Motorcycle fatalities and the related fatality rates have been significantly increasing over the last 10 years based on total registrations as a proxy for volumes and usage/exposure. Motorcycle fatalities have become a serious safety issue for the National Highway Transportation Safety Administration (NHTSA) and the Federal Highway Administration (FHWA). According to FHWA data between 1996 and 2005, motorcyclist fatalities increased more than 110 percent and currently account for more than 10 percent of all motor vehicle traffic crash fatalities. The best measure of exposure risk for motor vehicle crashes is based on actual vehicle volumes and vehicle-miles traveled (VMT). Therefore it is critical that timely, complete, and accurate volume and VMT data are collected and reported. Furthermore, beginning in 2008, the reporting of motorcycle travel to the federal Highway Performance Monitoring System (HPMS) is now required for all states. To date, research has indicated that there are significant problems with methodologies currently used to detect motorcycles. Most current detection systems primarily focus on the collection and classification of trucks and automobiles. These systems frequently misclassify motorcycles or miss them altogether, making the data unacceptable for mandated reporting purposes. There is a need for improved methods that could be used by transportation agencies at all levels to assist them in determining the policies and decisions necessary to improve safety and mobility.

 

The objective of this research is to identify, analyze, and recommend the most effective and efficient detection methodologies to obtain more accurate motorcycle volume and VMT-related data.