Collision detection VLSI processor for intelligent vehicles using a hierarchically-content-addressable memory

Masanori Hariyama, Kazuhiro Sasaki, Michitaka Kameyama

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


High-speed collision detection is important to realize a highly-safe intelligent vehicle. In collision detection, high-computational power is required to perform matching operation between discrete points on surfaces of a vehicle and obstacles in real-world environment. To achieve the highest performance, a hierarchical matching scheme is proposed based on two representations: the coarse representation and the fine representation. A vehicle is represented as a set of rectangular solids in the fine representation (fine rectangular solids), and the coarse representation, which is also a set of rectangular solids, is produced by enlarging the fine representation. If collision occurs between an obstacle discrete point and a rectangular solid in the coarse representation (coarse rectangular solid), then it is sufficient to check the only fine rectangular solids contained in the coarse one. Consequently, checks for the other fine rectangular solids can be omitted. To perform the hierarchical matching operation in parallel, a hierarchically-content-addressable memory (HCAM) is proposed. Since there is no need to perform matching operation in parallel with fine rectangular solids contained in different coarse ones, the fine ones are mapped onto a matching unit. As a result, the number of matching units can be reduced without decreasing the performance. Under the condition of the same execution time, the area of the HCAM is reduced to 46.4% in comparison with that of the conventional CAM in which the hierarchical matching scheme is not used.

Original languageEnglish
Pages (from-to)1722-1729
Number of pages8
JournalIEICE Transactions on Electronics
Issue number9
Publication statusPublished - 1999


  • Area-time product minimization
  • CAM
  • Hierarchical collision detection
  • Path planning


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