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This master thesis has been done in the field of Advanced Driver Assistance Systems and presents a method to assist cross traffic at road junctions. An accurate tracking of crossing objects is necessary in order to assist traffic at road junctions. At Continental, the stable tracking of crossing objects is available, but the system still gives false alarms for non-colliding objects (e.g. Target Braking at crossroads). Hence the main focus of this thesis is on the reduction of false alarms for non colliding objects. Radar based Maneuver Detection function has been developed for Crossing Emergency Brake Assist system, which uses radar measurement parameters to detect the maneuvering of target objects in order to differentiate between collision and non-collision cases. Different crossing scenarios have been created in a Matlab environment and the algorithm is tested. Secondly, the algorithm is tested by using the measurement data from real recordings and evaluation is made. The proposed algorithm has reliably detected the non-collided objects (in normal cases) and helped in reducing the false alarm rate significantly.

This master thesis has been done in the field of Advanced Driver Assistance Systems and presents a method to assist cross traffic at road junctions. An accurate tracking of crossing objects is necessary in order to assist traffic at road junctions. At Continental, the stable tracking of crossing objects is available, but the system still gives false alarms for non-colliding objects (e.g. Target Braking at crossroads). Hence the main focus of this thesis is on the reduction of false alarms for non colliding objects. Radar based Maneuver Detection function has been developed for Crossing Emergency Brake Assist system, which uses radar measurement parameters to detect the maneuvering of target objects in order to differentiate between collision and non-collision cases. Different crossing scenarios have been created in a Matlab environment and the algorithm is tested. Secondly, the algorithm is tested by using the measurement data from real recordings and evaluation is made. The proposed algorithm has reliably detected the non-collided objects (in normal cases) and helped in reducing the false alarm rate significantly.