CAREER: Integrated Multiresolution Transportation Network Modeling

该学院早期职业发展(Career)项目奖的目标是调查不同规模/规模的交通网络之间的关系，学习如何量化这些关系，并发现对交通规划的影响。研究集中于规模和规模是重要问题的三个例子：除地方规模外还考虑多个州或国家规模的货运模型，区域内运输资金的分配，以及随时间快速变化的运输网络(例如，由于事故或其他中断)。当前的多尺度模型通常是以一种特别的方式构建的，不了解模型之间的基本联系。这项拨款中的研究调查将以这样一个猜想为指导：将一个模型的简化版本与另一个模型合并在一起，而不是将它们完全分开是有效找到一致解决方案的关键。如果成功，这项工作将使网络模型能够代表更大的区域，特别是支持改进的交通规划，但也有助于在其他领域建立多尺度网络模型。与研究计划相辅相成的教育和推广计划有四个主要组成部分。首先，将在最近的教学研究的基础上，为运输工程和网络分析课程开发主动学习课程。其次，将公开最先进的交通算法代码库，允许学生在课程项目中使用大规模实用数据，并允许实践者试验最先进的模型，促进技术转让。代码和课程材料都将以开放获取的形式免费发布。第三，PI将积极招聘和指导本科生和研究生研究人员，与大学项目对接，从代表性不足的群体中发现有才华的学生。最后，在研究成果的基础上，开发了一门新的多尺度建模课程。

The objective of this Faculty Early Career Development (CAREER) program award is to investigate the relationships between transportation networks of different scales/sizes, learn how to quantify these relationships, and discover the implications for transportation planning. The research focuses on three examples where scale and size are important issues: freight models where a multistate or national scale is considered in addition to a local scale, allocation of transportation funds within a region, and transportation networks that change rapidly with time (e.g., due to accidents or other disruptions). Current multi-scale models are often constructed in an ad hoc manner, without understanding the fundamental connections between the models. The research investigation in this grant will be guided by the conjecture that "mixing" models incorporating simplified versions of one model into another, rather than separating them completely is the key to efficiently finding consistent solutions.If successful, this work will allow network models to represent much larger regions, specifically supporting improved transportation planning, but also contributing to multi-scale network models in other domains. A complementary education and outreach plan to the research plan has four major components. First, active-learning curricula will be developed for transportation engineering and network analysis courses, building on recent pedagogical research. Second, a library of state-of-the-art transportation algorithm codes will be made public, allowing students to work with large-scale practical data in course projects and allowing practitioners to experiment with state-of-the-art models, facilitating technology transfer. Both the code and curriculum materials will be released in open-access form, free of charge. Third, the PI will actively recruit and mentor undergraduate and graduate researchers, interfacing with university programs to identify talented students from underrepresented groups. Finally, a new course in multi-scale modeling will be developed, based on the research results.