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Recently, Lane Detection technology has been used for passenger safety systems such as the Lane Departure Warning System and Lane Keeping assist system to the most of the recently launched vehicles. There are many researches for lane detection algorithm but approaches of the previous studies such as template matching method, probabilistic method, color model method, etc. have limitations that are high sensitivity to noise similar to lane shape and non-uniform illumination. In this paper, we proposed lane detection algorithm based on generated Top-View image through Inverse Perspective Mapping using Random Sample Consensus algorithm. Moreover, the detected lane is extended to the bottom of the Region of Interest by applying the Curve road model. The proposed algorithm has been tested in various environment conditions. Experimental results show that the proposed algorithm can detect both straight and curve lane and can process about 25 frames per second.

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Recently, the number of automotive electrical and electronic system has been increased due to growth of the requirements for safety and convenience for drivers and passengers. In most cases, the data for either user or system to be used in runtime should be stored on internal or external nonvolatile memory. However, the non-volatile memory has a constraint with write limitation. The limit causes fatal accidents or unexpected results.In this paper, we proposed a management algorithm for using none-volatile memory to prolong the writing access times. Our proposal uses an algorithm which swaps a frequently modified block for a least modified block. In the resorting to our experimental results, the proposed scheme can extend the lifetime of non-volatile memory about 1.78 to 2.56 times.