Excellence in Research/Collaborative Research: Modeling Transportation Choices Under the Presence of Real-time Information Using Simulated-based Virtual Experiments

卓越的研究/合作研究:使用基于模拟的虚拟实验在实时信息存在下对交通选择进行建模

基本信息

  • 批准号:
    2200633
  • 负责人:
  • 金额:
    $ 20.56万
  • 依托单位:
  • 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
  • 起止时间:
    2022-10-01 至 2025-09-30
  • 项目状态:
    未结题

项目摘要

This Excellence in Research (EiR) project will investigate the impacts of real-time information on the sequential choice-making behavior of travelers using transportation infrastructure and services in smart cities. Smart cities of the future are envisioned as a place where digitalization of day-to-day services, interconnectedness of sensing technologies, and intelligent algorithms for city management lead to innovative socioeconomic and socio-technical growth. Travelers using transportation services in these “cities of the future” make various choices in a dynamically evolving system such as the choice of destination, departure time, mode of travel, travel route, and/or parking location. This project studies the interrelation of choices and the impact of real-time information on choices by adopting a data-driven modeling approach. The tools and models developed as part of this project will enable data-driven choice modeling and management of future transportation systems and will contribute toward NSF’s mission of promoting the progress of science and advancing the nation’s prosperity and welfare. Beyond its intellectual merit, this project will (a) enable underrepresented students at Historically Black Colleges and Universities to participate in research on future transportation systems, (b) develop educational tools for accurate choice modeling of travelers in response to real-time information, and (c) develop incentives that guide the design and development of smart cities of the future. Eventually, the project will enable agencies to perform better short-term and long-term transportation planning, which will have a substantial societal impact.As its primary goal, the project will explain travelers’ choices under the presence of real-time information using an advanced econometric framework that identifies the factors affecting these choices, including time-varying characteristics of emerging technologies, level-of-service, and socio-demographic variables. This project will contribute to the choice modeling theory and experiments by (1) explicitly incorporating real-time information in sequential dynamic choices of travelers, (2) modeling the impact of the error-prone or aggregated information on travel choices through D-efficient experimental design, and (3) developing a policy-sensitive tool that will be able to evaluate a wide range of smart-city-related transportation policies. This project will adopt innovative techniques such as creating a simulation-based virtual environment for experiments on choices made by travelers in a dynamically evolving system, and developing and calibrating robust mathematical models useful for accurate forecasting of travel behavior. The focus applications in this project will also provide guidance on optimization and operations of civil infrastructure systems and will enable methodological evaluation of transportation policies in Smart Cities that may impact travel behavior over the long term.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.
这个卓越研究(EiR)项目将调查实时信息对使用智能城市中交通基础设施和服务的旅行者的顺序选择行为的影响。未来的智慧城市被设想为一个日常服务数字化、传感技术互联和城市管理智能算法带来创新社会经济和社会技术增长的地方。在这些“未来城市”中使用交通服务的旅行者在动态演变的系统中做出各种选择,诸如目的地、出发时间、旅行模式、旅行路线和/或停车位置的选择。本研究采用数据驱动的建模方法,研究选择之间的相互关系以及实时信息对选择的影响。作为该项目的一部分开发的工具和模型将实现数据驱动的选择建模和未来交通系统的管理,并将有助于NSF的使命,促进科学的进步和国家的繁荣和福利。除了其智力价值,该项目将(a)使历史上黑人学院和大学的学生能够参与未来交通系统的研究,(B)开发教育工具,用于响应实时信息的旅行者准确选择建模,以及(c)制定激励措施,指导未来智慧城市的设计和开发。最终,该项目将使各机构能够更好地执行短期和长期交通规划,这将产生重大的社会影响。作为其主要目标,该项目将使用先进的计量经济学框架来解释旅行者在实时信息存在下的选择,该框架确定了影响这些选择的因素,包括新兴技术的时变特征,服务水平,和社会人口统计变量。该项目将通过以下方式为选择建模理论和实验做出贡献:(1)明确地将实时信息纳入旅行者的顺序动态选择中,(2)通过D-有效实验设计对易出错或聚合信息对旅行选择的影响进行建模,以及(3)开发能够评估广泛的智能城市相关交通政策的政策敏感工具。该项目将采用创新技术,例如创建基于模拟的虚拟环境,用于在动态演化系统中对旅行者的选择进行实验,以及开发和校准用于准确预测旅行行为的强大数学模型。该项目的重点应用还将为民用基础设施系统的优化和运营提供指导,并将对可能长期影响出行行为的智能城市交通政策进行方法评估。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Imtiaz Ahmed其他文献

