详情

Macroscopic Fundamental Diagram Estimation using Loop-Detector Data (Project I6)

项目名称：	Macroscopic Fundamental Diagram Estimation using Loop-Detector Data (Project I6)
摘要：	This project aims to examine the empirical estimation approach of the Macroscopic Fundamental Diagram (MFD) using loop detector data. The MFD give the network-wide relationship between average traffic variables, and has become an invaluable tool for congestion management on large transportation networks. However, deriving the MFD using the empirical data is challenging since (1) the required loop detector data is not available in most of the cities, (2) in the networks with available loop detector data, the loop detectors cover only a fraction of streets in the network, and (3) the data coming from various loop detectors is prone to bias and inaccuracy, which makes the data cleaning and processing cumbersome. This project will rely on the recently published loop detector data from more than 40 cities over the globe and simulation experiments to investigate three main impacting factors on the network MFD: (1) the distribution of the loop detectors over the network, (2) the distribution of loop detectors on the links, and (3) the extent of the coverage area of the loop detectors and its relationship with the accuracy of the resulting MFD. As a result of this project, we aim to develop a robust method to accurately estimate the network MFDs considering the aforementioned impacting factors.
状态：	Active
资金：	101368
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)
项目负责人：	Tucker-Thomas, Dawn
执行机构：	Georgia Institute of Technology
主要研究人员：	Laval, Jorge
开始时间：	20220215
预计完成日期：	20230501
主题领域：	Highways；Operations and Traffic Management；Planning and Forecasting