The Study of Applying ANFIS on the Route Guidance of Emergency Management Systems 吳鎧佑、張隆池
E-mail: 9607648@mail.dyu.edu.tw
ABSTRACT
To make route guidance of ambulance effective, it is important that the system should be able to provide timely and correct traffic information to the ambulances. We propose an approach that utilizes the Adaptive Network-Based Fuzzy Inference Systems (ANFIS) to develop the Emergency Route Guidance Systems (ERGS) that combines with real-time traffic information. The ambulances make use of the vehicle navigation systems that are connected with an automatic calling system and crumple sensor to get to the traffic accident scene in time so that the traffic victims can have more opportunity to be survive. We have prototyped an ERGS system based on ANFIS approach. Our test case utilizes the peripheral topography of hospitals in Taichung. By revising every weight parameters of ANFIS, the result shows the average error rate is below 1%. Empirical results demonstrate the error rate can be extremely low, as long as our system is provided with real road information of this area.
Keywords : Real-Time traffic information ; Adaptive Network-Based Fuzzy Inference Systems ; Emergency Route Guidance Systems
Table of Contents
中文摘要 ．．．．．．．．．．．．．．．．．．．．．． iii 英文摘要 ．．．．．．．．．．．．．．．．．．．．
．．．iv 致謝詞 ．．．．．．．．．．．．．．．．．．．．．．． v 內容目錄 ．．．．．．．．．．．．．．．．．
．．．．． vi 表目錄 ．．．．．．．．．．．．．．．．．．．．．． viii 圖目錄 ．．．．．．．．．．．．．
．．．．．．．．． ix 第一章 緒論．．．．．．．．．．．．．．．．．．．． 1 第一節 研究背景與動機．
．．．．．．．．．．．． 1 第二節 研究目的．．．．．．．．．．．．．．．． 3 第三節 研究範圍與 限制．．．．．．．．．．．．． 4 第四節 研究架構與流程．．．．．．．．．．．．． 4 第二章 文獻回顧
．．．．．．．．．．．．．．．．．． 6 第一節 危機處理暨緊急救援系統．．．．．．．．． 6 第二節 即時交通資訊．．．．．．．．．．．．．． 8 第三節 路徑導引系統．．．．．．．．．．．．．． 9 第 四節 類神經模糊理論．．．．．．．．．．．．． 11 第五節 K條最短路徑演算法．．．．．．．．．．．
12 第六節 即時資訊．．．．．．．．．．．．．．．． 16 第七節 模糊推論系統．．．．．．．．．．
．．．． 19 第八節 適應性類神經模糊推論系統．．．．．．．． 29 第三章 研究方法與設計．．．．．．．
．．．．．．．． 36 第一節 系統架構．．．．．．．．．．．．．．．． 36 第二節 建立初始歸屬函數 參數．．．．．．．．．． 37 第三節 模擬資料產生模式．．．．．．．．．．．． 39 第四節 建立前提 規則庫．．．．．．．．．．．．． 46 第四章 系統實作與驗證．．．．．．．．．．．．．．． 48 第一節 系統實作步驟．．．．．．．．．．．．．． 48 第二節 系統開發工具與環境．．．．．．．．．．． 50 第 三節 系統介面．．．．．．．．．．．．．．．． 50 第四節 訓練結果．．．．．．．．．．．．．．．．
52 第五節 訓練與測試結果驗證．．．．．．．．．．． 55 第五章 結論與後續研究建議．．．．．．．．．
．．．． 59 第一節 結論．．．．．．．．．．．．．．．．．． 59 第二節 後續研究建議．．．．．．
．．．．．．．． 60 參考文獻．．．．．．．．．．．．．．．．．．．．．．． 61 REFERENCES
一、中文部份 王文俊(2005)，認識Fuzzy，台北:全華書局。 李治綱，何志宏，傅介棠，方仁鳳(1992)，可測試行車路徑導引效果之交通流 模擬模式，運輸計劃季刊，21(2)，163-188。 李德紘(1992)，以多種用路人行車路徑導引模擬模式探討交通資訊效益與感應時制之研究，
