A New Methodology to Estimate Capacity for Freeway Work Zones

Taehyung Kim, David J. Lovell, and Jawad Paracha

ABSTRACT

The objectives of this study were to investigate various independent factors that contribute to capacity reduction in work zones and to suggest a new methodology to estimate the work zone capacity. To develop the new capacity estimation model, traffic and geometric data were collected at 12 work zone sites with lane closures on four normal lanes in one direction, mainly after the peak-hour during daylight and night.
The multiple regression model was developed to estimate capacity on work zones for establishing a functional relationship between work zone capacity and several key independent factors such as the number of closed lanes, the proportion of heavy vehicles, grade, and the intensity of work activity. The proposed model was compared with existing capacity models and the HCM using the root mean square (RMS) error, and it showed that the new capacity estimation model is better than the others that excluded various key independent factors that might affect work zone capacity.