Verkehrssimulationsmodellen

Verkehrssimulation (traffic simulation) refers to the use of computational models to reproduce the movement of vehicles and pedestrians on road networks for analysis, planning, and decision support. The goal is to understand traffic performance under various conditions, test interventions, and inform design or policy choices without relying solely on real-world experiments.

Simulations can be categorized by level of detail. Macroscopic models describe aggregate flow variables such as density, speed, and traffic flux. Microscopic models simulate individual vehicle dynamics and driver behavior. Mesoscopic models strike a balance between the two. Common modeling approaches include cellular automata, such as the Nagel-Schreckenberg model, car-following models (for example Gipps, Wiedemann, Intelligent Driver Model), and fluid-dynamics–based Lighthill-Whitham-Richards (LWR) models used at the network level.

A road network is typically represented as a set of nodes (intersections) and links (roads), with inputs including origin-destination demand, turning probabilities, signal timings, speed limits, and incident scenarios. Data sources for calibration and validation can consist of loop detectors, GPS traces, probe data, and travel surveys. Simulations can incorporate behavioral rules for pedestrians, cyclists, and other non-vehicular actors as needed.

Applications span traffic management, signal optimization, and infrastructure planning; they are also used for evacuation planning, disaster response, and testing autonomous vehicle algorithms. Popular simulation platforms include SUMO, MATSim, VISSIM, AIMSUN, and Paramics, each supporting varying scales, data requirements, and modeling approaches. Validation and calibration against observed data are essential, given uncertainties in driver behavior and data quality, and models may be computationally intensive for large networks.