POWRE: Scaling the Two-Fluid Model of Town Traffic to Characterize Traffic Flow Through Signalized Intersections

9973788琼斯智能交通系统（ITS）代表了交通系统设计和运行方式的根本转变。智能交通系统项目的效益在不同的地理尺度上累积，但没有一种交通流量质量模型能够在不同的尺度上评估这些效益。一个能够对不同运输系统规模的交通流量质量进行量化的模型，将有利于评估智能交通系统项目在局部和全系统影响方面的效益和运作。这种可扩展的模型有可能极大地增强我们对交通流控制过程的理解。该项目由POWRE计划支持，研究城镇交通的双流体模型，这是一种似乎具有可扩展特性的模型。该模型的可扩展性将通过利用机器视觉处理的数据收集和分析程序进行调查。该研究有望为信号交叉口的交通流研究提供一种新的模型。与双流体模型的可扩展性相关的分析工作以及在机器视觉处理方面获得的经验将扩展PI的研究能力，并使她能够在未来从事与其他交通流模型的可扩展性相关的工作

9973788JonesIntelligent transportation systems (ITS) represent a fundamental shift in how transportation systems are designed and operated. Benefits from ITS projects accrue at different geographic scales, yet no one model of traffic flow quality is able to assess these benefits at various scales. A model that is capable of quantifying the quality of traffic flow across scales of transportation systems will be beneficial in assessing the benefits and operations of ITS projects in terms of both localized and system-wide effects. Such a scalable model has the potential to greatly enhance our understanding of the processes governing traffic flow. This project, which is supported under the POWRE Program, investigates the two-fluid model of town traffic, which is one model that appears to have scalable properties. The scalability of this model will be investigated through a program of data collection and analysis that utilizes machine vision processing. The research is expected to provide a novel model for traffic flow through signalized intersections. The analytical work related to the scalability of the two-fluid model and the experienced gained with machine vision processing will expand the research capabilities of the PI and will allow her to do future work related to the scalability of other traffic flow models.***