A Technical Concept for sensor-based Traffic Flow Optimization on connected real-world intersections via a SUMO Feature Gap Analysis

Abstract

Traffic within cities has increased in the last decades due to increasing mobility, changing mobility behavior and new mobility offerings. These accelerating changes make it increasingly difficult for responsible authorities or other stakeholders to predict mobility behavior, to configure traffic rules or to size roads, bridges and parking lots. Traffic simulations are a powerful tool for estimating and evaluating current and future mobility, upcoming traffic services and automated functionalities in the domain of traffic management. For being able to simulate a complex real-world traffic environment and traffic incidents, the simulation environment needs to fulfill requirements from real-world scenarios related to sensor-based data processing. In addition, it must be possible to include latest advancements of technology in the simulation environment, for instance, (1) connected intersections that communicate with each other, (2) a complex and flexible set of rules for traffic sign control and traffic management or a well-defined data processing of relevant sensor data. In this paper we therefore define requirements for a traffic simulation based on a complex real-world scenario in Germany. The project addresses major urban challenges and aims at demonstrating the contribution that the upcoming 5G mobile generation can make to solving real-time traffic flow optimization. In a second step, we investigate in detail if the simulation environment SUMO (Simulation of Urban Mobility) fulfills the postulated requirements. Thirdly, we propose a technical concept to close the gap of the uncovered requirements for later implementation.

Keywords

• Traffic flow optimization
• connected intersections
• traffic light systems