臺灣博碩士論文加值系統

隨著經濟的快速發展、都市化的推進和生活水平的提高,讓汽車數量迅速增加,造 成停車空間不足的狀況,使得停車問題越來越受到人們的關注。目前,國內停車場停車 導引等方面研究較少。現今主要的停車導引僅提供停車場空位的數量,並沒有指明具體 位置和停車路線,降低了停車效率,花費了大量時間,給人造成不便。本論文之研究主 要是開發一套可行的停車場導引系統,開發上利用全球定位系統(Global Positioning System, GPS)定位停車點,再藉由超音波模組判斷停車位是否有物體,然後藉由ZigBee 網路傳輸至電腦,最後再運用 A∗ Manhattan 演算法計算出入口至停車位的最短路徑, 並提供使用者最佳路徑行駛方向。
硬體方面使用德州儀器(Texas Instruments,TI)的CC2430射頻晶片模組,藉由可程式 化設計的晶片使得系統在開發設計時可以獲得具有靈活變化的實用性。運用ZigBee網路 回傳超音波判斷的數值以及停車位GPS的數值至電腦端。
軟體方面使用Javascript,Javascript可使用物件為導向語言,可以快速提供程式介面 開發;最短路徑的找尋是使用 A∗ Manhattan 演算法進行分析,最後可以提供給使用者 行駛方向。

With the rapid economic development, urbanization and the improvement of living standards, so that the rapid increase in the number of cars, resulting in inadequate parking space situation, making parking problems more and more peoples attention. At present, the domestic parking lot parking guidance and other research less. Todays main parking guides only provide the number of parking spaces and do not specify the specific location and parking routes, reducing the parking efficiency, spent a lot of time, causing inconvenience. The main research is to develop a feasible parking lot guidance system, the use of global positioning system (Global Positioning System, GPS) positioning parking point, and then by the ultrasound module to determine whether the parking spaces have objects, and then by ZigBee network to the computer, and finally use the A∗ Manhattan algorithm to calculate the entrance to the parking area of the shortest path, and provide users with the best path travel direction.
The hardware uses the CC2430 RF chip module from Texas Instruments (TI), which allows the system to be flexible and adaptable when developing designs. Using the ZigBee network to return the value of the ultrasound and parking GPS value to the computer side.
Software using Javascript, Javascript can use object-oriented language, you can quickly provide programming interface development; the shortest path to find the use of A∗ Manhattan algorithm for analysis, and finally, can provide users with the direction of travel.

摘　要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 viii
圖目錄 x
第一章 緒論 1
1.1 研究動機及目的 1
1.2 參考文獻 2
1.3 研究方法 8
1.4 論文架構 9
第二章 停車場組成架構 10
2.1 現今停車場類型 10
2.2 停車場基本架構 11
2.3 停車場管理系統 14
第三章 最短路徑問題 17
3.1 A*演算法 18
3.1.1 A*演算法的時間複雜度 18
3.1.2 A*演算法的計算方式 18
3.1.3 A*演算法的移動成本g(n) 19
3.1.4 A*演算法的啟發函式h(n) 20
3.1.4.1 Manhattan Method 20
3.1.4.2 Diagonal Shortcut 21
3.1.5 A*演算法的搜索過程 21
3.1.6 實驗模擬 26
3.1.6.1 Manhattan Method模擬 26
3.1.6.2 Diagonal Shortcut模擬 29
3.2 Dijkstra演算法 32
3.2.1 Dijkstra演算法的時間複雜度 32
3.2.2 Dijkstra演算法的搜索過程 33
3.2.2 實驗模擬 37
3.3 最短路徑實驗結論 40
第四章 智能停車導引系統之探討 41
4.1 超音波感測技術 41
4.2 ZigBee無線通訊技術 44
4.2.1 ZigBee 44
4.2.1.1 ZigBee之特性 44
4.2.1.2 ZigBee之裝置類型與協議裝置種類 45
4.2.1.3 ZigBee之網路拓樸 46
4.2.2 ZigBee之無線網路協定 50
4.2.2.1 ZigBee之PHY層 51
4.2.2.2 ZigBee之MAC層 54
4.2.2.3 ZigBee之網路層 59
4.2.2.4 ZigBee之應用層 60
4.2.2.5 ZigBee之安全服務規範 64
4.2.2.6 ZigBee與其他通訊協定之比較 64
第五章 智能停車導引系統之硬體與開發環境 67
5.1 硬體架構 67
5.1.1 CC2430射頻模組 67
5.1.1.1 CC2430晶片 67
5.1.1.2 CC2430射頻模組之傳輸介紹 72
5.1.1.3 CC2430射頻模組之RS-232串列通訊 74
5.1.1.4 CC2430射頻模組之串列通訊工作模式 74
5.1.1.5 CC2430射頻模組之腳位意義及方向 76
5.1.2 U-Blox Neo-6M GPS接收模組 80
5.1.3 HC-SR04超音波感測器模組 82
5.2 開發環境 84
5.2.1 CC2430開發環境與工具 84
5.2.2 導引系統開發環境 85
第六章 智能停車導引系統之實作 89
6.1 實驗說明 89
6.2 實驗流程 91
6.2.1 建置實驗環境圖 91
6.2.2 判斷起始點和停車位位置 92
6.2.3 計算出最短路徑並顯示於介面上 93
6.2.3.1 原A^* Manhattan演算法 93
6.2.3.2 改良A^* Manhattan演算法 97
第七章 結論與未來展望 102
7.1 結論 102
7.2 未來規劃 104
參考文獻 106

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