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EAGER: Congestion Mitigation via Better Parking: New Fundamental Models and A Living Lab

EAGER：通过更好的停车缓解拥堵：新的基本模型和生活实验室

基本信息

批准号：
1634136
负责人：
Baosen Zhang
金额：
$ 21.81万
依托单位：
University of Washington
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2019-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1634136&HistoricalAwards=false
关键词：
EAGER Congestion Mitigation via Better

项目摘要

This EAGER project on Smart and Connected Communities focuses on developing new fundamental models of urban parking in order to address issues of congestion that negatively impact mobility and health. Traffic congestions are increasingly becoming bottlenecks to sustainable urban growth as infrastructures are being stretched to their limits. A significant amount-up to 40%-of all surface level traffic in urban areas stems from drivers looking for parking. This project will develop new parking management tools (algorithms for cities and apps for drivers) that allow municipalities to achieve better congestion control and enable drivers to act more efficiently. These tools are more targeted, robust and accurate than the current control scheme of only using price to influence the average occupancy rate over a city. This project will result in fundamental advances in queuing theory and mechanism design. Specifically, the models study circulating traffic at block level resolution and the role of information plays in driver decisions. The three main thrusts of the project are: 1) Develop a queue-flow network model of traffic informed by real data that captures network topology and spatio-temporal behavior. 2) Impose a game theoretic structure on the queue-flow network that captures the strategic nature of heterogeneous users. 3) Create a living lab experimental platform in collaboration with the city of Seattle and industry partners for validation of our theories.This project engages with the City of Seattle, industrial partners such as Sidewalk Labs, and undergraduate students. Seattle will provide data and the opportunities to test and validate the results developed, industrial partners will provide technical support, and students will develop mobile apps and learn how a modern smart city can be managed. If successful, this project provides a demonstration of how cities, academia, and industry can partner to conduct rigorous research that will have short-term, practical impact.

EAGER关于智能和互联社区的项目专注于开发新的城市停车基本模式，以解决对移动性和健康产生负面影响的拥堵问题。随着基础设施的极限使用，交通拥堵日益成为城市可持续发展的瓶颈。在城市地区，高达40%的地面交通量是由司机寻找停车位造成的。该项目将开发新的停车管理工具（城市算法和司机应用程序），使市政当局能够更好地控制拥堵，并使司机能够更有效地采取行动。这些工具比目前仅用价格来影响城市平均入住率的控制方案更有针对性，更强大，更准确。这个项目将导致排队论和机制设计的根本性进步。具体来说，该模型研究循环交通在块级分辨率和信息的作用，在司机的决定。该项目的三个主要目标是：1）开发一个由真实的数据提供信息的业务流网络模型，该模型捕获网络拓扑和时空行为。2)强加一个博弈论的结构，捕获异构用户的战略性质的流量网络。3)与西雅图市和行业合作伙伴合作创建一个生活实验室实验平台，以验证我们的理论。该项目与西雅图市，Sidewalk Labs等行业合作伙伴以及本科生合作。西雅图将提供数据和机会来测试和验证开发的结果，工业合作伙伴将提供技术支持，学生将开发移动的应用程序，并学习如何管理现代智慧城市。如果成功，该项目将展示城市、学术界和工业界如何合作开展严格的研究，并产生短期的实际影响。