13.5.6 Calibrating System Performance

The third calibration step is to calibrate traffic performance in the model to local conditions. Speed, density, travel time, and queue lengths are often used in comparison. It is recommended that system performance is modeled to meet established calibration targets. Methods for calibrating system performance on a freeway are shown here:
Criteria:
  • Car-following sensitivity factor, carfollowing sensitivity multiplier, lag acceleration and deceleration time, and Pitt car following constant
    – these factors are described in detail under the “Calibrating Capacity at Bottlenecks” section and are adjusted to calibrate system performance.
  • Time to complete lane change
     –A global parameter that represents the time a vehicle takes to change lanes. A higher value means the lane change takes longer, but this generally leads to a smoother system performance.
Methods for calibrating system performance on arterials are shown here:
  • Mean discharge headway, mean startup delay, acceptable gap in oncoming traffic (left turns and right turns), and cross-street acceptable gap distribution (near-side and far-side)
     – these factors are described in detail under the “Calibrating Capacity at Bottlenecks” section and are adjusted to calibrate system performance.
  • Spillback probabilities
     – A global parameter that impacts the probability that a vehicle enters an intersection with downstream queues, blocking the intersection.
  • Time to react to sudden deceleration of lead vehicle
    – A global parameter that represents the time it takes for vehicle to begin decelerating after the lead vehicle suddenly decelerates. A higher value represents declined system performance.
Additional information on CORSIM calibration is provided in FHWA Traffic Analysis Toolbox, Volume IV: Guidelines for Applying CORSIM Microsimulation Modeling Software, available here:
Appendix N, Section 4 – External References (Reference 2)
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