Joint Parameter and State Estimation Algorithms for Real-time Traffic Monitoring
http://www.purdue.edu/discoverypark/nextrans/research/research_in_progress.php
Record Type: UTC
Traffic congestion is a major problem. As the U.S. population continues to grow and move towards urban areas, the impact of traffic congestion on human mobility, the economy, and the environment is ever increasing. In many cases, solutions to traffic congestion will ultimately depend on improved management of existing infrastructure through the use of innovative, integrated solutions in technology and policy. This research will investigate the problem of simultaneously estimating the traffic state and the traffic model parameters online and in real-time, through the development of a new joint traffic state and parameter estimation algorithm relying on ensemble Kalman filtering.
Start date: 2012/9/1
Status: Active
Contract/Grant Number: DTRT12-G-UTC05
Total Dollars: 107342
Source Organization: Purdue University, West Lafayette
Notes: University of Illinois at Urbana-Champaign
Date Added: 07/12/2012
Index Terms: Traffic congestion, Traffic surveillance, Real time information, Technological innovations, Kalman filtering, Mobility,
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