先進駕駛輔助系統中的多樣警示資訊融合模式

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姓名

施承斈(Cheng-xue Shi) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

先進駕駛輔助系統中的多樣警示資訊融合模式
(The Fusion Model of Multiple Warning Data for Advanced Driver Assistance System)

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摘要(中)

有鑑於交通事故的頻繁，車輛安全系統的研發日益蓬勃。現今駕駛對於車輛的需求不再只是傳統的硬體規格，面對行車環境潛在的危險，提供偵測、預警的車輛安全系統需求與日俱增。然而，現行車輛安全系統著重在單一的功能的安全警示，面對複雜行車狀況，缺乏綜觀全局的考量。因此，本研究致力將多種警示資訊整合，提出一個以模糊推論為基礎的多樣警示資訊融合模式，提供駕駛面對複雜行車環境潛在危險的單一警示，作為採取相對反應的依歸。
本資訊融合模式整合包含車道偏離警示 (LDW)、前車碰撞警示 (FCW)、路口警示、路口警示、及彎曲道路車速 (CSW) 警示。藉由相機的影像輸入及GPS與電子地圖的配合，涵蓋近處與遠方的安全資訊。GPS配合電子地圖提供了當前道路的速限以及路口資訊，提醒駕駛要留心與斟酌減速。彎曲道路車速警示系統根據GPS與電子地圖所傳回之前方道路資訊，計算出前方100公尺至250公尺路段的道路曲率，並判斷當前車速是否超過安全車速而提出警示。最後，將車道偏離距離、前車距離、碰撞時間、彎路曲率、與車速等警示資料輸入至一模糊推論系統，以人類經驗知識建立一模糊規則庫，依據當前各項警示資料，查詢一系列的模糊規則及所選用的模糊推論引擎推論出結論。最後經由解模糊化界面得到一明確的結論值，此為當前的警示程度值。
本研究藉由多個街道場景實驗驗證了，我們系統可以成功地將前述FCW、LDW警示系統結合，接著透過GPS結合電子地圖將前方道路曲率、車速限制、及路口資訊彙整進來；再將這五種遠近警示輸入至模糊推論系統，以單點模糊的模糊化界面加上最大-最小模糊推論引擎，比對模糊規則庫中的44條規則，考量所有的行車情境，最終將推論而得的模糊結論利用面積中心法解模糊，得到單一危險數值，達成對駕駛提出單一警示的目的。

摘要(英)

Due to the frequent traffic accidents, the development of vehicle safety systems becomes more and more important. Nowadays, the demands for vehicles are not only convenience and comfortability but also the needs of vehicle safety which can detect dangerous states and issue warnings for drivers. Currently, the vehicle safety systems are separately developed one after one; each system has its own detection and warning modules. If a driver uses more than one system in his vehicle, the multiple warning signals maybe confuse and interfere the driver. On the other hand, the sensor-based detection systems can only detect the short-distance dangerous states; the long-distance detection functions were seldom considered. Thus, in this study, we propose a long-distance detection and warning system and then propose a fuzzy-based fusion model to combine the multiple warning data from all considered short-distance and long-distance detection and warning systems to provide the drivers only a single significant warning signal.
The proposed fusion model integrates Land departure Warning (LDW), Forward Collision Warning (FCW), Curve Speed Warning (CSW), speeding warning, and crossroad warning systems. GPS and electronic map provide speed limit on current road and the information of forward crossroad to warn drivers of the danger. CSW reminds the forward road information based on GPS and electronic map. CSW system computes the curvature radius of 100 to 250 meters road ahead and issue warning if current speed is higher than the critical speed in such radius.
Based on the experiments of several street sceneries, it is certified that the proposed system can successfully integrates FCW and LDW with CSW, speed warning and crossroad warning via GPS and electronic map. Then these five warning data are feed into the proposed fuzzy inference system and fuzzified into fuzzy singleton. We choose max-min inference engine and check the 44 rules in the rule base to conclude all driving situations. Eventually, we use center of area defuzzifier to defuzzify the final conclusion membership function to obtain a single warning. The experimental results show that the proposed system is reasonable and useful for practical ADAS applications.

關鍵字(中)

★ 駕駛輔助
★ 車輛安全
★ 模糊系統
★ 資訊融合

關鍵字(英)

★ ADAS
★ fuzzy
★ fuzzy system
★ data fusion
★ FCW
★ CSW

論文目次

摘要 i
Abstract ii
誌謝 iv
目錄 v
圖目錄 viii
表目錄 xi
第一章緒論 1
1.1 研究背景與動機 1
1.2 系統概述 2
1.3 論文架構 3
第二章相關研究 4
2.1 車道線偵測 4
2.2 車輛偵測 5
2.3 資訊融合 7
第三章模糊推論與模糊系統 11
3.1 關係 11
3.1.2模糊關係 12
3.2 合成運算 13
3.3 模糊規則 14
3.3.1語意式變數 14
3.3.2模糊蘊涵 (fuzzy implication) 15
3.4 模糊推論 16
3.5 模糊系統 19
3.5.1系統架構 19
3.5.2模糊化界面 20
3.5.3模糊規則庫 21
3.5.4模糊推論引擎 22
3.5.5解模糊化界面 23
第四章多樣警示資訊融合 26
4.1 車道偏離警示 26
4.2 前車碰撞警示 30
4.3 GPS與電子地圖 35
4.3.1 GPS資料格式 35
4.3.2電子地圖 37
4.3.3路口警示 39
4.3.4超速警示 39
4.4 彎曲道路車速警示 39
4.4.1曲率計算 39
4.4.2道路曲率與臨界車速 41
4.5 以模糊系統為基礎的資訊融合模式 42
4.5.1 LDW的歸屬函數制定 42
4.5.2 FCW的歸屬函數制定 43
4.5.3 CSW的歸屬函數制定 44
4.5.4模糊規則庫 44
第五章實驗結果 49
5.1 實驗設備 49
5.2 各警示系統的偵測結果 49
5.2.1 LDW的偵測結果 50
5.2.2 FCW的偵測結果 50
5.2.3路口警示 51
5.2.4超速警示 51
5.2.4 CSW彎曲道路曲率偵測結果 52
5.2.5資訊融合模式融合結果 52
第六章結論與未來工作 56
6.1結論 56
6.2未來工作 56
參考文獻 58

參考文獻

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指導教授

曾定章(Ding-chang Tseng)

審核日期

2015-7-30

推文