Intelligent Transport Systems
Intelligent transportation systems (ITS) apply information, sensor and communications technologies to vehicles and transportation infrastructure to improve traffic safety and efficiency. In addition, ITS applications reduce air pollution and energy consumption of the entire transportation network. Our research focus is on advanced driver assistance systems such as green light optimal speed advisory (GLOSA) and the green light optimal dwell time advisory (GLODTA).
Urban corridors with high mobility demands require high-capacity public transport (PT) operations. PT-based passenger flows represent a fraction of energy use, greenhouse gas and pollutants emissions of comparable travel in private vehicles. In our research we address the PT system combining the emerging technological trends referred to electrification, connectivity and automation. The objective is to analyse how to best use these technologies to deliver sustainable PT attractive to operators, authorities and citizens.
Data Analysis and Visualization
Selection and deployment of the right type of electric vehicle depends heavily on the operating conditions. In our research we study how a data-driven approach can lead to an optimally custom tailored e-bus system. Large amounts of heterogeneous data generated by Vehicles, combined with geospatial information of routes offer great opportunities to discover trends and learning causative relations. Key aspects in our research are visual analytics and machine learning for decision support, leveraging combined expertise from across different fields, to provide precise and actionable decisions based on understanding.