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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  • English

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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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