This article focusses on the fusion of information from various automotive sensors like radar,
video, and lidar for enhanced safety and traffic efficiency. Fusion is not restricted to data from …

The prediction of lane changes has been proven to be useful for collision avoidance support
in road vehicles. This paper proposes an interactive multiple model (IMM)-based method for …

Advanced driver assistance systems aim at an improved traffic safety, enhanced comfort and
driving pleasure. Sensors perceive the objects surrounding the vehicle and produce an …

Various sensors are adopted by autonomous driving systems to perceive objects and
surroundings. Thus, the multi-sensor data fusion techniques become essential to combine …

In order to develop a driver assistance system for pedestrian protection, pedestrians in the
environment of a truck are detected by radars and a camera and are tracked across …

Collision avoidance is currently one of the main research areas in road intelligent
transportation systems. Among the different possibilities available in the literature, the …

We propose a multi-target tracking method using an Interacting Multiple Model Joint
Probabilistic Data Association (IMM-JPDA) filter for tracking vesicles in Total Internal …

针对交互式多模型联合概率数据关联滤波算法(IMM-JPDAF) 在非线性情况下跟踪精度低,
并不适用于非高斯问题的情况, 提出了一种基于粒子滤波的交互式多模型多机动目标跟踪算法; …

Robots have been widely used in factories for executing repetitive, dangerous or laborious
tasks such as material handling and spot welding. Since industrial robots outperform …

Die vorliegende Arbeit beschreibt eine neuartige Objektverfolgung durch Fusion von Radar-
und Monokameradaten auf Merkmalsebene. In dieser Arbeit wird ein neues …