國立中央大學土木工程研究所未出版碩士論文。 邵福臨(1993)，應用動態號誌時制於行車導引系統之研究，成功大學交通管理研究所未 出版碩士論文。 周安正(2002)，汽車操控動態模擬與控制，私立大葉大學機械工程研究所未出版碩士論文。 胡大瀛，魏慶地(1997)，模 擬指派模式DYNASMART在台灣之建立與應用，八十六年電子計算機於土木水力工程運用論文研討會論文集(pp. 507-517)。 張式 先(1992)，動態路選擇模式應用行車路線導引系統之研究，國立成功大學交通管理科學研究所未出版碩士論文。 張貴貞(2003)，駕駛者在 不同路網型態下途中路徑選擇行為之研究，私立淡江大學運輸科學研究所未出版碩士論文。 張斐章，張麗秋，黃浩倫(2003)，類神經網 路理論與實務，台北:東華書局。 陳仲閔(2005)，應用ANFIS於整合式導航系統之誤差補償，國立臺灣海洋大學通訊與導航工程研究所未 出版碩士論文。 黃燦煌(2000)，即時資訊狀況下駕駛人路線選擇行為之分析，國立交通大學運輸研究所未出版博士論文。 傅介棠(1990)
，多條最短路方法應用於行車路線導引系統之運輸效果模擬分析，國立成功大學交通管理科學研究所未出版碩士論文。 葉信宏(1998)，
適應性類神經模糊推論系統於跟車模式之應用，國立交通大學交通運輸研究所未出版碩士論文。 蘇木春，張孝德(2004)，類神經網路、
模糊系統以及基因演算法則，台北:全華書局。 二、英文部份 Aboelmagd, N., Ahmed, E. S., & Mahmoud, R. T. (2007). Optimizing neuro-fuzzy modules for data fusion of vehicular navigation systems using temporal cross-validation. Artificial Intelligence, 20, 49-61. Ben, M., Palma, A., & Kaysi, I. (1991). Dynamic Network Models and Driver Information System. Transportation Science, 25A(5), 309-318. Chen, S. T., Srinivasan, K., & Mahmassani, S. (1999). Effect of information quality on compliance behavior of commuters ynder real-time traffic information.
Transportation Research Record 1676, 53-60. Dougherty, M. S., & Joint, M. (1992). A Behavioural Model of Driver Route Choice Using Neural Networks. On Artificial Intelligent Applications in Transportation Engineering, San Buenaventura, CA. Eiji, H., Shinichi, K., & Masaaki, T.
(1998). An Analysis of Drivers’ Route Choice and Information Acquisition Behavior Based on Stated Preference Data Collected Through an Intranet Survey. The 4th Intelligent Transportation Systems World Congress Proceedings. Hobeika, A. G., & Lee, S. K. (1998). An Adaptive Strategy for Dynamic Route Guidance Systems Under Incident Conditions. 5th ITS World Congress. Iida, Y., Uno, N., Yamada, Y. (1994).
Experimental Analysis Approach to Analyze Dynamic Route Choice Behavior of Driver with Travel Time Information. VNIS, 377-382. Jang, S.R., Sun, C. T., & Mizutani, E. (1997). Neuro-Fuzzy and Soft Computing. Prentice-Hall International, Inc. Jeffery, D. J. (1988). Driver Route Guidance System: State of the Art, Telemetric-Transportation and Spatial Development International Symposium. The Hague. Jeffrey, L. A.
(2001). Investigating the Learning Effects of Route Guidance and Traffic Advisories on Route Choice Behavior. TRC, 9(1), 1-14. Kobayashi, F.
