Mimic: A Microscopic Simulation Model for Rural Road Traffic
Doktorsavhandling, 1996

The purpose of this dissertation is to outline the theoretical basis of a road traffic simulation model, named Mimic, that constitutes the key elements of a system for estimating road user effects and environmental impacts. The simulation model suggested is a microscopic road traffic simulation model and it is structured to be used for networks of rural roads. The roads and intersections can be of arbitrary geometrical design. The characteristics of the simulation model are described in detail. Mimic is a periodic-scanned microscopic traffic simulation model in which each vehicle and driver has individual characteristics. The status of every vehicle is known at any given moment. A new car-following model has been developed, in which the choice of speed is relative to the speed and acceleration of the vehicle in front in the same platoon, as well as on the driver's desired time headway to the vehicle in front. The car following algorithm is verified by a sensitivity analysis. For this a newly developed computer program, ZIMUTEST, has been used. The time gap distributions and the speed distributions are compared with field data. The time gaps are presumed to be log normally distributed, and the speeds are presumed to be normally distributed.. A lot of statistical tests have been performed, testing the accuracy of different theoretical distributions that can describe these two traffic characteristics. A special computer software have been developed to do these tests, the KSTEST program, performing both a Kolmogorov-Smirnoff test and a Chi-Square test, and the PLOTSTATISTICS software, analysing and printing traffic data on a POSTSCRIPT printer.

computer model

time headway

log normal distribution

Chi-Square test


rural road network


traffic simulation model


sight distance

Kolmogorov-Smirnoff test

software system



Stig O. Simonsson

Institutionen för väg- och trafikplanering





Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 1203