EconPapers    
Economics at your fingertips  
 

Modular Neural Network Architecture for Detection of Operational Problems in Urban Arterials

Sarosh Islam Khan

University of California Transportation Center, Working Papers from University of California Transportation Center

Abstract: In recent years, transportation research has revealed that problems of widespread congestion cannot be solved by building more roads or by expanding existing infrastructure. A significant part of the solution lies in better management of traffic. One of the principal thrusts of the new national program on Intelligent Transportation Systems (ITS) is Advanced Transportation Management Systems (ATMS). To facilitate better management, recent research has focused on continuous monitoring of traffic to ascertain the 'normal' level of congestion and to provide an understanding of how it forms and spreads. Techniques for rapidly detecting incidents have become a vital link in the management of traffic.

Keywords: Social; and; Behavioral; Sciences (search for similar items in EconPapers)
Date: 1995-01-01
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.escholarship.org/uc/item/4mx432cn.pdf;origin=repeccitec (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:uctcwp:qt4mx432cn

Access Statistics for this paper

More papers in University of California Transportation Center, Working Papers from University of California Transportation Center Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().

 
Page updated 2025-06-08
Handle: RePEc:cdl:uctcwp:qt4mx432cn