Calibration and Validation of Microscopic Traffic Flow Models

Abstract

Microscopic simulation models are becoming increasingly important tools in modeling transport systems. There are a large number of available models used in many countries. the most difficult stage in the development and use of such models is the calibration and validation of the microscopic sub-models describing the traffic flow, such as the car following, lane changing and gap acceptance models. This difficulty is due to the lack of suitable methods for adapting models to empirical data. The aim of this paper is to present recent progress in calibratin a number of microscopic traffic flow models. By calibrating and validating various models using the same data sets, the models are directly comparable to each other. This sets the basis for a transparent benchmarking of those models. Furthermore, the advantages and disadvantages of each model can be analyzed better to develop a more realistic behavior of the simulated vehicles In this work various microscopic traffic flow models have been tested from a very microscopic point of view concerning the car-follwing behavior and gap-acceptance. The data used for calibration and validation is from car-following experiments performed in Japan in October 2001. The data have been collected by letting nine DGPS-equipped cars follow a lead car driving along a 3 km test track for about 15-30 minutes. So one gets the positions and speeds of each car in time intervals of 0.1 seconds. The experiment was repeated eight times letting the leading driver perform various driving in waves and emulating many acceleations/decelerations as they are typical at intersections. To minimize driver-dependent correlations between the data sets, the drivers were exchanged between the cars regularly after each experiment