Conventional road tracking approaches rely on direct measurements of the road. Using camera, LiDAR, or radar sensors, they detect lane markings, textures, road boundaries, curbs, or obstacles. However, all require a direct line of sight to the road. In shared spaces, e.g., a busy campus road, a lot of pedestrian groups are occluding the road for all sensors. Hence, we present a novel measurement concept to support road tracking in presence of other road users. In fact, we are taking advantage of them: Where other road users are moving, there might be the road. Therefore, we probabilistically identify dynamic objects based on radar Doppler measurements. Considering the measurement uncertainties, we then build a probability map of road user paths. This is used to derive probable road areas. Integrating this measurement into an existing camera-based road tracking, we evaluate the accuracy of the resulting road estimate using an HD map.