臺灣博碩士論文加值系統

由於國民的所得持續的提昇，使得車輛的擁有率以及道路使用率逐年的增加，因此造成交通道路網數量不斷地增加。另外，當路網上的交通狀況處在一個非穩定的情況下，隨時都可能會有交通狀況發生，例如：道路封閉、交通事件等狀況發生。有鑑於此，本研究提出一個雲端技術連結，即時性的更新車輛可能會行駛路口附近道路，協助避免以及排除交通狀況的規劃，讓使用者以最短時的時間到達目的地，加速更新的效率和即時性。
在本篇論文中，我們將模擬真實路況情境，在行進間將會有機會遭遇有問題的路況。當車輛從起點出發，在地圖上加入隨機事件來表示路況中斷的情形，行進間偵測到下一段路徑無法前進時，系統就會規劃新的路徑讓車輛避開有問題之路段，使車輛能順利到達所設定之目的地。藉此我們可以得到遭遇問題路況的次數，重複模擬數次以求得每次行駛會遭遇到的平均問題路況數。本論文提出的方式只需更新遭遇到的問題路況數，從實驗結果顯示，與傳統RDS-TMC全面廣播相比較，可以大幅的降低資料的傳輸量。

Owing to the raising of national income, the car ownership rate and road usage are on the increase in recent years. Therefore, the transportation network of quantity has been increasing constantly. In addition, the road information is not in a stable situation, there may cause the traffic problems at any time, such as the road closures, traffic accidents or road conditions. Therefore, this research proposes a map update mechanism of GPS interaction with cloud computing unlike currently offline updating of a whole map. Through the connection of cloud computing, it will update the map information immediately and help to exclude the traffic problems when the car passes through the junction. It makes the user arrive the goal in the shortest time and accelerate the efficiency and immediacy of updates.
In this paper, we will do the simulation according to real traffic situation, which means it might meet bad traffic during a ride. During the experiment, some random events were added to represent this section of the road is in a bad situation, if we detect the next section is not good to drive, we will replanning another path to avoid driving into traffic jam, so you can arrive your destination smoothly. After a ride, we will get how many times the bad section we had meet, then repeat this experiment for several times to get the average number of the bad sections we will meet during one ride. Our mechanism only need to update the average number of bad sections but not need to do full update, from the experimental results, we will get much improvement comparing with the traditional RDS-TMC method.

目 錄
中文摘要 I
Abstract III
誌 謝 V
目 錄 VII
表 目 錄 IX
圖 目 錄 XI
第 一 章 緒論 1
1.1 研究動機 1
1.2 研究目的 4
1.3 論文架構 5
第 二 章 文獻探討 6
2.1 全球衛星定位系統 6
2.2 交通訊息頻道 9
2.3 雲端運算 10
2.4 Dijkstra’s演算法 12
2.5 數值地圖 13
2.6 相鄰矩陣 14
第 三 章 研究方法及架構 16
3.1 研究架構及流程 17
3.2 隨機地圖的產生 19
3.3 隨機事件的產生 25
3.4 路徑規劃 29
3.5 實際行走模擬 33
第 四 章 實驗結果與分析 35
4.1 實驗設備 35
4.2 實驗流程 36
4.3 實驗結果 38
4.4 實驗分析 49
第 五 章 結論 50
第 六 章 未來展望 51
參考文獻 52

表 目 錄
表3.1 隨機產生之相鄰矩陣 21
表3.2 MapSize設定為10之空白矩陣 22
表3.3 第一行設定完成後矩陣 23
表3.4 將第一行映射至第一列矩陣表示 24
表3.5 重複上述步驟完成之相鄰矩陣 24
表3.6 隨機事件產生之相鄰矩陣 26
表3.7 隨機選取並將數值更改為2之相鄰矩陣 28
表4.1 模擬實驗結果表格 39
表4.2 節點50、模擬次數1225次及發生比例1%表格 40
表4.3 節點50、模擬次數1225次及發生比例2%表格 41
表4.4 節點50、模擬次數1225次及發生比例5%表格 42
表4.5 節點100、模擬次數4950次及發生比例1%表格 43
表4.6 節點100、模擬次數4950次及發生比例2%表格 44
表4.7 節點100、模擬次數4950次及發生比例5%表格 45
表4.8 節點200、模擬次數19900次及發生比例1%表格 46
表4.9 節點200、模擬次數19900次及發生比例2%表格 47
表4.10 節點200、模擬次數19900次及發生比例5%表格 48

圖 目 錄
圖2.1 衛星運行軌道 7
圖2.2 GPS導航機 8
圖2.3 無方向性之相鄰矩陣 15
圖2.4 有方向性之相鄰矩陣 15
圖3.1 系統架構圖 17
圖3.2 研究章節流程圖 18
圖3.3 利用相鄰矩陣生成之地圖 21
圖3.4 隨機事件產生後地圖 27
圖4.1 實驗流程圖 37

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