## 1 Introduction  
Traffic simulation tools can be divided into macroscopic, microscopic, mesoscopic scale simulations. Microscopic traffic simulation models each vehicle and its dynamics individually [1]. Moreover, microscopic traffic simulation has been developed into a cost-effective and powerful tool for traffic management and planning as well as the automotive industry. However, the accuracy of the simulation scenario is closely related to the usefulness of the simulation results. For realistic simulation scenarios, a road network, traffic demand, real traffic lights, and infrastructures are needed as input data [2]. The quality of all the input data is crucial for the accuracy of the simulation.  
SUMO (Simulation of Urban MObility) is a microscopic, open-source and space-continuous, time-discrete road traffic simulation package [1]. With the advantages of easy programming, scalability, input data extensiveness, and verification convenience, it has been widely used by many researchers in building realistic simulation scenarios. [PERSON] et.al. [3] introduced the network import of the city of Gothenburg and the evaluation of the traffic flow with the scenarios in and around Berlin. [PERSON] [2] imported three regions' scenarios of city Bologna from Vissim, another traffic simulation software. The scenario area was combined with three small scenarios, while the traffic demand contained one hour of a day. The traffic demand of this scenario was based on induction loop data provided by the local municipality. Codeca [4] rebuilt the city of Luxembourg in SUMO with buses and bus stations in a 24-h scenario. This scenario covers an area of almost 156 km\({}^{2}\) with 931 km of roads. The important traffic demand was generated from population and geographical location information and was not calibrated or verified with real traffic data. [PERSON] [5] reproduced Kobe city with an area of about 130 km\({}^{2}\). The traffic demand was also generated by geographical location information, gathered from mobile phone position data. These simulation results were compared with the measurements from the traffic censuses. However, the simulation results did not reflect the real traffic situation in every respect.  
In the establishment of realistic traffic scenarios, there are always some factors that affect the overall accuracy. The previous studies of the authors about the traffic scenarios in the city of Wuhan [6] also illustrated that the traffic demand generated from the geographical population distribution only roughly represents the status of the traffic and that high precision simulation scenarios must be built from precise traffic input data. In this study, thanks to the support from Wirtschaftsbetriebe Duisburg and the city of Duisburg, the traffic light positions, dynamic traffic light plans, OD (Origin/Destination) matrix and induction loop data are all available for this work. On this basis, this article is aiming to present the experiences of building a high-precision simulation scenario of the whole city of Duisburg with OD matrix data. The simulated traffic volume was also compared with the real traffic volume detected by the induction loops.