2003Journal of Transportation EngineeringRequires access

Guidelines for Estimating Capacity at Freeway Reconstruction Zones

Ahmed Al‐Kaisy, Fred L. Hall

Open publisher page 89 citations

Abstract

This paper reports findings from recent investigations into freeway capacity at several reconstruction zones in Ontario, Canada. The aim is to provide guidelines for estimating freeway capacity at reconstruction sites. Findings are presented in two parts. The first involved results of individual investigations to estimate a base capacity at freeway reconstruction sites and the individual effect of several important factors that are believed to affect this capacity, namely; the effect of heavy vehicles, driver population, rain, site configuration, work activity at site, and light condition. In the second part, attempts to model work zone capacity are presented. Initially, two types of “site-specific” capacity models were developed using different analytical techniques at sites that have the most extensive and comprehensive capacity data. Finally, a “generic” capacity model for freeway reconstruction sites is proposed based on results from the individual investigations and the site-specific models. The proposed model suggests a base capacity value of 2,000 passenger cars per hour per lane for reconstruction sites under favorable conditions. Heavy vehicles and driver population were found to have the most significant effect on capacity.

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What this paper is about

This paper reports findings from recent investigations into freeway capacity at several reconstruction zones in Ontario, Canada. The aim is to provide guidelines for estimating freeway capacity at reconstruction sites. Findings are presented in two parts. The first involved results of individual investigations to estimate a base capacity at freeway reconstruction sites and the individual effect of several important factors that are believed to affect this capacity, namely; the effect of heavy vehicles, driver population, rain, site configuration, work activity at site, and light condition. In the second part, attempts to model work zone capacity are presented. Initially, two types of “site-specific” capacity models were developed using different analytical techniques at sites that have the most extensive and comprehensive capacity data. Finally, a “generic” capacity model for freeway reconstruction sites is proposed based on results from the individual investigations and the site-specific models. The proposed model suggests a base capacity value of 2,000 passenger cars per hour per lane for reconstruction sites under favorable conditions. Heavy vehicles and driver population were found to have the most significant effect on capacity.

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Available abstract

This paper reports findings from recent investigations into freeway capacity at several reconstruction zones in Ontario, Canada. The aim is to provide guidelines for estimating freeway capacity at reconstruction sites. Findings are presented in two parts. The first involved results of individual investigations to estimate a base capacity at freeway reconstruction sites and the individual effect of several important factors that are believed to affect this capacity, namely; the effect of heavy vehicles, driver population, rain, site configuration, work activity at site, and light condition. In the second part, attempts to model work zone capacity are presented. Initially, two types of “site-specific” capacity models were developed using different analytical techniques at sites that have the most extensive and comprehensive capacity data. Finally, a “generic” capacity model for freeway reconstruction sites is proposed based on results from the individual investigations and the site-specific models. The proposed model suggests a base capacity value of 2,000 passenger cars per hour per lane for reconstruction sites under favorable conditions. Heavy vehicles and driver population were found to have the most significant effect on capacity.

Key concepts: Carrying capacity, Population, Transport engineering, Work (physics), Computer science, Environmental science, Engineering, Biology

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