HD Lane Map Generation Based on Trail Map Aggregation

We present a procedure to create high definition maps of lanes based on detected and tracked vehicles from perception sensor data as well as the ego vehicle using multiple observations of the same location. The procedure consists of two parts. First, an aggregation part in which the detected and tracked road users as well as the driving path of the ego vehicle are aggregated into a map representation. Second, lanes are extracted from those maps as lane center lines in a structured data format. The final lane centers are represented in a directed graph representation including the driving direction. They are accurate up to a few centimeters. Our procedure is not restricted to any environment and does not rely on any prior map information. In our experiments with real world data and available ground truth, we study the performance of different map aggregations e.g., based on the ego vehicle only or based on other road users. Furthermore, we study the dependence on the number of data recording repetitions.