CAREER: Improved Continuum Models of Vehicular Traffic Flow

职业：改进的车辆交通流连续体模型

• 批准号: 9984239
• 负责人: Michael Zhang
• 金额: $ 20万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-07-15 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9984239&HistoricalAwards=false
• 关键词: CAREER; Improved; Continuum; Models; Vehicular

PI: Michael H. Zhang, University of California, Davis Proposal Number: 9984239 Proposal Title:Improved Continuum Models of Vehicular Traffic Flow Project Abstract: This research seeks to expand the understanding of various critical phenomena in vehicular traffic flow and develops improved theories to model them. Comprising of heterogeneous intelligent "particles" -vehicles driven by diverse people, traffic flow exhibits complex dynamic patterns. Although some aspect of traffic flow, such as shock waves, is well understood and supports the well known traffic flow theory of kinematic waves, many other phenomena that are critical to traffic flow applications are not well understood. These include the laminar flow to stop-and-go flow transitions, stop-start waves, and phantom traffic jams. This research proposes to 1) better understand the nature of the aforementioned critical phenomena, 2) develop improved traffic theories to model these phenomena, and 3) apply the developed theories to better manage traffic congestion and reduce vehicle emissions. In the research, experimental evidence is carefully examined and past developments of traffic flow theory are scrutinized to gain insights on driver behavior and possible directions of new theory development. Improved theories are then developed based on a sound understanding of both driver behavior and existing theories, rigorously analyzed and carefully validated with experimental data. The success of this research can lead to a better understanding of traffic flow and greatly increase the ability to monitor, model and control traffic flow. These advances in turn lead to more efficient use of existing road infrastructure and better air quality planning.

PI：Michael H.张，加州大学戴维斯分校提案编号：9984239提案标题：改进连续模型的车辆交通流项目摘要：这项研究旨在扩大理解的各种关键现象，在车辆交通流和发展改进的理论来模拟它们。交通流是由不同的智能“粒子”--由不同的人驾驶的车辆--组成的，呈现出复杂的动态模式。虽然交通流的某些方面，如冲击波，是很好地理解和支持运动波的著名的交通流理论，许多其他现象，是交通流应用的关键是没有很好地理解。这些包括层流到走走停停的流动过渡，停止启动波和幻影交通堵塞。本研究建议：1）更好地理解上述关键现象的本质，2）开发改进的交通理论来模拟这些现象，3）应用开发的理论来更好地管理交通拥堵并减少车辆排放。在研究中，实验证据仔细检查和过去的发展交通流理论的审查，以获得洞察驾驶员的行为和新的理论发展的可能方向。改进的理论，然后开发基于对驾驶员行为和现有理论的充分理解，严格分析和仔细验证实验数据。这项研究的成功可以导致更好地了解交通流，并大大提高监测，建模和控制交通流的能力。这些进步反过来又导致更有效地利用现有的道路基础设施和更好的空气质量规划。