversible AV exclusive lane to the existing configuration of the I-15 expressway in San Diego, resulting in a 9-foot AV reversible lane, and in both directions of travel, two 12-feet lanes for HOV and HOT vehicles. Given the difference between the operation of AVs and human-driven vehicles and reliance of AVs on sensors as opposed to human capabilities, the question is whether we can provide exclusive and narrower roadways for AVs while maintaining proper safety and mobility? To accomplish the project’s goal, the research team conducted a series of research approaches including a literature review, an AV manufacturers product review, expert interviews, a consumer questionnaire review, a crash data analysis, and a traffic simulation analysis. Recommendations and guidelines from the results of the study may be used for practitioners and professional organizations involved or interested in AV development.