Experiences with Establishing a Simulation Scenario of the City of Duisburg with Real Traffic Volume

Abstract

This article presents the experience of building a simulation scenario of the whole city of Duisburg using real traffic data. The establishment of the simulation scenario is based on road network and traffic volume. In most cases, it is hard to collect all data sources with high precision. Moreover, it is time-consuming to set up a realistic traffic scenario. Even with available data, conversion, calibration, and validation all take a large effort. With the increase of the respective simulation area, the difficulty and workload rise. In this study, a simulation scenario of the whole city of Duisburg with the road network area of 232 km2 and Origin/Destination (OD) matrix area over 800 km2 was established in the software package SUMO. Four cases with different networks and traffic volumes were built and compared with real traffic data collected from induction loops. The percentage of simulated traffic volume in real traffic volume range can be up to 72.22%.

Evaluation of Accuracy of Traffic Flow Generation in SUMO

“…This article uses a macroscopic verification method for a microscopic traffic simulation in Jianghan Zone of the city of Wuhan. Comparing with our previous experiences of building traffic simulations [12,13,25,26] with more reliable traffic data sources including induction loops data, camera data, OD matrix data, etc., in this article, all the data sources which have been used in building the scenario are all public information gathered from the Internet. Comparing with accurate traffic estimation models using complicated calculation method such as neural network [27,28] and machine learning [29], the estimation method in this work can simulate the average speed of each intersection in the entire city with easy-to-obtain data, and does not require the actual speed of each simulated road section of the whole road network.…”

“…Bieker et al established a traffic scenario of the city of Bologna based on a project in cooperation with the European Commission [11]. Our previous work was supported by a cooperation with the administration of the city of Duisburg and had access to traffic data like the origin-destination (OD) matrix and detector data collected from induction loops and cameras [12,13]. Shafiei et al built a simulation-based dynamic traffic assignment model of Melbourne, Australia with detector data and OD matrix data [14].…”