课题基金 / 基金详情

Signatures and Barcodes: Data-driven Understanding of Transportation System Performance during Extreme Events

Signatures and Barcodes: Data-driven Understanding of Transportation System Performance during Extreme Events
签名和条形码:数据驱动的对极端事件期间运输系统性能的理解
批准号:
1727785
负责人:
Richard Sowers
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
This project focuses on understanding the effects of extreme events such as natural disasters on urban transportation systems necessary for emergency response and recovery services. Motivated both by continued urbanization and the frequency of extreme weather events, this project will investigate novel methods to quantify infrastructure performance and resilience at city-level scales. Outcomes of the project work will provide data-driven insights relevant to authorities responsible for extreme event mitigation and response. Seminars will be given to state and local transportation officials on the results of this work. Parts of the project will be carried out via partnerships with the Illinois Geometry Laboratory to facilitate interdisciplinary undergraduate research experiences for engineering and mathematics students.This project centers on the creation of data-driven methods to investigate the effects of extreme events on transportation infrastructure by interpreting citywide and multiyear traffic datasets. Concepts from multilinear algebra and computational topology will be investigated to rigorously quantify the effects of extreme events on the transportation system. The developed methods will be used to construct "signatures," which are interpretable patterns in the congestion level of a citywide road network, and "barcodes," which summarize the network connectivity. The signatures and barcodes will be designed to better quantify the spatiotemporal effects of extreme events as deviations from typical congestion patterns and connectivity structures. The developed methods will be applied on large publically available mobility datasets in US communities.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
Nonlinear Optimal Velocity Car Following Dynamics (II): Rate of Convergence In the Presence of Fast Perturbation
非线性最优速度汽车跟随动力学(二):存在快速扰动时的收敛率
DOI: 10.23919/acc45564.2020.9147244
发表时间: 2020
期刊: Nonlinear Optimal Velocity Car Following Dynamics (II
影响因子: --
作者: [Zinat Matin, Hossein Nick, Sowers, Richard B.]
通讯作者: Sowers, Richard B.
Nonlinear Optimal Velocity Car Following Dynamics (I): Approximation in Presence of Deterministic and Stochastic Perturbations
非线性最优速度汽车跟随动力学(一):存在确定性和随机扰动时的近似
DOI: 10.23919/acc45564.2020.9147363
发表时间: 2020
期刊: 2020 American Control Conference (ACC
影响因子: --
作者: [Zinat Matin, Hossein Nick, Sowers, Richard B.]
通讯作者: Sowers, Richard B.
A Data-Integration Analysis on Road Emissions and Traffic Patterns
道路排放和交通模式的数据集成分析
DOI: 10.1007/978-3-030-63393-6_34
发表时间: 2020
期刊: Smoky Mountains Computational Sciences and Engineering Conference
影响因子: --
作者: [Qu, A., Wang, Y., Hu, Y., Wang, Y., and Baroud, H.]
通讯作者: and Baroud, H.
DOI: 10.23919/acc50511.2021.9483012
发表时间: 2021
期刊: 2021 American Control Conference (ACC
影响因子: --
作者: [Matin, Hossein Nick, Sowers, Richard B.]
通讯作者: Sowers, Richard B.
7
    I-Corps: Real-time anxiety detection and modulation using wearables
    I-Corps: Data Analytics for Hand-Picked Agriculture
    BECS: Rare Systematic Risk in Markets: Modelling, Theory and Computation
    AMC-SS, Collaborative Research: Explorations in Stochastic Moving Boundary Value Problems
    海外基金