Towards a benchmarking of Microscopic Traffic Flow Models

Abstract

Several microscopic traffic models have been tested with a publicly available data set. The task was to predict the travel times between sever observers along a one-lane rural road, given as boundary conditions the flow into this road and the flow out of it. By using nonlinear optimization, for each of the models the best matching set of parameters have been estimated. For this particular data set, the models that performed best are the ones with the smalles number of parameters. The average error rate of the models is about 16 %, however, this value is not very reliable: the error rate fluctuates between 2.5 and 25 % for different parts of the data set.