在現今智慧型運輸系統中，定位技術已經是一項被廣泛使用的技術。然而，一般車輛所配備之定位裝置通常為較低價位的GPS，若要進一步結合防碰撞系統於車輛上，卻因其定位精度不足而無法達到安全上的演算及判斷。為此，本論文提出一套結合定位技術與路口代理人之車輛安全防撞系統，保障車輛駕駛人行駛於道路時之安全性。
此系統主要為利用車輛上之各式感測器及GPS資訊代入拓展式卡爾曼濾波器中達到最佳化的定位判斷，並進一步地利用地圖比對演算法將車輛位置比對到正確的道路上。在駕駛安全考慮上，利用安裝於車輛前方之雷射測距儀資訊，經模糊演算法後控制油門剎車以保持適當的車間距離。
此外在發生交通事故最頻繁之路口區域，本論文也結合路口代理人系統來增強路口的安全性，當車輛進入路口區域時，路口代理人會利用雷射測距儀來測量車輛的位置與速度，並代入安全防碰撞演算法中，且在預測可能發生碰撞時，發出警示訊號提醒駕駛者剎車。另一方面也把路口代理人所量測到的車輛位置資訊經由無線傳輸模組傳給車輛定位系統，使得車輛定位之精度達到更精確的定位，以降低車輛系統之定位誤差。
簡而言之，本論文結合了車輛定位、無線傳輸、自動跟車及防碰撞警示系統與路口代理人監控等多功能，並在多次實際道路的測試中，驗證本論文所發展之系統的確可以達到道路環境之需求。

Nowadays, the location technology in the field of the Intelligent Transformation System (ITS) is used generally. Most of location devices on the cars are low-cost GPS, however, it’s not enough if we want to combine with the safe algorithm. Hence, we present a suit of vehicle collision-avoidance system which combined location technology with Intersection-agent in this thesis.
The system uses vehicle sensors and GPS information to calculate in Extend Kalman Filter, in order to get the optimal location information. Furthermore, Map-Matching algorithm is used to match the vehicle location on the right road. As to the driver’s safety, laser range scanner’s data are used in fuzzy algorithm and calculate the safe distance between cars.
In the intersection area where accident happened most, we also combine with Intersection-agent system to enhance safety. When moving objects cross through the intersection area, Intersection-agent system would use laser range scanner to find the moving objects’ position and velocity, judging whether they can pass the intersection safely or not. Once it’s not safe, system would send out warning signal to the drivers to brake cars, also, passing the position information to car location system by wireless RS-232 transceiver, to decrease location error and let vehicle’s location precision more accurate.
In brief, this thesis combines with vehicle location, wireless transmission, car following warning system and Intersection-agent. And make sure this system we developed can fit in with traffic requirement in many experiments.

