即時交通資訊分享系統設計與實作

本論文中，我們設計與實作一套即時交通資訊分享系統，讓使用者可在行動電腦的觸控螢幕上，以簡易的操作方式，完成遠端回報及查詢即時交通資訊。本系統主要結合全球位置測定系統(Global Positioning System, GPS)，透過通用的美國國家海洋電子學會(National Marine Electronics Association, NMEA) 通訊協定，讓行動電腦也能取得GPS的訊號資料。並藉由自行開發的系統程式，讓行動電腦透過3G行動網路，連接到遠端的伺服器電腦上的伺服器程式，達到雙向資訊溝通的功能。同時為了讓使用者能快速取得即時交通資訊，本系統結合了谷歌地圖(Google Map)所提供的地圖資訊，讓系統能以街道地圖的方式快速呈現交通現況。本系統並不限定回報及查詢裝置，只要是可支援傳輸控制協議/互聯網協議(Transmission Control Protocol/Internet Protocol, TCP/IP)通訊協定的上網裝置，皆可回報或查詢即時交通資訊。相較於其他智慧型運輸系統，本系統所使用的設備費，成本相較現有其他系統低廉，又具跨平台資訊交換功能，使得本系統極具競爭力。現今車用電腦的發展快速，目前已有多家車廠準備推出內建車用通訊系統的車款。相信未來若結合此一“即時交通資訊分享系統”，更能提升汽車的附加價值。

關鍵字

即時交通資訊分享

並列摘要

In this thesis, we have implemented a real-time traffic information sharing system that can allow users to inquire the real-time traffic information through mobile devices with friendly user interface. Every vehicle with a GPS (Global Positioning System) enabled or 3G module equipped can be traced easily by the real-time traffic system. Moreover, the system uses the Google MAP to quickly show the up-to-date traffic information on the user mobile device. Any device follows TCP/IP (Transmission Control Protocol/Internet Protocol) communication protocol can access our real-time traffic information system without boundary. Compared to other traffic information sharing systems, our system is relatively competitive because of the low cost and the cross-platform interoperability. With the popularity of the mobile devices installed on automobiles, we expect the real time information sharing system can play an important role on supporting the added value of vehicles.

並列關鍵字

Real-time Traffic Information

參考文獻

[15] 周鴻儒, “以遺傳基因演算法為基礎的符號式回歸引擎及其於全球定位系統之座標轉換上的應用”,國立高雄大學電機工程研究所, 碩士論文,

[2] M. Tai, S. Ata, Anmd I. Oka, “Fast, Accurate, and Lightweight Real-Time Traffic Identification Method Based on Flow Statistics,” Lecture Notes in Computer Science, Vol. 4427/2007, pp. 255-259, April 2007.

[4] J. Hernández, J. Cuena, and M. Molina, “Real-time Traffic Management through Knowledge-based Models: The TRYS Approach,” in Proceedings of the 11th Mini-Euro Conference on Artificial Intelligence in Transportation Systems and Science, Helsinki, Finland, July 1999.

[8] M. Fathy and M.Y. Siyal, “Real-time Image Processing Approach to Measure Traffic Queue Parameters,” IEE Proceedings Vision, Image & Signal Processing, Vol. 142, No. 5, pp. 297 – 303, October 1995.

[10] L. Singh, S. Tripathi, and H. Arora, “Time Optimization for Traffic Signal Control Using Genetic Algorithm,” International Journal of Recent Trends in Engineering, Vol. 2, No. 2, pp. 4-6, November 2009.

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即時交通資訊分享系統設計與實作

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