Traffic Simulation of Future Intelligent Vehicles in Duisburg City Inner Ring

Abstract

Intelligent vehicles gradually enter the vehicular fleet with advanced driver-assistance technologies. Their impact on traffic should, therefore, be considered by transportation decision-makers. This paper examines the effect of vehicles with different levels of automation on traffic flow, such as non-assisted vehicles, vehicles with driver assistance systems, and fully autonomous vehicles. The accuracy of the examined traffic scenario is also an important factor in microscopic traffic simulation. In this paper, the central part of the city of Duisburg, Duisburg’s inner ring, is chosen for the traffic scenario. Through the cooperation with local government, official data of Origin/Destination matrices, induction loops, and traffic light plans are provided for this work. Thus, traffic demand from Origin/Destination matrices and induction loops are generated and compared, respectively. Finally, vehicles with different levels of automation are simulated in the Duisburg inner ring scenario.

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.…”

“…According to the Chinese government demographic census [19], the population in the Jianghan Zone is 683,500 (2010), and of those, the working population is calculated from working age (1960) and the unemployment rate in Wuhan [20]. According to the educational system in China, school-age is divided into primary school age (6-12) middle school age (13)(14)(15) and high school age (16)(17)(18). The number of residents in each community can be found on different estate websites, which also provides the number of households and the vacancy rate.…”

“…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].…”

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

“…The city road network can be obtained by several methods: using Wireless Sensor Networks (WSN) [7], acoustic signal [8], etc. Like in our previous study about the city Duisburg inner ring area [9], the road network used in this work was extracted from OSM (Open Street Map) [10]. A rectangular area encompassing the area we need was extracted from OSM.…”

Application of Kalman Filter to Improve 3D LiDAR Signals of Autonomous Vehicles in Adverse Weather

“…With the development of artificial intelligence, along with improvements in computer and chip technology, it is possible to design autonomous vehicles, which could become one of the most important ways to reduce traffic accidents. Autonomous vehicles have stimulated a great deal of research interest [1][2][3].…”