Nico Kaempchen

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Driver-assistance systems and automated driving applications in the future will require reliable and flexible surround environment perception. Sensor data fusion is typically used to increase reliability and the observable field of view. In this paper, a novel approach to track-to-track fusion in a high-level sensor data fusion architecture for automotive(More)
Accurate maps of the static environment are essential for many advanced driver-assistance systems. A new method for the fast computation of occupancy grid maps with laser range-finders and radar sensors is proposed. The approach utilizes the Graphics Processing Unit to overcome the limitations of classical occupancy grid computation in automotive(More)
The autonomous emergency brake (AEB) is an active safety function for vehicles which aims to reduce the severity of a collision. An AEB performs a full brake when an accident becomes unavoidable. Even if this system cannot, in general, avoid the accident, it reduces the energy of the crash impact and is therefore referred to as a collision mitigation(More)
Classical object tracking approaches use a Kalman-filter with a single dynamic model which is therefore optimised to a single driving maneuver. In contrast the interacting multiple model (IMM) filter allows for several parallel models which are combined to a weighted estimate. Choosing models for different driving modes, such as constant speed, acceleration(More)
Future advanced driver assistance systems will contain multiple sensors that are used for several applications, such as highly automated driving on freeways. The problem is that the sensors are usually asynchronous and their data possibly out-of-sequence, making fusion of the sensor data non-trivial. This paper presents a novel approach to track-to-track(More)
A scalable feature-level sensor fusion architecture combining the data of a multi-layer laserscanner and a monocular video has been developed. The approach aims at a maximization of synergetic effects by combining low-level measurement features and at the same time trying to keep the fusion architecture as general as possible. A new concept for the(More)
A system, particularly a decision-making concept, that facilitates highly automated driving on freeways in real traffic is presented. The system is capable of conducting fully automated lane change (LC) maneuvers with no need for driver approval. Due to the application in real traffic, a robust functionality and the general safety of all traffic(More)
Robust ego-localization is an essential technology for future intelligent vehicles and cooperative applications. In this paper a new localization algorithm based on IBEO AS Laserscanners and high accuracy digital maps is proposed. Algorithms to create accurate grid maps with Laserscanners and the extraction of static objects used as landmarks for(More)
In established driver assistance systems each application relies on its own sensor, which observes the vehicles environment. Advanced driver assistance systems (ADAS) have increasing demand for several sensor systems. The described Laserscanner and video based sensor fusion approach serves as a general platform for multiple active safety and comfort(More)
Volkswagen research has developed a system for vehicle surround perception which integrates different sensor data of the environment into a combined description by using a single model Kalman tracker. This paper deals with the extension of the tracking system by means of an interacting multiple-model algorithm (IMM) to improve the tracking stability during(More)