Neural network model for automatic traffic incident detection : final report, August 2001.

664264528Final report.PDFTech Reporthttp://ntl.bts.gov/lib/34000/34100/34155/PB2002100535.pdfFHWA/HWY-03/200214690(0)Advanced traffic management systemsIncident managementOhioOhio. Dept. of TransportationAdeli, HojjatOhio State University. Dept. of Civil and Environmental Engineering and Geodetic ScienceOhio. Dept. of TransportationUnited States. Federal Highway AdministrationNTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control DevicesNTL-OPERATIONS AND TRAFFIC CONTROLS-CongestionUS Transportation CollectionAutomatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelligent system approach and several innovative algorithms were developed for solution of the freeway traffic incident detection problem employing advanced signal processing, pattern recognition, and classification techniques. The methodology effectively integrates fuzzy, wavelet, and neural computing techniques to improve reliability and robustness