Energy optimized driving strategy in consideration of traffic participants at intersections without traffic lights

The increasing interconnectivity and automatization of vehicles allows for new degrees of freedom, especially concerning shaping the urban mobility more efficiently. To reduce the energy demand of a single vehicle for the crossing of a classic intersection that is not controlled by traffic lights, the current traffic situation of relevant traffic participants, which is made available by a Vehicle-to-X communication interface, can be predicted into the future. Further, it can be considered as a boundary condition in an optimization problem. In this article, a model based prediction algorithm is introduced for this purpose, which predicts the times at which the intersection is blocked by a priority vehicle. This information is part of the boundary conditions of a linear, model predictive controller to optimize the vehicle's own speed-trajectory. Investigations on a case study based on measurement data showed that the prediction horizon poses as a significant parameter to reduce the energy demand at the wheel. However, stochastic influences of the human driving behavior lead to a decrease in the accuracy of time-prediction concerning the navigability of intersections, while the horizon in forecast increases. In some situations, a greater horizon in forecast even causes an increased demand for energy.