Calibration of CORSIM models under saturated traffic flow conditions.
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Calibration of CORSIM models under saturated traffic flow conditions.

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  • Abstract:
    This study proposes a methodology to calibrate microscopic traffic flow simulation models.

    The proposed methodology has the capability to calibrate simultaneously all the calibration

    parameters as well as demand patterns for any network topology. These parameters include global and

    local parameters as well as driver behavior and vehicle performance parameters; all based on multiple

    performance measures, such as link counts and speeds. Demand patterns are included in the

    calibration framework in terms of turning volumes. A Simultaneous Perturbation Stochastic

    Approximation (SPSA) algorithm is proposed to search for the vector of the model’s parameters that

    minimizes the difference between actual and simulated network states. Previous studies proposed

    similar methodologies; however, only a small number of calibration parameters were considered, and

    none of the demand values. Moreover, an extensive and a priori process was used in order to choose

    the subset of parameters with the most potential impact.

    In the proposed methodology, the simultaneous consideration of all model parameters and

    multiple performance measures enables the determination of better estimates at a lower cost in terms

    of a user’s effort. Issues associated with convergence and stability are reduced because the effects of

    changing parameters are taken into consideration to adjust them slightly and simultaneously. The

    simultaneous adjustment of all parameters results in a small number of evaluations of the objective

    function. The experimental results illustrate the effectiveness and validity of this proposed

    methodology. Three networks were calibrated with excellent results. The first network was an arterial

    network with link counts and speeds used as performance measurements for calibration. The second

    network included a combination of freeway ramps and arterials, with link counts used as performance


    Considering simultaneously arterials and freeways is a significant challenge because the two

    models are different and their parameters are calibrated at the same time. This represents a higher

    number of parameters, which increases the complexity of the optimization problem. A proper solution

    from all feasible solutions becomes harder to find. The third network was an arterial network, with

    time-dependent link counts and speed used as performance measurements. The same set of calibration

    parameters was used in all experiments. All calibration parameters were constrained within reasonable

    boundaries. Hence, the design and implementation of the proposed methodology enables the

    calibration of generalized micro-simulation traffic flow simulation models.

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