Digital pathology for reporting histopathology samples, including cancer screening samples – definitive evidence from a multisite study
用于报告组织病理学样本(包括癌症筛查样本)的数字病理学——来自多中心研究的明确证据
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    A. Azam;Y. Tsang;Jenny Thirlwall;Peter K Kimani;Shatrughan Sah;K. Gopalakrishnan;Clinton Boyd;Maurice B Loughrey;Paul J Kelly;David P Boyle;Manuel Salto;David Clark;Ian O Ellis;Mohammad Ilyas;Emad A Rakha;Adam Bickers;Ian S D Roberts;Maria Fernanda Soares;Desley A H Neil;A. Takyi;Sinthuri Raveendran;E. Hero;H. Evans;Rania Osman;Khunsha Fatima;Rhian W Hughes;Stuart A McIntosh;Gordon W Moran;Jacobo Ortiz;N. Rajpoot;Ben Storey;Imtiaz Ahmed;Janet A. Dunn;L. Hiller;David R. J. Snead
  • 通讯作者:
    David R. J. Snead
Gemini-the most powerful LLM: Myth or Truth
双子座-最强大的LLM:神话还是真相
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Imtiaz Ahmed;Raisa Islam
  • 通讯作者:
    Raisa Islam
Comparative study of multiscale entropy analysis and symbolic time series analysis when applied to human gait dynamics
多尺度熵分析与符号时间序列分析应用于人体步态动力学的比较研究
Binary Gaussian Copula Synthesis: A Novel Data Augmentation Technique to Advance ML-based Clinical Decision Support Systems for Early Prediction of Dialysis Among CKD Patients
二元高斯 Copula 合成:一种新的数据增强技术,可推进基于 ML 的临床决策支持系统,以早期预测 CKD 患者的透析情况
  • DOI:
    10.48550/arxiv.2403.00965
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    H. Khosravi;Srinjoy Das;Abdullah Al;Imtiaz Ahmed
  • 通讯作者:
    Imtiaz Ahmed
Exploring Hf-mediated surface engineering to enhance Cosub3/subOsub4/sub/Agsub2/subS core-shell nanorods as bifunctional electrocatalysts for water splitting reaction
探索铪(Hf)介导的表面工程以增强Co₃O₄/Ag₂S核壳纳米棒作为水分解反应的双功能电催化剂
  • DOI:
    10.1016/j.fuel.2025.134752
  • 发表时间:
    2025-07-15
  • 期刊:
  • 影响因子:
    7.500
  • 作者:
    Ritu Raj;Imtiaz Ahmed;Gajendra Prasad Singh;Krishna Kanta Haldar
  • 通讯作者:
    Krishna Kanta Haldar

Imtiaz Ahmed的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Imtiaz Ahmed', 18)}}的其他基金

Collaborative Research: CISE-MSI: RCBP-RF: CNS: Enabling Secured and Artificial Intelligence Assisted Cell-Free Communications
合作研究:CISE-MSI:RCBP-RF:CNS:实现安全和人工智能辅助的无细胞通信
  • 批准号:
    2219657
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Excellence in Research: Artificial Intelligence Aided Metasurface Design and Application in Next Generation of Cellular Communication Systems
卓越研究:人工智能辅助超表面设计及其在下一代蜂窝通信系统中的应用
  • 批准号:
    2200640
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Research Initiation Award: Investigation and Design of Terahertz Communication Systems with Artificial Intelligence
研究启动奖:人工智能太赫兹通信系统研究与设计
  • 批准号:
    2200626
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Broadening Instructional Innovation in the Chemistry Laboratory through Excellence in Curriculum Development
合作研究:通过卓越的课程开发扩大化学实验室的教学创新
  • 批准号:
    2337028
  • 财政年份:
    2024
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Continuing Grant
Collaborative Research: Broadening Instructional Innovation in the Chemistry Laboratory through Excellence in Curriculum Development
合作研究:通过卓越的课程开发扩大化学实验室的教学创新
  • 批准号:
    2337027
  • 财政年份:
    2024
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Continuing Grant
Interdisciplinary Clinical Advances and Research Excellence in TMDs (ICARE 4 TMDs) Collaborative
TMD 跨学科临床进展和卓越研究 (ICARE 4 TMD) 协作
  • 批准号:
    10829180
  • 财政年份:
    2023
  • 资助金额:
    $ 20.56万
  • 项目类别:
Collaborative Research: NSF INCLUDES Alliance: Alliance Supporting Pacific Impact through Computational Excellence (ALL-SPICE)
合作研究:NSF 包括联盟:通过卓越计算支持太平洋影响力联盟 (ALL-SPICE)
  • 批准号:
    2217227
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Cooperative Agreement
Collaborative Research: NSF INCLUDES Alliance: Alliance Supporting Pacific Impact through Computational Excellence (ALL-SPICE)
合作研究:NSF 包括联盟:通过卓越计算支持太平洋影响力联盟 (ALL-SPICE)
  • 批准号:
    2217242
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Cooperative Agreement
Excellence in Research/Collaborative Research: Modeling Transportation Choices Under the Presence of Real-time Information Using Simulated-based Virtual Experiments
卓越的研究/合作研究:使用基于模拟的虚拟实验在实时信息存在下对交通选择进行建模
  • 批准号:
    2200590
  • 财政年份:
    2022
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Excellence in Research: Collaborative Research: Detecting Vulnerabilities in Internet of Things with Deep Learning
卓越研究:协作研究:利用深度学习检测物联网漏洞
  • 批准号:
    2101118
  • 财政年份:
    2021
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Excellence in Research: Collaborative Research: Computational Modeling and Experimental Investigation on Multivalent Interaction at Nano-Bio Interface for 2D Materials
卓越研究:协作研究:二维材料纳米生物界面多价相互作用的计算建模和实验研究
  • 批准号:
    2100946
  • 财政年份:
    2021
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Excellence in Research - Collaborative Proposal: Investigation of Quantum Effects and Nanostructures Through Research & Educational Partnership Between NCCU & Howard University
卓越研究 - 合作提案:通过研究调查量子效应和纳米结构
  • 批准号:
    2101121
  • 财政年份:
    2021
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
Collaborative Excellence in Research: Skill Acquisition, Technical Change and Differential Employment and Income Trajectories
卓越的研究协作:技能获取、技术变革以及差异化就业和收入轨迹
  • 批准号:
    2101244
  • 财政年份:
    2021
  • 资助金额:
    $ 20.56万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了