Sensor-based Traffic Simulation: law compliant and without personal data
Axel Schaffland* 1, Niklas Kruse* 1, Julius Schöning* 1,
Abstract
Traffic simulations offer an insight into the possibilities of recording and simulating traffic flows without using personal data. It will be shown, how sensors can be used to collect important traffic indicators without individual data from road users. The motivation behind this sensor-based traffic simulation is manifold - from improving public transport and reducing environmental pollution to human-centered urban planning, traffic flow optimization and accident prevention. The implementation is carried out through the fusion of static data, the recording of missing data, the modelling of traffic light systems and the use of dynamic databases. Great importance is attached to data economy.
An important aspect of sensor-based traffic simulation is the development of digital twins. Digital twins are virtual images of real systems that make it possible to simulate and analyze traffic scenarios in detail without directly intervening in the flow of traffic. By using sensors, digital twins can provide a more realistic image of the actual traffic situation. Simulation tools such as SUMO (Simulation of Urban MObility) and GIS software such as QGIS are used to analyze and visualize traffic flows in detail. These tools make it possible to accurately record traffic volumes, emissions, and accident risks and to test optimization measures without using personal data.