课题基金 / 基金详情

CAREER: Using Mobile Sensors for Traffic Knowledge Extraction and Dynamic Network Management

CAREER: Using Mobile Sensors for Traffic Knowledge Extraction and Dynamic Network Management
职业:使用移动传感器进行交通知识提取和动态网络管理
批准号:
1719551
负责人:
Xuegang Ban
金额:
$16.04万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2018-04-30

项目摘要

项目成果

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中文摘要
翻译
学院早期职业发展(Career)项目奖的目标是为交通科学的一个新领域奠定基础,该领域利用并应对使用移动交通传感器进行交通知识提取和动态系统管理的挑战。这项研究将研究如何使用广泛部署的移动传感器来(I)估计/预测干线网络上的交通状态;(Ii)发现正常和灾后情况下的新的交通知识和行为;以及(Iii)利用从移动传感器获得的知识来开发基于路径的动态网络管理策略。这项研究将开发一个基于移动数据的建模框架,丰富现有的基于固定位置传感器的建模技术。它还将开发基于路径的动态网络管理策略的理论、模型和算法,明确考虑来自移动传感器的多重均衡和实时信息,这将架起优化、网络建模和控制理论等多个领域的桥梁。该研究项目有望将当前交通数据收集和建模从基于固定位置传感器的范例转变为基于移动传感器的范例,并将帮助决策者和行业就如何最好地利用移动数据进行知识提取和交通系统管理做出明智的决策。该项目将开发新的教育工具,将基于项目的学习整合到土木工程课程中,并将开发短期课程和研究研讨会,促进学术界、政府机构和工业界之间的沟通。这项工作将开展外联活动,将研究和教育成果传播给广大受众,包括大学和K-12学校的学生,特别是少数族裔大学的学生。该项目还将使用一个由来自多学科背景的成员组成的外部咨询小组,以便研究能够解决一系列广泛的问题,并将结果应用于交通运输以外的其他领域。
英文摘要
The objective of the Faculty Early Career Development (CAREER) program award is to develop the foundations for a new area of transportation science that takes advantage of, and addresses the challenges of using mobile traffic sensors for traffic knowledge extraction and dynamic system management. This research will study the fundamental questions of how to use widely-deployed mobile sensors for (i) estimating/predicting traffic states on arterial networks; (ii) discovering new traffic knowledge and behaviors under normal and post-disaster situations; and (iii) developing path-based dynamic network management strategies utilizing the knowledge obtained from mobile sensors. This research will develop a mobile-data-based modeling framework that will enrich current fixed-location-sensor-based modeling techniques. It will also develop theories, models, and algorithms for path-based dynamic network management strategies, with explicit consideration of multiple equilibria and real time information from mobile sensors, which will bridge various fields such as optimization, network modeling, and control theory.This research project is expected to transform current traffic data collection and modeling from a fixed-location-sensor-based to a mobile-sensor-based paradigm and will help policy makers and industry make informed decisions on how mobile data can be best used for knowledge extraction and traffic system management. This project will develop new educational tools by integrating project-based learning in the civil engineering curriculum and will develop short courses and research seminars that will foster the communication among academia, government agencies, and industry. This work will conduct outreach activities by disseminating research and education outcomes to a wide audience that includes students in universities and K-12 schools, and in particular students in minority universities. This project will also use an external advisory panel with members from multidisciplinary backgrounds so that the research can address a broad set of questions and apply the results to other fields beyond transportation.
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Collaborative Research: Data Poisoning Attacks and Infrastructure-Enabled Solutions for Traffic State Estimation and Prediction
  • 批准号:
    2326340
  • 项目类别:
    Standard Grant
  • 资助金额:
    $33.0万
  • 财政年份:
    2023
  • 负责人:
    Xuegang Ban
  • 依托单位:
Collaborative Research: SaTC: CORE: Small: Privately Collecting and Analyzing V2X Data for Urban Traffic Modeling
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    2034615
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2021
  • 负责人:
    Xuegang Ban
  • 依托单位:
Collaborative Research: Bias Modeling and Estimation of Networked Transportation Data
  • 批准号:
    1825053
  • 项目类别:
    Standard Grant
  • 资助金额:
    $31.77万
  • 财政年份:
    2018
  • 负责人:
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  • 依托单位:
Collaborative Research: Transportation Network Identification: Information Fusion via Stochastic Optimization
  • 批准号:
    1719548
  • 项目类别:
    Standard Grant
  • 资助金额:
    $13.21万
  • 财政年份:
    2016
  • 负责人:
    Xuegang Ban
  • 依托单位:
国内基金
海外基金
Capture and Release of Droplets Using Advanced Materials for High Technology Applications
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    52073127
  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data