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Architecture of a CAM-Based Collision Detection VLSI Processor for Intelligent Vehicles
Author(s) -
Masanori Hariyama,
Michitaka Kameyama
Publication year - 1994
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.1994.p0137
Subject(s) - computer science , very large scale integration , collision detection , obstacle , collision , coordinate system , computation , transformation (genetics) , computer hardware , key (lock) , cordic , rotation (mathematics) , embedded system , real time computing , artificial intelligence , algorithm , field programmable gate array , political science , law , biochemistry , chemistry , computer security , gene
Since careless driving causes a terrible traffic accident, it is an important subject for a vehicle to avoid collision autonomously. Real-time collision detection between a vehicle and an obstacle will be a key target for the nextgeneration car electronics system. In collision detection, high-computational power is essential not only in coordinate transformation but also in matching operation. In the proposed collision detection VLSI processor, the matching operation is sharply accelerated by using a content-addressable memory which evaluates the magnitude relationships between an input word and all the stored words in parallel. Parallel architecture using several identical processor elements (PEs) is employed to perform the coordinate transformation at high speeds, and each PE performs coordinate transformation at high speeds based on the Coordinate Rotation Digital Computation (CORDIC) algorithms. When the 16 PEs and 144-kb CAM are used, the performance is evaluated to be 6.48ms.

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