致謝 i
目錄 ii
圖目錄 vi
表目錄 x
中文摘要 xi
Abstract xii
第1章 緒論 1
1-1 研究動機 1
1-2 文獻探討 4
1-3 主要貢獻 5
1-4 章節簡介 6
第2章 系統設計概念 7
2-1 系統功能介紹 8
2-2 系統流程 8
2-2-1 路口代理人系統 9
2-2-2 車輛定位系統 10
2-2-3 自動跟車及防碰撞警示系統 11
2-3 硬體實現 13
2-3-1 路口代理人系統 13
2-3-2 車輛定位系統＆自動跟車及防碰撞警示系統 13
第3章 系統設計 15
3-1 路口代理人系統 16
3-1-1 建立場景演算法 16
3-1-2 搜尋移動物體演算法 18
3-1-3 路口警示系統 19
3-1-4 路口定位系統 21
3-2 車輛定位系統 22
3-2-1 卡爾曼及拓展式卡爾曼濾波器應用於車輛定位 24
3-2-2 方位推估車輛定位演算法 33
3-2-3 地圖比對車輛定位演算法 35
3-2-4 定位矯正 39
3-3 自動跟車及防碰撞警示系統 40
3-3-1 自動跟車系統 40
3-3-2 防碰撞警示系統 47
第4章 系統實現 49
4-1 實驗平台 49
4-1-1 實驗車輛 49
4-1-2 路口代理人系統 50
4-2 DSP 開發平台 51
4-2-1 數位訊號發展板介紹eZdspTMF2812 51
4-3 感測器 52
4-3-1 雷射測距儀(Laser Range Scanner, LMS291-S05) 52
4-3-2 全球定位系統(Global Position System, GPS) 54
4-3-3 地理資訊系統(Geographic Information System, GIS) 56
4-3-4 慣性量測單元(Inertial Measurement Units, IMU) 58
4-3-5 無線串列傳輸模組(RF3105 Wireless RS-232 Transceiver) 60
4-3-6 拉線式位移計(EHP-SS-R) 61
4-4 致動器 62
4-4-1 剎車致動器(HIWIN LAS3-1) 62
4-4-2 油門驅動電路 62
第5章 實驗結果 64
5-1 路口代理人系統 64
5-2 車輛定位系統 67
5-2-1 EKF車輛定位 67
5-2-2 EKF&DR車輛定位 76
5-2-3 EKF&DR&MM車輛定位 77
5-2-4 EKF&MM車輛定位&路口車輛定位的結合 78
5-3 自動跟車及防碰撞警示系統 80
5-3-1 自動跟車系統之保持安全跟車距離 83
5-3-2 防碰撞警示系統之保持安全跟車距離 87
第6章 結論與未來展望 88
6-1 結論 88
6-2 未來展望 89
參考文獻 90

[1] G. Leen and D. Heffernan, “Expanding automotive electronic systems,” Computers, pp. 88 – 93, 2002.
[2] Preventive and Active Safety Applications Integrated Project Contract number FP6 – 507075 eSafety for road and air transport.
[3] S. Ammoun, F. Nashashibi and C. Laurgeau, “Crossroads risk assessment using GPS and inter-vehicle communications,” IEEE Intelligent Transport System, pp. 95 – 101, 2007.
[4] B. Thylefors, A. D. Negrel, R. Pararajasegaram, and K. Y. Dadzie, “Global data on blindness,” Bull. WHO, pp. 115 – 121, 1995.
[5] A. Eidehall, J. Pohl, F. Gustafsson, and J. Ekmark, “Toward Autonomous Collision Avoidance by Steering,” IEEE Intelligent Transportation Systems, pp. 84 – 94, 2007.
[6] M. Bursa, “Big names invest heavily in advanced ITS technology,” ISATA Mag., pp. 24 – 30, 2000.
[7] K. Yi, J. Hong, and Y. D. Kwon, “A vehicle control algorithm for stop-and-go cruise control,” J. Automob. Eng., pp. 1099 – 1115, 2001.
[8] M. M. Balas, and C. Barna, “Using CCD Cameras for Car Following Algorithms,” IEEE Industrial Electronics, pp. 57 – 62, 2005.
[9] S. Rezaei, and R. Sengupta, “Kalman Filter – Based Integration of DGPS and Vehicle Sensors for Localization,” IEEE Control Systems Technology, pp. 1080 – 1088, 2007
[10] S. S. Young, “Attitude Estimation Using Low Cost Accelerometer and Gyroscope,” IEEE Proceeding of 7th Korea-Russia International Symposium, pp. 423 – 427, 2003.
[11] M. Hoshino, Y. Gunji, S. Oho, and K. Takano, “A Kalman Filter to Estimate Direction for Automotive Navigation,” IEEE Multisensor Fusion and Integration for Intelligent Systems, pp. 145 – 150, 1996.
[12] M. Xin, S. Salah , and K. Jong – Hyuk, “Vehicle Model Aided Inertial navigation,” IEEE Intelligent Transportation Systems , pp. 1004 – 1009, 2003.
