Optimal VLSI Design for a Highly-Safe Intelligent Vehicle Based on a System Integration Theory

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Intelligent algorithms, advanced VLSI architectures and a system integration theory are studied to develop a highly-safe intelligent vehicle.(1) System-Application-Level Design TheoryA real-world intelligent integrated system consists of three basic modules of environment recognition, prediction or estimation, and behavior planning. A system integration theory including derivation of performance specification is studied to bridge the gap between the various design levels as well as their VLSI-oriented intelligent algorithms.(2) Processing Module for Highly-Safe Intelligent VehiclesVLSI-oriented algorithms for road extraction, vehicle extraction and human extraction using 3-dimensional image information are developed. Moreover, motion estimation of a vehicle is done based on Bayesian Network The problem is equivalent to estimation of a driver's intention. The driver's intentions are hierarchically defined, so that the designed Bayesian Network becomes as simple as possible. Then, causal relation between the intentions is discussed to reflect the real-world motion process.(3) Optimal Design Theory of VLSI Processors for Intelligent Integrated SystemsTo achieve power minimization under a time/area constraint, high-level synthesis techniques are investigated based on scheduling and allocation. One typical example is a parallel VLSI for 3-dimensional image processing with optimal memory allocation which solves the data transfer bottleneck between processing elements and memory modules.(4) Reconfigurable VLSI ComputingFine-grained reconfigurable VLSIs for real-world applications superior to the conventional FPGAs are designed and implemented based on new architectures such as direct allocation of a control-data-flow graph, a bit-serial arithmetic operation, a dynamic control of power dissipation, and a logic-in-memory architecture utilizing nonvolatile devices.