An investigation of freeway capacity before and during incidents

Abstract

This paper investigates freeway capacity before and during incidents. Data were obtained for approximately 1 year from five freeway facilities in North America. The data included flows, speeds, weather conditions, as well as incident information (location, duration, and lanes affected). Maximum throughput-related values were obtained to estimate capacity under non-incident conditions as well as under incident conditions. Under non-incident conditions, the data indicate that three-lane freeways are the most efficient in terms of per lane capacity. Measurements of capacity during incident conditions are provided by type of facility and number of lanes affected. These capacities are compared to values reported in previous research. Next, two sets of multiple linear regression models were developed to estimate the capacity under incident conditions and the capacity reduction (i.e. the difference between capacity under non-incident conditions and capacity under incident conditions) during incidents. Each of the two sets of models is developed for the three sites combined and for the Portland site on its own (because it has detailed information on the number of lanes blocked by incidents), based on factors such as the incident category, and the total number of lanes.

Keywords:

• Freeway capacity
• Non-incident conditions
• Incident conditions
• Breakdown
• Multiple regression models
• Incident capacity

This research was mainly based on data collected for the NCHRP 3-87 Project (Elefteriadou et al., 2009). The authors would like to acknowledge Dr. Alexandra Kondyli who was responsible for data collection under that project. We would also like to thank David Tsui of the Ontario Ministry of Transportation, Professor Baher Abdulhai of University of Toronto, Rich Bailey of Oregon Department of Transportation, Simon Foo at McMaster University in Canada, Professor Fred L. Hall of University of Calgary, for their generous help in providing the data. The authors would also like to acknowledge the reviewers for their invaluable comments.