Research Initiation Awards provide support for junior and mid-career faculty at Historically Black Colleges and Universities who are building new research programs or redirecting and rebuilding existing research programs. It is expected that the award helps to further the faculty member's research capability and effectiveness, improves research and teaching at the home institution, and involves undergraduate students in research experiences. The award to Florida Agricultural and Mechanical University (FAMU) supports research in industrial engineering. More specifically, it supports research that contributes to research questions pertaining to the distribution of autonomous vehicles. Furthermore, the project engages undergraduate engineering students in the research activities.
The overall project goal is to develop and evaluate a novel scheme for distributing finished vehicles from automobile manufacturers to dealers, assuming that self-driving technology is market ready. This project is motivated by a substantial literature gap: the implications of autonomous vehicle (AV) technologies for the distribution of AVs themselves are not yet understood. This novel distribution scheme requires the collaboration of larger AVs (i.e., auto-carriers) and smaller AVs (i.e., finished automobiles), which can bring significant benefits through the routing cost tradeoff between heterogeneous AVs. The project team proposes a space-state network flow formulation and algorithm for the auto-carrier loading and unloading problem; develop learning-based algorithms to predict the loading feasibility and the loading/unloading cost for a given auto-carrier route; design a fully integrated auto-carrier loading and routing optimization algorithm, with and without AV technologies. Managerial insights will be generated through extensive computational experiments, which can inform automobile manufacturers in making cost-effective automobile distribution plans. The project facilitates the preparation of engineering students at FAMU for academic pursuits in operations research and machine learning by engaging undergraduates as student researchers, and through the integration of research findings from this project with two courses taught by the PI.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.