Optimizing Information Value in Heterogeneous Multi-agent Transportation Systems (OPTIMA)
Optimizing Information Value in Heterogeneous Multi-agent Transportation Systems (OPTIMA)
批准号:
2041446
负责人:
Zhaomiao Guo
金额:
$35.15万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-01-01 至 2024-12-31
中文摘要
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英文摘要
This project addresses the use of advanced sensing, communications, and computing technologies in studying value of information in transportation systems made up of heterogeneous traffic (cars, autonomous and connected vehicles, buses, bicycles, etc.) The wealth of data available on these systems enables new approaches to information provisioning that have the potential to improve transportation system efficiency, reliability, and resilience. The project develops a unified modeling framework for information provision considering heterogeneous non-cooperative stakeholders and addresses three critical questions: (1) How do we model adaptive behavior of different traffic components in response to evolving information updates? (2) What are the limits of positive and negative information on systems efficiency, reliability, and resilience? (3) Given limited resources, what, when, and where should the information be communicated with which groups of stakeholders to optimize system performance? The project develops the theoretical foundation to study information provisioning over heterogeneous multi-agent transportation networks and provides critical insights on information sensing, sharing, and protection for smart mobility. The approach integrates stochastic multi-agent optimization, traffic network equilibrium modeling, and variational analysis to study value of information and information design for modern multi-modal transportation systems. The project will leverage recent theoretical advancements on convexification, decomposition, and approximation theories to cope with the computational challenges brought by multi-agent interaction, multi-stage decision making, and multi-dimensional scenarios. The project leverages collaborations with the University of Central Florida (UCF) transportation system, City of Orlando, and Argonne National Laboratory. The project will also develop educational materials for a broad audience and support the development of a new generation of transportation engineers.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.
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DOI:
10.1016/j.trc.2022.103777
发表时间:
2020-05
期刊:
Transportation Research Part C: Emerging Technologies
影响因子:
--
作者:
[Fatima Afifah;Zhaomiao Guo]
通讯作者:
Fatima Afifah;Zhaomiao Guo
DOI:
10.1016/j.trc.2023.104242
发表时间:
2023-04
期刊:
Transportation Research Part C: Emerging Technologies
影响因子:
--
作者:
[Sina Baghali;Zhaomiao Guo;Julio Deride;Yueyue Fan]
通讯作者:
Sina Baghali;Zhaomiao Guo;Julio Deride;Yueyue Fan
Co-optimization of charging scheduling and platooning for long-haul electric freight vehicles
长途电动货运车辆充电调度与队列协同优化
DOI:
10.1016/j.trc.2022.104009
发表时间:
2023
期刊:
Transportation Research Part C: Emerging Technologies
影响因子:
--
作者:
[Alam, Md Rakibul, Guo, Zhaomiao]
通讯作者:
Guo, Zhaomiao
DOI:
10.1016/j.trc.2023.104075
发表时间:
2023-04
期刊:
Transportation Research Part C: Emerging Technologies
影响因子:
--
作者:
[Fatima Afifah;Zhaomiao Guo;M. Abdel-Aty]
通讯作者:
Fatima Afifah;Zhaomiao Guo;M. Abdel-Aty
CAREER: A Decentralized Optimization Framework for Next-Gen Transportation and Power Systems with Large-scale Transportation Electrification
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批准号:2237413
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项目类别:Standard Grant
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资助金额:$52.58万
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财政年份:2023
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负责人:Zhaomiao Guo
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依托单位:
国内基金
海外基金
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
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批准号:--
-
项目类别:外国青年学者研究基金项目
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资助金额:--
-
批准年份:2024
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负责人:江洋子
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依托单位:
Exploring the Intrinsic Mechanisms of CEO Turnover and Market Reaction: An Explanation Based on Information Asymmetry
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批准号:W2433169
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项目类别:外国学者研究基金项目
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资助金额:--
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批准年份:2024
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负责人:HAOFEI ZHANG
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依托单位:
SCIENCE CHINA Information Sciences
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批准号:61224002
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项目类别:专项基金项目
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资助金额:24.0万元
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批准年份:2012
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负责人:宋扉
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依托单位: