Department of Computer Science

Environment Perception and Driver Assistance


The Environment Perception and Driver Assistance (.enpeda..) project searches for solutions for vision-based driver assistance systems (DAS) which are currently starting to be active safety components of cars (eg, lane departure warning, blind spot supervision). Safety systems, that perceive the environment around them and act accordingly, are the next step to assure safe driving conditions. DAS are developed to predict traffic situations, adapt driving and car to current traffic situations and optimize for safety. Vision-based DAS uses one or more cameras to capture the environment and help achieve these goals.

Correspondence techniques (stereo or motion analysis) are designed for providing the basic (ie, low-level) information for more advanced DAS solutions (eg, 3D lane modeling, ego-motion analysis, tracking of pedestrians or cars or understanding complex traffic situations). Ego-motion describes the movements of the ego-vehicle, which is the car the given system is operating in.

Members (academic staff or PhD students):

R. Klette, S. Manoharan, J. Morris, N. Amarasinghe, H. Geng, R. Haeusler, S. Hermann, R. Kalarot, T. Khan, W. Khan, D. Liu, M. Rezaei, and J. Tao

More information:

Environment Perception and Driver Assistance website