Handmann, Uwe 
  
sensors (e.g., Radar, Lidar and image processing) can be incorporated for the analysis and interpretation of the scene to 
increase the quality of the system. In the part of the scene interpretation, neural field dynamics (Amari, 1983) will be 
used to stabilize the given object hypotheses with an adequate interaction kernel. For behavior planning a dynamical 
system is supposed to be realized as well. A successful solution to a behavior planning using this method was presented 
by (Handmann et al., 2000b). 
REFERENCES 
Amari, S.-I., 1983. Field Theory of Self-Organizing Neural Nets. IEEE Transactions on Systems, Man, and Cybernetics. 
Bergener, T., Bruckhoff, C., Dahm, P., Janfen, H., Joublin, E, Menzner, R., Steinhage, A. and von Seelen, W., 1999, 
Complex Behavior by means of Dynamical Systems for an Anthropomorphic Robot. special issue of Neural Networks. 
Bertozzi, M. and Broggi, A., 1998. GOLD: a Parallel Real-Time Stereo Vision System for Generic Obstacle and Lane 
Detection. In: IEEE (ed.), IEEE Transactions on Image Processing, Vol. 7(1), pp. 62-81. 
Brauckmann, M. E., 1994. Visuelle Automobilerkennung zur Fahrzeugführung im Strafenverkehr. Fortschrittberichte, 
Reihe 12, VDI Verlag. 
Dickmanns, E. et al., 1997. Vehicles capable of dynamic vision. In: 15th International Joint Conference on Artificial 
Intelligence (IJCAI), Nagoya, Japan, pp. 1-16. 
Goerzig, S. and Franke, U., 1998. ANTS - Intelligent Vision in Urban Traffic. In: IV’98, IEEE International Conference 
on Intelligent Vehicles 1998, IEEE, Stuttgart, Germany, pp. 545-549. 
Handmann, U., Kalinke, T., Tzomakas, C., Werner, M. and von Seelen, W., 1998a. An Image Processing System for 
Driver Assistance. In: IV’98, IEEE International Conference on Intelligent Vehicles 1998, IEEE, Stuttgart, Germany, 
pp. 481 — 486. 
Handmann, U., Kalinke, T., Tzomakas, C., Werner, M. and von Seelen, W., 1998b. Computer Vision for Driver Assistance 
Systems. In: Proceedings of SPIE Vol. 3364, SPIE, Orlando, pp. 136 — 147. Session Enhanced and Synthetic Vision 1998. 
Handmann, U., Kalinke, T., Tzomakas, C., Werner, M. and von Seelen, W., 2000a. An Image Processing System for 
Driver Assistance. Image and Vision Computing (Elsevier) 18(5), pp. 367 — 376. 
Handmann, U., Leefken, I., Steinhage, A. and v.Seelen, W., 2000b. Behavior Planning for Driver Assistance using Neural 
Field Dynamics. In: NC 2000, second international symposium *Neural Computation', Berlin, Germany. 
Handmann, U., Leefken, L, Tzomakas, C. and von Seelen, W., 1999. A Flexible Architecture for Intelligent Cruise 
Control. In: ITSC'99, IEEE Conference on Intelligent Transportation Systems 1999, IEEE, Tokyo, Japan, pp. 959 — 963. 
Handmann, U., Lorenz, G., Schnitger, T. and von Seelen, W., 1998c. Fusion of Different Sensors and Algorithms for 
Segmentation. In: IV'98, IEEE International Conference on Intelligent Vehicles 1998, IEEE, Stuttgart, Germany, pp. 499 
— 504. 
Noll, D., Werner, M. and von Seelen, W., 1995. Real-Time Vehicle Tracking and Classification. In: Proceedings of the 
Intelligent Vehicles '95 Symposium, Detroit, USA, pp. 101—106. 
Rossi, M., Aste, M., Cattoni, R. and Caprile, B., 1996. The IRST Driver's Assistance System. Technical Report 9611-01, 
Instituto per la Ricerca Scientificia e Technologica, Povo, Trento, Italy. 
Sukthankar, R., 1997. Situation Awareness for Tactical Driving. Phd thesis, Carnegie Mellon University, Pittsburgh, PA, 
United States of America. 
Zhuang, Q., Gayko, J. and Kreutz, M., 1998. Optimization of a Fuzzy Controller for a Driver Assistant System. In: 
Proceedings of the Fuzzy-Neuro Systems 98, München, Germany, pp. 376 — 382. 
  
354 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000.