Connected and automated driving will not only impact traffic efficiency and safety in existing traffic environments but will also allow for a reorganization of traffic operation in the long-term. Lane-free automated driving allows for more flexible use of the road width, thus opening up new possibilities for intersection control as well. This paper presents an alternative approach to existing control methods by creating a dynamic environment that can later be expanded with selected optimization modules – with the aim of reduced computation times compared to a fully optimized approach. The presented methodology integrates the intersection control directly into a developed lane-free driving behavior based on artificial potential fields, similar to established social force models. Although this first development focuses on high capacity for vehicular traffic, lane-free force based environments have the potential to not only utilize existing urban space more efficiently but may also enable a seamless integration of vulnerable road users or prioritization of certain vehicle types (e.g., public transport). After an introduction to the developed methods, a proof of concept is performed in a customized simulation environment. Identified challenges are discussed and further research is identified.     «

Connected and automated driving will not only impact traffic efficiency and safety in existing traffic environments but will also allow for a reorganization of traffic operation in the long-term. Lane-free automated driving allows for more flexible use of the road width, thus opening up new possibilities for intersection control as well. This paper presents an alternative approach to existing control methods by creating a dynamic environment that can later be expanded with selected optimization...     »