Testing and Benchmarking of Microscopic Traffic Flow Models

Abstract

Microscopic simulation models are becoming increasingly important tools in modelling transport systems. There are large number of available models used in many countries. The important 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 models for example. The aim of this paper is to present recent progress in calibrating more than a dozen microscopic traffic flow models with very different data sets conducted by DGPS-equipped cars (Differential Global Positioning System), loop detectors and human observers. Different approaches to measure the errors the models produce in comparison to reality are compared. It can be stated that from a microscopic point of view errors of about 15-20 % in headway- and travel time-estimation and about 2-7 % in speed-estimation of individual vehicles in the car following process seem to be the minimal reachable level. Furthermore, the larger the simulation horizon is, the smaller the diversity of the analyzed models become in comparison to the diversity in the driver behaviour. Most interesting, no model cold be denoted to be the best and especially highly sophisticated models did not produce better results than very simple ones.