Three-Layer Model Calibration for SUMO: A Study on Speed-Limit Compliance in Chinese Work Zones

In China’s expressway work zones, it is a common phenomenon for drivers to have a low compliance rate with speed-limit instructions. Existing microscopic traffic simulation calibrations mainly focus on car-following and lane-changing behaviors, lacking research on speed-limit compliance behavior. Therefore, this paper proposes a method for collaborative calibration of the key parameters of a “car-following, lane-changing, speed-limit compliance” three-layer model based on the SUMO simulation platform. The research selects the key parameters in the IDM car-following model, LC2013 lane-changing model, and speed-limit compliance model to form a calibration parameter set, taking the time-mean speed and space-mean speed as optimization indicators, using the simultaneous perturbation stochastic approximation (SPSA) algorithm combined with a restart strategy, and aiming to minimize the root-mean-square error (RMSE) of the speed between the simulated and observed data for global optimization. The model is verified by the measured traffic flow and speed data in the expressway work zone. The verification results show that the three-layer calibration framework incorporating the speed-limit compliance model not only improves speed fitting but also better reproduces the distributional characteristics of real traffic flow in the work zone, especially the dispersion and heterogeneity of operating speeds. This research fills a gap in research involving SUMO calibration of speed-limit compliance in China and provides a theoretical basis and method-based support for microscopic simulation considering driver differences in speed-limit compliance.