| Summary: | 碩士 === 國立臺灣大學 === 電機工程學研究所 === 94 === Fixed Driver Assistance Systems consist of functionally isolated sensors to observe the environment around vehicle. These driver assistance systems have increasing demands for several sensors, which are complementary but also redundant. By fusing these sensors data, a large field of view is obtained and the certainty and precision of the estimates in the relevant regions is increased. It is an important issue to choose necessary object-detecting sensors in different driving conditions. In this thesis, we present a new active Driver Assistance System which is based on fixed Driver Assistance Systems including sensor types and the applications for different driving conditions implements a multi-sensor fusion architecture. Commonly used sensors of fixed Driver Assistance Systems are deployed on the new active Driver Assistance System.
In this thesis, a multi-sensor selection algorithm for Driver Assistance Systems is developed and a driving simulation interface is built up by Borland C++ Builder software. The multi-sensor selection problems for the new active Driver Assistance System is formulated by Integer Linear Programs (ILPs) and optimization theory. To consider system performances, there are two types of issues: static (off-line multi-sensor selection problem); dynamic (on-line driving condition transformation problem). We propose an objective to determine optimal selection of sensors off-line and on-line for guaranteed coverage, energy, bandwidth and reliability of sensors. Based on the multi-sensors network, different driving conditions, driving security transformation and driver commands, a multi-sensors selection approach for detecting the environment around the vehicle and warning the driver in time is developed. The performance of the proposed strategies is illustrated through extensive simulations.
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