Detecting the Breakdown of Traffic
2006
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Detecting the Breakdown of Traffic
Authors
Published Date
2006
Publisher
Type
Working Paper
Abstract
Timely traffic prediction is important in advanced traffic management systems to make possible rapid and effective response by traffic control facilities. From the observations of traffic flow, the time series present repetitive or regular behavior over time that distinguishes time series analysis of traffic flow from classical statistics, which assumes independence over time. By taking advantage of tools in frequency domain analysis, this paper proposes a new criterion function that can detect the onset of congestion. It is found that the changing rate of the cross-correlation between density dynamics and flow rate determines traffic transferring from free flow phase to the congestion phase. A definition of traffic stability is proposed based on the criterion function. The new method suggests that an unreturnable transition will occur only if the changing rate of the cross-correlation exceeds a threshold. Based on real traffic data, detection of congestion is conducted in which the new scheme performs well compared to previous studies.
Description
Related to
Replaces
License
Collections
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Zou, Xi; Levinson, David M. (2006). Detecting the Breakdown of Traffic. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/179810.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.