Global positioning using a digital map and an imaging radar sensor

Autor: Marcus Konrad, Florian Schule, Magdalena Szczot, Matthias Serfling, Otto Lohlein, Klaus Dietmayer
Rok vydání: 2010
Předmět:
Zdroj: Intelligent Vehicles Symposium
DOI: 10.1109/ivs.2010.5548043
Popis: This contribution presents a lane estimation system for night applications which covers distances up to 140 m in rural environment. The high detection range is essential for upcoming warning systems to decide whether a detected object is on the road and thus of immediate importance for the driving task. In order to realize a robust lane detection system we present a fusion system that combines the information provided by an imaging radar system and a digital map. The digital map is used to calculate the shape of the road. Past measurements of the radar sensor are integrated over time into a local map using an egomotion estimator. A particle filter realizes the matching of the digital and local map resulting in an accurate position of the vehicle on the digital map. This positioning algorithm enables an estimation of the position of the lane in front of the vehicle at high distances.
Databáze: OpenAIRE