In Cape Reviso, planning and decision support tools for conflict analysis and reduction between cyclists and pedestrians are being developed. For this purpose machine learning, sensor technology, network analysis and VR are combined in digital twins. These developed tools will support urban and traffic planning. Evidence-based sources such as analyses and simulations will provide a better basis for decision-making. Early implementation in planning and decision-making processes as well as the integration of different expertise in collaborative and participative processes aims to improve the perceived and real safety in road traffic and public space.
In the sub-project of the HLRS, different methods that build on each other or are mutually dependent are to be used. Innovative approaches of machine learning, scenario-based driving simulation and the use of digital twins in virtual and augmented reality will be researched in the context of urban and traffic planning and for the analysis and reduction of conflicts between pedestrians and cyclists. The desired result is a set of methods in which the above-mentioned key technologies are used in a closely interlinked approach in order to achieve an improved basis for decision-making in the planning of junctions and forms of traffic guidance in cycling and walking. The development will also be carried out under the aspect of being able to derive a tool for urban and traffic planning (Planning- and Decision-Support-Tool).