2012•Canadian Journal of Civil EngineeringRequires access

Passenger car equivalents of trucks on four-lane rural freeways under lane restriction and different traffic conditions

Ciprian Alecsandru, Sherif Ishak, Yan Qi

Open publisher page 20 citations

Abstract

Truck lane restriction and differential speed limits for trucks and passenger cars are becoming more common policies to improve freeway operations and safety. The most recent edition of the Highway Capacity Manual (HCM) recognizes that the passenger car equivalent (ET) values may differ with various traffic conditions, but does not explicitly address how ET values may be impacted by truck lane restrictions or differential speed limit policies. This study developed a flow-based methodology to determine ET for trucks under truck lane restriction policies and different levels of demand and traffic composition. A simulation model (VISSIM) was calibrated to reproduce ET in HCM on a level terrain freeway segment and then used to simulate various scenarios to capture the effect of demand flow rate, truck percentage, and compliance ratio to lane restriction, all under the enforcement of differential speed limit policy. The results showed that ET increases as the compliance ratio increases, regardless of the truck percentage and demand flow rate. For a given traffic flow rate, ET decreases as the truck percentage increases. Moreover, regardless of the compliance ratio to lane restriction and the truck percentage, ET increases with the demand flow rate. The statistical analysis revealed that the truck percentage has a significant effect on ET for most cases, except when the truck percentage exceeds 30%. The results also showed significant differences in ET for all demand flow rates at 95% confidence level. The study also developed linear regression models for each level of service to estimate the value of ET as a function of the truck percentage and compliance ratio.

About this research paper

What this paper is about

Truck lane restriction and differential speed limits for trucks and passenger cars are becoming more common policies to improve freeway operations and safety. The most recent edition of the Highway Capacity Manual (HCM) recognizes that the passenger car equivalent (ET) values may differ with various traffic conditions, but does not explicitly address how ET values may be impacted by truck lane restrictions or differential speed limit policies. This study developed a flow-based methodology to determine ET for trucks under truck lane restriction policies and different levels of demand and traffic composition. A simulation model (VISSIM) was calibrated to reproduce ET in HCM on a level terrain freeway segment and then used to simulate various scenarios to capture the effect of demand flow rate, truck percentage, and compliance ratio to lane restriction, all under the enforcement of differential speed limit policy. The results showed that ET increases as the compliance ratio increases, regardless of the truck percentage and demand flow rate. For a given traffic flow rate, ET decreases as the truck percentage increases. Moreover, regardless of the compliance ratio to lane restriction and the truck percentage, ET increases with the demand flow rate. The statistical analysis revealed that the truck percentage has a significant effect on ET for most cases, except when the truck percentage exceeds 30%. The results also showed significant differences in ET for all demand flow rates at 95% confidence level. The study also developed linear regression models for each level of service to estimate the value of ET as a function of the truck percentage and compliance ratio.

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Available abstract

Truck lane restriction and differential speed limits for trucks and passenger cars are becoming more common policies to improve freeway operations and safety. The most recent edition of the Highway Capacity Manual (HCM) recognizes that the passenger car equivalent (ET) values may differ with various traffic conditions, but does not explicitly address how ET values may be impacted by truck lane restrictions or differential speed limit policies. This study developed a flow-based methodology to determine ET for trucks under truck lane restriction policies and different levels of demand and traffic composition. A simulation model (VISSIM) was calibrated to reproduce ET in HCM on a level terrain freeway segment and then used to simulate various scenarios to capture the effect of demand flow rate, truck percentage, and compliance ratio to lane restriction, all under the enforcement of differential speed limit policy. The results showed that ET increases as the compliance ratio increases, regardless of the truck percentage and demand flow rate. For a given traffic flow rate, ET decreases as the truck percentage increases. Moreover, regardless of the compliance ratio to lane restriction and the truck percentage, ET increases with the demand flow rate. The statistical analysis revealed that the truck percentage has a significant effect on ET for most cases, except when the truck percentage exceeds 30%. The results also showed significant differences in ET for all demand flow rates at 95% confidence level. The study also developed linear regression models for each level of service to estimate the value of ET as a function of the truck percentage and compliance ratio.

Key concepts: Truck, Transport engineering, Traffic flow (computer networking), Speed limit, VisSim, Differential (mechanical device), Automotive engineering, Computer science

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