Predicting and Visualizing the Uncertainty Propagations in Traffic Assignments Model Using Monte Carlo Simulation Method

Algorithm 1

Prediction of uncertainty in traffic assignment using Monte Carlo simulation.

Require: ; Zone definition.

    ; Origin definition.

    ; Destination definition.

    ; number of zones.

    ; Matrix of Origin Destination (OD).

    ; Observed value of OD pair.

     Traffic Assignment function.

    ; Observed values of traffic assignment function.

     Number of Links of the transport network.

     Define the Probability Distribution type.

     Parameters range for the probability distribution.

     Number of iterations.

(01) Get samples by the defined probability distribution and

parameters using Monte Carlo procedure.

(02) For do

(03)  For do

(04)    For do

(05)     Get OD matrix randomly.

(06)    end for

(07)  end for

(08) end for

(09) For doRun Visum.

(10)  Get result attribute from traffic assignment function.

(11) end for

(12) For do

(13)  For do

(14)   Get the value of GEH statistic for each iteration.

(15)  end for

(16)  Get the average value of GEH statistic for each link.

(17)  Get the average for each link.

(18)  Get the total bias for each link.

(19)  Get the standard deviation for each link.

(20)  Get the bias lower limit for each link.

(21)  Get the bias upper limit for each link.

(22) end for

(23) For do

(24)  If Then end for

(25)  For doCheck the error and the bias for each iteration.

(26)    If Thenlow variety

Elsehigh variety

(27)    If Thenlow bias

Elsehigh bias

(28)  end for

(29) end for

(30) End