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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68690

    Title: 基於多重感測器之模糊判定的汽車駕駛行為分析;Driver Behavior Analysis based on The Multi-Sensor Fuzzy Decision
    Authors: 胡國柱;Hu,Kuo-Chu
    Contributors: 資訊工程學系在職專班
    Keywords: 駕駛行為分析;模糊邏輯理論;慣性感測元件;嵌入式系統;Driver behavior analysis;fuzzy logical theory;inertial sensors;embedded system
    Date: 2015-07-27
    Issue Date: 2015-09-23 14:12:17 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 在本論文中,我們發展了一個以慣性感測器為基礎的汽車駕駛行為分析系統。此系統可以讓我們偵測出車輛的加速、減速、左轉、與右轉等事件狀況是否為正常行駛或是激烈行駛;另外,我們也可以偵測車輛行駛中的路面是否過於顛簸。
    ;In this thesis, we have developed an inertial sensor-based automobile driver behavior analysis system. This system can help us to detect if a car is in a normal or extreme driving condition during vehicle acceleration, deceleration, and left or right turning.
    We used an Arduino open hardware and software platform core, and a three-axis accelerometer and three-axis gyroscope inertial sensing element analysis as a source of the signal. In the pre-processing of the sensed signals we used a digital low pass filter to filter out some of the vehicle engine or road surface interference caused by vibration. This was done in addition to previous measurement error correction.
    To be able to more reliably detect a variety of driving behavior events, we used the fuzzy logic theory as the basis of our analytic judgment. Fuzzy logic includes fuzzy membership function, the main step synthesis, and the maximum and minimum gravity defuzzification. After the above steps, we finally got a proper driving event classification based on the results of each logic judgment.
    Finally, we conduct experiments on a vehicle. Two passengers in a running vehicle record the vehicle status sequences. The status sequences were compared with those generated by the proposed behavior analysis system based on the fuzzy logic theory. The experiments results validate that indeed the system can successfully detect various driving behavior events; the results generated by the proposed system are consistent with the determination of cognitive passengers.
    Appears in Collections:[資訊工程學系碩士在職專班 ] 博碩士論文

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