Angewandte Forschung im Zukunftsfeld digitale Kommunikation (diko 19)

Informations- und Kommunikationstechnologie - Simulationsgestützte Optimierung von Verkehrsberuhigungsmaßnahmen / Teilthema


07/2017 - 12/2019

Projektleitung (Organisationseinheit):

Prof. Dr. Silke Kolbig (Fakultät Physikalische Technik/Informatik)


Forschungsprojekt der Westsächsischen Hochschule Zwickau


Prof. Dr. Silke Kolbig

+49 (375) 536 1382




The aim of the traffic calming is to reduce the pollution and noise level, together with increase of road safety. These objectives can be achieved by slowing down and reducing traffic. The aim of this project is to create a micro and macrosimulation model, which shows the traffic assignment changes after the introduction of traffic calmed zones. Simulations will be carried out in PTV Vissim and Visum software.


Traffic calming measures cause different driving behaviour, speed as well as changes the paths used by drivers, which avoid traffic calming in transit traffic. Microsimulation model requires a set of parameters to reproduce the driving behaviour, as well as speed profiles. Neither these parameters, nor speed profiles are known for the traffic-calmed road, and need to be discovered. Moreover, traffic calming can change the basic macrosimulation traffic link parameter – volume-delay function, which shows the relation between travel time and traffic flow on the road link. Estimation of that function require tests with various amounts of traffic flow.


Drivers’ behaviour is modelled based on video recording of traffic in traffic-calmed links. Survey area is filmed vertically down with an unmanned quadrocopter flying approximately 70 meters above ground level, covering the area of 100x60 meters. Later, during the video processing, with the use of neural networks classifiers and computer vision tracking algoritms, street users are recognised with its type (pedestrian, bike, car, bus, heavy vehicle), and given the specific ID and coordinates in every frame. With this data, with resolution of approx. 40 frames per second, following data can be acquired: traffic flow, vehicle composition, trajectory, speed, acceleration and deceleration. This data will are used to build a precise microscopic simulation with estimated parameters of Wiedemann car following model, which is widely used in PTV Vissim microsimulation traffic program. Results of microscopic link model, done in PTV Vissim will lead to modelling traffic assignment in macroscopic, four-step model, by estimating network link parameters. That kind of model consists of two main parts: demand and supply. Demand is represented by origin-destination matrix between the traffic areas, with homogenous urban and transport function. Supply is the transport network, set for various transport modes, both individual and public. The aim of the model is to assign the trips, from origin to destination to the road network. Traffic assignment is calculated by setting a path with the lowest cost (for example travel time) for every network users. In this project, demand remains unchanged, although link parameters regarding traffic will be modified. Traffic on the link is described with three basic variables: traffic flow q – amount of vehicles passing one point in the unit of time, traffic density – amount of vehicles on the link, velocity – is a length of the link divided by time to pass it or traffic flow divided by traffic density. In PTV Visum model, relation between the amount of traffic flow and link travel time are described by a volume-delay function. Its shape can be chosen from default function formulas, as well as its parameter can be changed freely.  Measuring and modelling drivers’ behaviour and creating a microsimulation model will help to create a volume-delay function for traffic calmed road. Vissim microsimulation will be tested on various traffic volumes, with various traffic compositions, with the estimated speed profiles and other Wiedemann’s model parameters. Finally, macrosimulation results in areas, where traffic calming devices are planned or built are likely to deliver more authoritative forecasts than it could be reached by traditional methods.