(1979). Feasibility Study of Route Guidance System. Transportation Research Record, 107-112. Kurosawa, A., Toshihiro Y., Teruyuki T., Takashi K., & Akihiko N. (1999). Status Report of Field Verification Test in UTMS’s Emergency Call Systems. 6th World Congress on ITS, 8-12. King, G. F., & Mast, T. M. (1987). Excess Travel: Causes, Extent and Consequences. Transportation Research Record, 126-134. Lotan, T. (1992).
Modeling Route Choice Behavior in the Presence of Information Using Concepts from Fuzzy Set Theory and Approximate Reasoning. Ph. D.
Dissertation, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology. Makoto, Toshihiro, Zuiki (1999). Fast Emergency Vehicle Preemption Systems (FAST). 6th World Congress on ITS, 8-12. Mahmassani, H. & Chen, S. P. (1993). An investigation of the reliability of real-time information for route choice decisions in a congested traffic system. Transportation. 20, 157-178. Mar, J. & Lin, F. J. (2001).
An ANFIS controller for the car-following collision prevention system. 0018-9545 IEEE, 1106-1113. Nina, M. (2003). Crash Location Systems.
CTC & Associates LLC WisDOT RD&T Program. Niina, V., & Anna, S. (2005). Results of the Finnish Study on Impacts of an Automatic Emergency Call System on Accident Consequences. VTT Technical Research Centre of Finland. Omar, C. (1999). Mayday Plus Operational Test.
Minnesota Department of Transportation Office of Advanced Transportation Systems. Peter, B. & Tim, P. (1991). Using an Interactive
Route-Choice Simulator to Investigate Drivers’ Compliance with Route Guidance Advice. TRR 1306, 59-68. Pang, G., Takahashi, K., Yokota, T., & Takenaga, H. (1995). Adaptive Route Selection for Dynamic Route Guidance System Based on Fuzzy-Neural Approaches. Hitachi Research Laboratory. Richard, M., Prter, N., Rietveld, J., & Vanommeren, N. (1996). Variable message signs and radio traffic information: An integrated empirical analysis of driver’s route behavior. Transportation Research Part A, 99, 135-153. Seiji, Yukio, Hiroyuki, & Takashi (1999).
Development of Basic Technologies for the MayDay System. 6th World Congress on ITS, 8-12. Smith, J.C. (1989). Some Possible Effects of Autoguide on Traffic in London. IEEE VNIS'89, 282-287. Tsuji, H., Takahashi, R., & Yamamoto, Y. (1985). A Stochastic Approach for Estimating the Effectiveness of a Route Guidance System and Its Related Parameter. Transportation Science, 333-351. Tsuji, H. (1985). A Stochastic Approach for Estimating the Effectiveness of a Route Guidance System and Its Related Parameters. Transportation, 19(4). Thakuriah, P., & Sen, A. (1996). Quality of Information Given by Advanced Traveler Information Systems. TRC, 4(5), 249-266. Von, A. C. (1996). Fuzzy Logic & Neuro Fuzzy Applications In Business & Finance. Upper Saddle River, N.J: Prentice Hall PTR. Wardman, M., Bonsall, P. W., & Shires, J.
D. (1997). Driver Response to Variable Message Signs: A Stated Preference Investigation. TRC, 5(6), 389-405. Yang, H., Kitamura, R., Jovanis, P., Vaughn, K., & Abdel-aty, M. (1992). Exploration of Route Choice Behaviour With Advanced Traveller Information Using Neural Network Concepts. Transportation, 20(2), 199-223. Yen, J. Y. (1971). Finding The K Shortest Loopless Paths in a Network. Management Science, 17(11), 712-716. Zhang, S. T., & Wei, X. Y. (2003). Fuzzy Adaptive Kalman Filtering For DR/GPS. 0-7803-7865-2 IEEE, 2634-2637. 國道高速公路交 通資訊系統(2007)，國道即時路況資料庫[線上資料]，來源: http://1968.nfreeway.gov.tw/[2007, May 5]。