[13] G. Dissanayake, S. Sukkarieh, E. Nebot, and H. Durrant – Whytr, “The Aiding of a Low – Cost Strapdown Inertial Measurement Unit Using Vehicle Model Constraints for Land Vehicle Applications” IEEE Transactions on Robotics and Automotor, pp. 731 – 747, 2001.
[14] 黃良吉，GPS與感測器整合於三維地面車輛定位之應用，碩士論文，國立台灣科技大學機械工程所，1996。
[15] H. Zhao, X. W. Shao, K. Katabira, and R. Shibasaki, “Joint Tracking and Classification of Moving Objects at Intersection Using a Single-Row Laser Range Scanner,” IEEE Intelligent Transportation Systems , pp. 287 – 294, 2006.
[16] D. M. Bevly, and B. Parkinson, “Cascaded Kalman Filters for Accurate Estimation of Multiple Biases, Dead-Reckoning Navigation, and Full State Feedback Control of Ground Vehicles,” IEEE Transactions on Control Systems Technology, pp. 199 – 208, 2008.
[17] T. Ardeshiri, S. Kharrazi, R. Thomson, and J. Bargman, “Offset Eliminative Map Matching Algorithm for Intersection Active Safety Applications,” IEEE Intelligent Vehicles Symposium, pp. 82 – 88, 2006.
[18] F. H. Somda, H. Cormerais, and J. Buisson, “Intelligent transportation systems：a safe, robust and comfortable strategy for longitudinal monitoring,” IEEE Intelligent Transport Systems, pp. 188 – 197, 2009
[19] 周聖雄，加速規判定載具三維姿態估測法，碩士論文，國立臺灣大學應用力學研究所，1992。
[20] 賴俊男，非線性濾波器於GPS導航之設計，碩士論文，國立臺灣海洋大學通訊與導航工程學系，1996。
[21] R. G. Brown, and P. Y. C. Hwang, “Introduction to Random Signals and Applied Kalman Filtering,” John Wiley & Sons, New York,3rd edn. 1997.
[22] 江忠潔，以DSP 平台實現多感測器資訊整合之車輛安全輔助駕駛系統，碩士論文，國立交通大學電機與控制工程學系，2007。
[23] 孫隸華、王春麗，基於模糊模式識別的車輛定位地圖比對算法，重慶大學自動化學院，2007。
[24] 何威儀，以DSP為基礎之合作式路口安全策略之市區巡航及停走系統，碩士論文，國立交通大學電機與控制工程學系，2008。
[25] 陳致成，智慧型CAN-based汽車雷達防撞警告系統，碩士論文，國立交通大學電機與控制工程學系，1992。
[26] LMS291, http://team.caltech.edu/members/SICK/LMS_Quick_Manual_V1_1.pdf.
[27] 安守中，進階GPS定位原理及應用，崑崙文化，2007。
[28] WBT201, http://www.xgps.ro/detalii/wbt201/WBT201_User_%20Manual.html.
[29] 維基百科–地理信息系統, http://zh.wikipedia.org/zh-tw/GIS.
[30] 謝權信，智慧型e化車輛導航系統研究，碩士論文，中華大學機械與航太工程研究所，1992。
[31] 資策會，地理資訊系統市場發展趨勢，財團法人資訊工業策進會，1984。
[32] Xsens, http://www.xsens.com
[33] RF3105, ANCHER TECHNOLOGY.
[34] H. Ohara, and T. Murakami, “A Stability Control by Active Angle Control of Front-Wheel in a Vehicle System,” IEEE Industrial Electronics, pp. 1277 – 1285, 2008
[35] M. M. Balas, V. E. Balas, and J. Duplaix, “Optimizing the Distance-Gap between Cars by Constant Time to Collision Planning,” IEEE Industrial Electronics, pp. 304 – 309, 2007.