近幾年，自駕車快速發展且越來越普及，設計導航控制系統是主要的研究重點之一。自駕車的導航控制必須因應複雜多變的行車環境，且須考慮安全、成本、法規等諸多因素。仰賴模擬器的輔助設計是必經之途，但是目前的模擬系統僅局限於部分功能的測試，甚少關注導航系統在複雜多變的行車環境做出正確決策的重要議題。
本研究目的在於設計自駕車導航決策系統，並且實現於實驗載具及車輛虛實整合系統(Cyber-Physical Vehicle System, CPVS)，在虛擬行車場景下做模擬和測試。本研究提出的CPVS由ROS2整合實體系統載具的車輛資訊，虛擬系統以Unity為主，可模擬V2X環境生成模擬行駛資料或是接收ROS2發出的資料，並透過兩者的結合達成協同最佳化。
車輛導航及決策系統除了路線跟隨，遇到障礙物時則透過V2X進行預測並進行避障，接著以模糊決策根據兩車關係得到危險程度，進一步推論出車速和方向的調整。以此方式可以模擬人們駕駛車輛時對下情況的判斷做出的駕駛決策。除此之外，設定一α值對模糊推論進行調整，可調整以執行效率為主或是舒適度與安全性為主的決策模式。
本研究在車輛虛實整合系統下測試模擬及實際載具，並設定數種情況測試導航及決策系統，皆能夠以安全的情況避開來車並到達終點。未來，此CPVS架構可運用於真實車輛的控制系統設計和測試。

In recent years, automated guided vehicle (AGV) technology has been advancing rapidly. AGV navigation and control must adapt to complex and volatile driving environments while considering factors such as safety, cost, and legal approval. Thus, the simulation system is always an important issue. However, most existing systems are restricted to limited aspects that fail to accurately correspond with reality in complex and volatile environments.
The objective of this study is to design an AGV navigation decision making system and implement it within a Cyber-Physical Vehicle System (CPVS). Furthermore, we simulate and test the system on both simulated and physical vehicle. The proposed framework is based on CPVS, with the physical-system integrating vehicle information with ROS2, and the virtual-system built on Unity platform. The virtual-system can simulate the V2X environment to generate test data for testing AGV system. Combining both systems to achieve co-optimization.
The AGV navigation and decision making system not only follows routes but also avoid obstacles with V2X data. Fuzzy inference is then used to determine the degree of danger based on the relationship between the two vehicles. It further infers the necessary adjustments of vehicle speed and direction. In this way, it is possible to simulate the driving decisions made by people when driving a vehicle. In addition, the parameter α is adjusted to focus the fuzzy decision-making system on either execution efficiency or comfort and safety
This study tests the navigation and decision-making system on both simulated and physical vehicles with the the proposed CPVS. The system successfully avoids oncoming vehicles and safely reaches the destination in various testing scenarios. In the future, this CPVS framework could be applied to the designing and testing control systems for real AGVs.

摘要 I
ABSTRACT III
誌謝 V
目錄 VII
圖目錄 IX
表目錄 XI
第一章 緒論 1
1-1 前言 1
1-2 研究動機 4
1-3 文獻回顧 5
1-4 研究方法 6
1-5 論文架構 8
第二章 相關理論與應用 9
2-1 模糊推論系統 9
2-1-1 模糊推論的架構 9
2-1-2 模糊規則庫 10
2-1-3 模糊化階段 11
2-1-4 模糊推論 13
2-1-5 解模糊階段 16
2-2 車輛虛實整合系統 18
2-2-1 虛實整合系統 19
2-2-2 車輛虛實整合系統 20
第三章 車輛虛實整合系統設計與實現 21
3-1 車輛虛實整合系統功能 21
3-2 系統特性 22
3-3 虛擬系統的設計與實現 23
3-3-1 模擬器 25
3-3-2 車聯網 31
3-3-3 行車場景編輯子系統及運行腳本 33
3-4 實際系統的設計與實現 44
3-4-1 架構說明 44
3-4-2 實驗車體 45
第四章 載具導航與決策系統的設計與實現 51
4-1 路線跟隨 52
4-2 避障演算法 55
4-3 導航模糊決策 59
4-4 導航與決策系統整合 73
第五章 實驗與結果 77
5-1 車輛虛實整合系統 77
5-2 導航模糊決策 79
第六章 結論及未來研究方向 95
6-1 結論 95
6-2 未來研究方向 95
參考文獻 97
作者簡歷 101

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