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ICES: Small: Collaborative Research: Dynamic Parking Assignment Games

ICES: Small: Collaborative Research: Dynamic Parking Assignment Games
ICES:小型:协作研究:动态停车分配游戏
批准号:
1216096
负责人:
Bhaskar DasGupta
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2015-08-31

项目摘要

项目成果

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中文摘要
翻译
几十年来,在许多城市环境中,寻找停车位一直是司机的一大麻烦。例如,在11个主要城市进行的研究显示,寻找路边停车位的平均时间为8.1分钟,平均而言,这些城市的交通拥堵占这些停车位的30%。每个停车位每年产生4,927车辆行驶里程(VMT),通过将此数字乘以城市中的停车位数量(例如,芝加哥35,000人)。 受这些因素的激励,并通过当前的无线通信,传感器网络和移动的计算革命,一个跨学科的团队将调查一些核心算法,博弈论和计算复杂性问题,以解决停车位选择问题。因此,该项目旨在促进更有效的城市交通系统的发展。该方案的技术优点包括对空间资源的实时分布式竞争进行调查和分析。问题的竞争性质导致了一个动态的多玩家博弈理论框架来分析解决方案的质量。研究人员将制定计算问题,研究它们的数学性质,为它们设计有效的算法,并实施由此产生的算法来评估准确性和效率。特别是,部分受到牛顿万有引力定律的启发,研究人员将研究广泛的停车导航策略,粗略地称为引力停车范式。该项目的最终目标是开发应用程序的理论基础,根据停车位的位置,将驾驶员引导到最合适的停车位。该项目的其他组成部分包括通过若干手段将研究和教育结合起来,如课程和课程编制、有效传播研究成果、指导本科生和研究生,以及促进相关研究和教育活动的多样性。
英文摘要
Finding parking has been a major hassle for drivers in many urban environments for decades. For example, studies conducted in 11 major cities revealed that the average time to search for curbside parking was 8.1 minutes and cruising for these parking spaces accounted for 30% of the traffic congestion in those cities, on average. Each parking slot generated 4,927 vehicle miles traveled (VMT) per year, and the overall increase in traffic is obtained by multiplying this number by the number of parking slots in the city (e.g., 35,000 in Chicago). Motivated by these factors and enabled by the current revolution in wireless communication, sensor networks, and mobile computing, an interdisciplinary team will investigate a number of core algorithmic, game-theoretic, and computational complexity issues to address parking slot selection problems. Thus, this project seeks to contribute to development of more efficient urban transportation systems. The technical merits of the proposal include the investigation and analysis of real-time distributed competition for spatial resources. The competitive nature of the problem leads to a dynamic multi-player game-theoretic framework to analyze the quality of a solution. The investigators will formulate computational problems, study their mathematical properties, design efficient algorithms for them, and implement resulting algorithms to assess accuracy and efficiency. In particular, partly inspired by Newton's laws of gravitation, the investigators will research a broad class of parking navigation strategies loosely termed as the Gravitational Parking Paradigms.The final goal of this project is to develop the theoretical underpinnings of applications that, given the locations of parking slots, will guide a driver to a most appropriate parking slot. Other components of the project include the integration of research and education via several means such as course and curriculum development, effective dissemination of research, mentoring undergraduate and graduate students, and promoting diversity in related research and educational activities.
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III: Small: Collaborative Research: Network Analysis and Anomaly Detection via Global Curvatures
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