Research Initiation Award: Automated Distribution of Autonomous Vehicles

研究启动奖为历史上黑人学院和大学的初级和中级职业教师提供支持，他们正在建立新的研究项目或重新定向和重建现有的研究项目。预计该奖项将有助于进一步提高教师的研究能力和效率，改善家庭机构的研究和教学，并使本科生参与研究经验。 该奖项授予佛罗里达农业和机械大学（FAMU）支持工业工程研究。 更具体地说，它支持有助于研究与自动驾驶汽车分布有关的问题的研究。 此外，该项目还邀请工科本科生参与研究活动。项目的总体目标是开发和评估一种新的方案，以将成品车从汽车制造商分销到经销商，假设自动驾驶技术已准备就绪。这个项目的动机是一个巨大的文献空白：自动驾驶汽车（AV）技术对AV本身的分布的影响还没有被理解。这种新颖的分发方案需要较大AV的协作（即，自动载具）和较小的AV（即，成品汽车），这可以通过异构AV之间的路由成本权衡带来显著的益处。该项目团队提出了一种用于自动承运人装卸问题的空间状态网络流公式和算法;开发基于学习的算法来预测给定自动承运人路线的装载可行性和装载/卸载成本;设计一种完全集成的自动承运人装载和路由优化算法，有和没有AV技术。通过大量的计算实验，将产生管理洞察力，这可以为汽车制造商制定具有成本效益的汽车分销计划提供信息。 该项目通过将本科生作为学生研究员，并将该项目的研究成果与PI教授的两门课程相结合，为FAMU的工程专业学生在运筹学和机器学习方面的学术追求做好准备。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.