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this post aims to show how dynamic assignment routing in vissim works using the same dataset and scenarios as outlined in a previous post. we will also show the relationship between the number of final assignments (uniform (path) and equilibrium assignment) on the path file and the number of intersections per trip (expressed as vehicle trips).

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in order to conduct the following analysis and experiments we first need to prepare the dataset and the required parameters in our simulation tool. in this post we are going to use the same dataset as introduced in the previous post. in the next post we will focus on dynamic assignment, so if you havent yet read that one, you might want to do it first. feel free to jump to part 2

the only differences are the addition of the times at which the vehicles actually arrive and depart at the different intersections (inclusive of the arrival time of the next vehicle) in order to calculate the total time at the intersections. we have also divided the dataset into smaller packages to make it faster to process.

for a detailed discussion of dynamic assignment please refer to the kock, j. / artz, h. and coombs, r. (2003) dynamic assignment routing in operations research. in: experimental methods of choice based computation in operations research ed. by kock, j. and pesch, t. (springer, berlin) volume 4303.

in stochastic assignment, the source node is the node that is assigned the task at the next iteration step. for example, in a single iteration, if node 1 is assigned a task, then node 1 is the source for the next iteration step. this relationship between assignment and the iteration continues until the loop is finished.