EXPLORING THE VIABILITY OF NONCONVENTIONAL CRASH MODELING TECHNIQUES IN ENHANCING TRAFFIC SAFETY RESEARCH
This dissertation examines the use of innovative modeling techniques including several artificial neural networks (ANN) and statistical models in order to study drivers' injury severity, crash location, and future crash trends in the U.S. A variety of models were applied to study driver's injury severity at roadway sections,signalized intersections,and toll plazas. The analysis was extended to study the location for crashes that occurred in the vicinity of toll plazas on the Orlando-Orange County expressway system using 1999 and 2000 crash reports. It was found, among the results, that vehicles equipped with automated toll collection devices, particularly medium to heavy duty trucks, have a higher risk of experiencing a crash at the toll plaza. It was also found that mainline toll plazas have a higher percentage of crash occurrences upstream of the toll plaza structure.
- Publication Date: 2002. UMI Company, Ann Arbor MI. Remarks: Thesis (Ph. D.)--University of Central Florida, 2002. Abstract also in: Dissertation abstracts international. B. Vol. 63 no. 2 (August 2002), p. 914. Format: website
University of Central Florida, Orlando4000 Central Florida Boulevard
Orlando, FL United States 32816-2450
- Abdelwahab, Hassan Tahsin
- Publication Date: 2002
- Pagination: 244 p.
- TRT Terms: Automated toll collection; Crashes; Fuzzy systems; Neural networks; Risk assessment
- Subject Areas: Safety and Human Factors;
- Accession Number: 00962348
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Report/Paper Numbers: AAT 3042939 (UMI order #)
- Files: PATH
- Created Date: Sep 2 2003 12:00AM