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We have developed a Lane Change Decision Aid System (LCDAS), which detects vehicles and motorcycles behind in adjacent lanes with a single camera and informs the driver of dangerous situations during lane change maneuvers. A key technology in LCDAS depends on how it can exactly detect approaching vehicles in spite of weather and environment change. Especially, it's not proper to apply same image analysis algorithm against environment change such as day/night/rainy weather because camera image is very sensitive to illumination condition and weather condition. Therefore it is very important to choose each mode according to vehicle's signals for improving the performance. In this paper, we propose an adaptive LCDAS against weather and environment change. For this purpose, we divide each mode and vehicle signal (wiper, headlamp and vehicle speed sensor) is used as an input and the right/left turn signal is used to choose left/right camera image.

Adaptive cruise control (ACC) systems, which detect distance of a preceding vehicle and a radar-mounted vehicle using the radar, are available from automobile manufacturers. The distance and a relative velocity of the preceding vehicle and the radar-mounted vehicle can be estimated by analyzing a millimeter-wave signal obtained through the radar. Due to a characteristic of the radar and the relative velocity between the preceding vehicle and the radar-mounted vehicle, it is difficult to detect and track the preceding vehicle in the same lane where the radar-mounted vehicle is moving. In this paper, an algorithm is proposed to solve the above difficulties. The proposed algorithm separates a radar-search range into several blocks. And it detects and tracks a preceding object as a detected block of the several blocks. Applying this algorithm and assigning priority among the blocks, the searching range for the targeting vehicle and response time of the system are reduced.