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The recently completed SHRP 2 L08 project developed methods, guidance, and associated computational engines for incorporating travel time reliability into the Highway Capacity Manual (HCM) analyses. This paper presents an investigation of the use of these products to assess advanced traffic management strategies such as incident management and ramp metering. The paper examines the impacts of input parameters to the traffic flow model and of the scenario generation module incorporated as part of the computational engines of the HCM-based reliability estimation procedure of freeway facilities. The results from the calibration of the traffic flow model of the computational engine indicate that adjusting the capacity values to the measured values based on traffic detector data improves the system's ability to replicate real-world queues and travel times. The results show that the methods used to derive incident attributes in the computational engine affect reliability performance measures, particularly the 95th percentile travel time index and the misery index, which are indicators of the worst 5th percentile conditions on the corridor. The assessment based on modeling results indicates that incident management can significantly reduce the 95th percentile travel time index and the misery index. The assessment of ramp metering shows only a slight improvement in reliability, but this result may be because of the inability of the model to assess adaptive ramp metering, which is the main type of ramp metering in use.

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