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according to their capabilities. The processing can be performed for each sensor, also information from different sensors 
may be fused as shown by (Handmann et al., 1998c). Objects are extracted by segmentation, classification and tracking 
(fig. 3). 
  
  
Figure 3: Vision-based object detection, object classification and object tracking. 
3.0 Sensor-based Representations 
The results of the sensor information processing stage are stabilized in movement-sensitive representations by introducing 
the time dimension, which was presented by (Handmann et al., 1999). In this sense, a ROI is accepted as a valid hypothesis 
only if it has a consistent history. This is implemented by spatio-temporal accumulation using different representations 
with predefined sensitivities. The sensitivities are functions of the objects' supposed relative velocity and of the distance 
to the observer (fig. 4). In order to apply a time stabilization to these regions and to decide whether they are valid or 
not, a prediction of their position in the knowledge integration part is realized. A competition between the different 
  
Figure 4: Image and representation. The value in the representation indicates the activation for an ROI. 
representations and a winner-takes-all mechanism ensures reliable object detection. An implementation of an object- 
related analysis on vision data has been presented by (Handmann et al., 1998a, Handmann et al., 20002). The results are 
passed to the scene interpretation. 
4 KNOWLEDGE BASE 
The knowledge needed for the evaluation of the data and for information management is determined by the specific task of 
driver assistance, physical laws and traffic rules. An improvement of the results can be achieved by the information from 
the knowledge base. In the knowledge base, static and dynamic knowledge is represented. Static knowledge is known in 
advance independently of the scenery of movement (e.g., physical laws, traffic rules). Dynamic knowledge (e.g., actual 
traffic situation, scenery, lane-information) is knowledge changing with the actual information or with the task to be 
performed (e.g., objects in front of the car). It can also be influenced by external knowledge like GPS-information. The 
accumulation results of the movement-sensitive representations in the object-related analysis, i.e., can be additionally 
supported by a preactivation depending on the dynamic knowledge (lane-information, fig. 5). 
  
Figure 5: Oncoming traffic (image with lane-information, movement-sensitive representation without and with preactiva- 
tion). The preactivated region is determined by the lane information. The value indicates the grade of activation. 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000. 349