Research Initiation Award: Automated Distribution of Autonomous Vehicles

研究启动奖：自动驾驶车辆的自动配送

• 批准号: 2100745
• 负责人: Yanshuo Sun
• 金额: $ 30万
• 依托单位: Florida Agricultural and Mechanical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2100745&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Automated; Distribution

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.

研究启动奖为历史悠久的黑人学院和大学的初级和中期教师提供支持，他们正在建立新的研究项目或重新调整和重建现有的研究项目。预计该奖项有助于提高教师的研究能力和效率，改善所在机构的研究和教学，并让本科生参与研究经验。 授予佛罗里达农业机械大学 (FAMU) 的奖项支持工业工程研究。 更具体地说，它支持有助于解决与自动驾驶汽车分布相关的问题的研究。 此外，该项目还让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颖的方案，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做好市场准备。该项目的动机是巨大的文献空白：自动驾驶汽车（AV）技术对自动驾驶汽车本身的分布的影响尚不清楚。这种新颖的分配方案需要大型自动驾驶汽车（即汽车运输商）和较小自动驾驶汽车（即成品汽车）的协作，这可以通过异构自动驾驶汽车之间的路由成本权衡带来显着的好处。项目组针对汽车载体装卸问题提出了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汽车运输路线的装载可行性和装载/卸载成本；设计完全集成的自动载体加载和路由优化算法，无论是否使用 AV 技术。管理见解将通过广泛的计算实验产生，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。 该项目通过让本科生作为学生研究人员，并将该项目的研究成果与 PI 教授的两门课程相结合，促进 FAMU 的工程专业学生为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 的法定使命通过使用基金会的智力优点和更广泛的影响审查标准进行评估，并被认为值得支持。

项目成果

A survey of finished vehicle distribution and related problems from an optimization perspective

优化视角下的整车配送及相关问题综述

• DOI: 10.1016/j.tre.2021.102302
• 发表时间: 2021-05-01
• 期刊: Transportation Research Part E-logistics and Transportation Review
• 影响因子: 10.6
• 作者: Yanshuo Sun;S. Kirtonia;Zhi
• 通讯作者: Zhi

Evaluating the Environmental Benefits of Personalized Travel Incentives in Dynamic Carpooling

评估动态拼车中个性化旅行激励措施的环境效益

• DOI: 10.1007/s12205-022-1568-1
• 发表时间: 2022-01
• 期刊: KSCE Journal of Civil Engineering
• 影响因子: 2.2
• 作者: Sun, Yanshuo;Chen, Shijie;Guo, Qianwen
• 通讯作者: Guo, Qianwen

Predicting in-stream water quality constituents at the watershed scale using machine learning

使用机器学习预测流域范围内的河流水质成分

• DOI: 10.1016/j.jconhyd.2022.104078
• 发表时间: 2022-12
• 期刊: Journal of Contaminant Hydrology
• 影响因子: 3.6
• 作者: Adedeji, Itunu C.;Ahmadisharaf, Ebrahim;Sun, Yanshuo
• 通讯作者: Sun, Yanshuo

Investment timing and length choice for a rail transit line under demand uncertainty

需求不确定下轨道交通线路投资时机及长度选择

• DOI: 10.1016/j.trb.2023.102800
• 发表时间: 2023-09
• 期刊: Transportation Research Part B: Methodological
• 作者: Guo, Qianwen;Chen, Shumin;Sun, Yanshuo;Schonfeld, Paul
• 通讯作者: Schonfeld, Paul

Perception of Hurricane and COVID-19 Risks for Household Evacuation and Shelter Intentions

对家庭疏散和避难意图的飓风和 COVID-19 风险的认知

• DOI: 10.1080/00330124.2022.2103722
• 发表时间: 2023-07
• 期刊: The Professional Geographer
• 作者: Zhao, Tingting;Jia, Minna;Tang, Tian;Sun, Yanshuo
• 通讯作者: Sun, Yanshuo