Autonomous road vehicle guidance in normal traffic

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Abstract

A passenger car Mercedes 500 SEL has been equipped with the sense of vision in the framework of the EUREKA-project ‘Prometheus III’. Road and object recognition is performed both in a look-ahead and in a look-back region; this allows an internal servo-maintained representation of the entire situation around the vehicle using the 4-D approach to dynamic machine vision. Obstacles are detected and tracked both in the forward and in the backward viewing range up to about 100 meters distance; depending on the computing power available for this purpose up to 4 or 5 objects may be tracked in parallel in each hemisphere. A fixation type viewing direction control with the capability of saccadic shifts of viewing direction for attention focussing has been developed. The overall system comprises about 45 transputers T-222 (16-bit, for edge extraction and communication) and T-805 (32-bit, for number crunching and knowledge processing) and 4 boards based on the Motorola Power Chip (MPC-601) for obstacle detection including image segmentation and state estimation. A description of the parallel processing architecture is given; system integration follows the well proven paradigm of orientation towards 4D physical objects and expectations with prediction error feedback. This allows frequent data driven bottom-up and model driven top-down integration steps for efficient and robust object tracking.

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APA

Thomanek, F., & Dickmanns, E. D. (1996). Autonomous road vehicle guidance in normal traffic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1035, pp. 499–507). Springer Verlag. https://doi.org/10.1007/3-540-60793-5_103

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